diff --git a/bioimageio/spec.html b/bioimageio/spec.html index 6d149bbde..3e2da37c5 100644 --- a/bioimageio/spec.html +++ b/bioimageio/spec.html @@ -21,6 +21,22 @@ +

Contents

+ +

Submodules

@@ -75,170 +78,182 @@

- 
  1from types import MappingProxyType
-  2from typing import Any, Literal, Optional, TypeVar, Union
-  3
-  4from pydantic import Discriminator
-  5from typing_extensions import Annotated
-  6
-  7from ._build_description import DISCOVER, build_description_impl, get_rd_class_impl
-  8from ._internal.common_nodes import InvalidDescr
-  9from ._internal.io import BioimageioYamlContent
- 10from ._internal.types import FormatVersionPlaceholder
- 11from ._internal.validation_context import ValidationContext, validation_context_var
- 12from .application import AnyApplicationDescr, ApplicationDescr
- 13from .application.v0_2 import ApplicationDescr as ApplicationDescr02
- 14from .application.v0_3 import ApplicationDescr as ApplicationDescr03
- 15from .collection import AnyCollectionDescr, CollectionDescr
- 16from .collection.v0_2 import CollectionDescr as CollectionDescr02
- 17from .collection.v0_3 import CollectionDescr as CollectionDescr03
- 18from .dataset import AnyDatasetDescr, DatasetDescr
- 19from .dataset.v0_2 import DatasetDescr as DatasetDescr02
- 20from .dataset.v0_3 import DatasetDescr as DatasetDescr03
- 21from .generic import AnyGenericDescr, GenericDescr
- 22from .generic.v0_2 import GenericDescr as GenericDescr02
- 23from .generic.v0_3 import GenericDescr as GenericDescr03
- 24from .model import AnyModelDescr, ModelDescr
- 25from .model.v0_4 import ModelDescr as ModelDescr04
- 26from .model.v0_5 import ModelDescr as ModelDescr05
- 27from .notebook import AnyNotebookDescr, NotebookDescr
- 28from .notebook.v0_2 import NotebookDescr as NotebookDescr02
- 29from .notebook.v0_3 import NotebookDescr as NotebookDescr03
- 30from .summary import ValidationSummary
- 31
- 32LATEST: FormatVersionPlaceholder = "latest"
- 33"""placeholder for the latest available format version"""
- 34
+                        
  1from pathlib import Path
+  2from types import MappingProxyType
+  3from typing import Any, Literal, Optional, TypeVar, Union
+  4
+  5from pydantic import Discriminator
+  6from typing_extensions import Annotated
+  7
+  8from ._build_description import DISCOVER, build_description_impl, get_rd_class_impl
+  9from ._internal.common_nodes import InvalidDescr
+ 10from ._internal.io import BioimageioYamlContent, BioimageioYamlSource
+ 11from ._internal.types import FormatVersionPlaceholder
+ 12from ._internal.validation_context import ValidationContext, validation_context_var
+ 13from .application import AnyApplicationDescr, ApplicationDescr
+ 14from .application.v0_2 import ApplicationDescr as ApplicationDescr02
+ 15from .application.v0_3 import ApplicationDescr as ApplicationDescr03
+ 16from .collection import AnyCollectionDescr, CollectionDescr
+ 17from .collection.v0_2 import CollectionDescr as CollectionDescr02
+ 18from .collection.v0_3 import CollectionDescr as CollectionDescr03
+ 19from .dataset import AnyDatasetDescr, DatasetDescr
+ 20from .dataset.v0_2 import DatasetDescr as DatasetDescr02
+ 21from .dataset.v0_3 import DatasetDescr as DatasetDescr03
+ 22from .generic import AnyGenericDescr, GenericDescr
+ 23from .generic.v0_2 import GenericDescr as GenericDescr02
+ 24from .generic.v0_3 import GenericDescr as GenericDescr03
+ 25from .model import AnyModelDescr, ModelDescr
+ 26from .model.v0_4 import ModelDescr as ModelDescr04
+ 27from .model.v0_5 import ModelDescr as ModelDescr05
+ 28from .notebook import AnyNotebookDescr, NotebookDescr
+ 29from .notebook.v0_2 import NotebookDescr as NotebookDescr02
+ 30from .notebook.v0_3 import NotebookDescr as NotebookDescr03
+ 31from .summary import ValidationSummary
+ 32
+ 33LATEST: FormatVersionPlaceholder = "latest"
+ 34"""placeholder for the latest available format version"""
  35
- 36LatestResourceDescr = Union[
- 37    Annotated[
- 38        Union[
- 39            ApplicationDescr,
- 40            CollectionDescr,
- 41            DatasetDescr,
- 42            ModelDescr,
- 43            NotebookDescr,
- 44        ],
- 45        Discriminator("type"),
- 46    ],
- 47    GenericDescr,
- 48]
- 49"""A resource description following the latest specification format"""
- 50
+ 36
+ 37LatestResourceDescr = Union[
+ 38    Annotated[
+ 39        Union[
+ 40            ApplicationDescr,
+ 41            CollectionDescr,
+ 42            DatasetDescr,
+ 43            ModelDescr,
+ 44            NotebookDescr,
+ 45        ],
+ 46        Discriminator("type"),
+ 47    ],
+ 48    GenericDescr,
+ 49]
+ 50"""A resource description following the latest specification format"""
  51
- 52SpecificResourceDescr = Annotated[
- 53    Union[
- 54        AnyApplicationDescr,
- 55        AnyCollectionDescr,
- 56        AnyDatasetDescr,
- 57        AnyModelDescr,
- 58        AnyNotebookDescr,
- 59    ],
- 60    Discriminator("type"),
- 61]
- 62"""Any of the implemented, non-generic resource descriptions"""
- 63
- 64ResourceDescr = Union[SpecificResourceDescr, AnyGenericDescr]
- 65"""Any of the implemented resource descriptions"""
- 66
+ 52
+ 53SpecificResourceDescr = Annotated[
+ 54    Union[
+ 55        AnyApplicationDescr,
+ 56        AnyCollectionDescr,
+ 57        AnyDatasetDescr,
+ 58        AnyModelDescr,
+ 59        AnyNotebookDescr,
+ 60    ],
+ 61    Discriminator("type"),
+ 62]
+ 63"""Any of the implemented, non-generic resource descriptions"""
+ 64
+ 65ResourceDescr = Union[SpecificResourceDescr, AnyGenericDescr]
+ 66"""Any of the implemented resource descriptions"""
  67
- 68def dump_description(
- 69    rd: Union[ResourceDescr, InvalidDescr], exclude_unset: bool = True
- 70) -> BioimageioYamlContent:
- 71    """Converts a resource to a dictionary containing only simple types that can directly be serialzed to YAML."""
- 72    return rd.model_dump(mode="json", exclude_unset=exclude_unset)
- 73
+ 68
+ 69def dump_description(
+ 70    rd: Union[ResourceDescr, InvalidDescr], exclude_unset: bool = True
+ 71) -> BioimageioYamlContent:
+ 72    """Converts a resource to a dictionary containing only simple types that can directly be serialzed to YAML."""
+ 73    return rd.model_dump(mode="json", exclude_unset=exclude_unset)
  74
- 75RD = TypeVar("RD", bound=ResourceDescr)
- 76
+ 75
+ 76RD = TypeVar("RD", bound=ResourceDescr)
  77
- 78DESCRIPTIONS_MAP = MappingProxyType(
- 79    {
- 80        None: MappingProxyType(
- 81            {
- 82                "0.2": GenericDescr02,
- 83                "0.3": GenericDescr03,
- 84                None: GenericDescr,
- 85            }
- 86        ),
- 87        "generic": MappingProxyType(
- 88            {
- 89                "0.2": GenericDescr02,
- 90                "0.3": GenericDescr03,
- 91                None: GenericDescr,
- 92            }
- 93        ),
- 94        "application": MappingProxyType(
- 95            {
- 96                "0.2": ApplicationDescr02,
- 97                "0.3": ApplicationDescr03,
- 98                None: ApplicationDescr,
- 99            }
-100        ),
-101        "collection": MappingProxyType(
-102            {
-103                "0.2": CollectionDescr02,
-104                "0.3": CollectionDescr03,
-105                None: CollectionDescr,
-106            }
-107        ),
-108        "dataset": MappingProxyType(
-109            {
-110                "0.2": DatasetDescr02,
-111                "0.3": DatasetDescr03,
-112                None: DatasetDescr,
-113            }
-114        ),
-115        "notebook": MappingProxyType(
-116            {
-117                "0.2": NotebookDescr02,
-118                "0.3": NotebookDescr03,
-119                None: NotebookDescr,
-120            }
-121        ),
-122        "model": MappingProxyType(
-123            {
-124                "0.3": ModelDescr04,
-125                "0.4": ModelDescr04,
-126                "0.5": ModelDescr05,
-127                None: ModelDescr,
-128            }
-129        ),
-130    }
-131)
-132
+ 78
+ 79DESCRIPTIONS_MAP = MappingProxyType(
+ 80    {
+ 81        None: MappingProxyType(
+ 82            {
+ 83                "0.2": GenericDescr02,
+ 84                "0.3": GenericDescr03,
+ 85                None: GenericDescr,
+ 86            }
+ 87        ),
+ 88        "generic": MappingProxyType(
+ 89            {
+ 90                "0.2": GenericDescr02,
+ 91                "0.3": GenericDescr03,
+ 92                None: GenericDescr,
+ 93            }
+ 94        ),
+ 95        "application": MappingProxyType(
+ 96            {
+ 97                "0.2": ApplicationDescr02,
+ 98                "0.3": ApplicationDescr03,
+ 99                None: ApplicationDescr,
+100            }
+101        ),
+102        "collection": MappingProxyType(
+103            {
+104                "0.2": CollectionDescr02,
+105                "0.3": CollectionDescr03,
+106                None: CollectionDescr,
+107            }
+108        ),
+109        "dataset": MappingProxyType(
+110            {
+111                "0.2": DatasetDescr02,
+112                "0.3": DatasetDescr03,
+113                None: DatasetDescr,
+114            }
+115        ),
+116        "notebook": MappingProxyType(
+117            {
+118                "0.2": NotebookDescr02,
+119                "0.3": NotebookDescr03,
+120                None: NotebookDescr,
+121            }
+122        ),
+123        "model": MappingProxyType(
+124            {
+125                "0.3": ModelDescr04,
+126                "0.4": ModelDescr04,
+127                "0.5": ModelDescr05,
+128                None: ModelDescr,
+129            }
+130        ),
+131    }
+132)
 133
-134def _get_rd_class(typ: Any, format_version: Any):
-135    return get_rd_class_impl(typ, format_version, DESCRIPTIONS_MAP)
-136
+134
+135def _get_rd_class(typ: Any, format_version: Any):
+136    return get_rd_class_impl(typ, format_version, DESCRIPTIONS_MAP)
 137
-138def build_description(
-139    content: BioimageioYamlContent,
-140    /,
-141    *,
-142    context: Optional[ValidationContext] = None,
-143    format_version: Union[FormatVersionPlaceholder, str] = DISCOVER,
-144) -> Union[ResourceDescr, InvalidDescr]:
-145    return build_description_impl(
-146        content,
-147        context=context,
-148        format_version=format_version,
-149        get_rd_class=_get_rd_class,
-150    )
-151
+138
+139def build_description(
+140    content: BioimageioYamlContent,
+141    /,
+142    *,
+143    context: Optional[ValidationContext] = None,
+144    format_version: Union[FormatVersionPlaceholder, str] = DISCOVER,
+145) -> Union[ResourceDescr, InvalidDescr]:
+146    return build_description_impl(
+147        content,
+148        context=context,
+149        format_version=format_version,
+150        get_rd_class=_get_rd_class,
+151    )
 152
-153def validate_format(
-154    data: BioimageioYamlContent,
-155    /,
-156    *,
-157    format_version: Union[Literal["discover", "latest"], str] = DISCOVER,
-158    context: Optional[ValidationContext] = None,
-159) -> ValidationSummary:
-160    with context or validation_context_var.get():
-161        rd = build_description(data, format_version=format_version)
-162
-163    assert rd.validation_summary is not None
-164    return rd.validation_summary
+153
+154def validate_format(
+155    data: BioimageioYamlContent,
+156    /,
+157    *,
+158    format_version: Union[Literal["discover", "latest"], str] = DISCOVER,
+159    context: Optional[ValidationContext] = None,
+160) -> ValidationSummary:
+161    """validate a bioimageio.yaml file (RDF)"""
+162    with context or validation_context_var.get():
+163        rd = build_description(data, format_version=format_version)
+164
+165    assert rd.validation_summary is not None
+166    return rd.validation_summary
+167
+168
+169def update_format(
+170    source: BioimageioYamlSource,
+171    *,
+172    output_path: Optional[Path] = None,
+173    target_format_version: Union[Literal["latest"], str] = LATEST,
+174) -> BioimageioYamlContent:
+175    """update a bioimageio.yaml file without validating it"""
+176    raise NotImplementedError("Oh no! This feature is not yet implemented")
 

 
 
@@ -313,11 +328,11 @@
- 
69def dump_description(
-70    rd: Union[ResourceDescr, InvalidDescr], exclude_unset: bool = True
-71) -> BioimageioYamlContent:
-72    """Converts a resource to a dictionary containing only simple types that can directly be serialzed to YAML."""
-73    return rd.model_dump(mode="json", exclude_unset=exclude_unset)
+            
70def dump_description(
+71    rd: Union[ResourceDescr, InvalidDescr], exclude_unset: bool = True
+72) -> BioimageioYamlContent:
+73    """Converts a resource to a dictionary containing only simple types that can directly be serialzed to YAML."""
+74    return rd.model_dump(mode="json", exclude_unset=exclude_unset)
 

 
 
@@ -350,19 +365,19 @@
- 
139def build_description(
-140    content: BioimageioYamlContent,
-141    /,
-142    *,
-143    context: Optional[ValidationContext] = None,
-144    format_version: Union[FormatVersionPlaceholder, str] = DISCOVER,
-145) -> Union[ResourceDescr, InvalidDescr]:
-146    return build_description_impl(
-147        content,
-148        context=context,
-149        format_version=format_version,
-150        get_rd_class=_get_rd_class,
-151    )
+            
140def build_description(
+141    content: BioimageioYamlContent,
+142    /,
+143    *,
+144    context: Optional[ValidationContext] = None,
+145    format_version: Union[FormatVersionPlaceholder, str] = DISCOVER,
+146) -> Union[ResourceDescr, InvalidDescr]:
+147    return build_description_impl(
+148        content,
+149        context=context,
+150        format_version=format_version,
+151        get_rd_class=_get_rd_class,
+152    )
 

 
 
@@ -380,22 +395,52 @@
- 
154def validate_format(
-155    data: BioimageioYamlContent,
-156    /,
-157    *,
-158    format_version: Union[Literal["discover", "latest"], str] = DISCOVER,
-159    context: Optional[ValidationContext] = None,
-160) -> ValidationSummary:
-161    with context or validation_context_var.get():
-162        rd = build_description(data, format_version=format_version)
-163
-164    assert rd.validation_summary is not None
-165    return rd.validation_summary
+            
155def validate_format(
+156    data: BioimageioYamlContent,
+157    /,
+158    *,
+159    format_version: Union[Literal["discover", "latest"], str] = DISCOVER,
+160    context: Optional[ValidationContext] = None,
+161) -> ValidationSummary:
+162    """validate a bioimageio.yaml file (RDF)"""
+163    with context or validation_context_var.get():
+164        rd = build_description(data, format_version=format_version)
+165
+166    assert rd.validation_summary is not None
+167    return rd.validation_summary
 

 
 
-    
+            
validate a bioimageio.yaml file (RDF)

+

+
+
+                
+                

+                            
+

+            
+        def
+        update_format(	source: Union[Annotated[pathlib.Path, PathType(path_type='file')], bioimageio.spec._internal.io.RelativeFilePath, bioimageio.spec._internal.url.HttpUrl, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)], str, Dict[str, YamlValue]],	*,	output_path: Optional[pathlib.Path] = None,	target_format_version: Union[Literal['latest'], str] = 'latest') -> Dict[str, YamlValue]:
+
+                
+
+    

+    
+            
170def update_format(
+171    source: BioimageioYamlSource,
+172    *,
+173    output_path: Optional[Path] = None,
+174    target_format_version: Union[Literal["latest"], str] = LATEST,
+175) -> BioimageioYamlContent:
+176    """update a bioimageio.yaml file without validating it"""
+177    raise NotImplementedError("Oh no! This feature is not yet implemented")
+

+
+
+            
update a bioimageio.yaml file without validating it

+

+
 
                 

     
diff --git a/bioimageio/spec/_internal.html b/bioimageio/spec/_internal.html
index dd36f9177..142b2f8b2 100644
--- a/bioimageio/spec/_internal.html
+++ b/bioimageio/spec/_internal.html
@@ -46,6 +46,7 @@ 
Submodules

                     
  • utils
    • 
                     
  • validated_string
    • 
                     
  • validation_context
    • 
+                    
  • validator_annotations
    • 
                     
  • version_type
    • 
                     
  • warning_levels
    • 
             
diff --git a/bioimageio/spec/_internal/common_nodes.html b/bioimageio/spec/_internal/common_nodes.html
index 7161e24db..f2716c675 100644
--- a/bioimageio/spec/_internal/common_nodes.html
+++ b/bioimageio/spec/_internal/common_nodes.html
@@ -1418,7 +1418,7 @@ 
    Inherited Members
    
                             
    
                                 
    
             fields_to_set_explicitly: ClassVar[FrozenSet[LiteralString]]        =
-frozenset({'type', 'format_version'})
+frozenset({'format_version', 'type'})
 
         
     
    
diff --git a/bioimageio/spec/_internal/constants.html b/bioimageio/spec/_internal/constants.html
index 4bcd8f159..e990acf6c 100644
--- a/bioimageio/spec/_internal/constants.html
+++ b/bioimageio/spec/_internal/constants.html
@@ -338,7 +338,7 @@ 
    Inherited Members
    
                     
    
             KNOWN_GH_USERS: Set[str]        =
 
-            {'danifranco', 'jansanrom', 'lenkaback', 'ctr26', 'k-dominik', 'iarganda', 'fynnbe', 'pedgomgal1', 'githubuser2', 'ivanhcenalmor', 'carlosuc3m', 'esgomezm', 'aaitorg', 'bioimageiobot', 'clementcaporal', 'cfusterbarcelo', 'constantinpape', 'oeway', 'donglaiw'}
+            {'lenkaback', 'k-dominik', 'constantinpape', 'aaitorg', 'danifranco', 'bioimageiobot', 'ctr26', 'iarganda', 'donglaiw', 'esgomezm', 'fynnbe', 'jansanrom', 'clementcaporal', 'githubuser2', 'ivanhcenalmor', 'pedgomgal1', 'cfusterbarcelo', 'oeway', 'carlosuc3m'}
 
         
     
    
diff --git a/bioimageio/spec/_internal/field_validation.html b/bioimageio/spec/_internal/field_validation.html
index fe6862540..5569dd32e 100644
--- a/bioimageio/spec/_internal/field_validation.html
+++ b/bioimageio/spec/_internal/field_validation.html
@@ -30,21 +30,6 @@
 
             
    API Documentation
    
                 
      
-            
    • 
-                    RestrictCharacters
-                            
-
-            
      • 
             
    • 
                     is_valid_yaml_leaf_value
             
      • 
@@ -63,33 +48,6 @@ 
      API Documentation
      
             
    • 
                     validate_unique_entries
             
      • 
-            
    • 
-                    AfterValidator
-                            
-
-            
      • 
-            
    • 
-                    BeforeValidator
-                            
-
-            
      • 
-            
    • 
-                    Predicate
-                            
-
-            
      • 
             
    • 
                     validate_gh_user
             
      • 
@@ -114,241 +72,99 @@ 
      
 
                         
 
-                        
        1from __future__ import annotations
-  2
-  3import collections.abc
-  4import dataclasses
-  5import sys
-  6from dataclasses import dataclass
-  7from datetime import date, datetime
-  8from typing import (
-  9    Any,
- 10    Dict,
- 11    Hashable,
- 12    Mapping,
- 13    Sequence,
- 14    Type,
- 15    Union,
- 16)
- 17
- 18import annotated_types
- 19import requests
- 20from pydantic import GetCoreSchemaHandler, functional_validators
- 21from pydantic_core.core_schema import CoreSchema, no_info_after_validator_function
- 22
- 23from bioimageio.spec._internal._settings import settings
- 24from bioimageio.spec._internal.constants import KNOWN_GH_USERS, KNOWN_INVALID_GH_USERS
- 25from bioimageio.spec._internal.field_warning import issue_warning
- 26from bioimageio.spec._internal.validation_context import validation_context_var
- 27
- 28if sys.version_info < (3, 10):
- 29    SLOTS: Dict[str, bool] = {}
- 30    KW_ONLY: Dict[str, bool] = {}
- 31else:
- 32    SLOTS = {"slots": True}
- 33    KW_ONLY = {"kw_only": True}
- 34
- 35
- 36@dataclasses.dataclass(frozen=True, **SLOTS)
- 37class RestrictCharacters:
- 38    alphabet: str
- 39
- 40    def __get_pydantic_core_schema__(
- 41        self, source: Type[Any], handler: GetCoreSchemaHandler
- 42    ) -> CoreSchema:
- 43        if not self.alphabet:
- 44            raise ValueError("Alphabet may not be empty")
- 45        schema = handler(source)  # get the CoreSchema from the type / inner constraints
- 46        if schema["type"] != "str":
- 47            raise TypeError("RestrictCharacters can only be applied to strings")
- 48        return no_info_after_validator_function(
- 49            self.validate,
- 50            schema,
- 51        )
- 52
- 53    def validate(self, value: str) -> str:
- 54        if any(c not in self.alphabet for c in value):
- 55            raise ValueError(f"{value!r} is not restricted to {self.alphabet!r}")
- 56        return value
- 57
- 58
- 59def is_valid_yaml_leaf_value(value: Any) -> bool:
- 60    return value is None or isinstance(value, (bool, date, datetime, int, float, str))
- 61
- 62
- 63def is_valid_yaml_key(value: Union[Any, Sequence[Any]]) -> bool:
- 64    return (
- 65        is_valid_yaml_leaf_value(value)
- 66        or isinstance(value, tuple)
- 67        and all(is_valid_yaml_leaf_value(v) for v in value)
- 68    )
- 69
- 70
- 71def is_valid_yaml_mapping(value: Union[Any, Mapping[Any, Any]]) -> bool:
- 72    return isinstance(value, collections.abc.Mapping) and all(
- 73        is_valid_yaml_key(k) and is_valid_yaml_value(v) for k, v in value.items()
- 74    )
- 75
- 76
- 77def is_valid_yaml_sequence(value: Union[Any, Sequence[Any]]) -> bool:
- 78    return isinstance(value, collections.abc.Sequence) and all(
- 79        is_valid_yaml_value(v) for v in value
- 80    )
- 81
- 82
- 83def is_valid_yaml_value(value: Any) -> bool:
- 84    return any(
- 85        is_valid(value)
- 86        for is_valid in (
- 87            is_valid_yaml_key,
- 88            is_valid_yaml_mapping,
- 89            is_valid_yaml_sequence,
- 90        )
- 91    )
- 92
- 93
- 94def validate_unique_entries(seq: Sequence[Hashable]):
- 95    if len(seq) != len(set(seq)):
- 96        raise ValueError("Entries are not unique.")
- 97    return seq
- 98
- 99
-100# TODO: make sure we use this one everywhere and not the vanilla pydantic one
-101@dataclass(frozen=True, **SLOTS)
-102class AfterValidator(functional_validators.AfterValidator):
-103    def __str__(self):
-104        return f"AfterValidator({self.func.__name__})"
-105
-106
-107# TODO: make sure we use this one everywhere and not the vanilla pydantic one
-108@dataclass(frozen=True, **SLOTS)
-109class BeforeValidator(functional_validators.BeforeValidator):
-110    def __str__(self):
-111        return f"BeforeValidator({self.func.__name__})"
-112
-113
-114# TODO: make sure we use this one everywhere and not the vanilla pydantic one
-115@dataclass(frozen=True, **SLOTS)
-116class Predicate(annotated_types.Predicate):
-117    def __str__(self):
-118        return f"Predicate({self.func.__name__})"
-119
-120
-121def validate_gh_user(username: str, hotfix_known_errorenous_names: bool = True) -> str:
-122    if hotfix_known_errorenous_names:
-123        if username == "Constantin Pape":
-124            return "constantinpape"
-125
-126    if (
-127        username.lower() in KNOWN_GH_USERS
-128        or not validation_context_var.get().perform_io_checks
-129    ):
-130        return username
-131
-132    if username.lower() in KNOWN_INVALID_GH_USERS:
-133        raise ValueError(f"Known invalid GitHub user '{username}'")
-134
-135    r = requests.get(
-136        f"https://api.github.com/users/{username}", auth=settings.github_auth
-137    )
-138    if r.status_code == 403 and r.reason == "rate limit exceeded":
-139        issue_warning(
-140            "Could not verify GitHub user '{value}' due to GitHub API rate limit",
-141            value=username,
-142        )
-143    elif r.status_code != 200:
-144        KNOWN_INVALID_GH_USERS.add(username.lower())
-145        raise ValueError(f"Could not find GitHub user '{username}'")
-146
-147    KNOWN_GH_USERS.add(username.lower())
-148    return username
+                        
       1from __future__ import annotations
+ 2
+ 3import collections.abc
+ 4from datetime import date, datetime
+ 5from typing import (
+ 6    Any,
+ 7    Hashable,
+ 8    Mapping,
+ 9    Sequence,
+10    Union,
+11)
+12
+13import requests
+14
+15from bioimageio.spec._internal._settings import settings
+16from bioimageio.spec._internal.constants import KNOWN_GH_USERS, KNOWN_INVALID_GH_USERS
+17from bioimageio.spec._internal.field_warning import issue_warning
+18from bioimageio.spec._internal.validation_context import validation_context_var
+19
+20
+21def is_valid_yaml_leaf_value(value: Any) -> bool:
+22    return value is None or isinstance(value, (bool, date, datetime, int, float, str))
+23
+24
+25def is_valid_yaml_key(value: Union[Any, Sequence[Any]]) -> bool:
+26    return (
+27        is_valid_yaml_leaf_value(value)
+28        or isinstance(value, tuple)
+29        and all(is_valid_yaml_leaf_value(v) for v in value)
+30    )
+31
+32
+33def is_valid_yaml_mapping(value: Union[Any, Mapping[Any, Any]]) -> bool:
+34    return isinstance(value, collections.abc.Mapping) and all(
+35        is_valid_yaml_key(k) and is_valid_yaml_value(v) for k, v in value.items()
+36    )
+37
+38
+39def is_valid_yaml_sequence(value: Union[Any, Sequence[Any]]) -> bool:
+40    return isinstance(value, collections.abc.Sequence) and all(
+41        is_valid_yaml_value(v) for v in value
+42    )
+43
+44
+45def is_valid_yaml_value(value: Any) -> bool:
+46    return any(
+47        is_valid(value)
+48        for is_valid in (
+49            is_valid_yaml_key,
+50            is_valid_yaml_mapping,
+51            is_valid_yaml_sequence,
+52        )
+53    )
+54
+55
+56def validate_unique_entries(seq: Sequence[Hashable]):
+57    if len(seq) != len(set(seq)):
+58        raise ValueError("Entries are not unique.")
+59    return seq
+60
+61
+62def validate_gh_user(username: str, hotfix_known_errorenous_names: bool = True) -> str:
+63    if hotfix_known_errorenous_names:
+64        if username == "Constantin Pape":
+65            return "constantinpape"
+66
+67    if (
+68        username.lower() in KNOWN_GH_USERS
+69        or not validation_context_var.get().perform_io_checks
+70    ):
+71        return username
+72
+73    if username.lower() in KNOWN_INVALID_GH_USERS:
+74        raise ValueError(f"Known invalid GitHub user '{username}'")
+75
+76    r = requests.get(
+77        f"https://api.github.com/users/{username}", auth=settings.github_auth
+78    )
+79    if r.status_code == 403 and r.reason == "rate limit exceeded":
+80        issue_warning(
+81            "Could not verify GitHub user '{value}' due to GitHub API rate limit",
+82            value=username,
+83        )
+84    elif r.status_code != 200:
+85        KNOWN_INVALID_GH_USERS.add(username.lower())
+86        raise ValueError(f"Could not find GitHub user '{username}'")
+87
+88    KNOWN_GH_USERS.add(username.lower())
+89    return username
 
      
 
 
             
-                
      
-                            
-
      
-                    
      @dataclasses.dataclass(frozen=True, **SLOTS)
      
-
-    class
-    RestrictCharacters:
-
-                
-
-    
      
-    
-            
      37@dataclasses.dataclass(frozen=True, **SLOTS)
-38class RestrictCharacters:
-39    alphabet: str
-40
-41    def __get_pydantic_core_schema__(
-42        self, source: Type[Any], handler: GetCoreSchemaHandler
-43    ) -> CoreSchema:
-44        if not self.alphabet:
-45            raise ValueError("Alphabet may not be empty")
-46        schema = handler(source)  # get the CoreSchema from the type / inner constraints
-47        if schema["type"] != "str":
-48            raise TypeError("RestrictCharacters can only be applied to strings")
-49        return no_info_after_validator_function(
-50            self.validate,
-51            schema,
-52        )
-53
-54    def validate(self, value: str) -> str:
-55        if any(c not in self.alphabet for c in value):
-56            raise ValueError(f"{value!r} is not restricted to {self.alphabet!r}")
-57        return value
-
      
-
-
-    
-
-                            
      
-                                
      
-            
-        RestrictCharacters(alphabet: str)
-
-        
-    
      
-    
-    
-    
-
-                            
      
-                            
      
-                                
      
-            alphabet: str
-
-        
-    
      
-    
-    
-    
-
-                            
      
-                            
      
-                                        
-
      
-            
-        def
-        validate(self, value: str) -> str:
-
-                
-
-    
      
-    
-            
      54    def validate(self, value: str) -> str:
-55        if any(c not in self.alphabet for c in value):
-56            raise ValueError(f"{value!r} is not restricted to {self.alphabet!r}")
-57        return value
-
      
-
-
-    
-
-                            
      
-                
      
                 
      
                             
 
      
@@ -360,8 +176,8 @@ 
      
 
     
      
     
-            
      60def is_valid_yaml_leaf_value(value: Any) -> bool:
-61    return value is None or isinstance(value, (bool, date, datetime, int, float, str))
+            
      22def is_valid_yaml_leaf_value(value: Any) -> bool:
+23    return value is None or isinstance(value, (bool, date, datetime, int, float, str))
 
      
 
 
@@ -379,12 +195,12 @@ 
      
 
     
      
     
-            
      64def is_valid_yaml_key(value: Union[Any, Sequence[Any]]) -> bool:
-65    return (
-66        is_valid_yaml_leaf_value(value)
-67        or isinstance(value, tuple)
-68        and all(is_valid_yaml_leaf_value(v) for v in value)
-69    )
+            
      26def is_valid_yaml_key(value: Union[Any, Sequence[Any]]) -> bool:
+27    return (
+28        is_valid_yaml_leaf_value(value)
+29        or isinstance(value, tuple)
+30        and all(is_valid_yaml_leaf_value(v) for v in value)
+31    )
 
      
 
 
@@ -402,10 +218,10 @@ 
      
 
     
      
     
-            
      72def is_valid_yaml_mapping(value: Union[Any, Mapping[Any, Any]]) -> bool:
-73    return isinstance(value, collections.abc.Mapping) and all(
-74        is_valid_yaml_key(k) and is_valid_yaml_value(v) for k, v in value.items()
-75    )
+            
      34def is_valid_yaml_mapping(value: Union[Any, Mapping[Any, Any]]) -> bool:
+35    return isinstance(value, collections.abc.Mapping) and all(
+36        is_valid_yaml_key(k) and is_valid_yaml_value(v) for k, v in value.items()
+37    )
 
      
 
 
@@ -423,10 +239,10 @@ 
      
 
     
      
     
-            
      78def is_valid_yaml_sequence(value: Union[Any, Sequence[Any]]) -> bool:
-79    return isinstance(value, collections.abc.Sequence) and all(
-80        is_valid_yaml_value(v) for v in value
-81    )
+            
      40def is_valid_yaml_sequence(value: Union[Any, Sequence[Any]]) -> bool:
+41    return isinstance(value, collections.abc.Sequence) and all(
+42        is_valid_yaml_value(v) for v in value
+43    )
 
      
 
 
@@ -444,15 +260,15 @@ 
      
 
     
      
     
-            
      84def is_valid_yaml_value(value: Any) -> bool:
-85    return any(
-86        is_valid(value)
-87        for is_valid in (
-88            is_valid_yaml_key,
-89            is_valid_yaml_mapping,
-90            is_valid_yaml_sequence,
-91        )
-92    )
+            
      46def is_valid_yaml_value(value: Any) -> bool:
+47    return any(
+48        is_valid(value)
+49        for is_valid in (
+50            is_valid_yaml_key,
+51            is_valid_yaml_mapping,
+52            is_valid_yaml_sequence,
+53        )
+54    )
 
      
 
 
@@ -470,144 +286,15 @@ 
      
 
     
      
     
-            
      95def validate_unique_entries(seq: Sequence[Hashable]):
-96    if len(seq) != len(set(seq)):
-97        raise ValueError("Entries are not unique.")
-98    return seq
+            
      57def validate_unique_entries(seq: Sequence[Hashable]):
+58    if len(seq) != len(set(seq)):
+59        raise ValueError("Entries are not unique.")
+60    return seq
 
      
 
 
     
 
-                
      
-                
      
-                            
-
      
-                    
      @dataclass(frozen=True, **SLOTS)
      
-
-    class
-    AfterValidator(pydantic.functional_validators.AfterValidator):
-
-                
-
-    
      
-    
-            
      102@dataclass(frozen=True, **SLOTS)
-103class AfterValidator(functional_validators.AfterValidator):
-104    def __str__(self):
-105        return f"AfterValidator({self.func.__name__})"
-
      
-
-
-    
-
-                            
      
-                                
      
-            
-        AfterValidator(	func: 'core_schema.NoInfoValidatorFunction | core_schema.WithInfoValidatorFunction')
-
-        
-    
      
-    
-    
-    
-
-                            
      
-                            
      
-                                
      Inherited Members
      
-                                
      
-                                    
      pydantic.functional_validators.AfterValidator
      
-                                
      func
      
-
-            
      
-                                
      
-                            
      
-                
      
-                
      
-                            
-
      
-                    
      @dataclass(frozen=True, **SLOTS)
      
-
-    class
-    BeforeValidator(pydantic.functional_validators.BeforeValidator):
-
-                
-
-    
      
-    
-            
      109@dataclass(frozen=True, **SLOTS)
-110class BeforeValidator(functional_validators.BeforeValidator):
-111    def __str__(self):
-112        return f"BeforeValidator({self.func.__name__})"
-
      
-
-
-    
-
-                            
      
-                                
      
-            
-        BeforeValidator(	func: 'core_schema.NoInfoValidatorFunction | core_schema.WithInfoValidatorFunction')
-
-        
-    
      
-    
-    
-    
-
-                            
      
-                            
      
-                                
      Inherited Members
      
-                                
      
-                                    
      pydantic.functional_validators.BeforeValidator
      
-                                
      func
      
-
-            
      
-                                
      
-                            
      
-                
      
-                
      
-                            
-
      
-                    
      @dataclass(frozen=True, **SLOTS)
      
-
-    class
-    Predicate(annotated_types.Predicate):
-
-                
-
-    
      
-    
-            
      116@dataclass(frozen=True, **SLOTS)
-117class Predicate(annotated_types.Predicate):
-118    def __str__(self):
-119        return f"Predicate({self.func.__name__})"
-
      
-
-
-    
-
-                            
      
-                                
      
-            
-        Predicate(func: Callable[[Any], bool])
-
-        
-    
      
-    
-    
-    
-
-                            
      
-                            
      
-                                
      Inherited Members
      
-                                
      
-                                    
      annotated_types.Predicate
      
-                                
      func
      
-
-            
      
-                                
      
-                            
      
                 
      
                 
      
                             
@@ -620,34 +307,34 @@ 
      Inherited Members
      
 
     
      
     
-            
      122def validate_gh_user(username: str, hotfix_known_errorenous_names: bool = True) -> str:
-123    if hotfix_known_errorenous_names:
-124        if username == "Constantin Pape":
-125            return "constantinpape"
-126
-127    if (
-128        username.lower() in KNOWN_GH_USERS
-129        or not validation_context_var.get().perform_io_checks
-130    ):
-131        return username
-132
-133    if username.lower() in KNOWN_INVALID_GH_USERS:
-134        raise ValueError(f"Known invalid GitHub user '{username}'")
-135
-136    r = requests.get(
-137        f"https://api.github.com/users/{username}", auth=settings.github_auth
-138    )
-139    if r.status_code == 403 and r.reason == "rate limit exceeded":
-140        issue_warning(
-141            "Could not verify GitHub user '{value}' due to GitHub API rate limit",
-142            value=username,
-143        )
-144    elif r.status_code != 200:
-145        KNOWN_INVALID_GH_USERS.add(username.lower())
-146        raise ValueError(f"Could not find GitHub user '{username}'")
-147
-148    KNOWN_GH_USERS.add(username.lower())
-149    return username
+            
      63def validate_gh_user(username: str, hotfix_known_errorenous_names: bool = True) -> str:
+64    if hotfix_known_errorenous_names:
+65        if username == "Constantin Pape":
+66            return "constantinpape"
+67
+68    if (
+69        username.lower() in KNOWN_GH_USERS
+70        or not validation_context_var.get().perform_io_checks
+71    ):
+72        return username
+73
+74    if username.lower() in KNOWN_INVALID_GH_USERS:
+75        raise ValueError(f"Known invalid GitHub user '{username}'")
+76
+77    r = requests.get(
+78        f"https://api.github.com/users/{username}", auth=settings.github_auth
+79    )
+80    if r.status_code == 403 and r.reason == "rate limit exceeded":
+81        issue_warning(
+82            "Could not verify GitHub user '{value}' due to GitHub API rate limit",
+83            value=username,
+84        )
+85    elif r.status_code != 200:
+86        KNOWN_INVALID_GH_USERS.add(username.lower())
+87        raise ValueError(f"Could not find GitHub user '{username}'")
+88
+89    KNOWN_GH_USERS.add(username.lower())
+90    return username
 
      
 
 
diff --git a/bioimageio/spec/_internal/io.html b/bioimageio/spec/_internal/io.html
index 5c73409b4..eda60c0dc 100644
--- a/bioimageio/spec/_internal/io.html
+++ b/bioimageio/spec/_internal/io.html
@@ -298,46 +298,46 @@ 
      
  26import pooch
  27import pydantic
  28from pydantic import (
- 29    AfterValidator,
- 30    AnyUrl,
- 31    DirectoryPath,
- 32    FilePath,
- 33    GetCoreSchemaHandler,
- 34    PlainSerializer,
- 35    PrivateAttr,
- 36    RootModel,
- 37    SerializationInfo,
- 38    StringConstraints,
- 39    TypeAdapter,
- 40    model_validator,
- 41)
- 42from pydantic_core import core_schema
- 43from typing_extensions import (
- 44    Annotated,
- 45    LiteralString,
- 46    NotRequired,
- 47    Self,
- 48    Unpack,
- 49    assert_never,
- 50)
- 51from typing_extensions import TypeAliasType as _TypeAliasType
- 52
- 53from .._internal._settings import settings
- 54from .._internal.io_basics import (
- 55    ALL_BIOIMAGEIO_YAML_NAMES,
- 56    BIOIMAGEIO_YAML,
- 57    AbsoluteDirectory,
- 58    AbsoluteFilePath,
- 59    FileName,
- 60)
- 61from .._internal.node import Node
- 62from .._internal.packaging_context import packaging_context_var
- 63from .._internal.root_url import RootHttpUrl
- 64from .._internal.url import HttpUrl
- 65from .._internal.validated_string import ValidatedString
- 66from .._internal.validation_context import (
- 67    validation_context_var,
- 68)
+ 29    AnyUrl,
+ 30    DirectoryPath,
+ 31    FilePath,
+ 32    GetCoreSchemaHandler,
+ 33    PlainSerializer,
+ 34    PrivateAttr,
+ 35    RootModel,
+ 36    SerializationInfo,
+ 37    StringConstraints,
+ 38    TypeAdapter,
+ 39    model_validator,
+ 40)
+ 41from pydantic_core import core_schema
+ 42from typing_extensions import (
+ 43    Annotated,
+ 44    LiteralString,
+ 45    NotRequired,
+ 46    Self,
+ 47    Unpack,
+ 48    assert_never,
+ 49)
+ 50from typing_extensions import TypeAliasType as _TypeAliasType
+ 51
+ 52from .._internal._settings import settings
+ 53from .._internal.io_basics import (
+ 54    ALL_BIOIMAGEIO_YAML_NAMES,
+ 55    BIOIMAGEIO_YAML,
+ 56    AbsoluteDirectory,
+ 57    AbsoluteFilePath,
+ 58    FileName,
+ 59)
+ 60from .._internal.node import Node
+ 61from .._internal.packaging_context import packaging_context_var
+ 62from .._internal.root_url import RootHttpUrl
+ 63from .._internal.url import HttpUrl
+ 64from .._internal.validated_string import ValidatedString
+ 65from .._internal.validation_context import (
+ 66    validation_context_var,
+ 67)
+ 68from .validator_annotations import AfterValidator
  69
  70if sys.version_info < (3, 10):
  71    SLOTS: Dict[str, bool] = {}
@@ -1237,7 +1237,7 @@ 
      Inherited Members
      
 
      
             
         def
-        get_absolute(	self,	root: bioimageio.spec._internal.root_url.RootHttpUrl | pathlib.Path | pydantic_core._pydantic_core.Url) -> Union[Annotated[pathlib.Path, PathType(path_type='file'), Predicate(func=<function PurePath.is_absolute at 0x7f1c25245940>)], Annotated[pathlib.Path, PathType(path_type='dir'), Predicate(func=<function PurePath.is_absolute at 0x7f1c25245940>)], bioimageio.spec._internal.url.HttpUrl]:
+        get_absolute(	self,	root: bioimageio.spec._internal.root_url.RootHttpUrl | pathlib.Path | pydantic_core._pydantic_core.Url) -> Union[Annotated[pathlib.Path, PathType(path_type='file'), Predicate(func=<function PurePath.is_absolute at 0x7afca4145940>)], Annotated[pathlib.Path, PathType(path_type='dir'), Predicate(func=<function PurePath.is_absolute at 0x7afca4145940>)], bioimageio.spec._internal.url.HttpUrl]:
 
                 
 
@@ -1355,7 +1355,7 @@ 
      Inherited Members
      
 
      
             
         def
-        get_absolute(	self,	root: bioimageio.spec._internal.root_url.RootHttpUrl | pathlib.Path | pydantic_core._pydantic_core.Url) -> Union[Annotated[pathlib.Path, PathType(path_type='file'), Predicate(func=<function PurePath.is_absolute at 0x7f1c25245940>)], bioimageio.spec._internal.url.HttpUrl]:
+        get_absolute(	self,	root: bioimageio.spec._internal.root_url.RootHttpUrl | pathlib.Path | pydantic_core._pydantic_core.Url) -> Union[Annotated[pathlib.Path, PathType(path_type='file'), Predicate(func=<function PurePath.is_absolute at 0x7afca4145940>)], bioimageio.spec._internal.url.HttpUrl]:
 
                 
 
@@ -1475,7 +1475,7 @@ 
      Inherited Members
      
 
      
             
         def
-        get_absolute(	self,	root: bioimageio.spec._internal.root_url.RootHttpUrl | pathlib.Path | pydantic_core._pydantic_core.Url) -> Union[Annotated[pathlib.Path, PathType(path_type='dir'), Predicate(func=<function PurePath.is_absolute at 0x7f1c25245940>)], bioimageio.spec._internal.url.HttpUrl]:
+        get_absolute(	self,	root: bioimageio.spec._internal.root_url.RootHttpUrl | pathlib.Path | pydantic_core._pydantic_core.Url) -> Union[Annotated[pathlib.Path, PathType(path_type='dir'), Predicate(func=<function PurePath.is_absolute at 0x7afca4145940>)], bioimageio.spec._internal.url.HttpUrl]:
 
                 
 
@@ -1997,7 +1997,7 @@ 
      Inherited Members
      
                             
      
                             
      
                                 
      
-            original_root: Union[Annotated[pathlib.Path, PathType(path_type='dir'), Predicate(func=<function PurePath.is_absolute at 0x7f1c25245940>)], bioimageio.spec._internal.root_url.RootHttpUrl]
+            original_root: Union[Annotated[pathlib.Path, PathType(path_type='dir'), Predicate(func=<function PurePath.is_absolute at 0x7afca4145940>)], bioimageio.spec._internal.root_url.RootHttpUrl]
 
         
     
      
@@ -2065,7 +2065,7 @@ 
      Inherited Members
      
                             
      
                             
      
                                 
      
-            original_root: Union[Annotated[pathlib.Path, PathType(path_type='dir'), Predicate(func=<function PurePath.is_absolute at 0x7f1c25245940>)], bioimageio.spec._internal.root_url.RootHttpUrl]
+            original_root: Union[Annotated[pathlib.Path, PathType(path_type='dir'), Predicate(func=<function PurePath.is_absolute at 0x7afca4145940>)], bioimageio.spec._internal.root_url.RootHttpUrl]
 
         
     
      
@@ -2284,7 +2284,7 @@ 
      Inherited Members
      
 
                             
      
                                 
      
-            source: Annotated[Union[Annotated[pathlib.Path, PathType(path_type='file')], RelativeFilePath, bioimageio.spec._internal.url.HttpUrl, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator(func=<function wo_special_file_name at 0x7f1c21c3ef20>), PlainSerializer(func=<function _package at 0x7f1c21c782c0>, return_type=PydanticUndefined, when_used='unless-none')]
+            source: Annotated[Union[Annotated[pathlib.Path, PathType(path_type='file')], RelativeFilePath, bioimageio.spec._internal.url.HttpUrl, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator(func=<function wo_special_file_name at 0x7afca0d90540>), PlainSerializer(func=<function _package at 0x7afca0d91760>, return_type=PydanticUndefined, when_used='unless-none')]
 
         
     
      
diff --git a/bioimageio/spec/_internal/io_utils.html b/bioimageio/spec/_internal/io_utils.html
index b6a95dc6a..964aef92a 100644
--- a/bioimageio/spec/_internal/io_utils.html
+++ b/bioimageio/spec/_internal/io_utils.html
@@ -43,10 +43,10 @@ 
      API Documentation
      
                     open_bioimageio_yaml
             
             
    • 
-                    identify_bioimageio_yaml_file
+                    identify_bioimageio_yaml_file_name
             
      • 
             
    • 
-                    find_description_file_name
+                    find_bioimageio_yaml_file_name
             
      • 
             
    • 
                     unzip
@@ -167,14 +167,14 @@ 
      
  84
  85    if local_source.is_dir():
  86        root = local_source
- 87        local_source = local_source / find_description_file_name(local_source)
+ 87        local_source = local_source / find_bioimageio_yaml_file_name(local_source)
  88
  89    content = _sanitize_bioimageio_yaml(read_yaml(local_source))
  90
  91    return OpenedBioimageioYaml(content, root, downloaded.original_file_name)
  92
  93
- 94def identify_bioimageio_yaml_file(file_names: Iterable[FileName]) -> FileName:
+ 94def identify_bioimageio_yaml_file_name(file_names: Iterable[FileName]) -> FileName:
  95    file_names = sorted(file_names)
  96    for bioimageio_name in ALL_BIOIMAGEIO_YAML_NAMES:
  97        for fname in file_names:
@@ -189,17 +189,17 @@ 
      
 106    )
 107
 108
-109def find_description_file_name(path: Path) -> FileName:
+109def find_bioimageio_yaml_file_name(path: Path) -> FileName:
 110    if path.is_file():
 111        if not is_zipfile(path):
 112            return path.name
 113
 114        with ZipFile(path, "r") as f:
-115            file_names = identify_bioimageio_yaml_file(f.namelist())
+115            file_names = identify_bioimageio_yaml_file_name(f.namelist())
 116    else:
 117        file_names = [p.name for p in path.glob("*")]
 118
-119    return identify_bioimageio_yaml_file(file_names)
+119    return identify_bioimageio_yaml_file_name(file_names)
 120
 121
 122def unzip(
@@ -383,7 +383,7 @@ 
      
 85
 86    if local_source.is_dir():
 87        root = local_source
-88        local_source = local_source / find_description_file_name(local_source)
+88        local_source = local_source / find_bioimageio_yaml_file_name(local_source)
 89
 90    content = _sanitize_bioimageio_yaml(read_yaml(local_source))
 91
@@ -394,58 +394,58 @@ 
      
     
 
                 
-                
      
-                            
+                
      
+                            
 
      
             
         def
-        identify_bioimageio_yaml_file(file_names: Iterable[str]) -> str:
+        identify_bioimageio_yaml_file_name(file_names: Iterable[str]) -> str:
 
-                
+                
 
     
      
-    
-            
       95def identify_bioimageio_yaml_file(file_names: Iterable[FileName]) -> FileName:
- 96    file_names = sorted(file_names)
- 97    for bioimageio_name in ALL_BIOIMAGEIO_YAML_NAMES:
- 98        for fname in file_names:
- 99            if fname == bioimageio_name or fname.endswith(f".{bioimageio_name}"):
-100                return fname
-101
-102    raise ValueError(
-103        f"No {BIOIMAGEIO_YAML} found in {file_names}. (Looking for '{BIOIMAGEIO_YAML}'"
-104        + " or or any of the alterntive file names:"
-105        + f" {ALTERNATIVE_BIOIMAGEIO_YAML_NAMES}, or any file with an extension of"
-106        + f"  those, e.g. 'anything.{BIOIMAGEIO_YAML}')."
-107    )
+    
+            
       95def identify_bioimageio_yaml_file_name(file_names: Iterable[FileName]) -> FileName:
+ 96    file_names = sorted(file_names)
+ 97    for bioimageio_name in ALL_BIOIMAGEIO_YAML_NAMES:
+ 98        for fname in file_names:
+ 99            if fname == bioimageio_name or fname.endswith(f".{bioimageio_name}"):
+100                return fname
+101
+102    raise ValueError(
+103        f"No {BIOIMAGEIO_YAML} found in {file_names}. (Looking for '{BIOIMAGEIO_YAML}'"
+104        + " or or any of the alterntive file names:"
+105        + f" {ALTERNATIVE_BIOIMAGEIO_YAML_NAMES}, or any file with an extension of"
+106        + f"  those, e.g. 'anything.{BIOIMAGEIO_YAML}')."
+107    )
 
      
 
 
     
 
                 
      
-                
      
-                            
+                
      
+                            
 
      
             
         def
-        find_description_file_name(path: pathlib.Path) -> str:
+        find_bioimageio_yaml_file_name(path: pathlib.Path) -> str:
 
-                
+                
 
     
      
-    
-            
      110def find_description_file_name(path: Path) -> FileName:
-111    if path.is_file():
-112        if not is_zipfile(path):
-113            return path.name
-114
-115        with ZipFile(path, "r") as f:
-116            file_names = identify_bioimageio_yaml_file(f.namelist())
-117    else:
-118        file_names = [p.name for p in path.glob("*")]
-119
-120    return identify_bioimageio_yaml_file(file_names)
+    
+            
      110def find_bioimageio_yaml_file_name(path: Path) -> FileName:
+111    if path.is_file():
+112        if not is_zipfile(path):
+113            return path.name
+114
+115        with ZipFile(path, "r") as f:
+116            file_names = identify_bioimageio_yaml_file_name(f.namelist())
+117    else:
+118        file_names = [p.name for p in path.glob("*")]
+119
+120    return identify_bioimageio_yaml_file_name(file_names)
 
      
 
 
diff --git a/bioimageio/spec/_internal/packaging_context.html b/bioimageio/spec/_internal/packaging_context.html
index 9c2218716..788cb0d07 100644
--- a/bioimageio/spec/_internal/packaging_context.html
+++ b/bioimageio/spec/_internal/packaging_context.html
@@ -207,7 +207,7 @@ 
      
                             
      
                             
      
                                 
      
-            file_sources: Dict[str, Union[Annotated[pathlib.Path, PathType(path_type='file'), Predicate(func=<function PurePath.is_absolute at 0x7f1c25245940>)], bioimageio.spec._internal.url.HttpUrl]]
+            file_sources: Dict[str, Union[Annotated[pathlib.Path, PathType(path_type='file'), Predicate(func=<function PurePath.is_absolute at 0x7afca4145940>)], bioimageio.spec._internal.url.HttpUrl]]
 
         
     
      
diff --git a/bioimageio/spec/_internal/root_url.html b/bioimageio/spec/_internal/root_url.html
index e44a3549b..eb1237c5f 100644
--- a/bioimageio/spec/_internal/root_url.html
+++ b/bioimageio/spec/_internal/root_url.html
@@ -75,65 +75,66 @@ 
      
  4from urllib.parse import urlsplit, urlunsplit
  5
  6import pydantic
- 7from pydantic import AfterValidator, TypeAdapter
+ 7from pydantic import TypeAdapter
  8from typing_extensions import Annotated
  9
 10from .validated_string import ValidatedString
-11
-12_http_url_adapter = TypeAdapter(pydantic.HttpUrl)  # pyright: ignore[reportCallIssue]
-13
+11from .validator_annotations import AfterValidator
+12
+13_http_url_adapter = TypeAdapter(pydantic.HttpUrl)  # pyright: ignore[reportCallIssue]
 14
-15class RootHttpUrl(
-16    ValidatedString[
-17        Annotated[
-18            str,
-19            AfterValidator(lambda value: str(_http_url_adapter.validate_python(value))),
-20        ]
-21    ],
-22    frozen=True,
-23):
-24    """A 'URL folder', possibly an invalid http URL"""
-25
-26    @property
-27    def _url(self):
-28        return pydantic.AnyUrl(str(self))
-29
-30    @property
-31    def scheme(self) -> str:
-32        return self._url.scheme
-33
-34    @property
-35    def host(self) -> Optional[str]:
-36        return self._url.host
-37
-38    @property
-39    def path(self) -> Optional[str]:
-40        return self._url.path
-41
-42    @property
-43    def parent(self) -> RootHttpUrl:
-44        parsed = urlsplit(str(self))
-45        path = list(parsed.path.split("/"))
-46        if (
-47            parsed.netloc == "zenodo.org"
-48            and parsed.path.startswith("/api/records/")
-49            and parsed.path.endswith("/content")
-50        ):
-51            path[-2:-1] = []
-52        else:
-53            path = path[:-1]
-54
-55        return RootHttpUrl(
-56            urlunsplit(
-57                (
-58                    parsed.scheme,
-59                    parsed.netloc,
-60                    "/".join(path),
-61                    parsed.query,
-62                    parsed.fragment,
-63                )
-64            )
-65        )
+15
+16class RootHttpUrl(
+17    ValidatedString[
+18        Annotated[
+19            str,
+20            AfterValidator(lambda value: str(_http_url_adapter.validate_python(value))),
+21        ]
+22    ],
+23    frozen=True,
+24):
+25    """A 'URL folder', possibly an invalid http URL"""
+26
+27    @property
+28    def _url(self):
+29        return pydantic.AnyUrl(str(self))
+30
+31    @property
+32    def scheme(self) -> str:
+33        return self._url.scheme
+34
+35    @property
+36    def host(self) -> Optional[str]:
+37        return self._url.host
+38
+39    @property
+40    def path(self) -> Optional[str]:
+41        return self._url.path
+42
+43    @property
+44    def parent(self) -> RootHttpUrl:
+45        parsed = urlsplit(str(self))
+46        path = list(parsed.path.split("/"))
+47        if (
+48            parsed.netloc == "zenodo.org"
+49            and parsed.path.startswith("/api/records/")
+50            and parsed.path.endswith("/content")
+51        ):
+52            path[-2:-1] = []
+53        else:
+54            path = path[:-1]
+55
+56        return RootHttpUrl(
+57            urlunsplit(
+58                (
+59                    parsed.scheme,
+60                    parsed.netloc,
+61                    "/".join(path),
+62                    parsed.query,
+63                    parsed.fragment,
+64                )
+65            )
+66        )
 
      • 
 
 
@@ -149,57 +150,57 @@ 
      
 
     
    
     
-            
    16class RootHttpUrl(
-17    ValidatedString[
-18        Annotated[
-19            str,
-20            AfterValidator(lambda value: str(_http_url_adapter.validate_python(value))),
-21        ]
-22    ],
-23    frozen=True,
-24):
-25    """A 'URL folder', possibly an invalid http URL"""
-26
-27    @property
-28    def _url(self):
-29        return pydantic.AnyUrl(str(self))
-30
-31    @property
-32    def scheme(self) -> str:
-33        return self._url.scheme
-34
-35    @property
-36    def host(self) -> Optional[str]:
-37        return self._url.host
-38
-39    @property
-40    def path(self) -> Optional[str]:
-41        return self._url.path
-42
-43    @property
-44    def parent(self) -> RootHttpUrl:
-45        parsed = urlsplit(str(self))
-46        path = list(parsed.path.split("/"))
-47        if (
-48            parsed.netloc == "zenodo.org"
-49            and parsed.path.startswith("/api/records/")
-50            and parsed.path.endswith("/content")
-51        ):
-52            path[-2:-1] = []
-53        else:
-54            path = path[:-1]
-55
-56        return RootHttpUrl(
-57            urlunsplit(
-58                (
-59                    parsed.scheme,
-60                    parsed.netloc,
-61                    "/".join(path),
-62                    parsed.query,
-63                    parsed.fragment,
-64                )
-65            )
-66        )
+            
    17class RootHttpUrl(
+18    ValidatedString[
+19        Annotated[
+20            str,
+21            AfterValidator(lambda value: str(_http_url_adapter.validate_python(value))),
+22        ]
+23    ],
+24    frozen=True,
+25):
+26    """A 'URL folder', possibly an invalid http URL"""
+27
+28    @property
+29    def _url(self):
+30        return pydantic.AnyUrl(str(self))
+31
+32    @property
+33    def scheme(self) -> str:
+34        return self._url.scheme
+35
+36    @property
+37    def host(self) -> Optional[str]:
+38        return self._url.host
+39
+40    @property
+41    def path(self) -> Optional[str]:
+42        return self._url.path
+43
+44    @property
+45    def parent(self) -> RootHttpUrl:
+46        parsed = urlsplit(str(self))
+47        path = list(parsed.path.split("/"))
+48        if (
+49            parsed.netloc == "zenodo.org"
+50            and parsed.path.startswith("/api/records/")
+51            and parsed.path.endswith("/content")
+52        ):
+53            path[-2:-1] = []
+54        else:
+55            path = path[:-1]
+56
+57        return RootHttpUrl(
+58            urlunsplit(
+59                (
+60                    parsed.scheme,
+61                    parsed.netloc,
+62                    "/".join(path),
+63                    parsed.query,
+64                    parsed.fragment,
+65                )
+66            )
+67        )
 
    
 
 
@@ -216,9 +217,9 @@ 
    
 
     
    
     
-            
    31    @property
-32    def scheme(self) -> str:
-33        return self._url.scheme
+            
    32    @property
+33    def scheme(self) -> str:
+34        return self._url.scheme
 
    
 
 
@@ -234,9 +235,9 @@ 
    
 
     
    
     
-            
    35    @property
-36    def host(self) -> Optional[str]:
-37        return self._url.host
+            
    36    @property
+37    def host(self) -> Optional[str]:
+38        return self._url.host
 
    
 
 
@@ -252,9 +253,9 @@ 
    
 
     
    
     
-            
    39    @property
-40    def path(self) -> Optional[str]:
-41        return self._url.path
+            
    40    @property
+41    def path(self) -> Optional[str]:
+42        return self._url.path
 
    
 
 
@@ -270,30 +271,30 @@ 
    
 
     
    
     
-            
    43    @property
-44    def parent(self) -> RootHttpUrl:
-45        parsed = urlsplit(str(self))
-46        path = list(parsed.path.split("/"))
-47        if (
-48            parsed.netloc == "zenodo.org"
-49            and parsed.path.startswith("/api/records/")
-50            and parsed.path.endswith("/content")
-51        ):
-52            path[-2:-1] = []
-53        else:
-54            path = path[:-1]
-55
-56        return RootHttpUrl(
-57            urlunsplit(
-58                (
-59                    parsed.scheme,
-60                    parsed.netloc,
-61                    "/".join(path),
-62                    parsed.query,
-63                    parsed.fragment,
-64                )
-65            )
-66        )
+            
    44    @property
+45    def parent(self) -> RootHttpUrl:
+46        parsed = urlsplit(str(self))
+47        path = list(parsed.path.split("/"))
+48        if (
+49            parsed.netloc == "zenodo.org"
+50            and parsed.path.startswith("/api/records/")
+51            and parsed.path.endswith("/content")
+52        ):
+53            path[-2:-1] = []
+54        else:
+55            path = path[:-1]
+56
+57        return RootHttpUrl(
+58            urlunsplit(
+59                (
+60                    parsed.scheme,
+61                    parsed.netloc,
+62                    "/".join(path),
+63                    parsed.query,
+64                    parsed.fragment,
+65                )
+66            )
+67        )
 
    
 
 
diff --git a/bioimageio/spec/_internal/types.html b/bioimageio/spec/_internal/types.html
index 34b9d514b..84415a3ae 100644
--- a/bioimageio/spec/_internal/types.html
+++ b/bioimageio/spec/_internal/types.html
@@ -114,19 +114,19 @@ 
    
  10from typing_extensions import Annotated, Literal
  11
  12from .constants import DOI_REGEX, SI_UNIT_REGEX
- 13from .field_validation import AfterValidator, BeforeValidator
- 14from .io import FileSource as FileSource
- 15from .io import ImportantFileSource as ImportantFileSource
- 16from .io import PermissiveFileSource as PermissiveFileSource
- 17from .io import RelativeFilePath as RelativeFilePath
- 18from .io import Sha256 as Sha256
- 19from .io_basics import AbsoluteDirectory as AbsoluteDirectory
- 20from .io_basics import AbsoluteFilePath as AbsoluteFilePath
- 21from .io_basics import FileName as FileName
- 22from .license_id import DeprecatedLicenseId as DeprecatedLicenseId
- 23from .license_id import LicenseId as LicenseId
- 24from .url import HttpUrl as HttpUrl
- 25from .validated_string import ValidatedString
+ 13from .io import FileSource as FileSource
+ 14from .io import ImportantFileSource as ImportantFileSource
+ 15from .io import PermissiveFileSource as PermissiveFileSource
+ 16from .io import RelativeFilePath as RelativeFilePath
+ 17from .io import Sha256 as Sha256
+ 18from .io_basics import AbsoluteDirectory as AbsoluteDirectory
+ 19from .io_basics import AbsoluteFilePath as AbsoluteFilePath
+ 20from .io_basics import FileName as FileName
+ 21from .license_id import DeprecatedLicenseId as DeprecatedLicenseId
+ 22from .license_id import LicenseId as LicenseId
+ 23from .url import HttpUrl as HttpUrl
+ 24from .validated_string import ValidatedString
+ 25from .validator_annotations import AfterValidator, BeforeValidator
  26from .version_type import Version as Version
  27
  28S = TypeVar("S", bound=Sequence[Any])
diff --git a/bioimageio/spec/_internal/validated_string.html b/bioimageio/spec/_internal/validated_string.html
index 14d90ef4c..734e48965 100644
--- a/bioimageio/spec/_internal/validated_string.html
+++ b/bioimageio/spec/_internal/validated_string.html
@@ -90,9 +90,6 @@ 
    API Documentation
    
                 
 
             
-            
  • 
-                    ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]_
-            
    • 
     
 
 
@@ -735,19 +732,6 @@ 
    Inherited Members
    - -
    -
    - ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]_ = - - <class 'ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]'> - - -
    - - - -
    + \ No newline at end of file diff --git a/bioimageio/spec/_package.html b/bioimageio/spec/_package.html index df7be84fc..0d0f23556 100644 --- a/bioimageio/spec/_package.html +++ b/bioimageio/spec/_package.html @@ -350,7 +350,7 @@

    def - get_resource_package_content( rd: Union[Annotated[Union[Annotated[Union[bioimageio.spec.application.v0_2.ApplicationDescr, bioimageio.spec.application.v0_3.ApplicationDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.collection.v0_2.CollectionDescr, bioimageio.spec.collection.v0_3.CollectionDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.dataset.v0_2.DatasetDescr, bioimageio.spec.dataset.v0_3.DatasetDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.model.v0_4.ModelDescr, bioimageio.spec.model.v0_5.ModelDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.notebook.v0_2.NotebookDescr, bioimageio.spec.notebook.v0_3.NotebookDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)]], Discriminator(discriminator='type', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.generic.v0_2.GenericDescr, bioimageio.spec.generic.v0_3.GenericDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)]], /, *, bioimageio_yaml_file_name: str = 'rdf.yaml', weights_priority_order: Optional[Sequence[Literal['keras_hdf5', 'onnx', 'pytorch_state_dict', 'tensorflow_js', 'tensorflow_saved_model_bundle', 'torchscript']]] = None) -> Dict[str, Union[bioimageio.spec._internal.url.HttpUrl, Annotated[pathlib.Path, PathType(path_type='file'), Predicate(func=<function PurePath.is_absolute at 0x7f1c25245940>)], Dict[str, YamlValue]]]: + get_resource_package_content( rd: Union[Annotated[Union[Annotated[Union[bioimageio.spec.application.v0_2.ApplicationDescr, bioimageio.spec.application.v0_3.ApplicationDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.collection.v0_2.CollectionDescr, bioimageio.spec.collection.v0_3.CollectionDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.dataset.v0_2.DatasetDescr, bioimageio.spec.dataset.v0_3.DatasetDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.model.v0_4.ModelDescr, bioimageio.spec.model.v0_5.ModelDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.notebook.v0_2.NotebookDescr, bioimageio.spec.notebook.v0_3.NotebookDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)]], Discriminator(discriminator='type', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.generic.v0_2.GenericDescr, bioimageio.spec.generic.v0_3.GenericDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)]], /, *, bioimageio_yaml_file_name: str = 'rdf.yaml', weights_priority_order: Optional[Sequence[Literal['keras_hdf5', 'onnx', 'pytorch_state_dict', 'tensorflow_js', 'tensorflow_saved_model_bundle', 'torchscript']]] = None) -> Dict[str, Union[bioimageio.spec._internal.url.HttpUrl, Annotated[pathlib.Path, PathType(path_type='file'), Predicate(func=<function PurePath.is_absolute at 0x7afca4145940>)], Dict[str, YamlValue]]]: diff --git a/bioimageio/spec/application/v0_2.html b/bioimageio/spec/application/v0_2.html index b6578d94f..4b448a23c 100644 --- a/bioimageio/spec/application/v0_2.html +++ b/bioimageio/spec/application/v0_2.html @@ -211,7 +211,7 @@

    - source: Annotated[Optional[Annotated[Union[Annotated[pathlib.Path, PathType(path_type='file')], bioimageio.spec._internal.io.RelativeFilePath, bioimageio.spec._internal.url.HttpUrl, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator(func=<function wo_special_file_name at 0x7f1c21c3ef20>), PlainSerializer(func=<function _package at 0x7f1c21c782c0>, return_type=PydanticUndefined, when_used='unless-none')]], FieldInfo(annotation=NoneType, required=True, description='URL or path to the source of the application')] + source: Annotated[Optional[Annotated[Union[Annotated[pathlib.Path, PathType(path_type='file')], bioimageio.spec._internal.io.RelativeFilePath, bioimageio.spec._internal.url.HttpUrl, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator(func=<function wo_special_file_name at 0x7afca0d90540>), PlainSerializer(func=<function _package at 0x7afca0d91760>, return_type=PydanticUndefined, when_used='unless-none')]], FieldInfo(annotation=NoneType, required=True, description='URL or path to the source of the application')]
    diff --git a/bioimageio/spec/application/v0_3.html b/bioimageio/spec/application/v0_3.html index 4eea5f920..ba4c58df4 100644 --- a/bioimageio/spec/application/v0_3.html +++ b/bioimageio/spec/application/v0_3.html @@ -234,7 +234,7 @@

    - source: Annotated[Optional[Annotated[Union[Annotated[pathlib.Path, PathType(path_type='file')], bioimageio.spec._internal.io.RelativeFilePath, bioimageio.spec._internal.url.HttpUrl, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator(func=<function wo_special_file_name at 0x7f1c21c3ef20>), PlainSerializer(func=<function _package at 0x7f1c21c782c0>, return_type=PydanticUndefined, when_used='unless-none')]], FieldInfo(annotation=NoneType, required=True, description='URL or path to the source of the application')] + source: Annotated[Optional[Annotated[Union[Annotated[pathlib.Path, PathType(path_type='file')], bioimageio.spec._internal.io.RelativeFilePath, bioimageio.spec._internal.url.HttpUrl, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator(func=<function wo_special_file_name at 0x7afca0d90540>), PlainSerializer(func=<function _package at 0x7afca0d91760>, return_type=PydanticUndefined, when_used='unless-none')]], FieldInfo(annotation=NoneType, required=True, description='URL or path to the source of the application')]
    diff --git a/bioimageio/spec/common.html b/bioimageio/spec/common.html index e4f58901d..f303d1d05 100644 --- a/bioimageio/spec/common.html +++ b/bioimageio/spec/common.html @@ -56,11 +56,14 @@

    7from ._internal.io import Sha256 as Sha256 8from ._internal.io import YamlValue as YamlValue 9from ._internal.io_basics import FileName as FileName -10from ._internal.root_url import RootHttpUrl as RootHttpUrl -11from ._internal.types import FileSource as FileSource -12from ._internal.types import PermissiveFileSource as PermissiveFileSource -13from ._internal.types import RelativeFilePath as RelativeFilePath -14from ._internal.url import HttpUrl as HttpUrl +10from ._internal.io_utils import ( +11 identify_bioimageio_yaml_file_name as identify_bioimageio_yaml_file_name, +12) +13from ._internal.root_url import RootHttpUrl as RootHttpUrl +14from ._internal.types import FileSource as FileSource +15from ._internal.types import PermissiveFileSource as PermissiveFileSource +16from ._internal.types import RelativeFilePath as RelativeFilePath +17from ._internal.url import HttpUrl as HttpUrl

    diff --git a/bioimageio/spec/generic/v0_2.html b/bioimageio/spec/generic/v0_2.html index 17f608786..241844ea0 100644 --- a/bioimageio/spec/generic/v0_2.html +++ b/bioimageio/spec/generic/v0_2.html @@ -376,419 +376,417 @@

    17 18from .._internal.common_nodes import Node, ResourceDescrBase 19from .._internal.constants import TAG_CATEGORIES - 20from .._internal.field_validation import ( - 21 AfterValidator as _AfterValidator, - 22) - 23from .._internal.field_warning import as_warning, issue_warning, warn - 24from .._internal.io import ( - 25 BioimageioYamlContent, - 26 WithSuffix, - 27 YamlValue, - 28 include_in_package_serializer, - 29) - 30from .._internal.io_basics import AbsoluteFilePath as AbsoluteFilePath - 31from .._internal.types import ( - 32 DeprecatedLicenseId, - 33 FileSource, - 34 ImportantFileSource, - 35 LicenseId, - 36 NotEmpty, - 37) - 38from .._internal.types import Doi as Doi - 39from .._internal.types import OrcidId as OrcidId - 40from .._internal.types import RelativeFilePath as RelativeFilePath - 41from .._internal.types import ResourceId as ResourceId - 42from .._internal.url import HttpUrl as HttpUrl - 43from .._internal.version_type import Version as Version - 44from ._v0_2_converter import convert_from_older_format as _convert_from_older_format - 45 - 46KNOWN_SPECIFIC_RESOURCE_TYPES = ( - 47 "application", - 48 "collection", - 49 "dataset", - 50 "model", - 51 "notebook", - 52) - 53 - 54VALID_COVER_IMAGE_EXTENSIONS = ( - 55 ".gif", - 56 ".jpeg", - 57 ".jpg", - 58 ".png", - 59 ".svg", - 60) - 61 - 62_WithImageSuffix = WithSuffix(VALID_COVER_IMAGE_EXTENSIONS, case_sensitive=False) - 63CoverImageSource = Annotated[ - 64 Union[HttpUrl, AbsoluteFilePath, RelativeFilePath], - 65 _WithImageSuffix, - 66 include_in_package_serializer, - 67] - 68 - 69 - 70class AttachmentsDescr(Node): - 71 model_config = {**Node.model_config, "extra": "allow"} - 72 """update pydantic model config to allow additional unknown keys""" - 73 files: List[ImportantFileSource] = Field(default_factory=list) - 74 """∈📦 File attachments""" - 75 - 76 - 77def _remove_slashes(s: str): - 78 return s.replace("/", "").replace("\\", "") - 79 - 80 - 81class Uploader(Node): - 82 email: EmailStr - 83 """Email""" - 84 name: Optional[Annotated[str, _AfterValidator(_remove_slashes)]] = None - 85 """name""" - 86 - 87 - 88class _Person(Node): - 89 affiliation: Optional[str] = None - 90 """Affiliation""" - 91 - 92 email: Optional[EmailStr] = None - 93 """Email""" - 94 - 95 orcid: Annotated[Optional[OrcidId], Field(examples=["0000-0001-2345-6789"])] = None - 96 """An [ORCID iD](https://support.orcid.org/hc/en-us/sections/360001495313-What-is-ORCID - 97 ) in hyphenated groups of 4 digits, (and [valid]( - 98 https://support.orcid.org/hc/en-us/articles/360006897674-Structure-of-the-ORCID-Identifier - 99 ) as per ISO 7064 11,2.) -100 """ -101 -102 -103class Author(_Person): -104 name: Annotated[str, _AfterValidator(_remove_slashes)] -105 github_user: Optional[str] = None # TODO: validate github_user -106 -107 -108class Maintainer(_Person): -109 name: Optional[Annotated[str, _AfterValidator(_remove_slashes)]] = None -110 github_user: str -111 -112 -113class BadgeDescr(Node, title="Custom badge"): -114 """A custom badge""" -115 -116 label: Annotated[str, Field(examples=["Open in Colab"])] -117 """badge label to display on hover""" -118 -119 icon: Annotated[ -120 Union[HttpUrl, None], -121 Field(examples=["https://colab.research.google.com/assets/colab-badge.svg"]), -122 ] = None -123 """badge icon""" -124 -125 url: Annotated[ -126 HttpUrl, -127 Field( -128 examples=[ -129 "https://colab.research.google.com/github/HenriquesLab/ZeroCostDL4Mic/blob/master/Colab_notebooks/U-net_2D_ZeroCostDL4Mic.ipynb" -130 ] -131 ), -132 ] -133 """target URL""" -134 -135 -136class CiteEntry(Node): -137 text: str -138 """free text description""" -139 -140 doi: Optional[Doi] = None -141 """A digital object identifier (DOI) is the prefered citation reference. -142 See https://www.doi.org/ for details. (alternatively specify `url`)""" -143 -144 @field_validator("doi", mode="before") -145 @classmethod -146 def accept_prefixed_doi(cls, doi: Any) -> Any: -147 if isinstance(doi, str): -148 for doi_prefix in ("https://doi.org/", "http://dx.doi.org/"): -149 if doi.startswith(doi_prefix): -150 doi = doi[len(doi_prefix) :] -151 break + 20from .._internal.field_warning import as_warning, issue_warning, warn + 21from .._internal.io import ( + 22 BioimageioYamlContent, + 23 WithSuffix, + 24 YamlValue, + 25 include_in_package_serializer, + 26) + 27from .._internal.io_basics import AbsoluteFilePath as AbsoluteFilePath + 28from .._internal.types import ( + 29 DeprecatedLicenseId, + 30 FileSource, + 31 ImportantFileSource, + 32 LicenseId, + 33 NotEmpty, + 34) + 35from .._internal.types import Doi as Doi + 36from .._internal.types import OrcidId as OrcidId + 37from .._internal.types import RelativeFilePath as RelativeFilePath + 38from .._internal.types import ResourceId as ResourceId + 39from .._internal.url import HttpUrl as HttpUrl + 40from .._internal.validator_annotations import AfterValidator + 41from .._internal.version_type import Version as Version + 42from ._v0_2_converter import convert_from_older_format as _convert_from_older_format + 43 + 44KNOWN_SPECIFIC_RESOURCE_TYPES = ( + 45 "application", + 46 "collection", + 47 "dataset", + 48 "model", + 49 "notebook", + 50) + 51 + 52VALID_COVER_IMAGE_EXTENSIONS = ( + 53 ".gif", + 54 ".jpeg", + 55 ".jpg", + 56 ".png", + 57 ".svg", + 58) + 59 + 60_WithImageSuffix = WithSuffix(VALID_COVER_IMAGE_EXTENSIONS, case_sensitive=False) + 61CoverImageSource = Annotated[ + 62 Union[HttpUrl, AbsoluteFilePath, RelativeFilePath], + 63 _WithImageSuffix, + 64 include_in_package_serializer, + 65] + 66 + 67 + 68class AttachmentsDescr(Node): + 69 model_config = {**Node.model_config, "extra": "allow"} + 70 """update pydantic model config to allow additional unknown keys""" + 71 files: List[ImportantFileSource] = Field(default_factory=list) + 72 """∈📦 File attachments""" + 73 + 74 + 75def _remove_slashes(s: str): + 76 return s.replace("/", "").replace("\\", "") + 77 + 78 + 79class Uploader(Node): + 80 email: EmailStr + 81 """Email""" + 82 name: Optional[Annotated[str, AfterValidator(_remove_slashes)]] = None + 83 """name""" + 84 + 85 + 86class _Person(Node): + 87 affiliation: Optional[str] = None + 88 """Affiliation""" + 89 + 90 email: Optional[EmailStr] = None + 91 """Email""" + 92 + 93 orcid: Annotated[Optional[OrcidId], Field(examples=["0000-0001-2345-6789"])] = None + 94 """An [ORCID iD](https://support.orcid.org/hc/en-us/sections/360001495313-What-is-ORCID + 95 ) in hyphenated groups of 4 digits, (and [valid]( + 96 https://support.orcid.org/hc/en-us/articles/360006897674-Structure-of-the-ORCID-Identifier + 97 ) as per ISO 7064 11,2.) + 98 """ + 99 +100 +101class Author(_Person): +102 name: Annotated[str, AfterValidator(_remove_slashes)] +103 github_user: Optional[str] = None # TODO: validate github_user +104 +105 +106class Maintainer(_Person): +107 name: Optional[Annotated[str, AfterValidator(_remove_slashes)]] = None +108 github_user: str +109 +110 +111class BadgeDescr(Node, title="Custom badge"): +112 """A custom badge""" +113 +114 label: Annotated[str, Field(examples=["Open in Colab"])] +115 """badge label to display on hover""" +116 +117 icon: Annotated[ +118 Union[HttpUrl, None], +119 Field(examples=["https://colab.research.google.com/assets/colab-badge.svg"]), +120 ] = None +121 """badge icon""" +122 +123 url: Annotated[ +124 HttpUrl, +125 Field( +126 examples=[ +127 "https://colab.research.google.com/github/HenriquesLab/ZeroCostDL4Mic/blob/master/Colab_notebooks/U-net_2D_ZeroCostDL4Mic.ipynb" +128 ] +129 ), +130 ] +131 """target URL""" +132 +133 +134class CiteEntry(Node): +135 text: str +136 """free text description""" +137 +138 doi: Optional[Doi] = None +139 """A digital object identifier (DOI) is the prefered citation reference. +140 See https://www.doi.org/ for details. (alternatively specify `url`)""" +141 +142 @field_validator("doi", mode="before") +143 @classmethod +144 def accept_prefixed_doi(cls, doi: Any) -> Any: +145 if isinstance(doi, str): +146 for doi_prefix in ("https://doi.org/", "http://dx.doi.org/"): +147 if doi.startswith(doi_prefix): +148 doi = doi[len(doi_prefix) :] +149 break +150 +151 return doi 152 -153 return doi -154 -155 url: Optional[str] = None -156 """URL to cite (preferably specify a `doi` instead)""" -157 -158 @model_validator(mode="after") -159 def _check_doi_or_url(self) -> Self: -160 if not self.doi and not self.url: -161 raise ValueError("Either 'doi' or 'url' is required") +153 url: Optional[str] = None +154 """URL to cite (preferably specify a `doi` instead)""" +155 +156 @model_validator(mode="after") +157 def _check_doi_or_url(self) -> Self: +158 if not self.doi and not self.url: +159 raise ValueError("Either 'doi' or 'url' is required") +160 +161 return self 162 -163 return self -164 -165 -166class LinkedResource(Node): -167 """Reference to a bioimage.io resource""" -168 -169 id: ResourceId -170 """A valid resource `id` from the bioimage.io collection.""" -171 -172 version_number: Optional[int] = None -173 """version number (n-th published version, not the semantic version) of linked resource""" -174 -175 -176class GenericModelDescrBase(ResourceDescrBase): -177 """Base for all resource descriptions including of model descriptions""" -178 -179 name: Annotated[NotEmpty[str], warn(MaxLen(128), "Longer than 128 characters.")] -180 """A human-friendly name of the resource description""" +163 +164class LinkedResource(Node): +165 """Reference to a bioimage.io resource""" +166 +167 id: ResourceId +168 """A valid resource `id` from the bioimage.io collection.""" +169 +170 version_number: Optional[int] = None +171 """version number (n-th published version, not the semantic version) of linked resource""" +172 +173 +174class GenericModelDescrBase(ResourceDescrBase): +175 """Base for all resource descriptions including of model descriptions""" +176 +177 name: Annotated[NotEmpty[str], warn(MaxLen(128), "Longer than 128 characters.")] +178 """A human-friendly name of the resource description""" +179 +180 description: str 181 -182 description: str -183 -184 covers: Annotated[ -185 List[CoverImageSource], -186 Field( -187 examples=["cover.png"], -188 description=( -189 "Cover images. Please use an image smaller than 500KB and an aspect" -190 " ratio width to height of 2:1.\nThe supported image formats are:" -191 f" {VALID_COVER_IMAGE_EXTENSIONS}" -192 ), -193 ), -194 ] = Field( -195 default_factory=list, -196 ) -197 """∈📦 Cover images. Please use an image smaller than 500KB and an aspect ratio width to height of 2:1.""" -198 -199 id_emoji: Optional[Annotated[str, Len(min_length=1, max_length=1)]] = None -200 """UTF-8 emoji for display alongside the `id`.""" -201 -202 authors: List[Author] = Field(default_factory=list) -203 """The authors are the creators of the RDF and the primary points of contact.""" -204 -205 @field_validator("authors", mode="before") -206 @classmethod -207 def accept_author_strings(cls, authors: Union[Any, Sequence[Any]]) -> Any: -208 """we unofficially accept strings as author entries""" -209 if isinstance(authors, collections.abc.Sequence): -210 authors = [{"name": a} if isinstance(a, str) else a for a in authors] -211 -212 if not authors: -213 issue_warning("No author specified.", value=authors) +182 covers: Annotated[ +183 List[CoverImageSource], +184 Field( +185 examples=["cover.png"], +186 description=( +187 "Cover images. Please use an image smaller than 500KB and an aspect" +188 " ratio width to height of 2:1.\nThe supported image formats are:" +189 f" {VALID_COVER_IMAGE_EXTENSIONS}" +190 ), +191 ), +192 ] = Field( +193 default_factory=list, +194 ) +195 """∈📦 Cover images. Please use an image smaller than 500KB and an aspect ratio width to height of 2:1.""" +196 +197 id_emoji: Optional[Annotated[str, Len(min_length=1, max_length=1)]] = None +198 """UTF-8 emoji for display alongside the `id`.""" +199 +200 authors: List[Author] = Field(default_factory=list) +201 """The authors are the creators of the RDF and the primary points of contact.""" +202 +203 @field_validator("authors", mode="before") +204 @classmethod +205 def accept_author_strings(cls, authors: Union[Any, Sequence[Any]]) -> Any: +206 """we unofficially accept strings as author entries""" +207 if isinstance(authors, collections.abc.Sequence): +208 authors = [{"name": a} if isinstance(a, str) else a for a in authors] +209 +210 if not authors: +211 issue_warning("No author specified.", value=authors) +212 +213 return authors 214 -215 return authors -216 -217 attachments: Optional[AttachmentsDescr] = None -218 """file and other attachments""" -219 -220 cite: List[CiteEntry] = Field(default_factory=list) -221 """citations""" -222 -223 @field_validator("cite", mode="after") -224 @classmethod -225 def _warn_empty_cite(cls, value: Any): -226 if not value: -227 issue_warning("No cite entry specified.", value=value) +215 attachments: Optional[AttachmentsDescr] = None +216 """file and other attachments""" +217 +218 cite: List[CiteEntry] = Field(default_factory=list) +219 """citations""" +220 +221 @field_validator("cite", mode="after") +222 @classmethod +223 def _warn_empty_cite(cls, value: Any): +224 if not value: +225 issue_warning("No cite entry specified.", value=value) +226 +227 return value 228 -229 return value -230 -231 config: Annotated[ -232 Dict[str, YamlValue], -233 Field( -234 examples=[ -235 dict( -236 bioimageio={ -237 "my_custom_key": 3837283, -238 "another_key": {"nested": "value"}, -239 }, -240 imagej={"macro_dir": "path/to/macro/file"}, -241 ) -242 ], -243 ), -244 ] = Field(default_factory=dict) -245 """A field for custom configuration that can contain any keys not present in the RDF spec. -246 This means you should not store, for example, a github repo URL in `config` since we already have the -247 `git_repo` field defined in the spec. -248 Keys in `config` may be very specific to a tool or consumer software. To avoid conflicting definitions, -249 it is recommended to wrap added configuration into a sub-field named with the specific domain or tool name, -250 for example: -251 ```yaml -252 config: -253 bioimageio: # here is the domain name -254 my_custom_key: 3837283 -255 another_key: -256 nested: value -257 imagej: # config specific to ImageJ -258 macro_dir: path/to/macro/file -259 ``` -260 If possible, please use [`snake_case`](https://en.wikipedia.org/wiki/Snake_case) for keys in `config`. -261 You may want to list linked files additionally under `attachments` to include them when packaging a resource -262 (packaging a resource means downloading/copying important linked files and creating a ZIP archive that contains -263 an altered rdf.yaml file with local references to the downloaded files)""" -264 -265 download_url: Optional[HttpUrl] = None -266 """URL to download the resource from (deprecated)""" -267 -268 git_repo: Annotated[ -269 Optional[str], -270 Field( -271 examples=[ -272 "https://github.com/bioimage-io/spec-bioimage-io/tree/main/example_descriptions/models/unet2d_nuclei_broad" -273 ], -274 ), -275 ] = None -276 """A URL to the Git repository where the resource is being developed.""" -277 -278 icon: Union[ -279 ImportantFileSource, Annotated[str, Len(min_length=1, max_length=2)], None -280 ] = None -281 """An icon for illustration""" -282 -283 links: Annotated[ -284 List[str], -285 Field( -286 examples=[ -287 ( -288 "ilastik/ilastik", -289 "deepimagej/deepimagej", -290 "zero/notebook_u-net_3d_zerocostdl4mic", -291 ) -292 ], -293 ), -294 ] = Field(default_factory=list) -295 """IDs of other bioimage.io resources""" -296 -297 uploader: Optional[Uploader] = None -298 """The person who uploaded the model (e.g. to bioimage.io)""" -299 -300 maintainers: List[Maintainer] = Field(default_factory=list) -301 """Maintainers of this resource. -302 If not specified `authors` are maintainers and at least some of them should specify their `github_user` name""" -303 -304 rdf_source: Optional[FileSource] = None -305 """Resource description file (RDF) source; used to keep track of where an rdf.yaml was loaded from. -306 Do not set this field in a YAML file.""" -307 -308 tags: Annotated[ -309 List[str], -310 Field(examples=[("unet2d", "pytorch", "nucleus", "segmentation", "dsb2018")]), -311 ] = Field(default_factory=list) -312 """Associated tags""" -313 -314 @as_warning -315 @field_validator("tags") -316 @classmethod -317 def warn_about_tag_categories( -318 cls, value: List[str], info: ValidationInfo -319 ) -> List[str]: -320 categories = TAG_CATEGORIES.get(info.data["type"], {}) -321 missing_categories: List[Mapping[str, Sequence[str]]] = [] -322 for cat, entries in categories.items(): -323 if not any(e in value for e in entries): -324 missing_categories.append({cat: entries}) -325 -326 if missing_categories: -327 raise ValueError( -328 "Missing tags from bioimage.io categories: {missing_categories}" -329 ) +229 config: Annotated[ +230 Dict[str, YamlValue], +231 Field( +232 examples=[ +233 dict( +234 bioimageio={ +235 "my_custom_key": 3837283, +236 "another_key": {"nested": "value"}, +237 }, +238 imagej={"macro_dir": "path/to/macro/file"}, +239 ) +240 ], +241 ), +242 ] = Field(default_factory=dict) +243 """A field for custom configuration that can contain any keys not present in the RDF spec. +244 This means you should not store, for example, a github repo URL in `config` since we already have the +245 `git_repo` field defined in the spec. +246 Keys in `config` may be very specific to a tool or consumer software. To avoid conflicting definitions, +247 it is recommended to wrap added configuration into a sub-field named with the specific domain or tool name, +248 for example: +249 ```yaml +250 config: +251 bioimageio: # here is the domain name +252 my_custom_key: 3837283 +253 another_key: +254 nested: value +255 imagej: # config specific to ImageJ +256 macro_dir: path/to/macro/file +257 ``` +258 If possible, please use [`snake_case`](https://en.wikipedia.org/wiki/Snake_case) for keys in `config`. +259 You may want to list linked files additionally under `attachments` to include them when packaging a resource +260 (packaging a resource means downloading/copying important linked files and creating a ZIP archive that contains +261 an altered rdf.yaml file with local references to the downloaded files)""" +262 +263 download_url: Optional[HttpUrl] = None +264 """URL to download the resource from (deprecated)""" +265 +266 git_repo: Annotated[ +267 Optional[str], +268 Field( +269 examples=[ +270 "https://github.com/bioimage-io/spec-bioimage-io/tree/main/example_descriptions/models/unet2d_nuclei_broad" +271 ], +272 ), +273 ] = None +274 """A URL to the Git repository where the resource is being developed.""" +275 +276 icon: Union[ +277 ImportantFileSource, Annotated[str, Len(min_length=1, max_length=2)], None +278 ] = None +279 """An icon for illustration""" +280 +281 links: Annotated[ +282 List[str], +283 Field( +284 examples=[ +285 ( +286 "ilastik/ilastik", +287 "deepimagej/deepimagej", +288 "zero/notebook_u-net_3d_zerocostdl4mic", +289 ) +290 ], +291 ), +292 ] = Field(default_factory=list) +293 """IDs of other bioimage.io resources""" +294 +295 uploader: Optional[Uploader] = None +296 """The person who uploaded the model (e.g. to bioimage.io)""" +297 +298 maintainers: List[Maintainer] = Field(default_factory=list) +299 """Maintainers of this resource. +300 If not specified `authors` are maintainers and at least some of them should specify their `github_user` name""" +301 +302 rdf_source: Optional[FileSource] = None +303 """Resource description file (RDF) source; used to keep track of where an rdf.yaml was loaded from. +304 Do not set this field in a YAML file.""" +305 +306 tags: Annotated[ +307 List[str], +308 Field(examples=[("unet2d", "pytorch", "nucleus", "segmentation", "dsb2018")]), +309 ] = Field(default_factory=list) +310 """Associated tags""" +311 +312 @as_warning +313 @field_validator("tags") +314 @classmethod +315 def warn_about_tag_categories( +316 cls, value: List[str], info: ValidationInfo +317 ) -> List[str]: +318 categories = TAG_CATEGORIES.get(info.data["type"], {}) +319 missing_categories: List[Mapping[str, Sequence[str]]] = [] +320 for cat, entries in categories.items(): +321 if not any(e in value for e in entries): +322 missing_categories.append({cat: entries}) +323 +324 if missing_categories: +325 raise ValueError( +326 "Missing tags from bioimage.io categories: {missing_categories}" +327 ) +328 +329 return value 330 -331 return value -332 -333 version: Optional[Version] = None -334 """The version of the resource following SemVer 2.0.""" -335 -336 version_number: Optional[int] = None -337 """version number (n-th published version, not the semantic version)""" -338 -339 -340class GenericDescrBase(GenericModelDescrBase): -341 """Base for all resource descriptions except for the model descriptions""" -342 -343 format_version: Literal["0.2.4"] = "0.2.4" -344 """The format version of this resource specification -345 (not the `version` of the resource description) -346 When creating a new resource always use the latest micro/patch version described here. -347 The `format_version` is important for any consumer software to understand how to parse the fields. -348 """ -349 -350 @model_validator(mode="before") -351 @classmethod -352 def _convert_from_older_format( -353 cls, data: BioimageioYamlContent, / -354 ) -> BioimageioYamlContent: -355 _convert_from_older_format(data) -356 return data -357 -358 badges: List[BadgeDescr] = Field(default_factory=list) -359 """badges associated with this resource""" -360 -361 documentation: Annotated[ -362 Optional[ImportantFileSource], -363 Field( -364 examples=[ -365 "https://raw.githubusercontent.com/bioimage-io/spec-bioimage-io/main/example_descriptions/models/unet2d_nuclei_broad/README.md", -366 "README.md", -367 ], -368 ), -369 ] = None -370 """∈📦 URL or relative path to a markdown file with additional documentation. -371 The recommended documentation file name is `README.md`. An `.md` suffix is mandatory.""" -372 -373 license: Annotated[ -374 Optional[Union[LicenseId, DeprecatedLicenseId, str]], -375 Field(examples=["CC-BY-4.0", "MIT", "BSD-2-Clause"]), -376 ] = None -377 """A [SPDX license identifier](https://spdx.org/licenses/). -378 We do not support custom license beyond the SPDX license list, if you need that please -379 [open a GitHub issue](https://github.com/bioimage-io/spec-bioimage-io/issues/new/choose -380 ) to discuss your intentions with the community.""" -381 -382 @field_validator("license", mode="after") -383 @classmethod -384 def deprecated_spdx_license( -385 cls, value: Optional[Union[LicenseId, DeprecatedLicenseId, str]] -386 ): -387 if isinstance(value, LicenseId): -388 pass -389 elif value is None: -390 issue_warning("missing license.", value=value) -391 elif isinstance(value, DeprecatedLicenseId): -392 issue_warning("'{value}' is a deprecated license identifier.", value=value) -393 elif isinstance(value, str): -394 issue_warning("'{value}' is an unknown license identifier.", value=value) -395 else: -396 assert_never(value) +331 version: Optional[Version] = None +332 """The version of the resource following SemVer 2.0.""" +333 +334 version_number: Optional[int] = None +335 """version number (n-th published version, not the semantic version)""" +336 +337 +338class GenericDescrBase(GenericModelDescrBase): +339 """Base for all resource descriptions except for the model descriptions""" +340 +341 format_version: Literal["0.2.4"] = "0.2.4" +342 """The format version of this resource specification +343 (not the `version` of the resource description) +344 When creating a new resource always use the latest micro/patch version described here. +345 The `format_version` is important for any consumer software to understand how to parse the fields. +346 """ +347 +348 @model_validator(mode="before") +349 @classmethod +350 def _convert_from_older_format( +351 cls, data: BioimageioYamlContent, / +352 ) -> BioimageioYamlContent: +353 _convert_from_older_format(data) +354 return data +355 +356 badges: List[BadgeDescr] = Field(default_factory=list) +357 """badges associated with this resource""" +358 +359 documentation: Annotated[ +360 Optional[ImportantFileSource], +361 Field( +362 examples=[ +363 "https://raw.githubusercontent.com/bioimage-io/spec-bioimage-io/main/example_descriptions/models/unet2d_nuclei_broad/README.md", +364 "README.md", +365 ], +366 ), +367 ] = None +368 """∈📦 URL or relative path to a markdown file with additional documentation. +369 The recommended documentation file name is `README.md`. An `.md` suffix is mandatory.""" +370 +371 license: Annotated[ +372 Optional[Union[LicenseId, DeprecatedLicenseId, str]], +373 Field(examples=["CC-BY-4.0", "MIT", "BSD-2-Clause"]), +374 ] = None +375 """A [SPDX license identifier](https://spdx.org/licenses/). +376 We do not support custom license beyond the SPDX license list, if you need that please +377 [open a GitHub issue](https://github.com/bioimage-io/spec-bioimage-io/issues/new/choose +378 ) to discuss your intentions with the community.""" +379 +380 @field_validator("license", mode="after") +381 @classmethod +382 def deprecated_spdx_license( +383 cls, value: Optional[Union[LicenseId, DeprecatedLicenseId, str]] +384 ): +385 if isinstance(value, LicenseId): +386 pass +387 elif value is None: +388 issue_warning("missing license.", value=value) +389 elif isinstance(value, DeprecatedLicenseId): +390 issue_warning("'{value}' is a deprecated license identifier.", value=value) +391 elif isinstance(value, str): +392 issue_warning("'{value}' is an unknown license identifier.", value=value) +393 else: +394 assert_never(value) +395 +396 return value 397 -398 return value -399 +398 +399ResourceDescrType = TypeVar("ResourceDescrType", bound=GenericDescrBase) 400 -401ResourceDescrType = TypeVar("ResourceDescrType", bound=GenericDescrBase) -402 -403 -404class GenericDescr( -405 GenericDescrBase, extra="ignore", title="bioimage.io generic specification" -406): -407 """Specification of the fields used in a generic bioimage.io-compliant resource description file (RDF). -408 -409 An RDF is a YAML file that describes a resource such as a model, a dataset, or a notebook. -410 Note that those resources are described with a type-specific RDF. -411 Use this generic resource description, if none of the known specific types matches your resource. -412 """ -413 -414 type: Annotated[str, LowerCase, Field(frozen=True)] = "generic" -415 """The resource type assigns a broad category to the resource.""" -416 -417 id: Optional[ResourceId] = None -418 """Model zoo (bioimage.io) wide, unique identifier (assigned by bioimage.io)""" -419 -420 source: Optional[HttpUrl] = None -421 """The primary source of the resource""" -422 -423 @field_validator("type", mode="after") -424 @classmethod -425 def check_specific_types(cls, value: str) -> str: -426 if value in KNOWN_SPECIFIC_RESOURCE_TYPES: -427 raise ValueError( -428 f"Use the {value} description instead of this generic description for" -429 + f" your '{value}' resource." -430 ) -431 -432 return value +401 +402class GenericDescr( +403 GenericDescrBase, extra="ignore", title="bioimage.io generic specification" +404): +405 """Specification of the fields used in a generic bioimage.io-compliant resource description file (RDF). +406 +407 An RDF is a YAML file that describes a resource such as a model, a dataset, or a notebook. +408 Note that those resources are described with a type-specific RDF. +409 Use this generic resource description, if none of the known specific types matches your resource. +410 """ +411 +412 type: Annotated[str, LowerCase, Field(frozen=True)] = "generic" +413 """The resource type assigns a broad category to the resource.""" +414 +415 id: Optional[ResourceId] = None +416 """Model zoo (bioimage.io) wide, unique identifier (assigned by bioimage.io)""" +417 +418 source: Optional[HttpUrl] = None +419 """The primary source of the resource""" +420 +421 @field_validator("type", mode="after") +422 @classmethod +423 def check_specific_types(cls, value: str) -> str: +424 if value in KNOWN_SPECIFIC_RESOURCE_TYPES: +425 raise ValueError( +426 f"Use the {value} description instead of this generic description for" +427 + f" your '{value}' resource." +428 ) +429 +430 return value @@ -841,11 +839,11 @@

    - 
    71class AttachmentsDescr(Node):
-72    model_config = {**Node.model_config, "extra": "allow"}
-73    """update pydantic model config to allow additional unknown keys"""
-74    files: List[ImportantFileSource] = Field(default_factory=list)
-75    """∈📦 File attachments"""
+            
    69class AttachmentsDescr(Node):
+70    model_config = {**Node.model_config, "extra": "allow"}
+71    """update pydantic model config to allow additional unknown keys"""
+72    files: List[ImportantFileSource] = Field(default_factory=list)
+73    """∈📦 File attachments"""
 
    
 
 
@@ -870,7 +868,7 @@
    - files: List[Annotated[Union[Annotated[pathlib.Path, PathType(path_type='file')], bioimageio.spec._internal.io.RelativeFilePath, bioimageio.spec._internal.url.HttpUrl, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator(func=<function wo_special_file_name at 0x7f1c21c3ef20>), PlainSerializer(func=<function _package at 0x7f1c21c782c0>, return_type=PydanticUndefined, when_used='unless-none')]] + files: List[Annotated[Union[Annotated[pathlib.Path, PathType(path_type='file')], bioimageio.spec._internal.io.RelativeFilePath, bioimageio.spec._internal.url.HttpUrl, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator(func=<function wo_special_file_name at 0x7afca0d90540>), PlainSerializer(func=<function _package at 0x7afca0d91760>, return_type=PydanticUndefined, when_used='unless-none')]]
    @@ -955,11 +953,11 @@
    Inherited Members
    - 
    82class Uploader(Node):
-83    email: EmailStr
-84    """Email"""
-85    name: Optional[Annotated[str, _AfterValidator(_remove_slashes)]] = None
-86    """name"""
+            
    80class Uploader(Node):
+81    email: EmailStr
+82    """Email"""
+83    name: Optional[Annotated[str, AfterValidator(_remove_slashes)]] = None
+84    """name"""
 
    
 
 
@@ -982,7 +980,7 @@ 
    Inherited Members
    - name: Optional[Annotated[str, AfterValidator(func=<function _remove_slashes at 0x7f1c21cbe700>)]] + name: Optional[Annotated[str, AfterValidator(func=<function _remove_slashes at 0x7afca0ba67a0>)]]
    @@ -1080,9 +1078,9 @@
    Inherited Members
    - 
    104class Author(_Person):
-105    name: Annotated[str, _AfterValidator(_remove_slashes)]
-106    github_user: Optional[str] = None  # TODO: validate github_user
+            
    102class Author(_Person):
+103    name: Annotated[str, AfterValidator(_remove_slashes)]
+104    github_user: Optional[str] = None  # TODO: validate github_user
 
    
 
 
@@ -1092,7 +1090,7 @@ 
    Inherited Members
    
 
                             
    
                                 
    
-            name: Annotated[str, AfterValidator(func=<function _remove_slashes at 0x7f1c21cbe700>)]
+            name: Annotated[str, AfterValidator(func=<function _remove_slashes at 0x7afca0ba67a0>)]
 
         
     
    
@@ -1205,9 +1203,9 @@ 
    Inherited Members
    
 
     
    
     
-            
    109class Maintainer(_Person):
-110    name: Optional[Annotated[str, _AfterValidator(_remove_slashes)]] = None
-111    github_user: str
+            
    107class Maintainer(_Person):
+108    name: Optional[Annotated[str, AfterValidator(_remove_slashes)]] = None
+109    github_user: str
 
    
 
 
@@ -1217,7 +1215,7 @@ 
    Inherited Members
    
 
                             
    
                                 
    
-            name: Optional[Annotated[str, AfterValidator(func=<function _remove_slashes at 0x7f1c21cbe700>)]]
+            name: Optional[Annotated[str, AfterValidator(func=<function _remove_slashes at 0x7afca0ba67a0>)]]
 
         
     
    
@@ -1330,27 +1328,27 @@ 
    Inherited Members
    
 
     
    
     
-            
    114class BadgeDescr(Node, title="Custom badge"):
-115    """A custom badge"""
-116
-117    label: Annotated[str, Field(examples=["Open in Colab"])]
-118    """badge label to display on hover"""
-119
-120    icon: Annotated[
-121        Union[HttpUrl, None],
-122        Field(examples=["https://colab.research.google.com/assets/colab-badge.svg"]),
-123    ] = None
-124    """badge icon"""
-125
-126    url: Annotated[
-127        HttpUrl,
-128        Field(
-129            examples=[
-130                "https://colab.research.google.com/github/HenriquesLab/ZeroCostDL4Mic/blob/master/Colab_notebooks/U-net_2D_ZeroCostDL4Mic.ipynb"
-131            ]
-132        ),
-133    ]
-134    """target URL"""
+            
    112class BadgeDescr(Node, title="Custom badge"):
+113    """A custom badge"""
+114
+115    label: Annotated[str, Field(examples=["Open in Colab"])]
+116    """badge label to display on hover"""
+117
+118    icon: Annotated[
+119        Union[HttpUrl, None],
+120        Field(examples=["https://colab.research.google.com/assets/colab-badge.svg"]),
+121    ] = None
+122    """badge icon"""
+123
+124    url: Annotated[
+125        HttpUrl,
+126        Field(
+127            examples=[
+128                "https://colab.research.google.com/github/HenriquesLab/ZeroCostDL4Mic/blob/master/Colab_notebooks/U-net_2D_ZeroCostDL4Mic.ipynb"
+129            ]
+130        ),
+131    ]
+132    """target URL"""
 
    
 
 
@@ -1484,34 +1482,34 @@ 
    Inherited Members
    
 
     
    
     
-            
    137class CiteEntry(Node):
-138    text: str
-139    """free text description"""
-140
-141    doi: Optional[Doi] = None
-142    """A digital object identifier (DOI) is the prefered citation reference.
-143    See https://www.doi.org/ for details. (alternatively specify `url`)"""
-144
-145    @field_validator("doi", mode="before")
-146    @classmethod
-147    def accept_prefixed_doi(cls, doi: Any) -> Any:
-148        if isinstance(doi, str):
-149            for doi_prefix in ("https://doi.org/", "http://dx.doi.org/"):
-150                if doi.startswith(doi_prefix):
-151                    doi = doi[len(doi_prefix) :]
-152                    break
+            
    135class CiteEntry(Node):
+136    text: str
+137    """free text description"""
+138
+139    doi: Optional[Doi] = None
+140    """A digital object identifier (DOI) is the prefered citation reference.
+141    See https://www.doi.org/ for details. (alternatively specify `url`)"""
+142
+143    @field_validator("doi", mode="before")
+144    @classmethod
+145    def accept_prefixed_doi(cls, doi: Any) -> Any:
+146        if isinstance(doi, str):
+147            for doi_prefix in ("https://doi.org/", "http://dx.doi.org/"):
+148                if doi.startswith(doi_prefix):
+149                    doi = doi[len(doi_prefix) :]
+150                    break
+151
+152        return doi
 153
-154        return doi
-155
-156    url: Optional[str] = None
-157    """URL to cite (preferably specify a `doi` instead)"""
-158
-159    @model_validator(mode="after")
-160    def _check_doi_or_url(self) -> Self:
-161        if not self.doi and not self.url:
-162            raise ValueError("Either 'doi' or 'url' is required")
-163
-164        return self
+154    url: Optional[str] = None
+155    """URL to cite (preferably specify a `doi` instead)"""
+156
+157    @model_validator(mode="after")
+158    def _check_doi_or_url(self) -> Self:
+159        if not self.doi and not self.url:
+160            raise ValueError("Either 'doi' or 'url' is required")
+161
+162        return self
 
    
 
 
@@ -1559,16 +1557,16 @@ 
    Inherited Members
    
 
     
    
     
-            
    145    @field_validator("doi", mode="before")
-146    @classmethod
-147    def accept_prefixed_doi(cls, doi: Any) -> Any:
-148        if isinstance(doi, str):
-149            for doi_prefix in ("https://doi.org/", "http://dx.doi.org/"):
-150                if doi.startswith(doi_prefix):
-151                    doi = doi[len(doi_prefix) :]
-152                    break
-153
-154        return doi
+            
    143    @field_validator("doi", mode="before")
+144    @classmethod
+145    def accept_prefixed_doi(cls, doi: Any) -> Any:
+146        if isinstance(doi, str):
+147            for doi_prefix in ("https://doi.org/", "http://dx.doi.org/"):
+148                if doi.startswith(doi_prefix):
+149                    doi = doi[len(doi_prefix) :]
+150                    break
+151
+152        return doi
 
    
 
 
@@ -1675,14 +1673,14 @@ 
    Inherited Members
    
 
     
    
     
-            
    167class LinkedResource(Node):
-168    """Reference to a bioimage.io resource"""
-169
-170    id: ResourceId
-171    """A valid resource `id` from the bioimage.io collection."""
-172
-173    version_number: Optional[int] = None
-174    """version number (n-th published version, not the semantic version) of linked resource"""
+            
    165class LinkedResource(Node):
+166    """Reference to a bioimage.io resource"""
+167
+168    id: ResourceId
+169    """A valid resource `id` from the bioimage.io collection."""
+170
+171    version_number: Optional[int] = None
+172    """version number (n-th published version, not the semantic version) of linked resource"""
 
    
 
 
@@ -1803,168 +1801,168 @@ 
    Inherited Members
    
 
     
    
     
-            
    177class GenericModelDescrBase(ResourceDescrBase):
-178    """Base for all resource descriptions including of model descriptions"""
-179
-180    name: Annotated[NotEmpty[str], warn(MaxLen(128), "Longer than 128 characters.")]
-181    """A human-friendly name of the resource description"""
+            
    175class GenericModelDescrBase(ResourceDescrBase):
+176    """Base for all resource descriptions including of model descriptions"""
+177
+178    name: Annotated[NotEmpty[str], warn(MaxLen(128), "Longer than 128 characters.")]
+179    """A human-friendly name of the resource description"""
+180
+181    description: str
 182
-183    description: str
-184
-185    covers: Annotated[
-186        List[CoverImageSource],
-187        Field(
-188            examples=["cover.png"],
-189            description=(
-190                "Cover images. Please use an image smaller than 500KB and an aspect"
-191                " ratio width to height of 2:1.\nThe supported image formats are:"
-192                f" {VALID_COVER_IMAGE_EXTENSIONS}"
-193            ),
-194        ),
-195    ] = Field(
-196        default_factory=list,
-197    )
-198    """∈📦 Cover images. Please use an image smaller than 500KB and an aspect ratio width to height of 2:1."""
-199
-200    id_emoji: Optional[Annotated[str, Len(min_length=1, max_length=1)]] = None
-201    """UTF-8 emoji for display alongside the `id`."""
-202
-203    authors: List[Author] = Field(default_factory=list)
-204    """The authors are the creators of the RDF and the primary points of contact."""
-205
-206    @field_validator("authors", mode="before")
-207    @classmethod
-208    def accept_author_strings(cls, authors: Union[Any, Sequence[Any]]) -> Any:
-209        """we unofficially accept strings as author entries"""
-210        if isinstance(authors, collections.abc.Sequence):
-211            authors = [{"name": a} if isinstance(a, str) else a for a in authors]
-212
-213        if not authors:
-214            issue_warning("No author specified.", value=authors)
+183    covers: Annotated[
+184        List[CoverImageSource],
+185        Field(
+186            examples=["cover.png"],
+187            description=(
+188                "Cover images. Please use an image smaller than 500KB and an aspect"
+189                " ratio width to height of 2:1.\nThe supported image formats are:"
+190                f" {VALID_COVER_IMAGE_EXTENSIONS}"
+191            ),
+192        ),
+193    ] = Field(
+194        default_factory=list,
+195    )
+196    """∈📦 Cover images. Please use an image smaller than 500KB and an aspect ratio width to height of 2:1."""
+197
+198    id_emoji: Optional[Annotated[str, Len(min_length=1, max_length=1)]] = None
+199    """UTF-8 emoji for display alongside the `id`."""
+200
+201    authors: List[Author] = Field(default_factory=list)
+202    """The authors are the creators of the RDF and the primary points of contact."""
+203
+204    @field_validator("authors", mode="before")
+205    @classmethod
+206    def accept_author_strings(cls, authors: Union[Any, Sequence[Any]]) -> Any:
+207        """we unofficially accept strings as author entries"""
+208        if isinstance(authors, collections.abc.Sequence):
+209            authors = [{"name": a} if isinstance(a, str) else a for a in authors]
+210
+211        if not authors:
+212            issue_warning("No author specified.", value=authors)
+213
+214        return authors
 215
-216        return authors
-217
-218    attachments: Optional[AttachmentsDescr] = None
-219    """file and other attachments"""
-220
-221    cite: List[CiteEntry] = Field(default_factory=list)
-222    """citations"""
-223
-224    @field_validator("cite", mode="after")
-225    @classmethod
-226    def _warn_empty_cite(cls, value: Any):
-227        if not value:
-228            issue_warning("No cite entry specified.", value=value)
+216    attachments: Optional[AttachmentsDescr] = None
+217    """file and other attachments"""
+218
+219    cite: List[CiteEntry] = Field(default_factory=list)
+220    """citations"""
+221
+222    @field_validator("cite", mode="after")
+223    @classmethod
+224    def _warn_empty_cite(cls, value: Any):
+225        if not value:
+226            issue_warning("No cite entry specified.", value=value)
+227
+228        return value
 229
-230        return value
-231
-232    config: Annotated[
-233        Dict[str, YamlValue],
-234        Field(
-235            examples=[
-236                dict(
-237                    bioimageio={
-238                        "my_custom_key": 3837283,
-239                        "another_key": {"nested": "value"},
-240                    },
-241                    imagej={"macro_dir": "path/to/macro/file"},
-242                )
-243            ],
-244        ),
-245    ] = Field(default_factory=dict)
-246    """A field for custom configuration that can contain any keys not present in the RDF spec.
-247    This means you should not store, for example, a github repo URL in `config` since we already have the
-248    `git_repo` field defined in the spec.
-249    Keys in `config` may be very specific to a tool or consumer software. To avoid conflicting definitions,
-250    it is recommended to wrap added configuration into a sub-field named with the specific domain or tool name,
-251    for example:
-252    ```yaml
-253    config:
-254        bioimageio:  # here is the domain name
-255            my_custom_key: 3837283
-256            another_key:
-257                nested: value
-258        imagej:       # config specific to ImageJ
-259            macro_dir: path/to/macro/file
-260    ```
-261    If possible, please use [`snake_case`](https://en.wikipedia.org/wiki/Snake_case) for keys in `config`.
-262    You may want to list linked files additionally under `attachments` to include them when packaging a resource
-263    (packaging a resource means downloading/copying important linked files and creating a ZIP archive that contains
-264    an altered rdf.yaml file with local references to the downloaded files)"""
-265
-266    download_url: Optional[HttpUrl] = None
-267    """URL to download the resource from (deprecated)"""
-268
-269    git_repo: Annotated[
-270        Optional[str],
-271        Field(
-272            examples=[
-273                "https://github.com/bioimage-io/spec-bioimage-io/tree/main/example_descriptions/models/unet2d_nuclei_broad"
-274            ],
-275        ),
-276    ] = None
-277    """A URL to the Git repository where the resource is being developed."""
-278
-279    icon: Union[
-280        ImportantFileSource, Annotated[str, Len(min_length=1, max_length=2)], None
-281    ] = None
-282    """An icon for illustration"""
-283
-284    links: Annotated[
-285        List[str],
-286        Field(
-287            examples=[
-288                (
-289                    "ilastik/ilastik",
-290                    "deepimagej/deepimagej",
-291                    "zero/notebook_u-net_3d_zerocostdl4mic",
-292                )
-293            ],
-294        ),
-295    ] = Field(default_factory=list)
-296    """IDs of other bioimage.io resources"""
-297
-298    uploader: Optional[Uploader] = None
-299    """The person who uploaded the model (e.g. to bioimage.io)"""
-300
-301    maintainers: List[Maintainer] = Field(default_factory=list)
-302    """Maintainers of this resource.
-303    If not specified `authors` are maintainers and at least some of them should specify their `github_user` name"""
-304
-305    rdf_source: Optional[FileSource] = None
-306    """Resource description file (RDF) source; used to keep track of where an rdf.yaml was loaded from.
-307    Do not set this field in a YAML file."""
-308
-309    tags: Annotated[
-310        List[str],
-311        Field(examples=[("unet2d", "pytorch", "nucleus", "segmentation", "dsb2018")]),
-312    ] = Field(default_factory=list)
-313    """Associated tags"""
-314
-315    @as_warning
-316    @field_validator("tags")
-317    @classmethod
-318    def warn_about_tag_categories(
-319        cls, value: List[str], info: ValidationInfo
-320    ) -> List[str]:
-321        categories = TAG_CATEGORIES.get(info.data["type"], {})
-322        missing_categories: List[Mapping[str, Sequence[str]]] = []
-323        for cat, entries in categories.items():
-324            if not any(e in value for e in entries):
-325                missing_categories.append({cat: entries})
-326
-327        if missing_categories:
-328            raise ValueError(
-329                "Missing tags from bioimage.io categories: {missing_categories}"
-330            )
+230    config: Annotated[
+231        Dict[str, YamlValue],
+232        Field(
+233            examples=[
+234                dict(
+235                    bioimageio={
+236                        "my_custom_key": 3837283,
+237                        "another_key": {"nested": "value"},
+238                    },
+239                    imagej={"macro_dir": "path/to/macro/file"},
+240                )
+241            ],
+242        ),
+243    ] = Field(default_factory=dict)
+244    """A field for custom configuration that can contain any keys not present in the RDF spec.
+245    This means you should not store, for example, a github repo URL in `config` since we already have the
+246    `git_repo` field defined in the spec.
+247    Keys in `config` may be very specific to a tool or consumer software. To avoid conflicting definitions,
+248    it is recommended to wrap added configuration into a sub-field named with the specific domain or tool name,
+249    for example:
+250    ```yaml
+251    config:
+252        bioimageio:  # here is the domain name
+253            my_custom_key: 3837283
+254            another_key:
+255                nested: value
+256        imagej:       # config specific to ImageJ
+257            macro_dir: path/to/macro/file
+258    ```
+259    If possible, please use [`snake_case`](https://en.wikipedia.org/wiki/Snake_case) for keys in `config`.
+260    You may want to list linked files additionally under `attachments` to include them when packaging a resource
+261    (packaging a resource means downloading/copying important linked files and creating a ZIP archive that contains
+262    an altered rdf.yaml file with local references to the downloaded files)"""
+263
+264    download_url: Optional[HttpUrl] = None
+265    """URL to download the resource from (deprecated)"""
+266
+267    git_repo: Annotated[
+268        Optional[str],
+269        Field(
+270            examples=[
+271                "https://github.com/bioimage-io/spec-bioimage-io/tree/main/example_descriptions/models/unet2d_nuclei_broad"
+272            ],
+273        ),
+274    ] = None
+275    """A URL to the Git repository where the resource is being developed."""
+276
+277    icon: Union[
+278        ImportantFileSource, Annotated[str, Len(min_length=1, max_length=2)], None
+279    ] = None
+280    """An icon for illustration"""
+281
+282    links: Annotated[
+283        List[str],
+284        Field(
+285            examples=[
+286                (
+287                    "ilastik/ilastik",
+288                    "deepimagej/deepimagej",
+289                    "zero/notebook_u-net_3d_zerocostdl4mic",
+290                )
+291            ],
+292        ),
+293    ] = Field(default_factory=list)
+294    """IDs of other bioimage.io resources"""
+295
+296    uploader: Optional[Uploader] = None
+297    """The person who uploaded the model (e.g. to bioimage.io)"""
+298
+299    maintainers: List[Maintainer] = Field(default_factory=list)
+300    """Maintainers of this resource.
+301    If not specified `authors` are maintainers and at least some of them should specify their `github_user` name"""
+302
+303    rdf_source: Optional[FileSource] = None
+304    """Resource description file (RDF) source; used to keep track of where an rdf.yaml was loaded from.
+305    Do not set this field in a YAML file."""
+306
+307    tags: Annotated[
+308        List[str],
+309        Field(examples=[("unet2d", "pytorch", "nucleus", "segmentation", "dsb2018")]),
+310    ] = Field(default_factory=list)
+311    """Associated tags"""
+312
+313    @as_warning
+314    @field_validator("tags")
+315    @classmethod
+316    def warn_about_tag_categories(
+317        cls, value: List[str], info: ValidationInfo
+318    ) -> List[str]:
+319        categories = TAG_CATEGORIES.get(info.data["type"], {})
+320        missing_categories: List[Mapping[str, Sequence[str]]] = []
+321        for cat, entries in categories.items():
+322            if not any(e in value for e in entries):
+323                missing_categories.append({cat: entries})
+324
+325        if missing_categories:
+326            raise ValueError(
+327                "Missing tags from bioimage.io categories: {missing_categories}"
+328            )
+329
+330        return value
 331
-332        return value
-333
-334    version: Optional[Version] = None
-335    """The version of the resource following SemVer 2.0."""
-336
-337    version_number: Optional[int] = None
-338    """version number (n-th published version, not the semantic version)"""
+332    version: Optional[Version] = None
+333    """The version of the resource following SemVer 2.0."""
+334
+335    version_number: Optional[int] = None
+336    """version number (n-th published version, not the semantic version)"""
 
    
 
 
@@ -1974,7 +1972,7 @@ 
    Inherited Members
    
 
                             
    
                                 
    
-            name: Annotated[str, MinLen(min_length=1), AfterWarner(func=<function as_warning.<locals>.wrapper at 0x7f1c21d18fe0>, severity=30, msg='Longer than 128 characters.', context={'typ': Annotated[Any, MaxLen(max_length=128)]})]
+            name: Annotated[str, MinLen(min_length=1), AfterWarner(func=<function as_warning.<locals>.wrapper at 0x7afca0c05080>, severity=30, msg='Longer than 128 characters.', context={'typ': Annotated[Any, MaxLen(max_length=128)]})]
 
         
     
    
@@ -1998,7 +1996,7 @@ 
    Inherited Members
    
                             
    
                             
    
                                 
    
-            covers: Annotated[List[Annotated[Union[bioimageio.spec._internal.url.HttpUrl, Annotated[pathlib.Path, PathType(path_type='file'), Predicate(func=<function PurePath.is_absolute at 0x7f1c25245940>)], bioimageio.spec._internal.io.RelativeFilePath], WithSuffix(suffix=('.gif', '.jpeg', '.jpg', '.png', '.svg'), case_sensitive=False), PlainSerializer(func=<function _package at 0x7f1c21c782c0>, return_type=PydanticUndefined, when_used='unless-none')]], FieldInfo(annotation=NoneType, required=True, description="Cover images. Please use an image smaller than 500KB and an aspect ratio width to height of 2:1.\nThe supported image formats are: ('.gif', '.jpeg', '.jpg', '.png', '.svg')", examples=['cover.png'])]
+            covers: Annotated[List[Annotated[Union[bioimageio.spec._internal.url.HttpUrl, Annotated[pathlib.Path, PathType(path_type='file'), Predicate(func=<function PurePath.is_absolute at 0x7afca4145940>)], bioimageio.spec._internal.io.RelativeFilePath], WithSuffix(suffix=('.gif', '.jpeg', '.jpg', '.png', '.svg'), case_sensitive=False), PlainSerializer(func=<function _package at 0x7afca0d91760>, return_type=PydanticUndefined, when_used='unless-none')]], FieldInfo(annotation=NoneType, required=True, description="Cover images. Please use an image smaller than 500KB and an aspect ratio width to height of 2:1.\nThe supported image formats are: ('.gif', '.jpeg', '.jpg', '.png', '.svg')", examples=['cover.png'])]
 
         
     
    
@@ -2048,17 +2046,17 @@ 
    Inherited Members
    
 
     
    
     
-            
    206    @field_validator("authors", mode="before")
-207    @classmethod
-208    def accept_author_strings(cls, authors: Union[Any, Sequence[Any]]) -> Any:
-209        """we unofficially accept strings as author entries"""
-210        if isinstance(authors, collections.abc.Sequence):
-211            authors = [{"name": a} if isinstance(a, str) else a for a in authors]
-212
-213        if not authors:
-214            issue_warning("No author specified.", value=authors)
-215
-216        return authors
+            
    204    @field_validator("authors", mode="before")
+205    @classmethod
+206    def accept_author_strings(cls, authors: Union[Any, Sequence[Any]]) -> Any:
+207        """we unofficially accept strings as author entries"""
+208        if isinstance(authors, collections.abc.Sequence):
+209            authors = [{"name": a} if isinstance(a, str) else a for a in authors]
+210
+211        if not authors:
+212            issue_warning("No author specified.", value=authors)
+213
+214        return authors
 
    
 
 
@@ -2155,7 +2153,7 @@ 
    Inherited Members
    
                             
    
                             
    
                                 
    
-            icon: Union[Annotated[Union[Annotated[pathlib.Path, PathType(path_type='file')], bioimageio.spec._internal.io.RelativeFilePath, bioimageio.spec._internal.url.HttpUrl, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator(func=<function wo_special_file_name at 0x7f1c21c3ef20>), PlainSerializer(func=<function _package at 0x7f1c21c782c0>, return_type=PydanticUndefined, when_used='unless-none')], Annotated[str, Len(min_length=1, max_length=2)], NoneType]
+            icon: Union[Annotated[Union[Annotated[pathlib.Path, PathType(path_type='file')], bioimageio.spec._internal.io.RelativeFilePath, bioimageio.spec._internal.url.HttpUrl, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator(func=<function wo_special_file_name at 0x7afca0d90540>), PlainSerializer(func=<function _package at 0x7afca0d91760>, return_type=PydanticUndefined, when_used='unless-none')], Annotated[str, Len(min_length=1, max_length=2)], NoneType]
 
         
     
    
@@ -2393,65 +2391,65 @@ 
    Inherited Members
    
 
     
    
     
-            
    341class GenericDescrBase(GenericModelDescrBase):
-342    """Base for all resource descriptions except for the model descriptions"""
-343
-344    format_version: Literal["0.2.4"] = "0.2.4"
-345    """The format version of this resource specification
-346    (not the `version` of the resource description)
-347    When creating a new resource always use the latest micro/patch version described here.
-348    The `format_version` is important for any consumer software to understand how to parse the fields.
-349    """
-350
-351    @model_validator(mode="before")
-352    @classmethod
-353    def _convert_from_older_format(
-354        cls, data: BioimageioYamlContent, /
-355    ) -> BioimageioYamlContent:
-356        _convert_from_older_format(data)
-357        return data
-358
-359    badges: List[BadgeDescr] = Field(default_factory=list)
-360    """badges associated with this resource"""
-361
-362    documentation: Annotated[
-363        Optional[ImportantFileSource],
-364        Field(
-365            examples=[
-366                "https://raw.githubusercontent.com/bioimage-io/spec-bioimage-io/main/example_descriptions/models/unet2d_nuclei_broad/README.md",
-367                "README.md",
-368            ],
-369        ),
-370    ] = None
-371    """∈📦 URL or relative path to a markdown file with additional documentation.
-372    The recommended documentation file name is `README.md`. An `.md` suffix is mandatory."""
-373
-374    license: Annotated[
-375        Optional[Union[LicenseId, DeprecatedLicenseId, str]],
-376        Field(examples=["CC-BY-4.0", "MIT", "BSD-2-Clause"]),
-377    ] = None
-378    """A [SPDX license identifier](https://spdx.org/licenses/).
-379    We do not support custom license beyond the SPDX license list, if you need that please
-380    [open a GitHub issue](https://github.com/bioimage-io/spec-bioimage-io/issues/new/choose
-381    ) to discuss your intentions with the community."""
-382
-383    @field_validator("license", mode="after")
-384    @classmethod
-385    def deprecated_spdx_license(
-386        cls, value: Optional[Union[LicenseId, DeprecatedLicenseId, str]]
-387    ):
-388        if isinstance(value, LicenseId):
-389            pass
-390        elif value is None:
-391            issue_warning("missing license.", value=value)
-392        elif isinstance(value, DeprecatedLicenseId):
-393            issue_warning("'{value}' is a deprecated license identifier.", value=value)
-394        elif isinstance(value, str):
-395            issue_warning("'{value}' is an unknown license identifier.", value=value)
-396        else:
-397            assert_never(value)
-398
-399        return value
+            
    339class GenericDescrBase(GenericModelDescrBase):
+340    """Base for all resource descriptions except for the model descriptions"""
+341
+342    format_version: Literal["0.2.4"] = "0.2.4"
+343    """The format version of this resource specification
+344    (not the `version` of the resource description)
+345    When creating a new resource always use the latest micro/patch version described here.
+346    The `format_version` is important for any consumer software to understand how to parse the fields.
+347    """
+348
+349    @model_validator(mode="before")
+350    @classmethod
+351    def _convert_from_older_format(
+352        cls, data: BioimageioYamlContent, /
+353    ) -> BioimageioYamlContent:
+354        _convert_from_older_format(data)
+355        return data
+356
+357    badges: List[BadgeDescr] = Field(default_factory=list)
+358    """badges associated with this resource"""
+359
+360    documentation: Annotated[
+361        Optional[ImportantFileSource],
+362        Field(
+363            examples=[
+364                "https://raw.githubusercontent.com/bioimage-io/spec-bioimage-io/main/example_descriptions/models/unet2d_nuclei_broad/README.md",
+365                "README.md",
+366            ],
+367        ),
+368    ] = None
+369    """∈📦 URL or relative path to a markdown file with additional documentation.
+370    The recommended documentation file name is `README.md`. An `.md` suffix is mandatory."""
+371
+372    license: Annotated[
+373        Optional[Union[LicenseId, DeprecatedLicenseId, str]],
+374        Field(examples=["CC-BY-4.0", "MIT", "BSD-2-Clause"]),
+375    ] = None
+376    """A [SPDX license identifier](https://spdx.org/licenses/).
+377    We do not support custom license beyond the SPDX license list, if you need that please
+378    [open a GitHub issue](https://github.com/bioimage-io/spec-bioimage-io/issues/new/choose
+379    ) to discuss your intentions with the community."""
+380
+381    @field_validator("license", mode="after")
+382    @classmethod
+383    def deprecated_spdx_license(
+384        cls, value: Optional[Union[LicenseId, DeprecatedLicenseId, str]]
+385    ):
+386        if isinstance(value, LicenseId):
+387            pass
+388        elif value is None:
+389            issue_warning("missing license.", value=value)
+390        elif isinstance(value, DeprecatedLicenseId):
+391            issue_warning("'{value}' is a deprecated license identifier.", value=value)
+392        elif isinstance(value, str):
+393            issue_warning("'{value}' is an unknown license identifier.", value=value)
+394        else:
+395            assert_never(value)
+396
+397        return value
 
    
 
 
@@ -2490,7 +2488,7 @@ 
    Inherited Members
    
                             
    
                             
    
                                 
    
-            documentation: Annotated[Optional[Annotated[Union[Annotated[pathlib.Path, PathType(path_type='file')], bioimageio.spec._internal.io.RelativeFilePath, bioimageio.spec._internal.url.HttpUrl, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator(func=<function wo_special_file_name at 0x7f1c21c3ef20>), PlainSerializer(func=<function _package at 0x7f1c21c782c0>, return_type=PydanticUndefined, when_used='unless-none')]], FieldInfo(annotation=NoneType, required=True, examples=['https://raw.githubusercontent.com/bioimage-io/spec-bioimage-io/main/example_descriptions/models/unet2d_nuclei_broad/README.md', 'README.md'])]
+            documentation: Annotated[Optional[Annotated[Union[Annotated[pathlib.Path, PathType(path_type='file')], bioimageio.spec._internal.io.RelativeFilePath, bioimageio.spec._internal.url.HttpUrl, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator(func=<function wo_special_file_name at 0x7afca0d90540>), PlainSerializer(func=<function _package at 0x7afca0d91760>, return_type=PydanticUndefined, when_used='unless-none')]], FieldInfo(annotation=NoneType, required=True, examples=['https://raw.githubusercontent.com/bioimage-io/spec-bioimage-io/main/example_descriptions/models/unet2d_nuclei_broad/README.md', 'README.md'])]
 
         
     
    
@@ -2531,23 +2529,23 @@ 
    Inherited Members
    
 
     
    
     
-            
    383    @field_validator("license", mode="after")
-384    @classmethod
-385    def deprecated_spdx_license(
-386        cls, value: Optional[Union[LicenseId, DeprecatedLicenseId, str]]
-387    ):
-388        if isinstance(value, LicenseId):
-389            pass
-390        elif value is None:
-391            issue_warning("missing license.", value=value)
-392        elif isinstance(value, DeprecatedLicenseId):
-393            issue_warning("'{value}' is a deprecated license identifier.", value=value)
-394        elif isinstance(value, str):
-395            issue_warning("'{value}' is an unknown license identifier.", value=value)
-396        else:
-397            assert_never(value)
-398
-399        return value
+            
    381    @field_validator("license", mode="after")
+382    @classmethod
+383    def deprecated_spdx_license(
+384        cls, value: Optional[Union[LicenseId, DeprecatedLicenseId, str]]
+385    ):
+386        if isinstance(value, LicenseId):
+387            pass
+388        elif value is None:
+389            issue_warning("missing license.", value=value)
+390        elif isinstance(value, DeprecatedLicenseId):
+391            issue_warning("'{value}' is a deprecated license identifier.", value=value)
+392        elif isinstance(value, str):
+393            issue_warning("'{value}' is an unknown license identifier.", value=value)
+394        else:
+395            assert_never(value)
+396
+397        return value
 
    
 
 
@@ -2703,35 +2701,35 @@ 
    Inherited Members
    
 
     
    
     
-            
    405class GenericDescr(
-406    GenericDescrBase, extra="ignore", title="bioimage.io generic specification"
-407):
-408    """Specification of the fields used in a generic bioimage.io-compliant resource description file (RDF).
-409
-410    An RDF is a YAML file that describes a resource such as a model, a dataset, or a notebook.
-411    Note that those resources are described with a type-specific RDF.
-412    Use this generic resource description, if none of the known specific types matches your resource.
-413    """
-414
-415    type: Annotated[str, LowerCase, Field(frozen=True)] = "generic"
-416    """The resource type assigns a broad category to the resource."""
-417
-418    id: Optional[ResourceId] = None
-419    """Model zoo (bioimage.io) wide, unique identifier (assigned by bioimage.io)"""
-420
-421    source: Optional[HttpUrl] = None
-422    """The primary source of the resource"""
-423
-424    @field_validator("type", mode="after")
-425    @classmethod
-426    def check_specific_types(cls, value: str) -> str:
-427        if value in KNOWN_SPECIFIC_RESOURCE_TYPES:
-428            raise ValueError(
-429                f"Use the {value} description instead of this generic description for"
-430                + f" your '{value}' resource."
-431            )
-432
-433        return value
+            
    403class GenericDescr(
+404    GenericDescrBase, extra="ignore", title="bioimage.io generic specification"
+405):
+406    """Specification of the fields used in a generic bioimage.io-compliant resource description file (RDF).
+407
+408    An RDF is a YAML file that describes a resource such as a model, a dataset, or a notebook.
+409    Note that those resources are described with a type-specific RDF.
+410    Use this generic resource description, if none of the known specific types matches your resource.
+411    """
+412
+413    type: Annotated[str, LowerCase, Field(frozen=True)] = "generic"
+414    """The resource type assigns a broad category to the resource."""
+415
+416    id: Optional[ResourceId] = None
+417    """Model zoo (bioimage.io) wide, unique identifier (assigned by bioimage.io)"""
+418
+419    source: Optional[HttpUrl] = None
+420    """The primary source of the resource"""
+421
+422    @field_validator("type", mode="after")
+423    @classmethod
+424    def check_specific_types(cls, value: str) -> str:
+425        if value in KNOWN_SPECIFIC_RESOURCE_TYPES:
+426            raise ValueError(
+427                f"Use the {value} description instead of this generic description for"
+428                + f" your '{value}' resource."
+429            )
+430
+431        return value
 
    
 
 
@@ -2795,16 +2793,16 @@ 
    Inherited Members
    
 
     
    
     
-            
    424    @field_validator("type", mode="after")
-425    @classmethod
-426    def check_specific_types(cls, value: str) -> str:
-427        if value in KNOWN_SPECIFIC_RESOURCE_TYPES:
-428            raise ValueError(
-429                f"Use the {value} description instead of this generic description for"
-430                + f" your '{value}' resource."
-431            )
-432
-433        return value
+            
    422    @field_validator("type", mode="after")
+423    @classmethod
+424    def check_specific_types(cls, value: str) -> str:
+425        if value in KNOWN_SPECIFIC_RESOURCE_TYPES:
+426            raise ValueError(
+427                f"Use the {value} description instead of this generic description for"
+428                + f" your '{value}' resource."
+429            )
+430
+431        return value
 
    
 
 
diff --git a/bioimageio/spec/generic/v0_3.html b/bioimageio/spec/generic/v0_3.html
index 8287a2049..829be0ef6 100644
--- a/bioimageio/spec/generic/v0_3.html
+++ b/bioimageio/spec/generic/v0_3.html
@@ -304,27 +304,27 @@ 
    
  17from .._internal.constants import (
  18    TAG_CATEGORIES,
  19)
- 20from .._internal.field_validation import AfterValidator, Predicate
- 21from .._internal.field_warning import as_warning, warn
- 22from .._internal.io import (
- 23    BioimageioYamlContent,
- 24    V_suffix,
- 25    YamlValue,
- 26    include_in_package_serializer,
- 27    validate_suffix,
- 28)
- 29from .._internal.io import FileDescr as FileDescr
- 30from .._internal.io import Sha256 as Sha256
- 31from .._internal.io_basics import AbsoluteFilePath
- 32from .._internal.license_id import LicenseId
- 33from .._internal.types import (
- 34    DeprecatedLicenseId,
- 35    ImportantFileSource,
- 36    NotEmpty,
- 37)
- 38from .._internal.types import RelativeFilePath as RelativeFilePath
- 39from .._internal.types import ResourceId as ResourceId
- 40from .._internal.url import HttpUrl as HttpUrl
+ 20from .._internal.field_warning import as_warning, warn
+ 21from .._internal.io import (
+ 22    BioimageioYamlContent,
+ 23    V_suffix,
+ 24    YamlValue,
+ 25    include_in_package_serializer,
+ 26    validate_suffix,
+ 27)
+ 28from .._internal.io import FileDescr as FileDescr
+ 29from .._internal.io import Sha256 as Sha256
+ 30from .._internal.io_basics import AbsoluteFilePath
+ 31from .._internal.license_id import LicenseId
+ 32from .._internal.types import (
+ 33    DeprecatedLicenseId,
+ 34    ImportantFileSource,
+ 35    NotEmpty,
+ 36)
+ 37from .._internal.types import RelativeFilePath as RelativeFilePath
+ 38from .._internal.types import ResourceId as ResourceId
+ 39from .._internal.url import HttpUrl as HttpUrl
+ 40from .._internal.validator_annotations import AfterValidator, Predicate
  41from .._internal.version_type import Version as Version
  42from .._internal.warning_levels import ALERT
  43from ._v0_3_converter import convert_from_older_format
@@ -732,7 +732,7 @@ 
    
 
                             
    
                                 
    
-            name: Annotated[str, Predicate(func=<function _has_no_slash at 0x7f1c21bacb80>)]
+            name: Annotated[str, Predicate(func=<function _has_no_slash at 0x7afca0a94cc0>)]
 
         
     
    
@@ -861,7 +861,7 @@ 
    Inherited Members
    
 
                             
    
                                 
    
-            name: Optional[Annotated[str, Predicate(func=<function _has_no_slash at 0x7f1c21bacb80>)]]
+            name: Optional[Annotated[str, Predicate(func=<function _has_no_slash at 0x7afca0a94cc0>)]]
 
         
     
    
@@ -1460,7 +1460,7 @@ 
    Inherited Members
    
                             
    
                             
    
                                 
    
-            description: Annotated[str, MaxLen(max_length=1024), AfterWarner(func=<function as_warning.<locals>.wrapper at 0x7f1c138bef20>, severity=30, msg='Description longer than 512 characters.', context={'typ': Annotated[Any, MaxLen(max_length=512)]})]
+            description: Annotated[str, MaxLen(max_length=1024), AfterWarner(func=<function as_warning.<locals>.wrapper at 0x7afc92925f80>, severity=30, msg='Description longer than 512 characters.', context={'typ': Annotated[Any, MaxLen(max_length=512)]})]
 
         
     
    
@@ -1473,7 +1473,7 @@ 
    Inherited Members
    
                             
    
                             
    
                                 
    
-            covers: Annotated[List[Annotated[Union[bioimageio.spec._internal.url.HttpUrl, Annotated[pathlib.Path, PathType(path_type='file'), Predicate(func=<function PurePath.is_absolute at 0x7f1c25245940>)], bioimageio.spec._internal.io.RelativeFilePath], WithSuffix(suffix=('.gif', '.jpeg', '.jpg', '.png', '.svg'), case_sensitive=False), PlainSerializer(func=<function _package at 0x7f1c21c782c0>, return_type=PydanticUndefined, when_used='unless-none')]], FieldInfo(annotation=NoneType, required=True, description="Cover images. Please use an image smaller than 500KB and an aspect ratio width to height of 2:1 or 1:1.\nThe supported image formats are: ('.gif', '.jpeg', '.jpg', '.png', '.svg')", examples=[])]
+            covers: Annotated[List[Annotated[Union[bioimageio.spec._internal.url.HttpUrl, Annotated[pathlib.Path, PathType(path_type='file'), Predicate(func=<function PurePath.is_absolute at 0x7afca4145940>)], bioimageio.spec._internal.io.RelativeFilePath], WithSuffix(suffix=('.gif', '.jpeg', '.jpg', '.png', '.svg'), case_sensitive=False), PlainSerializer(func=<function _package at 0x7afca0d91760>, return_type=PydanticUndefined, when_used='unless-none')]], FieldInfo(annotation=NoneType, required=True, description="Cover images. Please use an image smaller than 500KB and an aspect ratio width to height of 2:1 or 1:1.\nThe supported image formats are: ('.gif', '.jpeg', '.jpg', '.png', '.svg')", examples=[])]
 
         
     
    
@@ -1538,7 +1538,7 @@ 
    Inherited Members
    
                             
    
                             
    
                                 
    
-            license: Annotated[Union[bioimageio.spec._internal.license_id.LicenseId, bioimageio.spec._internal.license_id.DeprecatedLicenseId], AfterWarner(func=<function as_warning.<locals>.wrapper at 0x7f1c138bd620>, severity=30, msg='{value} is deprecated, see https://spdx.org/licenses/{value}.html', context={'typ': <class 'bioimageio.spec._internal.license_id.LicenseId'>}), FieldInfo(annotation=NoneType, required=True, examples=['CC-BY-4.0', 'MIT', 'BSD-2-Clause'])]
+            license: Annotated[Union[bioimageio.spec._internal.license_id.LicenseId, bioimageio.spec._internal.license_id.DeprecatedLicenseId], AfterWarner(func=<function as_warning.<locals>.wrapper at 0x7afc92925e40>, severity=30, msg='{value} is deprecated, see https://spdx.org/licenses/{value}.html', context={'typ': <class 'bioimageio.spec._internal.license_id.LicenseId'>}), FieldInfo(annotation=NoneType, required=True, examples=['CC-BY-4.0', 'MIT', 'BSD-2-Clause'])]
 
         
     
    
@@ -1600,7 +1600,7 @@ 
    Inherited Members
    
                             
    
                             
    
                                 
    
-            icon: Union[Annotated[Union[Annotated[pathlib.Path, PathType(path_type='file')], bioimageio.spec._internal.io.RelativeFilePath, bioimageio.spec._internal.url.HttpUrl, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator(func=<function wo_special_file_name at 0x7f1c21c3ef20>), PlainSerializer(func=<function _package at 0x7f1c21c782c0>, return_type=PydanticUndefined, when_used='unless-none')], Annotated[str, Len(min_length=1, max_length=2)], NoneType]
+            icon: Union[Annotated[Union[Annotated[pathlib.Path, PathType(path_type='file')], bioimageio.spec._internal.io.RelativeFilePath, bioimageio.spec._internal.url.HttpUrl, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator(func=<function wo_special_file_name at 0x7afca0d90540>), PlainSerializer(func=<function _package at 0x7afca0d91760>, return_type=PydanticUndefined, when_used='unless-none')], Annotated[str, Len(min_length=1, max_length=2)], NoneType]
 
         
     
    
@@ -1903,7 +1903,7 @@ 
    Inherited Members
    
                             
    
                             
    
                                 
    
-            documentation: Annotated[Optional[Annotated[Union[Annotated[pathlib.Path, PathType(path_type='file'), Predicate(func=<function PurePath.is_absolute at 0x7f1c25245940>)], bioimageio.spec._internal.io.RelativeFilePath, bioimageio.spec._internal.url.HttpUrl], AfterValidator(func=<function _validate_md_suffix at 0x7f1c21d1afc0>), PlainSerializer(func=<function _package at 0x7f1c21c782c0>, return_type=PydanticUndefined, when_used='unless-none')]], FieldInfo(annotation=NoneType, required=True, examples=['https://raw.githubusercontent.com/bioimage-io/spec-bioimage-io/main/example_descriptions/models/unet2d_nuclei_broad/README.md', 'README.md'])]
+            documentation: Annotated[Optional[Annotated[Union[Annotated[pathlib.Path, PathType(path_type='file'), Predicate(func=<function PurePath.is_absolute at 0x7afca4145940>)], bioimageio.spec._internal.io.RelativeFilePath, bioimageio.spec._internal.url.HttpUrl], AfterValidator(func=<function _validate_md_suffix at 0x7afca0c06ca0>), PlainSerializer(func=<function _package at 0x7afca0d91760>, return_type=PydanticUndefined, when_used='unless-none')]], FieldInfo(annotation=NoneType, required=True, examples=['https://raw.githubusercontent.com/bioimage-io/spec-bioimage-io/main/example_descriptions/models/unet2d_nuclei_broad/README.md', 'README.md'])]
 
         
     
    
diff --git a/bioimageio/spec/model/v0_4.html b/bioimageio/spec/model/v0_4.html
index 96970ad6a..c2da40337 100644
--- a/bioimageio/spec/model/v0_4.html
+++ b/bioimageio/spec/model/v0_4.html
@@ -1019,1097 +1019,1094 @@ 
    
   36    StringNode,
   37)
   38from .._internal.constants import SHA256_HINT
-  39from .._internal.field_validation import (
-  40    AfterValidator,
-  41    RestrictCharacters,
-  42    validate_unique_entries,
-  43)
-  44from .._internal.field_warning import issue_warning, warn
-  45from .._internal.io import (
-  46    BioimageioYamlContent,
-  47    WithSuffix,
-  48    download,
-  49    include_in_package_serializer,
-  50)
-  51from .._internal.io import FileDescr as FileDescr
-  52from .._internal.io import Sha256 as Sha256
-  53from .._internal.io_basics import AbsoluteFilePath as AbsoluteFilePath
-  54from .._internal.types import Datetime as Datetime
-  55from .._internal.types import Identifier as Identifier
-  56from .._internal.types import (
-  57    ImportantFileSource,
-  58    LowerCaseIdentifierAnno,
-  59)
-  60from .._internal.types import LicenseId as LicenseId
-  61from .._internal.types import ModelId as ModelId
-  62from .._internal.types import NotEmpty as NotEmpty
-  63from .._internal.types import ResourceId as ResourceId
-  64from .._internal.url import HttpUrl as HttpUrl
-  65from .._internal.version_type import Version as Version
-  66from .._internal.warning_levels import ALERT, INFO
-  67from ..dataset.v0_2 import DatasetDescr as DatasetDescr
-  68from ..dataset.v0_2 import LinkedDataset as LinkedDataset
-  69from ..generic.v0_2 import AttachmentsDescr as AttachmentsDescr
-  70from ..generic.v0_2 import Author as Author
-  71from ..generic.v0_2 import BadgeDescr as BadgeDescr
-  72from ..generic.v0_2 import CiteEntry as CiteEntry
-  73from ..generic.v0_2 import Doi as Doi
-  74from ..generic.v0_2 import GenericModelDescrBase
-  75from ..generic.v0_2 import LinkedResource as LinkedResource
-  76from ..generic.v0_2 import Maintainer as Maintainer
-  77from ..generic.v0_2 import OrcidId as OrcidId
-  78from ..generic.v0_2 import RelativeFilePath as RelativeFilePath
-  79from ..generic.v0_2 import Uploader as Uploader
-  80from ..utils import load_array
-  81from ._v0_4_converter import convert_from_older_format
-  82
-  83AxesStr = Annotated[
-  84    str, RestrictCharacters("bitczyx"), AfterValidator(validate_unique_entries)
+  39from .._internal.field_validation import validate_unique_entries
+  40from .._internal.field_warning import issue_warning, warn
+  41from .._internal.io import (
+  42    BioimageioYamlContent,
+  43    WithSuffix,
+  44    download,
+  45    include_in_package_serializer,
+  46)
+  47from .._internal.io import FileDescr as FileDescr
+  48from .._internal.io import Sha256 as Sha256
+  49from .._internal.io_basics import AbsoluteFilePath as AbsoluteFilePath
+  50from .._internal.types import Datetime as Datetime
+  51from .._internal.types import Identifier as Identifier
+  52from .._internal.types import (
+  53    ImportantFileSource,
+  54    LowerCaseIdentifierAnno,
+  55)
+  56from .._internal.types import LicenseId as LicenseId
+  57from .._internal.types import ModelId as ModelId
+  58from .._internal.types import NotEmpty as NotEmpty
+  59from .._internal.types import ResourceId as ResourceId
+  60from .._internal.url import HttpUrl as HttpUrl
+  61from .._internal.validator_annotations import AfterValidator, RestrictCharacters
+  62from .._internal.version_type import Version as Version
+  63from .._internal.warning_levels import ALERT, INFO
+  64from ..dataset.v0_2 import DatasetDescr as DatasetDescr
+  65from ..dataset.v0_2 import LinkedDataset as LinkedDataset
+  66from ..generic.v0_2 import AttachmentsDescr as AttachmentsDescr
+  67from ..generic.v0_2 import Author as Author
+  68from ..generic.v0_2 import BadgeDescr as BadgeDescr
+  69from ..generic.v0_2 import CiteEntry as CiteEntry
+  70from ..generic.v0_2 import Doi as Doi
+  71from ..generic.v0_2 import GenericModelDescrBase
+  72from ..generic.v0_2 import LinkedResource as LinkedResource
+  73from ..generic.v0_2 import Maintainer as Maintainer
+  74from ..generic.v0_2 import OrcidId as OrcidId
+  75from ..generic.v0_2 import RelativeFilePath as RelativeFilePath
+  76from ..generic.v0_2 import Uploader as Uploader
+  77from ..utils import load_array
+  78from ._v0_4_converter import convert_from_older_format
+  79
+  80AxesStr = Annotated[
+  81    str, RestrictCharacters("bitczyx"), AfterValidator(validate_unique_entries)
+  82]
+  83AxesInCZYX = Annotated[
+  84    str, RestrictCharacters("czyx"), AfterValidator(validate_unique_entries)
   85]
-  86AxesInCZYX = Annotated[
-  87    str, RestrictCharacters("czyx"), AfterValidator(validate_unique_entries)
-  88]
-  89
-  90PostprocessingName = Literal[
-  91    "binarize",
-  92    "clip",
-  93    "scale_linear",
-  94    "sigmoid",
-  95    "zero_mean_unit_variance",
-  96    "scale_range",
-  97    "scale_mean_variance",
-  98]
-  99PreprocessingName = Literal[
- 100    "binarize",
- 101    "clip",
- 102    "scale_linear",
- 103    "sigmoid",
- 104    "zero_mean_unit_variance",
- 105    "scale_range",
- 106]
+  86
+  87PostprocessingName = Literal[
+  88    "binarize",
+  89    "clip",
+  90    "scale_linear",
+  91    "sigmoid",
+  92    "zero_mean_unit_variance",
+  93    "scale_range",
+  94    "scale_mean_variance",
+  95]
+  96PreprocessingName = Literal[
+  97    "binarize",
+  98    "clip",
+  99    "scale_linear",
+ 100    "sigmoid",
+ 101    "zero_mean_unit_variance",
+ 102    "scale_range",
+ 103]
+ 104
+ 105TensorName = ValidatedString[LowerCaseIdentifierAnno]
+ 106
  107
- 108TensorName = ValidatedString[LowerCaseIdentifierAnno]
- 109
- 110
- 111class CallableFromDepencency(StringNode):
- 112    _pattern = r"^.+\..+$"
- 113    _submodule_adapter = TypeAdapter(Identifier)
- 114
- 115    module_name: str
- 116
- 117    @field_validator("module_name", mode="after")
- 118    def check_submodules(cls, module_name: str) -> str:
- 119        for submod in module_name.split("."):
- 120            _ = cls._submodule_adapter.validate_python(submod)
- 121
- 122        return module_name
- 123
- 124    callable_name: Identifier
- 125
- 126    @classmethod
- 127    def _get_data(cls, valid_string_data: str):
- 128        *mods, callname = valid_string_data.split(".")
- 129        return dict(module_name=".".join(mods), callable_name=callname)
- 130
- 131
- 132class CallableFromFile(StringNode):
- 133    _pattern = r"^.+:.+$"
- 134    source_file: Annotated[
- 135        Union[HttpUrl, RelativeFilePath],
- 136        include_in_package_serializer,
- 137    ]
- 138    """∈📦 Python module that implements `callable_name`"""
- 139    callable_name: Identifier
- 140    """The Python identifier of  """
- 141
- 142    @classmethod
- 143    def _get_data(cls, valid_string_data: str):
- 144        *file_parts, callname = valid_string_data.split(":")
- 145        return dict(source_file=":".join(file_parts), callable_name=callname)
+ 108class CallableFromDepencency(StringNode):
+ 109    _pattern = r"^.+\..+$"
+ 110    _submodule_adapter = TypeAdapter(Identifier)
+ 111
+ 112    module_name: str
+ 113
+ 114    @field_validator("module_name", mode="after")
+ 115    def check_submodules(cls, module_name: str) -> str:
+ 116        for submod in module_name.split("."):
+ 117            _ = cls._submodule_adapter.validate_python(submod)
+ 118
+ 119        return module_name
+ 120
+ 121    callable_name: Identifier
+ 122
+ 123    @classmethod
+ 124    def _get_data(cls, valid_string_data: str):
+ 125        *mods, callname = valid_string_data.split(".")
+ 126        return dict(module_name=".".join(mods), callable_name=callname)
+ 127
+ 128
+ 129class CallableFromFile(StringNode):
+ 130    _pattern = r"^.+:.+$"
+ 131    source_file: Annotated[
+ 132        Union[HttpUrl, RelativeFilePath],
+ 133        include_in_package_serializer,
+ 134    ]
+ 135    """∈📦 Python module that implements `callable_name`"""
+ 136    callable_name: Identifier
+ 137    """The Python identifier of  """
+ 138
+ 139    @classmethod
+ 140    def _get_data(cls, valid_string_data: str):
+ 141        *file_parts, callname = valid_string_data.split(":")
+ 142        return dict(source_file=":".join(file_parts), callable_name=callname)
+ 143
+ 144
+ 145CustomCallable = Union[CallableFromFile, CallableFromDepencency]
  146
  147
- 148CustomCallable = Union[CallableFromFile, CallableFromDepencency]
- 149
- 150
- 151class Dependencies(StringNode):
- 152    _pattern = r"^.+:.+$"
- 153    manager: Annotated[NotEmpty[str], Field(examples=["conda", "maven", "pip"])]
- 154    """Dependency manager"""
- 155
- 156    file: Annotated[
- 157        ImportantFileSource,
- 158        Field(examples=["environment.yaml", "pom.xml", "requirements.txt"]),
- 159    ]
- 160    """∈📦 Dependency file"""
- 161
- 162    @classmethod
- 163    def _get_data(cls, valid_string_data: str):
- 164        manager, *file_parts = valid_string_data.split(":")
- 165        return dict(manager=manager, file=":".join(file_parts))
- 166
- 167
- 168WeightsFormat = Literal[
- 169    "keras_hdf5",
- 170    "onnx",
- 171    "pytorch_state_dict",
- 172    "tensorflow_js",
- 173    "tensorflow_saved_model_bundle",
- 174    "torchscript",
- 175]
- 176
- 177
- 178class WeightsDescr(Node):
- 179    keras_hdf5: Optional[KerasHdf5WeightsDescr] = None
- 180    onnx: Optional[OnnxWeightsDescr] = None
- 181    pytorch_state_dict: Optional[PytorchStateDictWeightsDescr] = None
- 182    tensorflow_js: Optional[TensorflowJsWeightsDescr] = None
- 183    tensorflow_saved_model_bundle: Optional[TensorflowSavedModelBundleWeightsDescr] = (
- 184        None
- 185    )
- 186    torchscript: Optional[TorchscriptWeightsDescr] = None
- 187
- 188    @model_validator(mode="after")
- 189    def check_one_entry(self) -> Self:
- 190        if all(
- 191            entry is None
- 192            for entry in [
- 193                self.keras_hdf5,
- 194                self.onnx,
- 195                self.pytorch_state_dict,
- 196                self.tensorflow_js,
- 197                self.tensorflow_saved_model_bundle,
- 198                self.torchscript,
- 199            ]
- 200        ):
- 201            raise ValueError("Missing weights entry")
+ 148class Dependencies(StringNode):
+ 149    _pattern = r"^.+:.+$"
+ 150    manager: Annotated[NotEmpty[str], Field(examples=["conda", "maven", "pip"])]
+ 151    """Dependency manager"""
+ 152
+ 153    file: Annotated[
+ 154        ImportantFileSource,
+ 155        Field(examples=["environment.yaml", "pom.xml", "requirements.txt"]),
+ 156    ]
+ 157    """∈📦 Dependency file"""
+ 158
+ 159    @classmethod
+ 160    def _get_data(cls, valid_string_data: str):
+ 161        manager, *file_parts = valid_string_data.split(":")
+ 162        return dict(manager=manager, file=":".join(file_parts))
+ 163
+ 164
+ 165WeightsFormat = Literal[
+ 166    "keras_hdf5",
+ 167    "onnx",
+ 168    "pytorch_state_dict",
+ 169    "tensorflow_js",
+ 170    "tensorflow_saved_model_bundle",
+ 171    "torchscript",
+ 172]
+ 173
+ 174
+ 175class WeightsDescr(Node):
+ 176    keras_hdf5: Optional[KerasHdf5WeightsDescr] = None
+ 177    onnx: Optional[OnnxWeightsDescr] = None
+ 178    pytorch_state_dict: Optional[PytorchStateDictWeightsDescr] = None
+ 179    tensorflow_js: Optional[TensorflowJsWeightsDescr] = None
+ 180    tensorflow_saved_model_bundle: Optional[TensorflowSavedModelBundleWeightsDescr] = (
+ 181        None
+ 182    )
+ 183    torchscript: Optional[TorchscriptWeightsDescr] = None
+ 184
+ 185    @model_validator(mode="after")
+ 186    def check_one_entry(self) -> Self:
+ 187        if all(
+ 188            entry is None
+ 189            for entry in [
+ 190                self.keras_hdf5,
+ 191                self.onnx,
+ 192                self.pytorch_state_dict,
+ 193                self.tensorflow_js,
+ 194                self.tensorflow_saved_model_bundle,
+ 195                self.torchscript,
+ 196            ]
+ 197        ):
+ 198            raise ValueError("Missing weights entry")
+ 199
+ 200        return self
+ 201
  202
- 203        return self
- 204
- 205
- 206class WeightsEntryDescrBase(FileDescr):
- 207    type: ClassVar[WeightsFormat]
- 208    weights_format_name: ClassVar[str]  # human readable
+ 203class WeightsEntryDescrBase(FileDescr):
+ 204    type: ClassVar[WeightsFormat]
+ 205    weights_format_name: ClassVar[str]  # human readable
+ 206
+ 207    source: ImportantFileSource
+ 208    """∈📦 The weights file."""
  209
- 210    source: ImportantFileSource
- 211    """∈📦 The weights file."""
- 212
- 213    attachments: Annotated[
- 214        Union[AttachmentsDescr, None],
- 215        warn(None, "Weights entry depends on additional attachments.", ALERT),
- 216    ] = None
- 217    """Attachments that are specific to this weights entry."""
- 218
- 219    authors: Union[List[Author], None] = None
- 220    """Authors
- 221    Either the person(s) that have trained this model resulting in the original weights file.
- 222        (If this is the initial weights entry, i.e. it does not have a `parent`)
- 223    Or the person(s) who have converted the weights to this weights format.
- 224        (If this is a child weight, i.e. it has a `parent` field)
- 225    """
- 226
- 227    dependencies: Annotated[
- 228        Optional[Dependencies],
- 229        warn(
- 230            None,
- 231            "Custom dependencies ({value}) specified. Avoid this whenever possible "
- 232            + "to allow execution in a wider range of software environments.",
- 233        ),
- 234        Field(
- 235            examples=[
- 236                "conda:environment.yaml",
- 237                "maven:./pom.xml",
- 238                "pip:./requirements.txt",
- 239            ]
- 240        ),
- 241    ] = None
- 242    """Dependency manager and dependency file, specified as `<dependency manager>:<relative file path>`."""
- 243
- 244    parent: Annotated[
- 245        Optional[WeightsFormat], Field(examples=["pytorch_state_dict"])
- 246    ] = None
- 247    """The source weights these weights were converted from.
- 248    For example, if a model's weights were converted from the `pytorch_state_dict` format to `torchscript`,
- 249    The `pytorch_state_dict` weights entry has no `parent` and is the parent of the `torchscript` weights.
- 250    All weight entries except one (the initial set of weights resulting from training the model),
- 251    need to have this field."""
- 252
- 253    @model_validator(mode="after")
- 254    def check_parent_is_not_self(self) -> Self:
- 255        if self.type == self.parent:
- 256            raise ValueError("Weights entry can't be it's own parent.")
+ 210    attachments: Annotated[
+ 211        Union[AttachmentsDescr, None],
+ 212        warn(None, "Weights entry depends on additional attachments.", ALERT),
+ 213    ] = None
+ 214    """Attachments that are specific to this weights entry."""
+ 215
+ 216    authors: Union[List[Author], None] = None
+ 217    """Authors
+ 218    Either the person(s) that have trained this model resulting in the original weights file.
+ 219        (If this is the initial weights entry, i.e. it does not have a `parent`)
+ 220    Or the person(s) who have converted the weights to this weights format.
+ 221        (If this is a child weight, i.e. it has a `parent` field)
+ 222    """
+ 223
+ 224    dependencies: Annotated[
+ 225        Optional[Dependencies],
+ 226        warn(
+ 227            None,
+ 228            "Custom dependencies ({value}) specified. Avoid this whenever possible "
+ 229            + "to allow execution in a wider range of software environments.",
+ 230        ),
+ 231        Field(
+ 232            examples=[
+ 233                "conda:environment.yaml",
+ 234                "maven:./pom.xml",
+ 235                "pip:./requirements.txt",
+ 236            ]
+ 237        ),
+ 238    ] = None
+ 239    """Dependency manager and dependency file, specified as `<dependency manager>:<relative file path>`."""
+ 240
+ 241    parent: Annotated[
+ 242        Optional[WeightsFormat], Field(examples=["pytorch_state_dict"])
+ 243    ] = None
+ 244    """The source weights these weights were converted from.
+ 245    For example, if a model's weights were converted from the `pytorch_state_dict` format to `torchscript`,
+ 246    The `pytorch_state_dict` weights entry has no `parent` and is the parent of the `torchscript` weights.
+ 247    All weight entries except one (the initial set of weights resulting from training the model),
+ 248    need to have this field."""
+ 249
+ 250    @model_validator(mode="after")
+ 251    def check_parent_is_not_self(self) -> Self:
+ 252        if self.type == self.parent:
+ 253            raise ValueError("Weights entry can't be it's own parent.")
+ 254
+ 255        return self
+ 256
  257
- 258        return self
- 259
- 260
- 261class KerasHdf5WeightsDescr(WeightsEntryDescrBase):
- 262    type = "keras_hdf5"
- 263    weights_format_name: ClassVar[str] = "Keras HDF5"
- 264    tensorflow_version: Optional[Version] = None
- 265    """TensorFlow version used to create these weights"""
- 266
- 267    @field_validator("tensorflow_version", mode="after")
- 268    @classmethod
- 269    def _tfv(cls, value: Any):
- 270        if value is None:
- 271            issue_warning(
- 272                "Missing TensorFlow version. Please specify the TensorFlow version"
- 273                + " these weights were created with.",
- 274                value=value,
- 275                severity=ALERT,
- 276            )
- 277        return value
- 278
- 279
- 280class OnnxWeightsDescr(WeightsEntryDescrBase):
- 281    type = "onnx"
- 282    weights_format_name: ClassVar[str] = "ONNX"
- 283    opset_version: Optional[Annotated[int, Ge(7)]] = None
- 284    """ONNX opset version"""
- 285
- 286    @field_validator("opset_version", mode="after")
- 287    @classmethod
- 288    def _ov(cls, value: Any):
- 289        if value is None:
- 290            issue_warning(
- 291                "Missing ONNX opset version (aka ONNX opset number). "
- 292                + "Please specify the ONNX opset version these weights were created"
- 293                + " with.",
- 294                value=value,
- 295                severity=ALERT,
- 296            )
- 297        return value
- 298
- 299
- 300class PytorchStateDictWeightsDescr(WeightsEntryDescrBase):
- 301    type = "pytorch_state_dict"
- 302    weights_format_name: ClassVar[str] = "Pytorch State Dict"
- 303    architecture: CustomCallable = Field(
- 304        examples=["my_function.py:MyNetworkClass", "my_module.submodule.get_my_model"]
- 305    )
- 306    """callable returning a torch.nn.Module instance.
- 307    Local implementation: `<relative path to file>:<identifier of implementation within the file>`.
- 308    Implementation in a dependency: `<dependency-package>.<[dependency-module]>.<identifier>`."""
- 309
- 310    architecture_sha256: Annotated[
- 311        Optional[Sha256],
- 312        Field(
- 313            description=(
- 314                "The SHA256 of the architecture source file, if the architecture is not"
- 315                " defined in a module listed in `dependencies`\n"
- 316            )
- 317            + SHA256_HINT,
- 318        ),
- 319    ] = None
- 320    """The SHA256 of the architecture source file,
- 321    if the architecture is not defined in a module listed in `dependencies`"""
- 322
- 323    @model_validator(mode="after")
- 324    def check_architecture_sha256(self) -> Self:
- 325        if isinstance(self.architecture, CallableFromFile):
- 326            if self.architecture_sha256 is None:
- 327                raise ValueError(
- 328                    "Missing required `architecture_sha256` for `architecture` with"
- 329                    + " source file."
- 330                )
- 331        elif self.architecture_sha256 is not None:
- 332            raise ValueError(
- 333                "Got `architecture_sha256` for architecture that does not have a source"
- 334                + " file."
- 335            )
- 336
- 337        return self
+ 258class KerasHdf5WeightsDescr(WeightsEntryDescrBase):
+ 259    type = "keras_hdf5"
+ 260    weights_format_name: ClassVar[str] = "Keras HDF5"
+ 261    tensorflow_version: Optional[Version] = None
+ 262    """TensorFlow version used to create these weights"""
+ 263
+ 264    @field_validator("tensorflow_version", mode="after")
+ 265    @classmethod
+ 266    def _tfv(cls, value: Any):
+ 267        if value is None:
+ 268            issue_warning(
+ 269                "Missing TensorFlow version. Please specify the TensorFlow version"
+ 270                + " these weights were created with.",
+ 271                value=value,
+ 272                severity=ALERT,
+ 273            )
+ 274        return value
+ 275
+ 276
+ 277class OnnxWeightsDescr(WeightsEntryDescrBase):
+ 278    type = "onnx"
+ 279    weights_format_name: ClassVar[str] = "ONNX"
+ 280    opset_version: Optional[Annotated[int, Ge(7)]] = None
+ 281    """ONNX opset version"""
+ 282
+ 283    @field_validator("opset_version", mode="after")
+ 284    @classmethod
+ 285    def _ov(cls, value: Any):
+ 286        if value is None:
+ 287            issue_warning(
+ 288                "Missing ONNX opset version (aka ONNX opset number). "
+ 289                + "Please specify the ONNX opset version these weights were created"
+ 290                + " with.",
+ 291                value=value,
+ 292                severity=ALERT,
+ 293            )
+ 294        return value
+ 295
+ 296
+ 297class PytorchStateDictWeightsDescr(WeightsEntryDescrBase):
+ 298    type = "pytorch_state_dict"
+ 299    weights_format_name: ClassVar[str] = "Pytorch State Dict"
+ 300    architecture: CustomCallable = Field(
+ 301        examples=["my_function.py:MyNetworkClass", "my_module.submodule.get_my_model"]
+ 302    )
+ 303    """callable returning a torch.nn.Module instance.
+ 304    Local implementation: `<relative path to file>:<identifier of implementation within the file>`.
+ 305    Implementation in a dependency: `<dependency-package>.<[dependency-module]>.<identifier>`."""
+ 306
+ 307    architecture_sha256: Annotated[
+ 308        Optional[Sha256],
+ 309        Field(
+ 310            description=(
+ 311                "The SHA256 of the architecture source file, if the architecture is not"
+ 312                " defined in a module listed in `dependencies`\n"
+ 313            )
+ 314            + SHA256_HINT,
+ 315        ),
+ 316    ] = None
+ 317    """The SHA256 of the architecture source file,
+ 318    if the architecture is not defined in a module listed in `dependencies`"""
+ 319
+ 320    @model_validator(mode="after")
+ 321    def check_architecture_sha256(self) -> Self:
+ 322        if isinstance(self.architecture, CallableFromFile):
+ 323            if self.architecture_sha256 is None:
+ 324                raise ValueError(
+ 325                    "Missing required `architecture_sha256` for `architecture` with"
+ 326                    + " source file."
+ 327                )
+ 328        elif self.architecture_sha256 is not None:
+ 329            raise ValueError(
+ 330                "Got `architecture_sha256` for architecture that does not have a source"
+ 331                + " file."
+ 332            )
+ 333
+ 334        return self
+ 335
+ 336    kwargs: Dict[str, Any] = Field(default_factory=dict)
+ 337    """key word arguments for the `architecture` callable"""
  338
- 339    kwargs: Dict[str, Any] = Field(default_factory=dict)
- 340    """key word arguments for the `architecture` callable"""
- 341
- 342    pytorch_version: Optional[Version] = None
- 343    """Version of the PyTorch library used.
- 344    If `depencencies` is specified it should include pytorch and the verison has to match.
- 345    (`dependencies` overrules `pytorch_version`)"""
- 346
- 347    @field_validator("pytorch_version", mode="after")
- 348    @classmethod
- 349    def _ptv(cls, value: Any):
- 350        if value is None:
- 351            issue_warning(
- 352                "Missing PyTorch version. Please specify the PyTorch version these"
- 353                + " PyTorch state dict weights were created with.",
- 354                value=value,
- 355                severity=ALERT,
- 356            )
- 357        return value
- 358
- 359
- 360class TorchscriptWeightsDescr(WeightsEntryDescrBase):
- 361    type = "torchscript"
- 362    weights_format_name: ClassVar[str] = "TorchScript"
- 363    pytorch_version: Optional[Version] = None
- 364    """Version of the PyTorch library used."""
- 365
- 366    @field_validator("pytorch_version", mode="after")
- 367    @classmethod
- 368    def _ptv(cls, value: Any):
- 369        if value is None:
- 370            issue_warning(
- 371                "Missing PyTorch version. Please specify the PyTorch version these"
- 372                + " Torchscript weights were created with.",
- 373                value=value,
- 374                severity=ALERT,
- 375            )
- 376        return value
- 377
- 378
- 379class TensorflowJsWeightsDescr(WeightsEntryDescrBase):
- 380    type = "tensorflow_js"
- 381    weights_format_name: ClassVar[str] = "Tensorflow.js"
- 382    tensorflow_version: Optional[Version] = None
- 383    """Version of the TensorFlow library used."""
- 384
- 385    @field_validator("tensorflow_version", mode="after")
- 386    @classmethod
- 387    def _tfv(cls, value: Any):
- 388        if value is None:
- 389            issue_warning(
- 390                "Missing TensorFlow version. Please specify the TensorFlow version"
- 391                + " these TensorflowJs weights were created with.",
- 392                value=value,
- 393                severity=ALERT,
- 394            )
- 395        return value
- 396
- 397    source: ImportantFileSource
- 398    """∈📦 The multi-file weights.
- 399    All required files/folders should be a zip archive."""
- 400
- 401
- 402class TensorflowSavedModelBundleWeightsDescr(WeightsEntryDescrBase):
- 403    type = "tensorflow_saved_model_bundle"
- 404    weights_format_name: ClassVar[str] = "Tensorflow Saved Model"
- 405    tensorflow_version: Optional[Version] = None
- 406    """Version of the TensorFlow library used."""
- 407
- 408    @field_validator("tensorflow_version", mode="after")
- 409    @classmethod
- 410    def _tfv(cls, value: Any):
- 411        if value is None:
- 412            issue_warning(
- 413                "Missing TensorFlow version. Please specify the TensorFlow version"
- 414                + " these Tensorflow saved model bundle weights were created with.",
- 415                value=value,
- 416                severity=ALERT,
- 417            )
- 418        return value
- 419
+ 339    pytorch_version: Optional[Version] = None
+ 340    """Version of the PyTorch library used.
+ 341    If `depencencies` is specified it should include pytorch and the verison has to match.
+ 342    (`dependencies` overrules `pytorch_version`)"""
+ 343
+ 344    @field_validator("pytorch_version", mode="after")
+ 345    @classmethod
+ 346    def _ptv(cls, value: Any):
+ 347        if value is None:
+ 348            issue_warning(
+ 349                "Missing PyTorch version. Please specify the PyTorch version these"
+ 350                + " PyTorch state dict weights were created with.",
+ 351                value=value,
+ 352                severity=ALERT,
+ 353            )
+ 354        return value
+ 355
+ 356
+ 357class TorchscriptWeightsDescr(WeightsEntryDescrBase):
+ 358    type = "torchscript"
+ 359    weights_format_name: ClassVar[str] = "TorchScript"
+ 360    pytorch_version: Optional[Version] = None
+ 361    """Version of the PyTorch library used."""
+ 362
+ 363    @field_validator("pytorch_version", mode="after")
+ 364    @classmethod
+ 365    def _ptv(cls, value: Any):
+ 366        if value is None:
+ 367            issue_warning(
+ 368                "Missing PyTorch version. Please specify the PyTorch version these"
+ 369                + " Torchscript weights were created with.",
+ 370                value=value,
+ 371                severity=ALERT,
+ 372            )
+ 373        return value
+ 374
+ 375
+ 376class TensorflowJsWeightsDescr(WeightsEntryDescrBase):
+ 377    type = "tensorflow_js"
+ 378    weights_format_name: ClassVar[str] = "Tensorflow.js"
+ 379    tensorflow_version: Optional[Version] = None
+ 380    """Version of the TensorFlow library used."""
+ 381
+ 382    @field_validator("tensorflow_version", mode="after")
+ 383    @classmethod
+ 384    def _tfv(cls, value: Any):
+ 385        if value is None:
+ 386            issue_warning(
+ 387                "Missing TensorFlow version. Please specify the TensorFlow version"
+ 388                + " these TensorflowJs weights were created with.",
+ 389                value=value,
+ 390                severity=ALERT,
+ 391            )
+ 392        return value
+ 393
+ 394    source: ImportantFileSource
+ 395    """∈📦 The multi-file weights.
+ 396    All required files/folders should be a zip archive."""
+ 397
+ 398
+ 399class TensorflowSavedModelBundleWeightsDescr(WeightsEntryDescrBase):
+ 400    type = "tensorflow_saved_model_bundle"
+ 401    weights_format_name: ClassVar[str] = "Tensorflow Saved Model"
+ 402    tensorflow_version: Optional[Version] = None
+ 403    """Version of the TensorFlow library used."""
+ 404
+ 405    @field_validator("tensorflow_version", mode="after")
+ 406    @classmethod
+ 407    def _tfv(cls, value: Any):
+ 408        if value is None:
+ 409            issue_warning(
+ 410                "Missing TensorFlow version. Please specify the TensorFlow version"
+ 411                + " these Tensorflow saved model bundle weights were created with.",
+ 412                value=value,
+ 413                severity=ALERT,
+ 414            )
+ 415        return value
+ 416
+ 417
+ 418class ParameterizedInputShape(Node):
+ 419    """A sequence of valid shapes given by `shape_k = min + k * step for k in {0, 1, ...}`."""
  420
- 421class ParameterizedInputShape(Node):
- 422    """A sequence of valid shapes given by `shape_k = min + k * step for k in {0, 1, ...}`."""
+ 421    min: NotEmpty[List[int]]
+ 422    """The minimum input shape"""
  423
- 424    min: NotEmpty[List[int]]
- 425    """The minimum input shape"""
+ 424    step: NotEmpty[List[int]]
+ 425    """The minimum shape change"""
  426
- 427    step: NotEmpty[List[int]]
- 428    """The minimum shape change"""
+ 427    def __len__(self) -> int:
+ 428        return len(self.min)
  429
- 430    def __len__(self) -> int:
- 431        return len(self.min)
- 432
- 433    @model_validator(mode="after")
- 434    def matching_lengths(self) -> Self:
- 435        if len(self.min) != len(self.step):
- 436            raise ValueError("`min` and `step` required to have the same length")
+ 430    @model_validator(mode="after")
+ 431    def matching_lengths(self) -> Self:
+ 432        if len(self.min) != len(self.step):
+ 433            raise ValueError("`min` and `step` required to have the same length")
+ 434
+ 435        return self
+ 436
  437
- 438        return self
- 439
- 440
- 441class ImplicitOutputShape(Node):
- 442    """Output tensor shape depending on an input tensor shape.
- 443    `shape(output_tensor) = shape(input_tensor) * scale + 2 * offset`"""
+ 438class ImplicitOutputShape(Node):
+ 439    """Output tensor shape depending on an input tensor shape.
+ 440    `shape(output_tensor) = shape(input_tensor) * scale + 2 * offset`"""
+ 441
+ 442    reference_tensor: TensorName
+ 443    """Name of the reference tensor."""
  444
- 445    reference_tensor: TensorName
- 446    """Name of the reference tensor."""
- 447
- 448    scale: NotEmpty[List[Union[float, None]]]
- 449    """output_pix/input_pix for each dimension.
- 450    'null' values indicate new dimensions, whose length is defined by 2*`offset`"""
+ 445    scale: NotEmpty[List[Union[float, None]]]
+ 446    """output_pix/input_pix for each dimension.
+ 447    'null' values indicate new dimensions, whose length is defined by 2*`offset`"""
+ 448
+ 449    offset: NotEmpty[List[Union[int, Annotated[float, MultipleOf(0.5)]]]]
+ 450    """Position of origin wrt to input."""
  451
- 452    offset: NotEmpty[List[Union[int, Annotated[float, MultipleOf(0.5)]]]]
- 453    """Position of origin wrt to input."""
+ 452    def __len__(self) -> int:
+ 453        return len(self.scale)
  454
- 455    def __len__(self) -> int:
- 456        return len(self.scale)
- 457
- 458    @model_validator(mode="after")
- 459    def matching_lengths(self) -> Self:
- 460        if len(self.scale) != len(self.offset):
- 461            raise ValueError(
- 462                f"scale {self.scale} has to have same length as offset {self.offset}!"
- 463            )
- 464        # if we have an expanded dimension, make sure that it's offet is not zero
- 465        for sc, off in zip(self.scale, self.offset):
- 466            if sc is None and not off:
- 467                raise ValueError("`offset` must not be zero if `scale` is none/zero")
+ 455    @model_validator(mode="after")
+ 456    def matching_lengths(self) -> Self:
+ 457        if len(self.scale) != len(self.offset):
+ 458            raise ValueError(
+ 459                f"scale {self.scale} has to have same length as offset {self.offset}!"
+ 460            )
+ 461        # if we have an expanded dimension, make sure that it's offet is not zero
+ 462        for sc, off in zip(self.scale, self.offset):
+ 463            if sc is None and not off:
+ 464                raise ValueError("`offset` must not be zero if `scale` is none/zero")
+ 465
+ 466        return self
+ 467
  468
- 469        return self
- 470
- 471
- 472class TensorDescrBase(Node):
- 473    name: TensorName
- 474    """Tensor name. No duplicates are allowed."""
- 475
- 476    description: str = ""
- 477
- 478    axes: AxesStr
- 479    """Axes identifying characters. Same length and order as the axes in `shape`.
- 480    | axis | description |
- 481    | --- | --- |
- 482    |  b  |  batch (groups multiple samples) |
- 483    |  i  |  instance/index/element |
- 484    |  t  |  time |
- 485    |  c  |  channel |
- 486    |  z  |  spatial dimension z |
- 487    |  y  |  spatial dimension y |
- 488    |  x  |  spatial dimension x |
- 489    """
- 490
- 491    data_range: Optional[
- 492        Tuple[Annotated[float, AllowInfNan(True)], Annotated[float, AllowInfNan(True)]]
- 493    ] = None
- 494    """Tuple `(minimum, maximum)` specifying the allowed range of the data in this tensor.
- 495    If not specified, the full data range that can be expressed in `data_type` is allowed."""
- 496
+ 469class TensorDescrBase(Node):
+ 470    name: TensorName
+ 471    """Tensor name. No duplicates are allowed."""
+ 472
+ 473    description: str = ""
+ 474
+ 475    axes: AxesStr
+ 476    """Axes identifying characters. Same length and order as the axes in `shape`.
+ 477    | axis | description |
+ 478    | --- | --- |
+ 479    |  b  |  batch (groups multiple samples) |
+ 480    |  i  |  instance/index/element |
+ 481    |  t  |  time |
+ 482    |  c  |  channel |
+ 483    |  z  |  spatial dimension z |
+ 484    |  y  |  spatial dimension y |
+ 485    |  x  |  spatial dimension x |
+ 486    """
+ 487
+ 488    data_range: Optional[
+ 489        Tuple[Annotated[float, AllowInfNan(True)], Annotated[float, AllowInfNan(True)]]
+ 490    ] = None
+ 491    """Tuple `(minimum, maximum)` specifying the allowed range of the data in this tensor.
+ 492    If not specified, the full data range that can be expressed in `data_type` is allowed."""
+ 493
+ 494
+ 495class ProcessingKwargs(KwargsNode):
+ 496    """base class for pre-/postprocessing key word arguments"""
  497
- 498class ProcessingKwargs(KwargsNode):
- 499    """base class for pre-/postprocessing key word arguments"""
- 500
+ 498
+ 499class ProcessingDescrBase(NodeWithExplicitlySetFields):
+ 500    """processing base class"""
  501
- 502class ProcessingDescrBase(NodeWithExplicitlySetFields):
- 503    """processing base class"""
+ 502    # name: Literal[PreprocessingName, PostprocessingName]  # todo: make abstract field
+ 503    fields_to_set_explicitly: ClassVar[FrozenSet[LiteralString]] = frozenset({"name"})
  504
- 505    # name: Literal[PreprocessingName, PostprocessingName]  # todo: make abstract field
- 506    fields_to_set_explicitly: ClassVar[FrozenSet[LiteralString]] = frozenset({"name"})
- 507
- 508
- 509class BinarizeKwargs(ProcessingKwargs):
- 510    threshold: float
- 511    """The fixed threshold"""
- 512
- 513
- 514class BinarizeDescr(ProcessingDescrBase):
- 515    """BinarizeDescr the tensor with a fixed threshold.
- 516    Values above the threshold will be set to one, values below the threshold to zero.
- 517    """
+ 505
+ 506class BinarizeKwargs(ProcessingKwargs):
+ 507    threshold: float
+ 508    """The fixed threshold"""
+ 509
+ 510
+ 511class BinarizeDescr(ProcessingDescrBase):
+ 512    """BinarizeDescr the tensor with a fixed threshold.
+ 513    Values above the threshold will be set to one, values below the threshold to zero.
+ 514    """
+ 515
+ 516    name: Literal["binarize"] = "binarize"
+ 517    kwargs: BinarizeKwargs
  518
- 519    name: Literal["binarize"] = "binarize"
- 520    kwargs: BinarizeKwargs
- 521
- 522
- 523class ClipKwargs(ProcessingKwargs):
- 524    min: float
- 525    """minimum value for clipping"""
- 526    max: float
- 527    """maximum value for clipping"""
- 528
+ 519
+ 520class ClipKwargs(ProcessingKwargs):
+ 521    min: float
+ 522    """minimum value for clipping"""
+ 523    max: float
+ 524    """maximum value for clipping"""
+ 525
+ 526
+ 527class ClipDescr(ProcessingDescrBase):
+ 528    """Set tensor values below min to min and above max to max."""
  529
- 530class ClipDescr(ProcessingDescrBase):
- 531    """Set tensor values below min to min and above max to max."""
- 532
- 533    name: Literal["clip"] = "clip"
+ 530    name: Literal["clip"] = "clip"
+ 531
+ 532    kwargs: ClipKwargs
+ 533
  534
- 535    kwargs: ClipKwargs
- 536
- 537
- 538class ScaleLinearKwargs(ProcessingKwargs):
- 539    axes: Annotated[Optional[AxesInCZYX], Field(examples=["xy"])] = None
- 540    """The subset of axes to scale jointly.
- 541    For example xy to scale the two image axes for 2d data jointly."""
+ 535class ScaleLinearKwargs(ProcessingKwargs):
+ 536    axes: Annotated[Optional[AxesInCZYX], Field(examples=["xy"])] = None
+ 537    """The subset of axes to scale jointly.
+ 538    For example xy to scale the two image axes for 2d data jointly."""
+ 539
+ 540    gain: Union[float, List[float]] = 1.0
+ 541    """multiplicative factor"""
  542
- 543    gain: Union[float, List[float]] = 1.0
- 544    """multiplicative factor"""
+ 543    offset: Union[float, List[float]] = 0.0
+ 544    """additive term"""
  545
- 546    offset: Union[float, List[float]] = 0.0
- 547    """additive term"""
- 548
- 549    @model_validator(mode="after")
- 550    def either_gain_or_offset(self) -> Self:
- 551        if (
- 552            self.gain == 1.0
- 553            or isinstance(self.gain, list)
- 554            and all(g == 1.0 for g in self.gain)
- 555        ) and (
- 556            self.offset == 0.0
- 557            or isinstance(self.offset, list)
- 558            and all(off == 0.0 for off in self.offset)
- 559        ):
- 560            raise ValueError(
- 561                "Redunt linear scaling not allowd. Set `gain` != 1.0 and/or `offset` !="
- 562                + " 0.0."
- 563            )
+ 546    @model_validator(mode="after")
+ 547    def either_gain_or_offset(self) -> Self:
+ 548        if (
+ 549            self.gain == 1.0
+ 550            or isinstance(self.gain, list)
+ 551            and all(g == 1.0 for g in self.gain)
+ 552        ) and (
+ 553            self.offset == 0.0
+ 554            or isinstance(self.offset, list)
+ 555            and all(off == 0.0 for off in self.offset)
+ 556        ):
+ 557            raise ValueError(
+ 558                "Redunt linear scaling not allowd. Set `gain` != 1.0 and/or `offset` !="
+ 559                + " 0.0."
+ 560            )
+ 561
+ 562        return self
+ 563
  564
- 565        return self
- 566
+ 565class ScaleLinearDescr(ProcessingDescrBase):
+ 566    """Fixed linear scaling."""
  567
- 568class ScaleLinearDescr(ProcessingDescrBase):
- 569    """Fixed linear scaling."""
+ 568    name: Literal["scale_linear"] = "scale_linear"
+ 569    kwargs: ScaleLinearKwargs
  570
- 571    name: Literal["scale_linear"] = "scale_linear"
- 572    kwargs: ScaleLinearKwargs
- 573
+ 571
+ 572class SigmoidDescr(ProcessingDescrBase):
+ 573    """The logistic sigmoid funciton, a.k.a. expit function."""
  574
- 575class SigmoidDescr(ProcessingDescrBase):
- 576    """The logistic sigmoid funciton, a.k.a. expit function."""
- 577
- 578    name: Literal["sigmoid"] = "sigmoid"
- 579
- 580    @property
- 581    def kwargs(self) -> ProcessingKwargs:
- 582        """empty kwargs"""
- 583        return ProcessingKwargs()
- 584
- 585
- 586class ZeroMeanUnitVarianceKwargs(ProcessingKwargs):
- 587    mode: Literal["fixed", "per_dataset", "per_sample"] = "fixed"
- 588    """Mode for computing mean and variance.
- 589    |     mode    |             description              |
- 590    | ----------- | ------------------------------------ |
- 591    |   fixed     | Fixed values for mean and variance   |
- 592    | per_dataset | Compute for the entire dataset       |
- 593    | per_sample  | Compute for each sample individually |
- 594    """
- 595    axes: Annotated[AxesInCZYX, Field(examples=["xy"])]
- 596    """The subset of axes to normalize jointly.
- 597    For example `xy` to normalize the two image axes for 2d data jointly."""
- 598
- 599    mean: Annotated[
- 600        Union[float, NotEmpty[List[float]], None], Field(examples=[(1.1, 2.2, 3.3)])
- 601    ] = None
- 602    """The mean value(s) to use for `mode: fixed`.
- 603    For example `[1.1, 2.2, 3.3]` in the case of a 3 channel image with `axes: xy`."""
- 604    # todo: check if means match input axes (for mode 'fixed')
- 605
- 606    std: Annotated[
- 607        Union[float, NotEmpty[List[float]], None], Field(examples=[(0.1, 0.2, 0.3)])
- 608    ] = None
- 609    """The standard deviation values to use for `mode: fixed`. Analogous to mean."""
+ 575    name: Literal["sigmoid"] = "sigmoid"
+ 576
+ 577    @property
+ 578    def kwargs(self) -> ProcessingKwargs:
+ 579        """empty kwargs"""
+ 580        return ProcessingKwargs()
+ 581
+ 582
+ 583class ZeroMeanUnitVarianceKwargs(ProcessingKwargs):
+ 584    mode: Literal["fixed", "per_dataset", "per_sample"] = "fixed"
+ 585    """Mode for computing mean and variance.
+ 586    |     mode    |             description              |
+ 587    | ----------- | ------------------------------------ |
+ 588    |   fixed     | Fixed values for mean and variance   |
+ 589    | per_dataset | Compute for the entire dataset       |
+ 590    | per_sample  | Compute for each sample individually |
+ 591    """
+ 592    axes: Annotated[AxesInCZYX, Field(examples=["xy"])]
+ 593    """The subset of axes to normalize jointly.
+ 594    For example `xy` to normalize the two image axes for 2d data jointly."""
+ 595
+ 596    mean: Annotated[
+ 597        Union[float, NotEmpty[List[float]], None], Field(examples=[(1.1, 2.2, 3.3)])
+ 598    ] = None
+ 599    """The mean value(s) to use for `mode: fixed`.
+ 600    For example `[1.1, 2.2, 3.3]` in the case of a 3 channel image with `axes: xy`."""
+ 601    # todo: check if means match input axes (for mode 'fixed')
+ 602
+ 603    std: Annotated[
+ 604        Union[float, NotEmpty[List[float]], None], Field(examples=[(0.1, 0.2, 0.3)])
+ 605    ] = None
+ 606    """The standard deviation values to use for `mode: fixed`. Analogous to mean."""
+ 607
+ 608    eps: Annotated[float, Interval(gt=0, le=0.1)] = 1e-6
+ 609    """epsilon for numeric stability: `out = (tensor - mean) / (std + eps)`."""
  610
- 611    eps: Annotated[float, Interval(gt=0, le=0.1)] = 1e-6
- 612    """epsilon for numeric stability: `out = (tensor - mean) / (std + eps)`."""
- 613
- 614    @model_validator(mode="after")
- 615    def mean_and_std_match_mode(self) -> Self:
- 616        if self.mode == "fixed" and (self.mean is None or self.std is None):
- 617            raise ValueError("`mean` and `std` are required for `mode: fixed`.")
- 618        elif self.mode != "fixed" and (self.mean is not None or self.std is not None):
- 619            raise ValueError(f"`mean` and `std` not allowed for `mode: {self.mode}`")
+ 611    @model_validator(mode="after")
+ 612    def mean_and_std_match_mode(self) -> Self:
+ 613        if self.mode == "fixed" and (self.mean is None or self.std is None):
+ 614            raise ValueError("`mean` and `std` are required for `mode: fixed`.")
+ 615        elif self.mode != "fixed" and (self.mean is not None or self.std is not None):
+ 616            raise ValueError(f"`mean` and `std` not allowed for `mode: {self.mode}`")
+ 617
+ 618        return self
+ 619
  620
- 621        return self
- 622
+ 621class ZeroMeanUnitVarianceDescr(ProcessingDescrBase):
+ 622    """Subtract mean and divide by variance."""
  623
- 624class ZeroMeanUnitVarianceDescr(ProcessingDescrBase):
- 625    """Subtract mean and divide by variance."""
+ 624    name: Literal["zero_mean_unit_variance"] = "zero_mean_unit_variance"
+ 625    kwargs: ZeroMeanUnitVarianceKwargs
  626
- 627    name: Literal["zero_mean_unit_variance"] = "zero_mean_unit_variance"
- 628    kwargs: ZeroMeanUnitVarianceKwargs
- 629
- 630
- 631class ScaleRangeKwargs(ProcessingKwargs):
- 632    mode: Literal["per_dataset", "per_sample"]
- 633    """Mode for computing percentiles.
- 634    |     mode    |             description              |
- 635    | ----------- | ------------------------------------ |
- 636    | per_dataset | compute for the entire dataset       |
- 637    | per_sample  | compute for each sample individually |
- 638    """
- 639    axes: Annotated[AxesInCZYX, Field(examples=["xy"])]
- 640    """The subset of axes to normalize jointly.
- 641    For example xy to normalize the two image axes for 2d data jointly."""
+ 627
+ 628class ScaleRangeKwargs(ProcessingKwargs):
+ 629    mode: Literal["per_dataset", "per_sample"]
+ 630    """Mode for computing percentiles.
+ 631    |     mode    |             description              |
+ 632    | ----------- | ------------------------------------ |
+ 633    | per_dataset | compute for the entire dataset       |
+ 634    | per_sample  | compute for each sample individually |
+ 635    """
+ 636    axes: Annotated[AxesInCZYX, Field(examples=["xy"])]
+ 637    """The subset of axes to normalize jointly.
+ 638    For example xy to normalize the two image axes for 2d data jointly."""
+ 639
+ 640    min_percentile: Annotated[Union[int, float], Interval(ge=0, lt=100)] = 0.0
+ 641    """The lower percentile used for normalization."""
  642
- 643    min_percentile: Annotated[Union[int, float], Interval(ge=0, lt=100)] = 0.0
- 644    """The lower percentile used for normalization."""
- 645
- 646    max_percentile: Annotated[Union[int, float], Interval(gt=1, le=100)] = 100.0
- 647    """The upper percentile used for normalization
- 648    Has to be bigger than `min_percentile`.
- 649    The range is 1 to 100 instead of 0 to 100 to avoid mistakenly
- 650    accepting percentiles specified in the range 0.0 to 1.0."""
- 651
- 652    @model_validator(mode="after")
- 653    def min_smaller_max(self, info: ValidationInfo) -> Self:
- 654        if self.min_percentile >= self.max_percentile:
- 655            raise ValueError(
- 656                f"min_percentile {self.min_percentile} >= max_percentile"
- 657                + f" {self.max_percentile}"
- 658            )
- 659
- 660        return self
- 661
- 662    eps: Annotated[float, Interval(gt=0, le=0.1)] = 1e-6
- 663    """Epsilon for numeric stability.
- 664    `out = (tensor - v_lower) / (v_upper - v_lower + eps)`;
- 665    with `v_lower,v_upper` values at the respective percentiles."""
- 666
- 667    reference_tensor: Optional[TensorName] = None
- 668    """Tensor name to compute the percentiles from. Default: The tensor itself.
- 669    For any tensor in `inputs` only input tensor references are allowed.
- 670    For a tensor in `outputs` only input tensor refereences are allowed if `mode: per_dataset`"""
- 671
+ 643    max_percentile: Annotated[Union[int, float], Interval(gt=1, le=100)] = 100.0
+ 644    """The upper percentile used for normalization
+ 645    Has to be bigger than `min_percentile`.
+ 646    The range is 1 to 100 instead of 0 to 100 to avoid mistakenly
+ 647    accepting percentiles specified in the range 0.0 to 1.0."""
+ 648
+ 649    @model_validator(mode="after")
+ 650    def min_smaller_max(self, info: ValidationInfo) -> Self:
+ 651        if self.min_percentile >= self.max_percentile:
+ 652            raise ValueError(
+ 653                f"min_percentile {self.min_percentile} >= max_percentile"
+ 654                + f" {self.max_percentile}"
+ 655            )
+ 656
+ 657        return self
+ 658
+ 659    eps: Annotated[float, Interval(gt=0, le=0.1)] = 1e-6
+ 660    """Epsilon for numeric stability.
+ 661    `out = (tensor - v_lower) / (v_upper - v_lower + eps)`;
+ 662    with `v_lower,v_upper` values at the respective percentiles."""
+ 663
+ 664    reference_tensor: Optional[TensorName] = None
+ 665    """Tensor name to compute the percentiles from. Default: The tensor itself.
+ 666    For any tensor in `inputs` only input tensor references are allowed.
+ 667    For a tensor in `outputs` only input tensor refereences are allowed if `mode: per_dataset`"""
+ 668
+ 669
+ 670class ScaleRangeDescr(ProcessingDescrBase):
+ 671    """Scale with percentiles."""
  672
- 673class ScaleRangeDescr(ProcessingDescrBase):
- 674    """Scale with percentiles."""
+ 673    name: Literal["scale_range"] = "scale_range"
+ 674    kwargs: ScaleRangeKwargs
  675
- 676    name: Literal["scale_range"] = "scale_range"
- 677    kwargs: ScaleRangeKwargs
- 678
- 679
- 680class ScaleMeanVarianceKwargs(ProcessingKwargs):
- 681    mode: Literal["per_dataset", "per_sample"]
- 682    """Mode for computing mean and variance.
- 683    |     mode    |             description              |
- 684    | ----------- | ------------------------------------ |
- 685    | per_dataset | Compute for the entire dataset       |
- 686    | per_sample  | Compute for each sample individually |
- 687    """
+ 676
+ 677class ScaleMeanVarianceKwargs(ProcessingKwargs):
+ 678    mode: Literal["per_dataset", "per_sample"]
+ 679    """Mode for computing mean and variance.
+ 680    |     mode    |             description              |
+ 681    | ----------- | ------------------------------------ |
+ 682    | per_dataset | Compute for the entire dataset       |
+ 683    | per_sample  | Compute for each sample individually |
+ 684    """
+ 685
+ 686    reference_tensor: TensorName
+ 687    """Name of tensor to match."""
  688
- 689    reference_tensor: TensorName
- 690    """Name of tensor to match."""
- 691
- 692    axes: Annotated[Optional[AxesInCZYX], Field(examples=["xy"])] = None
- 693    """The subset of axes to scale jointly.
- 694    For example xy to normalize the two image axes for 2d data jointly.
- 695    Default: scale all non-batch axes jointly."""
- 696
- 697    eps: Annotated[float, Interval(gt=0, le=0.1)] = 1e-6
- 698    """Epsilon for numeric stability:
- 699    "`out  = (tensor - mean) / (std + eps) * (ref_std + eps) + ref_mean."""
- 700
+ 689    axes: Annotated[Optional[AxesInCZYX], Field(examples=["xy"])] = None
+ 690    """The subset of axes to scale jointly.
+ 691    For example xy to normalize the two image axes for 2d data jointly.
+ 692    Default: scale all non-batch axes jointly."""
+ 693
+ 694    eps: Annotated[float, Interval(gt=0, le=0.1)] = 1e-6
+ 695    """Epsilon for numeric stability:
+ 696    "`out  = (tensor - mean) / (std + eps) * (ref_std + eps) + ref_mean."""
+ 697
+ 698
+ 699class ScaleMeanVarianceDescr(ProcessingDescrBase):
+ 700    """Scale the tensor s.t. its mean and variance match a reference tensor."""
  701
- 702class ScaleMeanVarianceDescr(ProcessingDescrBase):
- 703    """Scale the tensor s.t. its mean and variance match a reference tensor."""
+ 702    name: Literal["scale_mean_variance"] = "scale_mean_variance"
+ 703    kwargs: ScaleMeanVarianceKwargs
  704
- 705    name: Literal["scale_mean_variance"] = "scale_mean_variance"
- 706    kwargs: ScaleMeanVarianceKwargs
- 707
- 708
- 709PreprocessingDescr = Annotated[
- 710    Union[
- 711        BinarizeDescr,
- 712        ClipDescr,
- 713        ScaleLinearDescr,
- 714        SigmoidDescr,
- 715        ZeroMeanUnitVarianceDescr,
- 716        ScaleRangeDescr,
- 717    ],
- 718    Field(discriminator="name"),
- 719]
- 720PostprocessingDescr = Annotated[
- 721    Union[
- 722        BinarizeDescr,
- 723        ClipDescr,
- 724        ScaleLinearDescr,
- 725        SigmoidDescr,
- 726        ZeroMeanUnitVarianceDescr,
- 727        ScaleRangeDescr,
- 728        ScaleMeanVarianceDescr,
- 729    ],
- 730    Field(discriminator="name"),
- 731]
- 732
- 733
- 734class InputTensorDescr(TensorDescrBase):
- 735    data_type: Literal["float32", "uint8", "uint16"]
- 736    """For now an input tensor is expected to be given as `float32`.
- 737    The data flow in bioimage.io models is explained
- 738    [in this diagram.](https://docs.google.com/drawings/d/1FTw8-Rn6a6nXdkZ_SkMumtcjvur9mtIhRqLwnKqZNHM/edit)."""
- 739
- 740    shape: Annotated[
- 741        Union[Sequence[int], ParameterizedInputShape],
- 742        Field(
- 743            examples=[(1, 512, 512, 1), dict(min=(1, 64, 64, 1), step=(0, 32, 32, 0))]
- 744        ),
- 745    ]
- 746    """Specification of input tensor shape."""
+ 705
+ 706PreprocessingDescr = Annotated[
+ 707    Union[
+ 708        BinarizeDescr,
+ 709        ClipDescr,
+ 710        ScaleLinearDescr,
+ 711        SigmoidDescr,
+ 712        ZeroMeanUnitVarianceDescr,
+ 713        ScaleRangeDescr,
+ 714    ],
+ 715    Field(discriminator="name"),
+ 716]
+ 717PostprocessingDescr = Annotated[
+ 718    Union[
+ 719        BinarizeDescr,
+ 720        ClipDescr,
+ 721        ScaleLinearDescr,
+ 722        SigmoidDescr,
+ 723        ZeroMeanUnitVarianceDescr,
+ 724        ScaleRangeDescr,
+ 725        ScaleMeanVarianceDescr,
+ 726    ],
+ 727    Field(discriminator="name"),
+ 728]
+ 729
+ 730
+ 731class InputTensorDescr(TensorDescrBase):
+ 732    data_type: Literal["float32", "uint8", "uint16"]
+ 733    """For now an input tensor is expected to be given as `float32`.
+ 734    The data flow in bioimage.io models is explained
+ 735    [in this diagram.](https://docs.google.com/drawings/d/1FTw8-Rn6a6nXdkZ_SkMumtcjvur9mtIhRqLwnKqZNHM/edit)."""
+ 736
+ 737    shape: Annotated[
+ 738        Union[Sequence[int], ParameterizedInputShape],
+ 739        Field(
+ 740            examples=[(1, 512, 512, 1), dict(min=(1, 64, 64, 1), step=(0, 32, 32, 0))]
+ 741        ),
+ 742    ]
+ 743    """Specification of input tensor shape."""
+ 744
+ 745    preprocessing: List[PreprocessingDescr] = Field(default_factory=list)
+ 746    """Description of how this input should be preprocessed."""
  747
- 748    preprocessing: List[PreprocessingDescr] = Field(default_factory=list)
- 749    """Description of how this input should be preprocessed."""
- 750
- 751    @model_validator(mode="after")
- 752    def zero_batch_step_and_one_batch_size(self) -> Self:
- 753        bidx = self.axes.find("b")
- 754        if bidx == -1:
- 755            return self
- 756
- 757        if isinstance(self.shape, ParameterizedInputShape):
- 758            step = self.shape.step
- 759            shape = self.shape.min
- 760            if step[bidx] != 0:
- 761                raise ValueError(
- 762                    "Input shape step has to be zero in the batch dimension (the batch"
- 763                    + " dimension can always be increased, but `step` should specify how"
- 764                    + " to increase the minimal shape to find the largest single batch"
- 765                    + " shape)"
- 766                )
- 767        else:
- 768            shape = self.shape
+ 748    @model_validator(mode="after")
+ 749    def zero_batch_step_and_one_batch_size(self) -> Self:
+ 750        bidx = self.axes.find("b")
+ 751        if bidx == -1:
+ 752            return self
+ 753
+ 754        if isinstance(self.shape, ParameterizedInputShape):
+ 755            step = self.shape.step
+ 756            shape = self.shape.min
+ 757            if step[bidx] != 0:
+ 758                raise ValueError(
+ 759                    "Input shape step has to be zero in the batch dimension (the batch"
+ 760                    + " dimension can always be increased, but `step` should specify how"
+ 761                    + " to increase the minimal shape to find the largest single batch"
+ 762                    + " shape)"
+ 763                )
+ 764        else:
+ 765            shape = self.shape
+ 766
+ 767        if shape[bidx] != 1:
+ 768            raise ValueError("Input shape has to be 1 in the batch dimension b.")
  769
- 770        if shape[bidx] != 1:
- 771            raise ValueError("Input shape has to be 1 in the batch dimension b.")
- 772
- 773        return self
- 774
- 775    @model_validator(mode="after")
- 776    def validate_preprocessing_kwargs(self) -> Self:
- 777        for p in self.preprocessing:
- 778            kwargs_axes = p.kwargs.get("axes", "")
- 779            if not isinstance(kwargs_axes, str):
- 780                raise ValueError(
- 781                    f"Expected an `axes` string, but got {type(kwargs_axes)}"
- 782                )
+ 770        return self
+ 771
+ 772    @model_validator(mode="after")
+ 773    def validate_preprocessing_kwargs(self) -> Self:
+ 774        for p in self.preprocessing:
+ 775            kwargs_axes = p.kwargs.get("axes", "")
+ 776            if not isinstance(kwargs_axes, str):
+ 777                raise ValueError(
+ 778                    f"Expected an `axes` string, but got {type(kwargs_axes)}"
+ 779                )
+ 780
+ 781            if any(a not in self.axes for a in kwargs_axes):
+ 782                raise ValueError("`kwargs.axes` needs to be subset of `axes`")
  783
- 784            if any(a not in self.axes for a in kwargs_axes):
- 785                raise ValueError("`kwargs.axes` needs to be subset of `axes`")
+ 784        return self
+ 785
  786
- 787        return self
- 788
- 789
- 790class OutputTensorDescr(TensorDescrBase):
- 791    data_type: Literal[
- 792        "float32",
- 793        "float64",
- 794        "uint8",
- 795        "int8",
- 796        "uint16",
- 797        "int16",
- 798        "uint32",
- 799        "int32",
- 800        "uint64",
- 801        "int64",
- 802        "bool",
- 803    ]
- 804    """Data type.
- 805    The data flow in bioimage.io models is explained
- 806    [in this diagram.](https://docs.google.com/drawings/d/1FTw8-Rn6a6nXdkZ_SkMumtcjvur9mtIhRqLwnKqZNHM/edit)."""
+ 787class OutputTensorDescr(TensorDescrBase):
+ 788    data_type: Literal[
+ 789        "float32",
+ 790        "float64",
+ 791        "uint8",
+ 792        "int8",
+ 793        "uint16",
+ 794        "int16",
+ 795        "uint32",
+ 796        "int32",
+ 797        "uint64",
+ 798        "int64",
+ 799        "bool",
+ 800    ]
+ 801    """Data type.
+ 802    The data flow in bioimage.io models is explained
+ 803    [in this diagram.](https://docs.google.com/drawings/d/1FTw8-Rn6a6nXdkZ_SkMumtcjvur9mtIhRqLwnKqZNHM/edit)."""
+ 804
+ 805    shape: Union[Sequence[int], ImplicitOutputShape]
+ 806    """Output tensor shape."""
  807
- 808    shape: Union[Sequence[int], ImplicitOutputShape]
- 809    """Output tensor shape."""
- 810
- 811    halo: Optional[Sequence[int]] = None
- 812    """The `halo` that should be cropped from the output tensor to avoid boundary effects.
- 813    The `halo` is to be cropped from both sides, i.e. `shape_after_crop = shape - 2 * halo`.
- 814    To document a `halo` that is already cropped by the model `shape.offset` has to be used instead."""
+ 808    halo: Optional[Sequence[int]] = None
+ 809    """The `halo` that should be cropped from the output tensor to avoid boundary effects.
+ 810    The `halo` is to be cropped from both sides, i.e. `shape_after_crop = shape - 2 * halo`.
+ 811    To document a `halo` that is already cropped by the model `shape.offset` has to be used instead."""
+ 812
+ 813    postprocessing: List[PostprocessingDescr] = Field(default_factory=list)
+ 814    """Description of how this output should be postprocessed."""
  815
- 816    postprocessing: List[PostprocessingDescr] = Field(default_factory=list)
- 817    """Description of how this output should be postprocessed."""
- 818
- 819    @model_validator(mode="after")
- 820    def matching_halo_length(self) -> Self:
- 821        if self.halo and len(self.halo) != len(self.shape):
- 822            raise ValueError(
- 823                f"halo {self.halo} has to have same length as shape {self.shape}!"
- 824            )
- 825
- 826        return self
- 827
- 828    @model_validator(mode="after")
- 829    def validate_postprocessing_kwargs(self) -> Self:
- 830        for p in self.postprocessing:
- 831            kwargs_axes = p.kwargs.get("axes", "")
- 832            if not isinstance(kwargs_axes, str):
- 833                raise ValueError(f"Expected {kwargs_axes} to be a string")
+ 816    @model_validator(mode="after")
+ 817    def matching_halo_length(self) -> Self:
+ 818        if self.halo and len(self.halo) != len(self.shape):
+ 819            raise ValueError(
+ 820                f"halo {self.halo} has to have same length as shape {self.shape}!"
+ 821            )
+ 822
+ 823        return self
+ 824
+ 825    @model_validator(mode="after")
+ 826    def validate_postprocessing_kwargs(self) -> Self:
+ 827        for p in self.postprocessing:
+ 828            kwargs_axes = p.kwargs.get("axes", "")
+ 829            if not isinstance(kwargs_axes, str):
+ 830                raise ValueError(f"Expected {kwargs_axes} to be a string")
+ 831
+ 832            if any(a not in self.axes for a in kwargs_axes):
+ 833                raise ValueError("`kwargs.axes` needs to be subset of axes")
  834
- 835            if any(a not in self.axes for a in kwargs_axes):
- 836                raise ValueError("`kwargs.axes` needs to be subset of axes")
+ 835        return self
+ 836
  837
- 838        return self
+ 838KnownRunMode = Literal["deepimagej"]
  839
  840
- 841KnownRunMode = Literal["deepimagej"]
- 842
- 843
- 844class RunMode(Node):
- 845    name: Annotated[
- 846        Union[KnownRunMode, str], warn(KnownRunMode, "Unknown run mode '{value}'.")
- 847    ]
- 848    """Run mode name"""
+ 841class RunMode(Node):
+ 842    name: Annotated[
+ 843        Union[KnownRunMode, str], warn(KnownRunMode, "Unknown run mode '{value}'.")
+ 844    ]
+ 845    """Run mode name"""
+ 846
+ 847    kwargs: Dict[str, Any] = Field(default_factory=dict)
+ 848    """Run mode specific key word arguments"""
  849
- 850    kwargs: Dict[str, Any] = Field(default_factory=dict)
- 851    """Run mode specific key word arguments"""
- 852
+ 850
+ 851class LinkedModel(Node):
+ 852    """Reference to a bioimage.io model."""
  853
- 854class LinkedModel(Node):
- 855    """Reference to a bioimage.io model."""
+ 854    id: ModelId
+ 855    """A valid model `id` from the bioimage.io collection."""
  856
- 857    id: ModelId
- 858    """A valid model `id` from the bioimage.io collection."""
+ 857    version_number: Optional[int] = None
+ 858    """version number (n-th published version, not the semantic version) of linked model"""
  859
- 860    version_number: Optional[int] = None
- 861    """version number (n-th published version, not the semantic version) of linked model"""
- 862
+ 860
+ 861class ModelDescr(GenericModelDescrBase, title="bioimage.io model specification"):
+ 862    """Specification of the fields used in a bioimage.io-compliant RDF that describes AI models with pretrained weights.
  863
- 864class ModelDescr(GenericModelDescrBase, title="bioimage.io model specification"):
- 865    """Specification of the fields used in a bioimage.io-compliant RDF that describes AI models with pretrained weights.
+ 864    These fields are typically stored in a YAML file which we call a model resource description file (model RDF).
+ 865    """
  866
- 867    These fields are typically stored in a YAML file which we call a model resource description file (model RDF).
- 868    """
- 869
- 870    format_version: Literal["0.4.10",] = "0.4.10"
- 871    """Version of the bioimage.io model description specification used.
- 872    When creating a new model always use the latest micro/patch version described here.
- 873    The `format_version` is important for any consumer software to understand how to parse the fields.
- 874    """
+ 867    format_version: Literal["0.4.10",] = "0.4.10"
+ 868    """Version of the bioimage.io model description specification used.
+ 869    When creating a new model always use the latest micro/patch version described here.
+ 870    The `format_version` is important for any consumer software to understand how to parse the fields.
+ 871    """
+ 872
+ 873    type: Literal["model"] = "model"
+ 874    """Specialized resource type 'model'"""
  875
- 876    type: Literal["model"] = "model"
- 877    """Specialized resource type 'model'"""
+ 876    id: Optional[ModelId] = None
+ 877    """Model zoo (bioimage.io) wide, unique identifier (assigned by bioimage.io)"""
  878
- 879    id: Optional[ModelId] = None
- 880    """Model zoo (bioimage.io) wide, unique identifier (assigned by bioimage.io)"""
+ 879    authors: NotEmpty[List[Author]]
+ 880    """The authors are the creators of the model RDF and the primary points of contact."""
  881
- 882    authors: NotEmpty[List[Author]]
- 883    """The authors are the creators of the model RDF and the primary points of contact."""
- 884
- 885    documentation: Annotated[
- 886        ImportantFileSource,
- 887        Field(
- 888            examples=[
- 889                "https://raw.githubusercontent.com/bioimage-io/spec-bioimage-io/main/example_descriptions/models/unet2d_nuclei_broad/README.md",
- 890                "README.md",
- 891            ],
- 892        ),
- 893    ]
- 894    """∈📦 URL or relative path to a markdown file with additional documentation.
- 895    The recommended documentation file name is `README.md`. An `.md` suffix is mandatory.
- 896    The documentation should include a '[#[#]]# Validation' (sub)section
- 897    with details on how to quantitatively validate the model on unseen data."""
+ 882    documentation: Annotated[
+ 883        ImportantFileSource,
+ 884        Field(
+ 885            examples=[
+ 886                "https://raw.githubusercontent.com/bioimage-io/spec-bioimage-io/main/example_descriptions/models/unet2d_nuclei_broad/README.md",
+ 887                "README.md",
+ 888            ],
+ 889        ),
+ 890    ]
+ 891    """∈📦 URL or relative path to a markdown file with additional documentation.
+ 892    The recommended documentation file name is `README.md`. An `.md` suffix is mandatory.
+ 893    The documentation should include a '[#[#]]# Validation' (sub)section
+ 894    with details on how to quantitatively validate the model on unseen data."""
+ 895
+ 896    inputs: NotEmpty[List[InputTensorDescr]]
+ 897    """Describes the input tensors expected by this model."""
  898
- 899    inputs: NotEmpty[List[InputTensorDescr]]
- 900    """Describes the input tensors expected by this model."""
- 901
- 902    license: Annotated[
- 903        Union[LicenseId, str],
- 904        warn(LicenseId, "Unknown license id '{value}'."),
- 905        Field(examples=["CC-BY-4.0", "MIT", "BSD-2-Clause"]),
- 906    ]
- 907    """A [SPDX license identifier](https://spdx.org/licenses/).
- 908    We do notsupport custom license beyond the SPDX license list, if you need that please
- 909    [open a GitHub issue](https://github.com/bioimage-io/spec-bioimage-io/issues/new/choose
- 910    ) to discuss your intentions with the community."""
- 911
- 912    name: Annotated[
- 913        str,
- 914        MinLen(1),
- 915        warn(MinLen(5), "Name shorter than 5 characters.", INFO),
- 916        warn(MaxLen(64), "Name longer than 64 characters.", INFO),
- 917    ]
- 918    """A human-readable name of this model.
- 919    It should be no longer than 64 characters and only contain letter, number, underscore, minus or space characters."""
+ 899    license: Annotated[
+ 900        Union[LicenseId, str],
+ 901        warn(LicenseId, "Unknown license id '{value}'."),
+ 902        Field(examples=["CC-BY-4.0", "MIT", "BSD-2-Clause"]),
+ 903    ]
+ 904    """A [SPDX license identifier](https://spdx.org/licenses/).
+ 905    We do notsupport custom license beyond the SPDX license list, if you need that please
+ 906    [open a GitHub issue](https://github.com/bioimage-io/spec-bioimage-io/issues/new/choose
+ 907    ) to discuss your intentions with the community."""
+ 908
+ 909    name: Annotated[
+ 910        str,
+ 911        MinLen(1),
+ 912        warn(MinLen(5), "Name shorter than 5 characters.", INFO),
+ 913        warn(MaxLen(64), "Name longer than 64 characters.", INFO),
+ 914    ]
+ 915    """A human-readable name of this model.
+ 916    It should be no longer than 64 characters and only contain letter, number, underscore, minus or space characters."""
+ 917
+ 918    outputs: NotEmpty[List[OutputTensorDescr]]
+ 919    """Describes the output tensors."""
  920
- 921    outputs: NotEmpty[List[OutputTensorDescr]]
- 922    """Describes the output tensors."""
- 923
- 924    @field_validator("inputs", "outputs")
- 925    @classmethod
- 926    def unique_tensor_descr_names(
- 927        cls, value: Sequence[Union[InputTensorDescr, OutputTensorDescr]]
- 928    ) -> Sequence[Union[InputTensorDescr, OutputTensorDescr]]:
- 929        unique_names = {str(v.name) for v in value}
- 930        if len(unique_names) != len(value):
- 931            raise ValueError("Duplicate tensor descriptor names")
- 932
- 933        return value
- 934
- 935    @model_validator(mode="after")
- 936    def unique_io_names(self) -> Self:
- 937        unique_names = {str(ss.name) for s in (self.inputs, self.outputs) for ss in s}
- 938        if len(unique_names) != (len(self.inputs) + len(self.outputs)):
- 939            raise ValueError("Duplicate tensor descriptor names across inputs/outputs")
- 940
- 941        return self
- 942
- 943    @model_validator(mode="after")
- 944    def minimum_shape2valid_output(self) -> Self:
- 945        tensors_by_name: Dict[
- 946            TensorName, Union[InputTensorDescr, OutputTensorDescr]
- 947        ] = {t.name: t for t in self.inputs + self.outputs}
- 948
- 949        for out in self.outputs:
- 950            if isinstance(out.shape, ImplicitOutputShape):
- 951                ndim_ref = len(tensors_by_name[out.shape.reference_tensor].shape)
- 952                ndim_out_ref = len(
- 953                    [scale for scale in out.shape.scale if scale is not None]
- 954                )
- 955                if ndim_ref != ndim_out_ref:
- 956                    expanded_dim_note = (
- 957                        " Note that expanded dimensions (`scale`: null) are not"
- 958                        + f" counted for {out.name}'sdimensionality here."
- 959                        if None in out.shape.scale
- 960                        else ""
- 961                    )
- 962                    raise ValueError(
- 963                        f"Referenced tensor '{out.shape.reference_tensor}' with"
- 964                        + f" {ndim_ref} dimensions does not match output tensor"
- 965                        + f" '{out.name}' with"
- 966                        + f" {ndim_out_ref} dimensions.{expanded_dim_note}"
- 967                    )
- 968
- 969            min_out_shape = self._get_min_shape(out, tensors_by_name)
- 970            if out.halo:
- 971                halo = out.halo
- 972                halo_msg = f" for halo {out.halo}"
- 973            else:
- 974                halo = [0] * len(min_out_shape)
- 975                halo_msg = ""
- 976
- 977            if any([s - 2 * h < 1 for s, h in zip(min_out_shape, halo)]):
- 978                raise ValueError(
- 979                    f"Minimal shape {min_out_shape} of output {out.name} is too"
- 980                    + f" small{halo_msg}."
- 981                )
- 982
- 983        return self
- 984
- 985    @classmethod
- 986    def _get_min_shape(
- 987        cls,
- 988        t: Union[InputTensorDescr, OutputTensorDescr],
- 989        tensors_by_name: Dict[TensorName, Union[InputTensorDescr, OutputTensorDescr]],
- 990    ) -> Sequence[int]:
- 991        """output with subtracted halo has to result in meaningful output even for the minimal input
- 992        see https://github.com/bioimage-io/spec-bioimage-io/issues/392
- 993        """
- 994        if isinstance(t.shape, collections.abc.Sequence):
- 995            return t.shape
- 996        elif isinstance(t.shape, ParameterizedInputShape):
- 997            return t.shape.min
- 998        elif isinstance(t.shape, ImplicitOutputShape):
- 999            pass
-1000        else:
-1001            assert_never(t.shape)
-1002
-1003        ref_shape = cls._get_min_shape(
-1004            tensors_by_name[t.shape.reference_tensor], tensors_by_name
-1005        )
-1006
-1007        if None not in t.shape.scale:
-1008            scale: Sequence[float, ...] = t.shape.scale  # type: ignore
-1009        else:
-1010            expanded_dims = [idx for idx, sc in enumerate(t.shape.scale) if sc is None]
-1011            new_ref_shape: List[int] = []
-1012            for idx in range(len(t.shape.scale)):
-1013                ref_idx = idx - sum(int(exp < idx) for exp in expanded_dims)
-1014                new_ref_shape.append(1 if idx in expanded_dims else ref_shape[ref_idx])
-1015
-1016            ref_shape = new_ref_shape
-1017            assert len(ref_shape) == len(t.shape.scale)
-1018            scale = [0.0 if sc is None else sc for sc in t.shape.scale]
-1019
-1020        offset = t.shape.offset
-1021        assert len(offset) == len(scale)
-1022        return [int(rs * s + 2 * off) for rs, s, off in zip(ref_shape, scale, offset)]
-1023
-1024    @model_validator(mode="after")
-1025    def validate_tensor_references_in_inputs(self) -> Self:
-1026        for t in self.inputs:
-1027            for proc in t.preprocessing:
-1028                if "reference_tensor" not in proc.kwargs:
-1029                    continue
-1030
-1031                ref_tensor = proc.kwargs["reference_tensor"]
-1032                if ref_tensor is not None and str(ref_tensor) not in {
-1033                    str(t.name) for t in self.inputs
-1034                }:
-1035                    raise ValueError(f"'{ref_tensor}' not found in inputs")
-1036
-1037                if ref_tensor == t.name:
-1038                    raise ValueError(
-1039                        f"invalid self reference for preprocessing of tensor {t.name}"
-1040                    )
-1041
-1042        return self
-1043
-1044    @model_validator(mode="after")
-1045    def validate_tensor_references_in_outputs(self) -> Self:
-1046        for t in self.outputs:
-1047            for proc in t.postprocessing:
-1048                if "reference_tensor" not in proc.kwargs:
-1049                    continue
-1050                ref_tensor = proc.kwargs["reference_tensor"]
-1051                if ref_tensor is not None and str(ref_tensor) not in {
-1052                    str(t.name) for t in self.inputs
-1053                }:
-1054                    raise ValueError(f"{ref_tensor} not found in inputs")
-1055
-1056        return self
-1057
-1058    packaged_by: List[Author] = Field(default_factory=list)
-1059    """The persons that have packaged and uploaded this model.
-1060    Only required if those persons differ from the `authors`."""
+ 921    @field_validator("inputs", "outputs")
+ 922    @classmethod
+ 923    def unique_tensor_descr_names(
+ 924        cls, value: Sequence[Union[InputTensorDescr, OutputTensorDescr]]
+ 925    ) -> Sequence[Union[InputTensorDescr, OutputTensorDescr]]:
+ 926        unique_names = {str(v.name) for v in value}
+ 927        if len(unique_names) != len(value):
+ 928            raise ValueError("Duplicate tensor descriptor names")
+ 929
+ 930        return value
+ 931
+ 932    @model_validator(mode="after")
+ 933    def unique_io_names(self) -> Self:
+ 934        unique_names = {str(ss.name) for s in (self.inputs, self.outputs) for ss in s}
+ 935        if len(unique_names) != (len(self.inputs) + len(self.outputs)):
+ 936            raise ValueError("Duplicate tensor descriptor names across inputs/outputs")
+ 937
+ 938        return self
+ 939
+ 940    @model_validator(mode="after")
+ 941    def minimum_shape2valid_output(self) -> Self:
+ 942        tensors_by_name: Dict[
+ 943            TensorName, Union[InputTensorDescr, OutputTensorDescr]
+ 944        ] = {t.name: t for t in self.inputs + self.outputs}
+ 945
+ 946        for out in self.outputs:
+ 947            if isinstance(out.shape, ImplicitOutputShape):
+ 948                ndim_ref = len(tensors_by_name[out.shape.reference_tensor].shape)
+ 949                ndim_out_ref = len(
+ 950                    [scale for scale in out.shape.scale if scale is not None]
+ 951                )
+ 952                if ndim_ref != ndim_out_ref:
+ 953                    expanded_dim_note = (
+ 954                        " Note that expanded dimensions (`scale`: null) are not"
+ 955                        + f" counted for {out.name}'sdimensionality here."
+ 956                        if None in out.shape.scale
+ 957                        else ""
+ 958                    )
+ 959                    raise ValueError(
+ 960                        f"Referenced tensor '{out.shape.reference_tensor}' with"
+ 961                        + f" {ndim_ref} dimensions does not match output tensor"
+ 962                        + f" '{out.name}' with"
+ 963                        + f" {ndim_out_ref} dimensions.{expanded_dim_note}"
+ 964                    )
+ 965
+ 966            min_out_shape = self._get_min_shape(out, tensors_by_name)
+ 967            if out.halo:
+ 968                halo = out.halo
+ 969                halo_msg = f" for halo {out.halo}"
+ 970            else:
+ 971                halo = [0] * len(min_out_shape)
+ 972                halo_msg = ""
+ 973
+ 974            if any([s - 2 * h < 1 for s, h in zip(min_out_shape, halo)]):
+ 975                raise ValueError(
+ 976                    f"Minimal shape {min_out_shape} of output {out.name} is too"
+ 977                    + f" small{halo_msg}."
+ 978                )
+ 979
+ 980        return self
+ 981
+ 982    @classmethod
+ 983    def _get_min_shape(
+ 984        cls,
+ 985        t: Union[InputTensorDescr, OutputTensorDescr],
+ 986        tensors_by_name: Dict[TensorName, Union[InputTensorDescr, OutputTensorDescr]],
+ 987    ) -> Sequence[int]:
+ 988        """output with subtracted halo has to result in meaningful output even for the minimal input
+ 989        see https://github.com/bioimage-io/spec-bioimage-io/issues/392
+ 990        """
+ 991        if isinstance(t.shape, collections.abc.Sequence):
+ 992            return t.shape
+ 993        elif isinstance(t.shape, ParameterizedInputShape):
+ 994            return t.shape.min
+ 995        elif isinstance(t.shape, ImplicitOutputShape):
+ 996            pass
+ 997        else:
+ 998            assert_never(t.shape)
+ 999
+1000        ref_shape = cls._get_min_shape(
+1001            tensors_by_name[t.shape.reference_tensor], tensors_by_name
+1002        )
+1003
+1004        if None not in t.shape.scale:
+1005            scale: Sequence[float, ...] = t.shape.scale  # type: ignore
+1006        else:
+1007            expanded_dims = [idx for idx, sc in enumerate(t.shape.scale) if sc is None]
+1008            new_ref_shape: List[int] = []
+1009            for idx in range(len(t.shape.scale)):
+1010                ref_idx = idx - sum(int(exp < idx) for exp in expanded_dims)
+1011                new_ref_shape.append(1 if idx in expanded_dims else ref_shape[ref_idx])
+1012
+1013            ref_shape = new_ref_shape
+1014            assert len(ref_shape) == len(t.shape.scale)
+1015            scale = [0.0 if sc is None else sc for sc in t.shape.scale]
+1016
+1017        offset = t.shape.offset
+1018        assert len(offset) == len(scale)
+1019        return [int(rs * s + 2 * off) for rs, s, off in zip(ref_shape, scale, offset)]
+1020
+1021    @model_validator(mode="after")
+1022    def validate_tensor_references_in_inputs(self) -> Self:
+1023        for t in self.inputs:
+1024            for proc in t.preprocessing:
+1025                if "reference_tensor" not in proc.kwargs:
+1026                    continue
+1027
+1028                ref_tensor = proc.kwargs["reference_tensor"]
+1029                if ref_tensor is not None and str(ref_tensor) not in {
+1030                    str(t.name) for t in self.inputs
+1031                }:
+1032                    raise ValueError(f"'{ref_tensor}' not found in inputs")
+1033
+1034                if ref_tensor == t.name:
+1035                    raise ValueError(
+1036                        f"invalid self reference for preprocessing of tensor {t.name}"
+1037                    )
+1038
+1039        return self
+1040
+1041    @model_validator(mode="after")
+1042    def validate_tensor_references_in_outputs(self) -> Self:
+1043        for t in self.outputs:
+1044            for proc in t.postprocessing:
+1045                if "reference_tensor" not in proc.kwargs:
+1046                    continue
+1047                ref_tensor = proc.kwargs["reference_tensor"]
+1048                if ref_tensor is not None and str(ref_tensor) not in {
+1049                    str(t.name) for t in self.inputs
+1050                }:
+1051                    raise ValueError(f"{ref_tensor} not found in inputs")
+1052
+1053        return self
+1054
+1055    packaged_by: List[Author] = Field(default_factory=list)
+1056    """The persons that have packaged and uploaded this model.
+1057    Only required if those persons differ from the `authors`."""
+1058
+1059    parent: Optional[LinkedModel] = None
+1060    """The model from which this model is derived, e.g. by fine-tuning the weights."""
 1061
-1062    parent: Optional[LinkedModel] = None
-1063    """The model from which this model is derived, e.g. by fine-tuning the weights."""
-1064
-1065    @field_validator("parent", mode="before")
-1066    @classmethod
-1067    def ignore_url_parent(cls, parent: Any):
-1068        if isinstance(parent, dict):
-1069            return None
+1062    @field_validator("parent", mode="before")
+1063    @classmethod
+1064    def ignore_url_parent(cls, parent: Any):
+1065        if isinstance(parent, dict):
+1066            return None
+1067
+1068        else:
+1069            return parent
 1070
-1071        else:
-1072            return parent
-1073
-1074    run_mode: Optional[RunMode] = None
-1075    """Custom run mode for this model: for more complex prediction procedures like test time
-1076    data augmentation that currently cannot be expressed in the specification.
-1077    No standard run modes are defined yet."""
-1078
-1079    sample_inputs: List[ImportantFileSource] = Field(default_factory=list)
-1080    """∈📦 URLs/relative paths to sample inputs to illustrate possible inputs for the model,
-1081    for example stored as PNG or TIFF images.
-1082    The sample files primarily serve to inform a human user about an example use case"""
+1071    run_mode: Optional[RunMode] = None
+1072    """Custom run mode for this model: for more complex prediction procedures like test time
+1073    data augmentation that currently cannot be expressed in the specification.
+1074    No standard run modes are defined yet."""
+1075
+1076    sample_inputs: List[ImportantFileSource] = Field(default_factory=list)
+1077    """∈📦 URLs/relative paths to sample inputs to illustrate possible inputs for the model,
+1078    for example stored as PNG or TIFF images.
+1079    The sample files primarily serve to inform a human user about an example use case"""
+1080
+1081    sample_outputs: List[ImportantFileSource] = Field(default_factory=list)
+1082    """∈📦 URLs/relative paths to sample outputs corresponding to the `sample_inputs`."""
 1083
-1084    sample_outputs: List[ImportantFileSource] = Field(default_factory=list)
-1085    """∈📦 URLs/relative paths to sample outputs corresponding to the `sample_inputs`."""
-1086
-1087    test_inputs: NotEmpty[
-1088        List[Annotated[ImportantFileSource, WithSuffix(".npy", case_sensitive=True)]]
-1089    ]
-1090    """∈📦 Test input tensors compatible with the `inputs` description for a **single test case**.
-1091    This means if your model has more than one input, you should provide one URL/relative path for each input.
-1092    Each test input should be a file with an ndarray in
-1093    [numpy.lib file format](https://numpy.org/doc/stable/reference/generated/numpy.lib.format.html#module-numpy.lib.format).
-1094    The extension must be '.npy'."""
-1095
-1096    test_outputs: NotEmpty[
-1097        List[Annotated[ImportantFileSource, WithSuffix(".npy", case_sensitive=True)]]
-1098    ]
-1099    """∈📦 Analog to `test_inputs`."""
-1100
-1101    timestamp: Datetime
-1102    """Timestamp in [ISO 8601](#https://en.wikipedia.org/wiki/ISO_8601) format
-1103    with a few restrictions listed [here](https://docs.python.org/3/library/datetime.html#datetime.datetime.fromisoformat)."""
+1084    test_inputs: NotEmpty[
+1085        List[Annotated[ImportantFileSource, WithSuffix(".npy", case_sensitive=True)]]
+1086    ]
+1087    """∈📦 Test input tensors compatible with the `inputs` description for a **single test case**.
+1088    This means if your model has more than one input, you should provide one URL/relative path for each input.
+1089    Each test input should be a file with an ndarray in
+1090    [numpy.lib file format](https://numpy.org/doc/stable/reference/generated/numpy.lib.format.html#module-numpy.lib.format).
+1091    The extension must be '.npy'."""
+1092
+1093    test_outputs: NotEmpty[
+1094        List[Annotated[ImportantFileSource, WithSuffix(".npy", case_sensitive=True)]]
+1095    ]
+1096    """∈📦 Analog to `test_inputs`."""
+1097
+1098    timestamp: Datetime
+1099    """Timestamp in [ISO 8601](#https://en.wikipedia.org/wiki/ISO_8601) format
+1100    with a few restrictions listed [here](https://docs.python.org/3/library/datetime.html#datetime.datetime.fromisoformat)."""
+1101
+1102    training_data: Union[LinkedDataset, DatasetDescr, None] = None
+1103    """The dataset used to train this model"""
 1104
-1105    training_data: Union[LinkedDataset, DatasetDescr, None] = None
-1106    """The dataset used to train this model"""
-1107
-1108    weights: WeightsDescr
-1109    """The weights for this model.
-1110    Weights can be given for different formats, but should otherwise be equivalent.
-1111    The available weight formats determine which consumers can use this model."""
-1112
-1113    @model_validator(mode="before")
-1114    @classmethod
-1115    def _convert_from_older_format(
-1116        cls, data: BioimageioYamlContent, /
-1117    ) -> BioimageioYamlContent:
-1118        convert_from_older_format(data)
-1119        return data
-1120
-1121    def get_input_test_arrays(self) -> List[NDArray[Any]]:
-1122        data = [load_array(download(ipt).path) for ipt in self.test_inputs]
-1123        assert all(isinstance(d, np.ndarray) for d in data)
-1124        return data
-1125
-1126    def get_output_test_arrays(self) -> List[NDArray[Any]]:
-1127        data = [load_array(download(out).path) for out in self.test_outputs]
-1128        assert all(isinstance(d, np.ndarray) for d in data)
-1129        return data
+1105    weights: WeightsDescr
+1106    """The weights for this model.
+1107    Weights can be given for different formats, but should otherwise be equivalent.
+1108    The available weight formats determine which consumers can use this model."""
+1109
+1110    @model_validator(mode="before")
+1111    @classmethod
+1112    def _convert_from_older_format(
+1113        cls, data: BioimageioYamlContent, /
+1114    ) -> BioimageioYamlContent:
+1115        convert_from_older_format(data)
+1116        return data
+1117
+1118    def get_input_test_arrays(self) -> List[NDArray[Any]]:
+1119        data = [load_array(download(ipt).path) for ipt in self.test_inputs]
+1120        assert all(isinstance(d, np.ndarray) for d in data)
+1121        return data
+1122
+1123    def get_output_test_arrays(self) -> List[NDArray[Any]]:
+1124        data = [load_array(download(out).path) for out in self.test_outputs]
+1125        assert all(isinstance(d, np.ndarray) for d in data)
+1126        return data
 
    
 
 
@@ -2190,25 +2187,25 @@ 
    
 
     
    
     
-            
    112class CallableFromDepencency(StringNode):
-113    _pattern = r"^.+\..+$"
-114    _submodule_adapter = TypeAdapter(Identifier)
-115
-116    module_name: str
-117
-118    @field_validator("module_name", mode="after")
-119    def check_submodules(cls, module_name: str) -> str:
-120        for submod in module_name.split("."):
-121            _ = cls._submodule_adapter.validate_python(submod)
-122
-123        return module_name
-124
-125    callable_name: Identifier
-126
-127    @classmethod
-128    def _get_data(cls, valid_string_data: str):
-129        *mods, callname = valid_string_data.split(".")
-130        return dict(module_name=".".join(mods), callable_name=callname)
+            
    109class CallableFromDepencency(StringNode):
+110    _pattern = r"^.+\..+$"
+111    _submodule_adapter = TypeAdapter(Identifier)
+112
+113    module_name: str
+114
+115    @field_validator("module_name", mode="after")
+116    def check_submodules(cls, module_name: str) -> str:
+117        for submod in module_name.split("."):
+118            _ = cls._submodule_adapter.validate_python(submod)
+119
+120        return module_name
+121
+122    callable_name: Identifier
+123
+124    @classmethod
+125    def _get_data(cls, valid_string_data: str):
+126        *mods, callname = valid_string_data.split(".")
+127        return dict(module_name=".".join(mods), callable_name=callname)
 
    
 
 
@@ -2239,12 +2236,12 @@ 
    
 
     
    
     
-            
    118    @field_validator("module_name", mode="after")
-119    def check_submodules(cls, module_name: str) -> str:
-120        for submod in module_name.split("."):
-121            _ = cls._submodule_adapter.validate_python(submod)
-122
-123        return module_name
+            
    115    @field_validator("module_name", mode="after")
+116    def check_submodules(cls, module_name: str) -> str:
+117        for submod in module_name.split("."):
+118            _ = cls._submodule_adapter.validate_python(submod)
+119
+120        return module_name
 
    
 
 
@@ -2334,20 +2331,20 @@ 
    Inherited Members
    
 
     
    
     
-            
    133class CallableFromFile(StringNode):
-134    _pattern = r"^.+:.+$"
-135    source_file: Annotated[
-136        Union[HttpUrl, RelativeFilePath],
-137        include_in_package_serializer,
-138    ]
-139    """∈📦 Python module that implements `callable_name`"""
-140    callable_name: Identifier
-141    """The Python identifier of  """
-142
-143    @classmethod
-144    def _get_data(cls, valid_string_data: str):
-145        *file_parts, callname = valid_string_data.split(":")
-146        return dict(source_file=":".join(file_parts), callable_name=callname)
+            
    130class CallableFromFile(StringNode):
+131    _pattern = r"^.+:.+$"
+132    source_file: Annotated[
+133        Union[HttpUrl, RelativeFilePath],
+134        include_in_package_serializer,
+135    ]
+136    """∈📦 Python module that implements `callable_name`"""
+137    callable_name: Identifier
+138    """The Python identifier of  """
+139
+140    @classmethod
+141    def _get_data(cls, valid_string_data: str):
+142        *file_parts, callname = valid_string_data.split(":")
+143        return dict(source_file=":".join(file_parts), callable_name=callname)
 
    
 
 
@@ -2357,7 +2354,7 @@ 
    Inherited Members
    
 
                             
    
                                 
    
-            source_file: Annotated[Union[bioimageio.spec._internal.url.HttpUrl, bioimageio.spec._internal.io.RelativeFilePath], PlainSerializer(func=<function _package at 0x7f1c21c782c0>, return_type=PydanticUndefined, when_used='unless-none')]
+            source_file: Annotated[Union[bioimageio.spec._internal.url.HttpUrl, bioimageio.spec._internal.io.RelativeFilePath], PlainSerializer(func=<function _package at 0x7afca0d91760>, return_type=PydanticUndefined, when_used='unless-none')]
 
         
     
    
@@ -2466,21 +2463,21 @@ 
    Inherited Members
    
 
     
    
     
-            
    152class Dependencies(StringNode):
-153    _pattern = r"^.+:.+$"
-154    manager: Annotated[NotEmpty[str], Field(examples=["conda", "maven", "pip"])]
-155    """Dependency manager"""
-156
-157    file: Annotated[
-158        ImportantFileSource,
-159        Field(examples=["environment.yaml", "pom.xml", "requirements.txt"]),
-160    ]
-161    """∈📦 Dependency file"""
-162
-163    @classmethod
-164    def _get_data(cls, valid_string_data: str):
-165        manager, *file_parts = valid_string_data.split(":")
-166        return dict(manager=manager, file=":".join(file_parts))
+            
    149class Dependencies(StringNode):
+150    _pattern = r"^.+:.+$"
+151    manager: Annotated[NotEmpty[str], Field(examples=["conda", "maven", "pip"])]
+152    """Dependency manager"""
+153
+154    file: Annotated[
+155        ImportantFileSource,
+156        Field(examples=["environment.yaml", "pom.xml", "requirements.txt"]),
+157    ]
+158    """∈📦 Dependency file"""
+159
+160    @classmethod
+161    def _get_data(cls, valid_string_data: str):
+162        manager, *file_parts = valid_string_data.split(":")
+163        return dict(manager=manager, file=":".join(file_parts))
 
    
 
 
@@ -2503,7 +2500,7 @@ 
    Inherited Members
    
                             
    
                             
    
                                 
    
-            file: Annotated[Union[Annotated[pathlib.Path, PathType(path_type='file')], bioimageio.spec._internal.io.RelativeFilePath, bioimageio.spec._internal.url.HttpUrl, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator(func=<function wo_special_file_name at 0x7f1c21c3ef20>), PlainSerializer(func=<function _package at 0x7f1c21c782c0>, return_type=PydanticUndefined, when_used='unless-none'), FieldInfo(annotation=NoneType, required=True, examples=['environment.yaml', 'pom.xml', 'requirements.txt'])]
+            file: Annotated[Union[Annotated[pathlib.Path, PathType(path_type='file')], bioimageio.spec._internal.io.RelativeFilePath, bioimageio.spec._internal.url.HttpUrl, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator(func=<function wo_special_file_name at 0x7afca0d90540>), PlainSerializer(func=<function _package at 0x7afca0d91760>, return_type=PydanticUndefined, when_used='unless-none'), FieldInfo(annotation=NoneType, required=True, examples=['environment.yaml', 'pom.xml', 'requirements.txt'])]
 
         
     
    
@@ -2599,32 +2596,32 @@ 
    Inherited Members
    
 
     
    
     
-            
    179class WeightsDescr(Node):
-180    keras_hdf5: Optional[KerasHdf5WeightsDescr] = None
-181    onnx: Optional[OnnxWeightsDescr] = None
-182    pytorch_state_dict: Optional[PytorchStateDictWeightsDescr] = None
-183    tensorflow_js: Optional[TensorflowJsWeightsDescr] = None
-184    tensorflow_saved_model_bundle: Optional[TensorflowSavedModelBundleWeightsDescr] = (
-185        None
-186    )
-187    torchscript: Optional[TorchscriptWeightsDescr] = None
-188
-189    @model_validator(mode="after")
-190    def check_one_entry(self) -> Self:
-191        if all(
-192            entry is None
-193            for entry in [
-194                self.keras_hdf5,
-195                self.onnx,
-196                self.pytorch_state_dict,
-197                self.tensorflow_js,
-198                self.tensorflow_saved_model_bundle,
-199                self.torchscript,
-200            ]
-201        ):
-202            raise ValueError("Missing weights entry")
-203
-204        return self
+            
    176class WeightsDescr(Node):
+177    keras_hdf5: Optional[KerasHdf5WeightsDescr] = None
+178    onnx: Optional[OnnxWeightsDescr] = None
+179    pytorch_state_dict: Optional[PytorchStateDictWeightsDescr] = None
+180    tensorflow_js: Optional[TensorflowJsWeightsDescr] = None
+181    tensorflow_saved_model_bundle: Optional[TensorflowSavedModelBundleWeightsDescr] = (
+182        None
+183    )
+184    torchscript: Optional[TorchscriptWeightsDescr] = None
+185
+186    @model_validator(mode="after")
+187    def check_one_entry(self) -> Self:
+188        if all(
+189            entry is None
+190            for entry in [
+191                self.keras_hdf5,
+192                self.onnx,
+193                self.pytorch_state_dict,
+194                self.tensorflow_js,
+195                self.tensorflow_saved_model_bundle,
+196                self.torchscript,
+197            ]
+198        ):
+199            raise ValueError("Missing weights entry")
+200
+201        return self
 
    
 
 
@@ -2710,22 +2707,22 @@ 
    Inherited Members
    
 
     
    
     
-            
    189    @model_validator(mode="after")
-190    def check_one_entry(self) -> Self:
-191        if all(
-192            entry is None
-193            for entry in [
-194                self.keras_hdf5,
-195                self.onnx,
-196                self.pytorch_state_dict,
-197                self.tensorflow_js,
-198                self.tensorflow_saved_model_bundle,
-199                self.torchscript,
-200            ]
-201        ):
-202            raise ValueError("Missing weights entry")
-203
-204        return self
+            
    186    @model_validator(mode="after")
+187    def check_one_entry(self) -> Self:
+188        if all(
+189            entry is None
+190            for entry in [
+191                self.keras_hdf5,
+192                self.onnx,
+193                self.pytorch_state_dict,
+194                self.tensorflow_js,
+195                self.tensorflow_saved_model_bundle,
+196                self.torchscript,
+197            ]
+198        ):
+199            raise ValueError("Missing weights entry")
+200
+201        return self
 
    
 
 
@@ -2819,59 +2816,59 @@ 
    Inherited Members
    
 
     
    
     
-            
    207class WeightsEntryDescrBase(FileDescr):
-208    type: ClassVar[WeightsFormat]
-209    weights_format_name: ClassVar[str]  # human readable
+            
    204class WeightsEntryDescrBase(FileDescr):
+205    type: ClassVar[WeightsFormat]
+206    weights_format_name: ClassVar[str]  # human readable
+207
+208    source: ImportantFileSource
+209    """∈📦 The weights file."""
 210
-211    source: ImportantFileSource
-212    """∈📦 The weights file."""
-213
-214    attachments: Annotated[
-215        Union[AttachmentsDescr, None],
-216        warn(None, "Weights entry depends on additional attachments.", ALERT),
-217    ] = None
-218    """Attachments that are specific to this weights entry."""
-219
-220    authors: Union[List[Author], None] = None
-221    """Authors
-222    Either the person(s) that have trained this model resulting in the original weights file.
-223        (If this is the initial weights entry, i.e. it does not have a `parent`)
-224    Or the person(s) who have converted the weights to this weights format.
-225        (If this is a child weight, i.e. it has a `parent` field)
-226    """
-227
-228    dependencies: Annotated[
-229        Optional[Dependencies],
-230        warn(
-231            None,
-232            "Custom dependencies ({value}) specified. Avoid this whenever possible "
-233            + "to allow execution in a wider range of software environments.",
-234        ),
-235        Field(
-236            examples=[
-237                "conda:environment.yaml",
-238                "maven:./pom.xml",
-239                "pip:./requirements.txt",
-240            ]
-241        ),
-242    ] = None
-243    """Dependency manager and dependency file, specified as `<dependency manager>:<relative file path>`."""
-244
-245    parent: Annotated[
-246        Optional[WeightsFormat], Field(examples=["pytorch_state_dict"])
-247    ] = None
-248    """The source weights these weights were converted from.
-249    For example, if a model's weights were converted from the `pytorch_state_dict` format to `torchscript`,
-250    The `pytorch_state_dict` weights entry has no `parent` and is the parent of the `torchscript` weights.
-251    All weight entries except one (the initial set of weights resulting from training the model),
-252    need to have this field."""
-253
-254    @model_validator(mode="after")
-255    def check_parent_is_not_self(self) -> Self:
-256        if self.type == self.parent:
-257            raise ValueError("Weights entry can't be it's own parent.")
-258
-259        return self
+211    attachments: Annotated[
+212        Union[AttachmentsDescr, None],
+213        warn(None, "Weights entry depends on additional attachments.", ALERT),
+214    ] = None
+215    """Attachments that are specific to this weights entry."""
+216
+217    authors: Union[List[Author], None] = None
+218    """Authors
+219    Either the person(s) that have trained this model resulting in the original weights file.
+220        (If this is the initial weights entry, i.e. it does not have a `parent`)
+221    Or the person(s) who have converted the weights to this weights format.
+222        (If this is a child weight, i.e. it has a `parent` field)
+223    """
+224
+225    dependencies: Annotated[
+226        Optional[Dependencies],
+227        warn(
+228            None,
+229            "Custom dependencies ({value}) specified. Avoid this whenever possible "
+230            + "to allow execution in a wider range of software environments.",
+231        ),
+232        Field(
+233            examples=[
+234                "conda:environment.yaml",
+235                "maven:./pom.xml",
+236                "pip:./requirements.txt",
+237            ]
+238        ),
+239    ] = None
+240    """Dependency manager and dependency file, specified as `<dependency manager>:<relative file path>`."""
+241
+242    parent: Annotated[
+243        Optional[WeightsFormat], Field(examples=["pytorch_state_dict"])
+244    ] = None
+245    """The source weights these weights were converted from.
+246    For example, if a model's weights were converted from the `pytorch_state_dict` format to `torchscript`,
+247    The `pytorch_state_dict` weights entry has no `parent` and is the parent of the `torchscript` weights.
+248    All weight entries except one (the initial set of weights resulting from training the model),
+249    need to have this field."""
+250
+251    @model_validator(mode="after")
+252    def check_parent_is_not_self(self) -> Self:
+253        if self.type == self.parent:
+254            raise ValueError("Weights entry can't be it's own parent.")
+255
+256        return self
 
    
 
 
@@ -2903,7 +2900,7 @@ 
    Inherited Members
    
                             
    
                             
    
                                 
    
-            source: Annotated[Union[Annotated[pathlib.Path, PathType(path_type='file')], bioimageio.spec._internal.io.RelativeFilePath, bioimageio.spec._internal.url.HttpUrl, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator(func=<function wo_special_file_name at 0x7f1c21c3ef20>), PlainSerializer(func=<function _package at 0x7f1c21c782c0>, return_type=PydanticUndefined, when_used='unless-none')]
+            source: Annotated[Union[Annotated[pathlib.Path, PathType(path_type='file')], bioimageio.spec._internal.io.RelativeFilePath, bioimageio.spec._internal.url.HttpUrl, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator(func=<function wo_special_file_name at 0x7afca0d90540>), PlainSerializer(func=<function _package at 0x7afca0d91760>, return_type=PydanticUndefined, when_used='unless-none')]
 
         
     
    
@@ -2916,7 +2913,7 @@ 
    Inherited Members
    
                             
    
                             
    
                                 
    
-            attachments: Annotated[Optional[bioimageio.spec.generic.v0_2.AttachmentsDescr], AfterWarner(func=<function as_warning.<locals>.wrapper at 0x7f1c1306dbc0>, severity=35, msg='Weights entry depends on additional attachments.', context={'typ': None})]
+            attachments: Annotated[Optional[bioimageio.spec.generic.v0_2.AttachmentsDescr], AfterWarner(func=<function as_warning.<locals>.wrapper at 0x7afc91ef1b20>, severity=35, msg='Weights entry depends on additional attachments.', context={'typ': None})]
 
         
     
    
@@ -2946,7 +2943,7 @@ 
    Inherited Members
    
                             
    
                             
    
                                 
    
-            dependencies: Annotated[Optional[Dependencies], AfterWarner(func=<function as_warning.<locals>.wrapper at 0x7f1c1306fce0>, severity=30, msg='Custom dependencies ({value}) specified. Avoid this whenever possible to allow execution in a wider range of software environments.', context={'typ': None}), FieldInfo(annotation=NoneType, required=True, examples=['conda:environment.yaml', 'maven:./pom.xml', 'pip:./requirements.txt'])]
+            dependencies: Annotated[Optional[Dependencies], AfterWarner(func=<function as_warning.<locals>.wrapper at 0x7afc91ef0b80>, severity=30, msg='Custom dependencies ({value}) specified. Avoid this whenever possible to allow execution in a wider range of software environments.', context={'typ': None}), FieldInfo(annotation=NoneType, required=True, examples=['conda:environment.yaml', 'maven:./pom.xml', 'pip:./requirements.txt'])]
 
         
     
    
@@ -2986,12 +2983,12 @@ 
    Inherited Members
    
 
     
    
     
-            
    254    @model_validator(mode="after")
-255    def check_parent_is_not_self(self) -> Self:
-256        if self.type == self.parent:
-257            raise ValueError("Weights entry can't be it's own parent.")
-258
-259        return self
+            
    251    @model_validator(mode="after")
+252    def check_parent_is_not_self(self) -> Self:
+253        if self.type == self.parent:
+254            raise ValueError("Weights entry can't be it's own parent.")
+255
+256        return self
 
    
 
 
@@ -3091,23 +3088,23 @@ 
    Inherited Members
    
 
     
    
     
-            
    262class KerasHdf5WeightsDescr(WeightsEntryDescrBase):
-263    type = "keras_hdf5"
-264    weights_format_name: ClassVar[str] = "Keras HDF5"
-265    tensorflow_version: Optional[Version] = None
-266    """TensorFlow version used to create these weights"""
-267
-268    @field_validator("tensorflow_version", mode="after")
-269    @classmethod
-270    def _tfv(cls, value: Any):
-271        if value is None:
-272            issue_warning(
-273                "Missing TensorFlow version. Please specify the TensorFlow version"
-274                + " these weights were created with.",
-275                value=value,
-276                severity=ALERT,
-277            )
-278        return value
+            
    259class KerasHdf5WeightsDescr(WeightsEntryDescrBase):
+260    type = "keras_hdf5"
+261    weights_format_name: ClassVar[str] = "Keras HDF5"
+262    tensorflow_version: Optional[Version] = None
+263    """TensorFlow version used to create these weights"""
+264
+265    @field_validator("tensorflow_version", mode="after")
+266    @classmethod
+267    def _tfv(cls, value: Any):
+268        if value is None:
+269            issue_warning(
+270                "Missing TensorFlow version. Please specify the TensorFlow version"
+271                + " these weights were created with.",
+272                value=value,
+273                severity=ALERT,
+274            )
+275        return value
 
    
 
 
@@ -3254,24 +3251,24 @@ 
    Inherited Members
    
 
     
    
     
-            
    281class OnnxWeightsDescr(WeightsEntryDescrBase):
-282    type = "onnx"
-283    weights_format_name: ClassVar[str] = "ONNX"
-284    opset_version: Optional[Annotated[int, Ge(7)]] = None
-285    """ONNX opset version"""
-286
-287    @field_validator("opset_version", mode="after")
-288    @classmethod
-289    def _ov(cls, value: Any):
-290        if value is None:
-291            issue_warning(
-292                "Missing ONNX opset version (aka ONNX opset number). "
-293                + "Please specify the ONNX opset version these weights were created"
-294                + " with.",
-295                value=value,
-296                severity=ALERT,
-297            )
-298        return value
+            
    278class OnnxWeightsDescr(WeightsEntryDescrBase):
+279    type = "onnx"
+280    weights_format_name: ClassVar[str] = "ONNX"
+281    opset_version: Optional[Annotated[int, Ge(7)]] = None
+282    """ONNX opset version"""
+283
+284    @field_validator("opset_version", mode="after")
+285    @classmethod
+286    def _ov(cls, value: Any):
+287        if value is None:
+288            issue_warning(
+289                "Missing ONNX opset version (aka ONNX opset number). "
+290                + "Please specify the ONNX opset version these weights were created"
+291                + " with.",
+292                value=value,
+293                severity=ALERT,
+294            )
+295        return value
 
    
 
 
@@ -3418,64 +3415,64 @@ 
    Inherited Members
    
 
     
    
     
-            
    301class PytorchStateDictWeightsDescr(WeightsEntryDescrBase):
-302    type = "pytorch_state_dict"
-303    weights_format_name: ClassVar[str] = "Pytorch State Dict"
-304    architecture: CustomCallable = Field(
-305        examples=["my_function.py:MyNetworkClass", "my_module.submodule.get_my_model"]
-306    )
-307    """callable returning a torch.nn.Module instance.
-308    Local implementation: `<relative path to file>:<identifier of implementation within the file>`.
-309    Implementation in a dependency: `<dependency-package>.<[dependency-module]>.<identifier>`."""
-310
-311    architecture_sha256: Annotated[
-312        Optional[Sha256],
-313        Field(
-314            description=(
-315                "The SHA256 of the architecture source file, if the architecture is not"
-316                " defined in a module listed in `dependencies`\n"
-317            )
-318            + SHA256_HINT,
-319        ),
-320    ] = None
-321    """The SHA256 of the architecture source file,
-322    if the architecture is not defined in a module listed in `dependencies`"""
-323
-324    @model_validator(mode="after")
-325    def check_architecture_sha256(self) -> Self:
-326        if isinstance(self.architecture, CallableFromFile):
-327            if self.architecture_sha256 is None:
-328                raise ValueError(
-329                    "Missing required `architecture_sha256` for `architecture` with"
-330                    + " source file."
-331                )
-332        elif self.architecture_sha256 is not None:
-333            raise ValueError(
-334                "Got `architecture_sha256` for architecture that does not have a source"
-335                + " file."
-336            )
-337
-338        return self
+            
    298class PytorchStateDictWeightsDescr(WeightsEntryDescrBase):
+299    type = "pytorch_state_dict"
+300    weights_format_name: ClassVar[str] = "Pytorch State Dict"
+301    architecture: CustomCallable = Field(
+302        examples=["my_function.py:MyNetworkClass", "my_module.submodule.get_my_model"]
+303    )
+304    """callable returning a torch.nn.Module instance.
+305    Local implementation: `<relative path to file>:<identifier of implementation within the file>`.
+306    Implementation in a dependency: `<dependency-package>.<[dependency-module]>.<identifier>`."""
+307
+308    architecture_sha256: Annotated[
+309        Optional[Sha256],
+310        Field(
+311            description=(
+312                "The SHA256 of the architecture source file, if the architecture is not"
+313                " defined in a module listed in `dependencies`\n"
+314            )
+315            + SHA256_HINT,
+316        ),
+317    ] = None
+318    """The SHA256 of the architecture source file,
+319    if the architecture is not defined in a module listed in `dependencies`"""
+320
+321    @model_validator(mode="after")
+322    def check_architecture_sha256(self) -> Self:
+323        if isinstance(self.architecture, CallableFromFile):
+324            if self.architecture_sha256 is None:
+325                raise ValueError(
+326                    "Missing required `architecture_sha256` for `architecture` with"
+327                    + " source file."
+328                )
+329        elif self.architecture_sha256 is not None:
+330            raise ValueError(
+331                "Got `architecture_sha256` for architecture that does not have a source"
+332                + " file."
+333            )
+334
+335        return self
+336
+337    kwargs: Dict[str, Any] = Field(default_factory=dict)
+338    """key word arguments for the `architecture` callable"""
 339
-340    kwargs: Dict[str, Any] = Field(default_factory=dict)
-341    """key word arguments for the `architecture` callable"""
-342
-343    pytorch_version: Optional[Version] = None
-344    """Version of the PyTorch library used.
-345    If `depencencies` is specified it should include pytorch and the verison has to match.
-346    (`dependencies` overrules `pytorch_version`)"""
-347
-348    @field_validator("pytorch_version", mode="after")
-349    @classmethod
-350    def _ptv(cls, value: Any):
-351        if value is None:
-352            issue_warning(
-353                "Missing PyTorch version. Please specify the PyTorch version these"
-354                + " PyTorch state dict weights were created with.",
-355                value=value,
-356                severity=ALERT,
-357            )
-358        return value
+340    pytorch_version: Optional[Version] = None
+341    """Version of the PyTorch library used.
+342    If `depencencies` is specified it should include pytorch and the verison has to match.
+343    (`dependencies` overrules `pytorch_version`)"""
+344
+345    @field_validator("pytorch_version", mode="after")
+346    @classmethod
+347    def _ptv(cls, value: Any):
+348        if value is None:
+349            issue_warning(
+350                "Missing PyTorch version. Please specify the PyTorch version these"
+351                + " PyTorch state dict weights were created with.",
+352                value=value,
+353                severity=ALERT,
+354            )
+355        return value
 
    
 
 
@@ -3548,21 +3545,21 @@ 
    Inherited Members
    
 
     
    
     
-            
    324    @model_validator(mode="after")
-325    def check_architecture_sha256(self) -> Self:
-326        if isinstance(self.architecture, CallableFromFile):
-327            if self.architecture_sha256 is None:
-328                raise ValueError(
-329                    "Missing required `architecture_sha256` for `architecture` with"
-330                    + " source file."
-331                )
-332        elif self.architecture_sha256 is not None:
-333            raise ValueError(
-334                "Got `architecture_sha256` for architecture that does not have a source"
-335                + " file."
-336            )
-337
-338        return self
+            
    321    @model_validator(mode="after")
+322    def check_architecture_sha256(self) -> Self:
+323        if isinstance(self.architecture, CallableFromFile):
+324            if self.architecture_sha256 is None:
+325                raise ValueError(
+326                    "Missing required `architecture_sha256` for `architecture` with"
+327                    + " source file."
+328                )
+329        elif self.architecture_sha256 is not None:
+330            raise ValueError(
+331                "Got `architecture_sha256` for architecture that does not have a source"
+332                + " file."
+333            )
+334
+335        return self
 
    
 
 
@@ -3699,23 +3696,23 @@ 
    Inherited Members
    
 
     
    
     
-            
    361class TorchscriptWeightsDescr(WeightsEntryDescrBase):
-362    type = "torchscript"
-363    weights_format_name: ClassVar[str] = "TorchScript"
-364    pytorch_version: Optional[Version] = None
-365    """Version of the PyTorch library used."""
-366
-367    @field_validator("pytorch_version", mode="after")
-368    @classmethod
-369    def _ptv(cls, value: Any):
-370        if value is None:
-371            issue_warning(
-372                "Missing PyTorch version. Please specify the PyTorch version these"
-373                + " Torchscript weights were created with.",
-374                value=value,
-375                severity=ALERT,
-376            )
-377        return value
+            
    358class TorchscriptWeightsDescr(WeightsEntryDescrBase):
+359    type = "torchscript"
+360    weights_format_name: ClassVar[str] = "TorchScript"
+361    pytorch_version: Optional[Version] = None
+362    """Version of the PyTorch library used."""
+363
+364    @field_validator("pytorch_version", mode="after")
+365    @classmethod
+366    def _ptv(cls, value: Any):
+367        if value is None:
+368            issue_warning(
+369                "Missing PyTorch version. Please specify the PyTorch version these"
+370                + " Torchscript weights were created with.",
+371                value=value,
+372                severity=ALERT,
+373            )
+374        return value
 
    
 
 
@@ -3862,27 +3859,27 @@ 
    Inherited Members
    
 
     
    
     
-            
    380class TensorflowJsWeightsDescr(WeightsEntryDescrBase):
-381    type = "tensorflow_js"
-382    weights_format_name: ClassVar[str] = "Tensorflow.js"
-383    tensorflow_version: Optional[Version] = None
-384    """Version of the TensorFlow library used."""
-385
-386    @field_validator("tensorflow_version", mode="after")
-387    @classmethod
-388    def _tfv(cls, value: Any):
-389        if value is None:
-390            issue_warning(
-391                "Missing TensorFlow version. Please specify the TensorFlow version"
-392                + " these TensorflowJs weights were created with.",
-393                value=value,
-394                severity=ALERT,
-395            )
-396        return value
-397
-398    source: ImportantFileSource
-399    """∈📦 The multi-file weights.
-400    All required files/folders should be a zip archive."""
+            
    377class TensorflowJsWeightsDescr(WeightsEntryDescrBase):
+378    type = "tensorflow_js"
+379    weights_format_name: ClassVar[str] = "Tensorflow.js"
+380    tensorflow_version: Optional[Version] = None
+381    """Version of the TensorFlow library used."""
+382
+383    @field_validator("tensorflow_version", mode="after")
+384    @classmethod
+385    def _tfv(cls, value: Any):
+386        if value is None:
+387            issue_warning(
+388                "Missing TensorFlow version. Please specify the TensorFlow version"
+389                + " these TensorflowJs weights were created with.",
+390                value=value,
+391                severity=ALERT,
+392            )
+393        return value
+394
+395    source: ImportantFileSource
+396    """∈📦 The multi-file weights.
+397    All required files/folders should be a zip archive."""
 
    
 
 
@@ -3929,7 +3926,7 @@ 
    Inherited Members
    
                             
    
                             
    
                                 
    
-            source: Annotated[Union[Annotated[pathlib.Path, PathType(path_type='file')], bioimageio.spec._internal.io.RelativeFilePath, bioimageio.spec._internal.url.HttpUrl, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator(func=<function wo_special_file_name at 0x7f1c21c3ef20>), PlainSerializer(func=<function _package at 0x7f1c21c782c0>, return_type=PydanticUndefined, when_used='unless-none')]
+            source: Annotated[Union[Annotated[pathlib.Path, PathType(path_type='file')], bioimageio.spec._internal.io.RelativeFilePath, bioimageio.spec._internal.url.HttpUrl, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator(func=<function wo_special_file_name at 0x7afca0d90540>), PlainSerializer(func=<function _package at 0x7afca0d91760>, return_type=PydanticUndefined, when_used='unless-none')]
 
         
     
    
@@ -4042,23 +4039,23 @@ 
    Inherited Members
    
 
     
    
     
-            
    403class TensorflowSavedModelBundleWeightsDescr(WeightsEntryDescrBase):
-404    type = "tensorflow_saved_model_bundle"
-405    weights_format_name: ClassVar[str] = "Tensorflow Saved Model"
-406    tensorflow_version: Optional[Version] = None
-407    """Version of the TensorFlow library used."""
-408
-409    @field_validator("tensorflow_version", mode="after")
-410    @classmethod
-411    def _tfv(cls, value: Any):
-412        if value is None:
-413            issue_warning(
-414                "Missing TensorFlow version. Please specify the TensorFlow version"
-415                + " these Tensorflow saved model bundle weights were created with.",
-416                value=value,
-417                severity=ALERT,
-418            )
-419        return value
+            
    400class TensorflowSavedModelBundleWeightsDescr(WeightsEntryDescrBase):
+401    type = "tensorflow_saved_model_bundle"
+402    weights_format_name: ClassVar[str] = "Tensorflow Saved Model"
+403    tensorflow_version: Optional[Version] = None
+404    """Version of the TensorFlow library used."""
+405
+406    @field_validator("tensorflow_version", mode="after")
+407    @classmethod
+408    def _tfv(cls, value: Any):
+409        if value is None:
+410            issue_warning(
+411                "Missing TensorFlow version. Please specify the TensorFlow version"
+412                + " these Tensorflow saved model bundle weights were created with.",
+413                value=value,
+414                severity=ALERT,
+415            )
+416        return value
 
    
 
 
@@ -4205,24 +4202,24 @@ 
    Inherited Members
    
 
     
    
     
-            
    422class ParameterizedInputShape(Node):
-423    """A sequence of valid shapes given by `shape_k = min + k * step for k in {0, 1, ...}`."""
+            
    419class ParameterizedInputShape(Node):
+420    """A sequence of valid shapes given by `shape_k = min + k * step for k in {0, 1, ...}`."""
+421
+422    min: NotEmpty[List[int]]
+423    """The minimum input shape"""
 424
-425    min: NotEmpty[List[int]]
-426    """The minimum input shape"""
+425    step: NotEmpty[List[int]]
+426    """The minimum shape change"""
 427
-428    step: NotEmpty[List[int]]
-429    """The minimum shape change"""
+428    def __len__(self) -> int:
+429        return len(self.min)
 430
-431    def __len__(self) -> int:
-432        return len(self.min)
-433
-434    @model_validator(mode="after")
-435    def matching_lengths(self) -> Self:
-436        if len(self.min) != len(self.step):
-437            raise ValueError("`min` and `step` required to have the same length")
-438
-439        return self
+431    @model_validator(mode="after")
+432    def matching_lengths(self) -> Self:
+433        if len(self.min) != len(self.step):
+434            raise ValueError("`min` and `step` required to have the same length")
+435
+436        return self
 
    
 
 
@@ -4268,12 +4265,12 @@ 
    Inherited Members
    
 
     
    
     
-            
    434    @model_validator(mode="after")
-435    def matching_lengths(self) -> Self:
-436        if len(self.min) != len(self.step):
-437            raise ValueError("`min` and `step` required to have the same length")
-438
-439        return self
+            
    431    @model_validator(mode="after")
+432    def matching_lengths(self) -> Self:
+433        if len(self.min) != len(self.step):
+434            raise ValueError("`min` and `step` required to have the same length")
+435
+436        return self
 
    
 
 
@@ -4367,35 +4364,35 @@ 
    Inherited Members
    
 
     
    
     
-            
    442class ImplicitOutputShape(Node):
-443    """Output tensor shape depending on an input tensor shape.
-444    `shape(output_tensor) = shape(input_tensor) * scale + 2 * offset`"""
+            
    439class ImplicitOutputShape(Node):
+440    """Output tensor shape depending on an input tensor shape.
+441    `shape(output_tensor) = shape(input_tensor) * scale + 2 * offset`"""
+442
+443    reference_tensor: TensorName
+444    """Name of the reference tensor."""
 445
-446    reference_tensor: TensorName
-447    """Name of the reference tensor."""
-448
-449    scale: NotEmpty[List[Union[float, None]]]
-450    """output_pix/input_pix for each dimension.
-451    'null' values indicate new dimensions, whose length is defined by 2*`offset`"""
+446    scale: NotEmpty[List[Union[float, None]]]
+447    """output_pix/input_pix for each dimension.
+448    'null' values indicate new dimensions, whose length is defined by 2*`offset`"""
+449
+450    offset: NotEmpty[List[Union[int, Annotated[float, MultipleOf(0.5)]]]]
+451    """Position of origin wrt to input."""
 452
-453    offset: NotEmpty[List[Union[int, Annotated[float, MultipleOf(0.5)]]]]
-454    """Position of origin wrt to input."""
+453    def __len__(self) -> int:
+454        return len(self.scale)
 455
-456    def __len__(self) -> int:
-457        return len(self.scale)
-458
-459    @model_validator(mode="after")
-460    def matching_lengths(self) -> Self:
-461        if len(self.scale) != len(self.offset):
-462            raise ValueError(
-463                f"scale {self.scale} has to have same length as offset {self.offset}!"
-464            )
-465        # if we have an expanded dimension, make sure that it's offet is not zero
-466        for sc, off in zip(self.scale, self.offset):
-467            if sc is None and not off:
-468                raise ValueError("`offset` must not be zero if `scale` is none/zero")
-469
-470        return self
+456    @model_validator(mode="after")
+457    def matching_lengths(self) -> Self:
+458        if len(self.scale) != len(self.offset):
+459            raise ValueError(
+460                f"scale {self.scale} has to have same length as offset {self.offset}!"
+461            )
+462        # if we have an expanded dimension, make sure that it's offet is not zero
+463        for sc, off in zip(self.scale, self.offset):
+464            if sc is None and not off:
+465                raise ValueError("`offset` must not be zero if `scale` is none/zero")
+466
+467        return self
 
    
 
 
@@ -4456,18 +4453,18 @@ 
    Inherited Members
    
 
     
    
     
-            
    459    @model_validator(mode="after")
-460    def matching_lengths(self) -> Self:
-461        if len(self.scale) != len(self.offset):
-462            raise ValueError(
-463                f"scale {self.scale} has to have same length as offset {self.offset}!"
-464            )
-465        # if we have an expanded dimension, make sure that it's offet is not zero
-466        for sc, off in zip(self.scale, self.offset):
-467            if sc is None and not off:
-468                raise ValueError("`offset` must not be zero if `scale` is none/zero")
-469
-470        return self
+            
    456    @model_validator(mode="after")
+457    def matching_lengths(self) -> Self:
+458        if len(self.scale) != len(self.offset):
+459            raise ValueError(
+460                f"scale {self.scale} has to have same length as offset {self.offset}!"
+461            )
+462        # if we have an expanded dimension, make sure that it's offet is not zero
+463        for sc, off in zip(self.scale, self.offset):
+464            if sc is None and not off:
+465                raise ValueError("`offset` must not be zero if `scale` is none/zero")
+466
+467        return self
 
    
 
 
@@ -4561,30 +4558,30 @@ 
    Inherited Members
    
 
     
    
     
-            
    473class TensorDescrBase(Node):
-474    name: TensorName
-475    """Tensor name. No duplicates are allowed."""
-476
-477    description: str = ""
-478
-479    axes: AxesStr
-480    """Axes identifying characters. Same length and order as the axes in `shape`.
-481    | axis | description |
-482    | --- | --- |
-483    |  b  |  batch (groups multiple samples) |
-484    |  i  |  instance/index/element |
-485    |  t  |  time |
-486    |  c  |  channel |
-487    |  z  |  spatial dimension z |
-488    |  y  |  spatial dimension y |
-489    |  x  |  spatial dimension x |
-490    """
-491
-492    data_range: Optional[
-493        Tuple[Annotated[float, AllowInfNan(True)], Annotated[float, AllowInfNan(True)]]
-494    ] = None
-495    """Tuple `(minimum, maximum)` specifying the allowed range of the data in this tensor.
-496    If not specified, the full data range that can be expressed in `data_type` is allowed."""
+            
    470class TensorDescrBase(Node):
+471    name: TensorName
+472    """Tensor name. No duplicates are allowed."""
+473
+474    description: str = ""
+475
+476    axes: AxesStr
+477    """Axes identifying characters. Same length and order as the axes in `shape`.
+478    | axis | description |
+479    | --- | --- |
+480    |  b  |  batch (groups multiple samples) |
+481    |  i  |  instance/index/element |
+482    |  t  |  time |
+483    |  c  |  channel |
+484    |  z  |  spatial dimension z |
+485    |  y  |  spatial dimension y |
+486    |  x  |  spatial dimension x |
+487    """
+488
+489    data_range: Optional[
+490        Tuple[Annotated[float, AllowInfNan(True)], Annotated[float, AllowInfNan(True)]]
+491    ] = None
+492    """Tuple `(minimum, maximum)` specifying the allowed range of the data in this tensor.
+493    If not specified, the full data range that can be expressed in `data_type` is allowed."""
 
    
 
 
@@ -4618,7 +4615,7 @@ 
    Inherited Members
    
                             
    
                             
    
                                 
    
-            axes: Annotated[str, RestrictCharacters(alphabet='bitczyx'), AfterValidator(func=<function validate_unique_entries at 0x7f1c21c7a340>)]
+            axes: Annotated[str, RestrictCharacters(alphabet='bitczyx'), AfterValidator(func=<function validate_unique_entries at 0x7afca0a94b80>)]
 
         
     
    
@@ -4739,8 +4736,8 @@ 
    Inherited Members
    
 
     
    
     
-            
    499class ProcessingKwargs(KwargsNode):
-500    """base class for pre-/postprocessing key word arguments"""
+            
    496class ProcessingKwargs(KwargsNode):
+497    """base class for pre-/postprocessing key word arguments"""
 
    
 
 
@@ -4838,11 +4835,11 @@ 
    Inherited Members
    
 
     
    
     
-            
    503class ProcessingDescrBase(NodeWithExplicitlySetFields):
-504    """processing base class"""
-505
-506    # name: Literal[PreprocessingName, PostprocessingName]  # todo: make abstract field
-507    fields_to_set_explicitly: ClassVar[FrozenSet[LiteralString]] = frozenset({"name"})
+            
    500class ProcessingDescrBase(NodeWithExplicitlySetFields):
+501    """processing base class"""
+502
+503    # name: Literal[PreprocessingName, PostprocessingName]  # todo: make abstract field
+504    fields_to_set_explicitly: ClassVar[FrozenSet[LiteralString]] = frozenset({"name"})
 
    
 
 
@@ -4955,9 +4952,9 @@ 
    Inherited Members
    
 
     
    
     
-            
    510class BinarizeKwargs(ProcessingKwargs):
-511    threshold: float
-512    """The fixed threshold"""
+            
    507class BinarizeKwargs(ProcessingKwargs):
+508    threshold: float
+509    """The fixed threshold"""
 
    
 
 
@@ -5068,13 +5065,13 @@ 
    Inherited Members
    
 
     
    
     
-            
    515class BinarizeDescr(ProcessingDescrBase):
-516    """BinarizeDescr the tensor with a fixed threshold.
-517    Values above the threshold will be set to one, values below the threshold to zero.
-518    """
-519
-520    name: Literal["binarize"] = "binarize"
-521    kwargs: BinarizeKwargs
+            
    512class BinarizeDescr(ProcessingDescrBase):
+513    """BinarizeDescr the tensor with a fixed threshold.
+514    Values above the threshold will be set to one, values below the threshold to zero.
+515    """
+516
+517    name: Literal["binarize"] = "binarize"
+518    kwargs: BinarizeKwargs
 
    
 
 
@@ -5200,11 +5197,11 @@ 
    Inherited Members
    
 
     
    
     
-            
    524class ClipKwargs(ProcessingKwargs):
-525    min: float
-526    """minimum value for clipping"""
-527    max: float
-528    """maximum value for clipping"""
+            
    521class ClipKwargs(ProcessingKwargs):
+522    min: float
+523    """minimum value for clipping"""
+524    max: float
+525    """maximum value for clipping"""
 
    
 
 
@@ -5329,12 +5326,12 @@ 
    Inherited Members
    
 
     
    
     
-            
    531class ClipDescr(ProcessingDescrBase):
-532    """Set tensor values below min to min and above max to max."""
-533
-534    name: Literal["clip"] = "clip"
-535
-536    kwargs: ClipKwargs
+            
    528class ClipDescr(ProcessingDescrBase):
+529    """Set tensor values below min to min and above max to max."""
+530
+531    name: Literal["clip"] = "clip"
+532
+533    kwargs: ClipKwargs
 
    
 
 
@@ -5459,34 +5456,34 @@ 
    Inherited Members
    
 
     
    
     
-            
    539class ScaleLinearKwargs(ProcessingKwargs):
-540    axes: Annotated[Optional[AxesInCZYX], Field(examples=["xy"])] = None
-541    """The subset of axes to scale jointly.
-542    For example xy to scale the two image axes for 2d data jointly."""
+            
    536class ScaleLinearKwargs(ProcessingKwargs):
+537    axes: Annotated[Optional[AxesInCZYX], Field(examples=["xy"])] = None
+538    """The subset of axes to scale jointly.
+539    For example xy to scale the two image axes for 2d data jointly."""
+540
+541    gain: Union[float, List[float]] = 1.0
+542    """multiplicative factor"""
 543
-544    gain: Union[float, List[float]] = 1.0
-545    """multiplicative factor"""
+544    offset: Union[float, List[float]] = 0.0
+545    """additive term"""
 546
-547    offset: Union[float, List[float]] = 0.0
-548    """additive term"""
-549
-550    @model_validator(mode="after")
-551    def either_gain_or_offset(self) -> Self:
-552        if (
-553            self.gain == 1.0
-554            or isinstance(self.gain, list)
-555            and all(g == 1.0 for g in self.gain)
-556        ) and (
-557            self.offset == 0.0
-558            or isinstance(self.offset, list)
-559            and all(off == 0.0 for off in self.offset)
-560        ):
-561            raise ValueError(
-562                "Redunt linear scaling not allowd. Set `gain` != 1.0 and/or `offset` !="
-563                + " 0.0."
-564            )
-565
-566        return self
+547    @model_validator(mode="after")
+548    def either_gain_or_offset(self) -> Self:
+549        if (
+550            self.gain == 1.0
+551            or isinstance(self.gain, list)
+552            and all(g == 1.0 for g in self.gain)
+553        ) and (
+554            self.offset == 0.0
+555            or isinstance(self.offset, list)
+556            and all(off == 0.0 for off in self.offset)
+557        ):
+558            raise ValueError(
+559                "Redunt linear scaling not allowd. Set `gain` != 1.0 and/or `offset` !="
+560                + " 0.0."
+561            )
+562
+563        return self
 
    
 
 
@@ -5496,7 +5493,7 @@ 
    Inherited Members
    
 
                             
    
                                 
    
-            axes: Annotated[Optional[Annotated[str, RestrictCharacters(alphabet='czyx'), AfterValidator(func=<function validate_unique_entries at 0x7f1c21c7a340>)]], FieldInfo(annotation=NoneType, required=True, examples=['xy'])]
+            axes: Annotated[Optional[Annotated[str, RestrictCharacters(alphabet='czyx'), AfterValidator(func=<function validate_unique_entries at 0x7afca0a94b80>)]], FieldInfo(annotation=NoneType, required=True, examples=['xy'])]
 
         
     
    
@@ -5546,23 +5543,23 @@ 
    Inherited Members
    
 
     
    
     
-            
    550    @model_validator(mode="after")
-551    def either_gain_or_offset(self) -> Self:
-552        if (
-553            self.gain == 1.0
-554            or isinstance(self.gain, list)
-555            and all(g == 1.0 for g in self.gain)
-556        ) and (
-557            self.offset == 0.0
-558            or isinstance(self.offset, list)
-559            and all(off == 0.0 for off in self.offset)
-560        ):
-561            raise ValueError(
-562                "Redunt linear scaling not allowd. Set `gain` != 1.0 and/or `offset` !="
-563                + " 0.0."
-564            )
-565
-566        return self
+            
    547    @model_validator(mode="after")
+548    def either_gain_or_offset(self) -> Self:
+549        if (
+550            self.gain == 1.0
+551            or isinstance(self.gain, list)
+552            and all(g == 1.0 for g in self.gain)
+553        ) and (
+554            self.offset == 0.0
+555            or isinstance(self.offset, list)
+556            and all(off == 0.0 for off in self.offset)
+557        ):
+558            raise ValueError(
+559                "Redunt linear scaling not allowd. Set `gain` != 1.0 and/or `offset` !="
+560                + " 0.0."
+561            )
+562
+563        return self
 
    
 
 
@@ -5660,11 +5657,11 @@ 
    Inherited Members
    
 
     
    
     
-            
    569class ScaleLinearDescr(ProcessingDescrBase):
-570    """Fixed linear scaling."""
-571
-572    name: Literal["scale_linear"] = "scale_linear"
-573    kwargs: ScaleLinearKwargs
+            
    566class ScaleLinearDescr(ProcessingDescrBase):
+567    """Fixed linear scaling."""
+568
+569    name: Literal["scale_linear"] = "scale_linear"
+570    kwargs: ScaleLinearKwargs
 
    
 
 
@@ -5789,15 +5786,15 @@ 
    Inherited Members
    
 
     
    
     
-            
    576class SigmoidDescr(ProcessingDescrBase):
-577    """The logistic sigmoid funciton, a.k.a. expit function."""
-578
-579    name: Literal["sigmoid"] = "sigmoid"
-580
-581    @property
-582    def kwargs(self) -> ProcessingKwargs:
-583        """empty kwargs"""
-584        return ProcessingKwargs()
+            
    573class SigmoidDescr(ProcessingDescrBase):
+574    """The logistic sigmoid funciton, a.k.a. expit function."""
+575
+576    name: Literal["sigmoid"] = "sigmoid"
+577
+578    @property
+579    def kwargs(self) -> ProcessingKwargs:
+580        """empty kwargs"""
+581        return ProcessingKwargs()
 
    
 
 
@@ -5825,10 +5822,10 @@ 
    Inherited Members
    
 
     
    
     
-            
    581    @property
-582    def kwargs(self) -> ProcessingKwargs:
-583        """empty kwargs"""
-584        return ProcessingKwargs()
+            
    578    @property
+579    def kwargs(self) -> ProcessingKwargs:
+580        """empty kwargs"""
+581        return ProcessingKwargs()
 
    
 
 
@@ -5931,42 +5928,42 @@ 
    Inherited Members
    
 
     
    
     
-            
    587class ZeroMeanUnitVarianceKwargs(ProcessingKwargs):
-588    mode: Literal["fixed", "per_dataset", "per_sample"] = "fixed"
-589    """Mode for computing mean and variance.
-590    |     mode    |             description              |
-591    | ----------- | ------------------------------------ |
-592    |   fixed     | Fixed values for mean and variance   |
-593    | per_dataset | Compute for the entire dataset       |
-594    | per_sample  | Compute for each sample individually |
-595    """
-596    axes: Annotated[AxesInCZYX, Field(examples=["xy"])]
-597    """The subset of axes to normalize jointly.
-598    For example `xy` to normalize the two image axes for 2d data jointly."""
-599
-600    mean: Annotated[
-601        Union[float, NotEmpty[List[float]], None], Field(examples=[(1.1, 2.2, 3.3)])
-602    ] = None
-603    """The mean value(s) to use for `mode: fixed`.
-604    For example `[1.1, 2.2, 3.3]` in the case of a 3 channel image with `axes: xy`."""
-605    # todo: check if means match input axes (for mode 'fixed')
-606
-607    std: Annotated[
-608        Union[float, NotEmpty[List[float]], None], Field(examples=[(0.1, 0.2, 0.3)])
-609    ] = None
-610    """The standard deviation values to use for `mode: fixed`. Analogous to mean."""
+            
    584class ZeroMeanUnitVarianceKwargs(ProcessingKwargs):
+585    mode: Literal["fixed", "per_dataset", "per_sample"] = "fixed"
+586    """Mode for computing mean and variance.
+587    |     mode    |             description              |
+588    | ----------- | ------------------------------------ |
+589    |   fixed     | Fixed values for mean and variance   |
+590    | per_dataset | Compute for the entire dataset       |
+591    | per_sample  | Compute for each sample individually |
+592    """
+593    axes: Annotated[AxesInCZYX, Field(examples=["xy"])]
+594    """The subset of axes to normalize jointly.
+595    For example `xy` to normalize the two image axes for 2d data jointly."""
+596
+597    mean: Annotated[
+598        Union[float, NotEmpty[List[float]], None], Field(examples=[(1.1, 2.2, 3.3)])
+599    ] = None
+600    """The mean value(s) to use for `mode: fixed`.
+601    For example `[1.1, 2.2, 3.3]` in the case of a 3 channel image with `axes: xy`."""
+602    # todo: check if means match input axes (for mode 'fixed')
+603
+604    std: Annotated[
+605        Union[float, NotEmpty[List[float]], None], Field(examples=[(0.1, 0.2, 0.3)])
+606    ] = None
+607    """The standard deviation values to use for `mode: fixed`. Analogous to mean."""
+608
+609    eps: Annotated[float, Interval(gt=0, le=0.1)] = 1e-6
+610    """epsilon for numeric stability: `out = (tensor - mean) / (std + eps)`."""
 611
-612    eps: Annotated[float, Interval(gt=0, le=0.1)] = 1e-6
-613    """epsilon for numeric stability: `out = (tensor - mean) / (std + eps)`."""
-614
-615    @model_validator(mode="after")
-616    def mean_and_std_match_mode(self) -> Self:
-617        if self.mode == "fixed" and (self.mean is None or self.std is None):
-618            raise ValueError("`mean` and `std` are required for `mode: fixed`.")
-619        elif self.mode != "fixed" and (self.mean is not None or self.std is not None):
-620            raise ValueError(f"`mean` and `std` not allowed for `mode: {self.mode}`")
-621
-622        return self
+612    @model_validator(mode="after")
+613    def mean_and_std_match_mode(self) -> Self:
+614        if self.mode == "fixed" and (self.mean is None or self.std is None):
+615            raise ValueError("`mean` and `std` are required for `mode: fixed`.")
+616        elif self.mode != "fixed" and (self.mean is not None or self.std is not None):
+617            raise ValueError(f"`mean` and `std` not allowed for `mode: {self.mode}`")
+618
+619        return self
 
    
 
 
@@ -5994,7 +5991,7 @@ 
    Inherited Members
    
                             
    
                             
    
                                 
    
-            axes: Annotated[str, RestrictCharacters(alphabet='czyx'), AfterValidator(func=<function validate_unique_entries at 0x7f1c21c7a340>), FieldInfo(annotation=NoneType, required=True, examples=['xy'])]
+            axes: Annotated[str, RestrictCharacters(alphabet='czyx'), AfterValidator(func=<function validate_unique_entries at 0x7afca0a94b80>), FieldInfo(annotation=NoneType, required=True, examples=['xy'])]
 
         
     
    
@@ -6058,14 +6055,14 @@ 
    Inherited Members
    
 
     
    
     
-            
    615    @model_validator(mode="after")
-616    def mean_and_std_match_mode(self) -> Self:
-617        if self.mode == "fixed" and (self.mean is None or self.std is None):
-618            raise ValueError("`mean` and `std` are required for `mode: fixed`.")
-619        elif self.mode != "fixed" and (self.mean is not None or self.std is not None):
-620            raise ValueError(f"`mean` and `std` not allowed for `mode: {self.mode}`")
-621
-622        return self
+            
    612    @model_validator(mode="after")
+613    def mean_and_std_match_mode(self) -> Self:
+614        if self.mode == "fixed" and (self.mean is None or self.std is None):
+615            raise ValueError("`mean` and `std` are required for `mode: fixed`.")
+616        elif self.mode != "fixed" and (self.mean is not None or self.std is not None):
+617            raise ValueError(f"`mean` and `std` not allowed for `mode: {self.mode}`")
+618
+619        return self
 
    
 
 
@@ -6163,11 +6160,11 @@ 
    Inherited Members
    
 
     
    
     
-            
    625class ZeroMeanUnitVarianceDescr(ProcessingDescrBase):
-626    """Subtract mean and divide by variance."""
-627
-628    name: Literal["zero_mean_unit_variance"] = "zero_mean_unit_variance"
-629    kwargs: ZeroMeanUnitVarianceKwargs
+            
    622class ZeroMeanUnitVarianceDescr(ProcessingDescrBase):
+623    """Subtract mean and divide by variance."""
+624
+625    name: Literal["zero_mean_unit_variance"] = "zero_mean_unit_variance"
+626    kwargs: ZeroMeanUnitVarianceKwargs
 
    
 
 
@@ -6292,46 +6289,46 @@ 
    Inherited Members
    
 
     
    
     
-            
    632class ScaleRangeKwargs(ProcessingKwargs):
-633    mode: Literal["per_dataset", "per_sample"]
-634    """Mode for computing percentiles.
-635    |     mode    |             description              |
-636    | ----------- | ------------------------------------ |
-637    | per_dataset | compute for the entire dataset       |
-638    | per_sample  | compute for each sample individually |
-639    """
-640    axes: Annotated[AxesInCZYX, Field(examples=["xy"])]
-641    """The subset of axes to normalize jointly.
-642    For example xy to normalize the two image axes for 2d data jointly."""
+            
    629class ScaleRangeKwargs(ProcessingKwargs):
+630    mode: Literal["per_dataset", "per_sample"]
+631    """Mode for computing percentiles.
+632    |     mode    |             description              |
+633    | ----------- | ------------------------------------ |
+634    | per_dataset | compute for the entire dataset       |
+635    | per_sample  | compute for each sample individually |
+636    """
+637    axes: Annotated[AxesInCZYX, Field(examples=["xy"])]
+638    """The subset of axes to normalize jointly.
+639    For example xy to normalize the two image axes for 2d data jointly."""
+640
+641    min_percentile: Annotated[Union[int, float], Interval(ge=0, lt=100)] = 0.0
+642    """The lower percentile used for normalization."""
 643
-644    min_percentile: Annotated[Union[int, float], Interval(ge=0, lt=100)] = 0.0
-645    """The lower percentile used for normalization."""
-646
-647    max_percentile: Annotated[Union[int, float], Interval(gt=1, le=100)] = 100.0
-648    """The upper percentile used for normalization
-649    Has to be bigger than `min_percentile`.
-650    The range is 1 to 100 instead of 0 to 100 to avoid mistakenly
-651    accepting percentiles specified in the range 0.0 to 1.0."""
-652
-653    @model_validator(mode="after")
-654    def min_smaller_max(self, info: ValidationInfo) -> Self:
-655        if self.min_percentile >= self.max_percentile:
-656            raise ValueError(
-657                f"min_percentile {self.min_percentile} >= max_percentile"
-658                + f" {self.max_percentile}"
-659            )
-660
-661        return self
-662
-663    eps: Annotated[float, Interval(gt=0, le=0.1)] = 1e-6
-664    """Epsilon for numeric stability.
-665    `out = (tensor - v_lower) / (v_upper - v_lower + eps)`;
-666    with `v_lower,v_upper` values at the respective percentiles."""
-667
-668    reference_tensor: Optional[TensorName] = None
-669    """Tensor name to compute the percentiles from. Default: The tensor itself.
-670    For any tensor in `inputs` only input tensor references are allowed.
-671    For a tensor in `outputs` only input tensor refereences are allowed if `mode: per_dataset`"""
+644    max_percentile: Annotated[Union[int, float], Interval(gt=1, le=100)] = 100.0
+645    """The upper percentile used for normalization
+646    Has to be bigger than `min_percentile`.
+647    The range is 1 to 100 instead of 0 to 100 to avoid mistakenly
+648    accepting percentiles specified in the range 0.0 to 1.0."""
+649
+650    @model_validator(mode="after")
+651    def min_smaller_max(self, info: ValidationInfo) -> Self:
+652        if self.min_percentile >= self.max_percentile:
+653            raise ValueError(
+654                f"min_percentile {self.min_percentile} >= max_percentile"
+655                + f" {self.max_percentile}"
+656            )
+657
+658        return self
+659
+660    eps: Annotated[float, Interval(gt=0, le=0.1)] = 1e-6
+661    """Epsilon for numeric stability.
+662    `out = (tensor - v_lower) / (v_upper - v_lower + eps)`;
+663    with `v_lower,v_upper` values at the respective percentiles."""
+664
+665    reference_tensor: Optional[TensorName] = None
+666    """Tensor name to compute the percentiles from. Default: The tensor itself.
+667    For any tensor in `inputs` only input tensor references are allowed.
+668    For a tensor in `outputs` only input tensor refereences are allowed if `mode: per_dataset`"""
 
    
 
 
@@ -6358,7 +6355,7 @@ 
    Inherited Members
    
                             
    
                             
    
                                 
    
-            axes: Annotated[str, RestrictCharacters(alphabet='czyx'), AfterValidator(func=<function validate_unique_entries at 0x7f1c21c7a340>), FieldInfo(annotation=NoneType, required=True, examples=['xy'])]
+            axes: Annotated[str, RestrictCharacters(alphabet='czyx'), AfterValidator(func=<function validate_unique_entries at 0x7afca0a94b80>), FieldInfo(annotation=NoneType, required=True, examples=['xy'])]
 
         
     
    
@@ -6411,15 +6408,15 @@ 
    Inherited Members
    
 
     
    
     
-            
    653    @model_validator(mode="after")
-654    def min_smaller_max(self, info: ValidationInfo) -> Self:
-655        if self.min_percentile >= self.max_percentile:
-656            raise ValueError(
-657                f"min_percentile {self.min_percentile} >= max_percentile"
-658                + f" {self.max_percentile}"
-659            )
-660
-661        return self
+            
    650    @model_validator(mode="after")
+651    def min_smaller_max(self, info: ValidationInfo) -> Self:
+652        if self.min_percentile >= self.max_percentile:
+653            raise ValueError(
+654                f"min_percentile {self.min_percentile} >= max_percentile"
+655                + f" {self.max_percentile}"
+656            )
+657
+658        return self
 
    
 
 
@@ -6547,11 +6544,11 @@ 
    Inherited Members
    
 
     
    
     
-            
    674class ScaleRangeDescr(ProcessingDescrBase):
-675    """Scale with percentiles."""
-676
-677    name: Literal["scale_range"] = "scale_range"
-678    kwargs: ScaleRangeKwargs
+            
    671class ScaleRangeDescr(ProcessingDescrBase):
+672    """Scale with percentiles."""
+673
+674    name: Literal["scale_range"] = "scale_range"
+675    kwargs: ScaleRangeKwargs
 
    
 
 
@@ -6676,26 +6673,26 @@ 
    Inherited Members
    
 
     
    
     
-            
    681class ScaleMeanVarianceKwargs(ProcessingKwargs):
-682    mode: Literal["per_dataset", "per_sample"]
-683    """Mode for computing mean and variance.
-684    |     mode    |             description              |
-685    | ----------- | ------------------------------------ |
-686    | per_dataset | Compute for the entire dataset       |
-687    | per_sample  | Compute for each sample individually |
-688    """
+            
    678class ScaleMeanVarianceKwargs(ProcessingKwargs):
+679    mode: Literal["per_dataset", "per_sample"]
+680    """Mode for computing mean and variance.
+681    |     mode    |             description              |
+682    | ----------- | ------------------------------------ |
+683    | per_dataset | Compute for the entire dataset       |
+684    | per_sample  | Compute for each sample individually |
+685    """
+686
+687    reference_tensor: TensorName
+688    """Name of tensor to match."""
 689
-690    reference_tensor: TensorName
-691    """Name of tensor to match."""
-692
-693    axes: Annotated[Optional[AxesInCZYX], Field(examples=["xy"])] = None
-694    """The subset of axes to scale jointly.
-695    For example xy to normalize the two image axes for 2d data jointly.
-696    Default: scale all non-batch axes jointly."""
-697
-698    eps: Annotated[float, Interval(gt=0, le=0.1)] = 1e-6
-699    """Epsilon for numeric stability:
-700    "`out  = (tensor - mean) / (std + eps) * (ref_std + eps) + ref_mean."""
+690    axes: Annotated[Optional[AxesInCZYX], Field(examples=["xy"])] = None
+691    """The subset of axes to scale jointly.
+692    For example xy to normalize the two image axes for 2d data jointly.
+693    Default: scale all non-batch axes jointly."""
+694
+695    eps: Annotated[float, Interval(gt=0, le=0.1)] = 1e-6
+696    """Epsilon for numeric stability:
+697    "`out  = (tensor - mean) / (std + eps) * (ref_std + eps) + ref_mean."""
 
    
 
 
@@ -6735,7 +6732,7 @@ 
    Inherited Members
    
                             
    
                             
    
                                 
    
-            axes: Annotated[Optional[Annotated[str, RestrictCharacters(alphabet='czyx'), AfterValidator(func=<function validate_unique_entries at 0x7f1c21c7a340>)]], FieldInfo(annotation=NoneType, required=True, examples=['xy'])]
+            axes: Annotated[Optional[Annotated[str, RestrictCharacters(alphabet='czyx'), AfterValidator(func=<function validate_unique_entries at 0x7afca0a94b80>)]], FieldInfo(annotation=NoneType, required=True, examples=['xy'])]
 
         
     
    
@@ -6853,11 +6850,11 @@ 
    Inherited Members
    
 
     
    
     
-            
    703class ScaleMeanVarianceDescr(ProcessingDescrBase):
-704    """Scale the tensor s.t. its mean and variance match a reference tensor."""
-705
-706    name: Literal["scale_mean_variance"] = "scale_mean_variance"
-707    kwargs: ScaleMeanVarianceKwargs
+            
    700class ScaleMeanVarianceDescr(ProcessingDescrBase):
+701    """Scale the tensor s.t. its mean and variance match a reference tensor."""
+702
+703    name: Literal["scale_mean_variance"] = "scale_mean_variance"
+704    kwargs: ScaleMeanVarianceKwargs
 
    
 
 
@@ -7008,60 +7005,60 @@ 
    Inherited Members
    
 
     
    
     
-            
    735class InputTensorDescr(TensorDescrBase):
-736    data_type: Literal["float32", "uint8", "uint16"]
-737    """For now an input tensor is expected to be given as `float32`.
-738    The data flow in bioimage.io models is explained
-739    [in this diagram.](https://docs.google.com/drawings/d/1FTw8-Rn6a6nXdkZ_SkMumtcjvur9mtIhRqLwnKqZNHM/edit)."""
-740
-741    shape: Annotated[
-742        Union[Sequence[int], ParameterizedInputShape],
-743        Field(
-744            examples=[(1, 512, 512, 1), dict(min=(1, 64, 64, 1), step=(0, 32, 32, 0))]
-745        ),
-746    ]
-747    """Specification of input tensor shape."""
+            
    732class InputTensorDescr(TensorDescrBase):
+733    data_type: Literal["float32", "uint8", "uint16"]
+734    """For now an input tensor is expected to be given as `float32`.
+735    The data flow in bioimage.io models is explained
+736    [in this diagram.](https://docs.google.com/drawings/d/1FTw8-Rn6a6nXdkZ_SkMumtcjvur9mtIhRqLwnKqZNHM/edit)."""
+737
+738    shape: Annotated[
+739        Union[Sequence[int], ParameterizedInputShape],
+740        Field(
+741            examples=[(1, 512, 512, 1), dict(min=(1, 64, 64, 1), step=(0, 32, 32, 0))]
+742        ),
+743    ]
+744    """Specification of input tensor shape."""
+745
+746    preprocessing: List[PreprocessingDescr] = Field(default_factory=list)
+747    """Description of how this input should be preprocessed."""
 748
-749    preprocessing: List[PreprocessingDescr] = Field(default_factory=list)
-750    """Description of how this input should be preprocessed."""
-751
-752    @model_validator(mode="after")
-753    def zero_batch_step_and_one_batch_size(self) -> Self:
-754        bidx = self.axes.find("b")
-755        if bidx == -1:
-756            return self
-757
-758        if isinstance(self.shape, ParameterizedInputShape):
-759            step = self.shape.step
-760            shape = self.shape.min
-761            if step[bidx] != 0:
-762                raise ValueError(
-763                    "Input shape step has to be zero in the batch dimension (the batch"
-764                    + " dimension can always be increased, but `step` should specify how"
-765                    + " to increase the minimal shape to find the largest single batch"
-766                    + " shape)"
-767                )
-768        else:
-769            shape = self.shape
+749    @model_validator(mode="after")
+750    def zero_batch_step_and_one_batch_size(self) -> Self:
+751        bidx = self.axes.find("b")
+752        if bidx == -1:
+753            return self
+754
+755        if isinstance(self.shape, ParameterizedInputShape):
+756            step = self.shape.step
+757            shape = self.shape.min
+758            if step[bidx] != 0:
+759                raise ValueError(
+760                    "Input shape step has to be zero in the batch dimension (the batch"
+761                    + " dimension can always be increased, but `step` should specify how"
+762                    + " to increase the minimal shape to find the largest single batch"
+763                    + " shape)"
+764                )
+765        else:
+766            shape = self.shape
+767
+768        if shape[bidx] != 1:
+769            raise ValueError("Input shape has to be 1 in the batch dimension b.")
 770
-771        if shape[bidx] != 1:
-772            raise ValueError("Input shape has to be 1 in the batch dimension b.")
-773
-774        return self
-775
-776    @model_validator(mode="after")
-777    def validate_preprocessing_kwargs(self) -> Self:
-778        for p in self.preprocessing:
-779            kwargs_axes = p.kwargs.get("axes", "")
-780            if not isinstance(kwargs_axes, str):
-781                raise ValueError(
-782                    f"Expected an `axes` string, but got {type(kwargs_axes)}"
-783                )
+771        return self
+772
+773    @model_validator(mode="after")
+774    def validate_preprocessing_kwargs(self) -> Self:
+775        for p in self.preprocessing:
+776            kwargs_axes = p.kwargs.get("axes", "")
+777            if not isinstance(kwargs_axes, str):
+778                raise ValueError(
+779                    f"Expected an `axes` string, but got {type(kwargs_axes)}"
+780                )
+781
+782            if any(a not in self.axes for a in kwargs_axes):
+783                raise ValueError("`kwargs.axes` needs to be subset of `axes`")
 784
-785            if any(a not in self.axes for a in kwargs_axes):
-786                raise ValueError("`kwargs.axes` needs to be subset of `axes`")
-787
-788        return self
+785        return self
 
    
 
 
@@ -7122,29 +7119,29 @@ 
    Inherited Members
    
 
     
    
     
-            
    752    @model_validator(mode="after")
-753    def zero_batch_step_and_one_batch_size(self) -> Self:
-754        bidx = self.axes.find("b")
-755        if bidx == -1:
-756            return self
-757
-758        if isinstance(self.shape, ParameterizedInputShape):
-759            step = self.shape.step
-760            shape = self.shape.min
-761            if step[bidx] != 0:
-762                raise ValueError(
-763                    "Input shape step has to be zero in the batch dimension (the batch"
-764                    + " dimension can always be increased, but `step` should specify how"
-765                    + " to increase the minimal shape to find the largest single batch"
-766                    + " shape)"
-767                )
-768        else:
-769            shape = self.shape
+            
    749    @model_validator(mode="after")
+750    def zero_batch_step_and_one_batch_size(self) -> Self:
+751        bidx = self.axes.find("b")
+752        if bidx == -1:
+753            return self
+754
+755        if isinstance(self.shape, ParameterizedInputShape):
+756            step = self.shape.step
+757            shape = self.shape.min
+758            if step[bidx] != 0:
+759                raise ValueError(
+760                    "Input shape step has to be zero in the batch dimension (the batch"
+761                    + " dimension can always be increased, but `step` should specify how"
+762                    + " to increase the minimal shape to find the largest single batch"
+763                    + " shape)"
+764                )
+765        else:
+766            shape = self.shape
+767
+768        if shape[bidx] != 1:
+769            raise ValueError("Input shape has to be 1 in the batch dimension b.")
 770
-771        if shape[bidx] != 1:
-772            raise ValueError("Input shape has to be 1 in the batch dimension b.")
-773
-774        return self
+771        return self
 
    
 
 
@@ -7163,19 +7160,19 @@ 
    Inherited Members
    
 
     
    
     
-            
    776    @model_validator(mode="after")
-777    def validate_preprocessing_kwargs(self) -> Self:
-778        for p in self.preprocessing:
-779            kwargs_axes = p.kwargs.get("axes", "")
-780            if not isinstance(kwargs_axes, str):
-781                raise ValueError(
-782                    f"Expected an `axes` string, but got {type(kwargs_axes)}"
-783                )
+            
    773    @model_validator(mode="after")
+774    def validate_preprocessing_kwargs(self) -> Self:
+775        for p in self.preprocessing:
+776            kwargs_axes = p.kwargs.get("axes", "")
+777            if not isinstance(kwargs_axes, str):
+778                raise ValueError(
+779                    f"Expected an `axes` string, but got {type(kwargs_axes)}"
+780                )
+781
+782            if any(a not in self.axes for a in kwargs_axes):
+783                raise ValueError("`kwargs.axes` needs to be subset of `axes`")
 784
-785            if any(a not in self.axes for a in kwargs_axes):
-786                raise ValueError("`kwargs.axes` needs to be subset of `axes`")
-787
-788        return self
+785        return self
 
    
 
 
@@ -7276,55 +7273,55 @@ 
    Inherited Members
    
 
     
    
     
-            
    791class OutputTensorDescr(TensorDescrBase):
-792    data_type: Literal[
-793        "float32",
-794        "float64",
-795        "uint8",
-796        "int8",
-797        "uint16",
-798        "int16",
-799        "uint32",
-800        "int32",
-801        "uint64",
-802        "int64",
-803        "bool",
-804    ]
-805    """Data type.
-806    The data flow in bioimage.io models is explained
-807    [in this diagram.](https://docs.google.com/drawings/d/1FTw8-Rn6a6nXdkZ_SkMumtcjvur9mtIhRqLwnKqZNHM/edit)."""
+            
    788class OutputTensorDescr(TensorDescrBase):
+789    data_type: Literal[
+790        "float32",
+791        "float64",
+792        "uint8",
+793        "int8",
+794        "uint16",
+795        "int16",
+796        "uint32",
+797        "int32",
+798        "uint64",
+799        "int64",
+800        "bool",
+801    ]
+802    """Data type.
+803    The data flow in bioimage.io models is explained
+804    [in this diagram.](https://docs.google.com/drawings/d/1FTw8-Rn6a6nXdkZ_SkMumtcjvur9mtIhRqLwnKqZNHM/edit)."""
+805
+806    shape: Union[Sequence[int], ImplicitOutputShape]
+807    """Output tensor shape."""
 808
-809    shape: Union[Sequence[int], ImplicitOutputShape]
-810    """Output tensor shape."""
-811
-812    halo: Optional[Sequence[int]] = None
-813    """The `halo` that should be cropped from the output tensor to avoid boundary effects.
-814    The `halo` is to be cropped from both sides, i.e. `shape_after_crop = shape - 2 * halo`.
-815    To document a `halo` that is already cropped by the model `shape.offset` has to be used instead."""
+809    halo: Optional[Sequence[int]] = None
+810    """The `halo` that should be cropped from the output tensor to avoid boundary effects.
+811    The `halo` is to be cropped from both sides, i.e. `shape_after_crop = shape - 2 * halo`.
+812    To document a `halo` that is already cropped by the model `shape.offset` has to be used instead."""
+813
+814    postprocessing: List[PostprocessingDescr] = Field(default_factory=list)
+815    """Description of how this output should be postprocessed."""
 816
-817    postprocessing: List[PostprocessingDescr] = Field(default_factory=list)
-818    """Description of how this output should be postprocessed."""
-819
-820    @model_validator(mode="after")
-821    def matching_halo_length(self) -> Self:
-822        if self.halo and len(self.halo) != len(self.shape):
-823            raise ValueError(
-824                f"halo {self.halo} has to have same length as shape {self.shape}!"
-825            )
-826
-827        return self
-828
-829    @model_validator(mode="after")
-830    def validate_postprocessing_kwargs(self) -> Self:
-831        for p in self.postprocessing:
-832            kwargs_axes = p.kwargs.get("axes", "")
-833            if not isinstance(kwargs_axes, str):
-834                raise ValueError(f"Expected {kwargs_axes} to be a string")
+817    @model_validator(mode="after")
+818    def matching_halo_length(self) -> Self:
+819        if self.halo and len(self.halo) != len(self.shape):
+820            raise ValueError(
+821                f"halo {self.halo} has to have same length as shape {self.shape}!"
+822            )
+823
+824        return self
+825
+826    @model_validator(mode="after")
+827    def validate_postprocessing_kwargs(self) -> Self:
+828        for p in self.postprocessing:
+829            kwargs_axes = p.kwargs.get("axes", "")
+830            if not isinstance(kwargs_axes, str):
+831                raise ValueError(f"Expected {kwargs_axes} to be a string")
+832
+833            if any(a not in self.axes for a in kwargs_axes):
+834                raise ValueError("`kwargs.axes` needs to be subset of axes")
 835
-836            if any(a not in self.axes for a in kwargs_axes):
-837                raise ValueError("`kwargs.axes` needs to be subset of axes")
-838
-839        return self
+836        return self
 
    
 
 
@@ -7400,14 +7397,14 @@ 
    Inherited Members
    
 
     
    
     
-            
    820    @model_validator(mode="after")
-821    def matching_halo_length(self) -> Self:
-822        if self.halo and len(self.halo) != len(self.shape):
-823            raise ValueError(
-824                f"halo {self.halo} has to have same length as shape {self.shape}!"
-825            )
-826
-827        return self
+            
    817    @model_validator(mode="after")
+818    def matching_halo_length(self) -> Self:
+819        if self.halo and len(self.halo) != len(self.shape):
+820            raise ValueError(
+821                f"halo {self.halo} has to have same length as shape {self.shape}!"
+822            )
+823
+824        return self
 
    
 
 
@@ -7426,17 +7423,17 @@ 
    Inherited Members
    
 
     
    
     
-            
    829    @model_validator(mode="after")
-830    def validate_postprocessing_kwargs(self) -> Self:
-831        for p in self.postprocessing:
-832            kwargs_axes = p.kwargs.get("axes", "")
-833            if not isinstance(kwargs_axes, str):
-834                raise ValueError(f"Expected {kwargs_axes} to be a string")
+            
    826    @model_validator(mode="after")
+827    def validate_postprocessing_kwargs(self) -> Self:
+828        for p in self.postprocessing:
+829            kwargs_axes = p.kwargs.get("axes", "")
+830            if not isinstance(kwargs_axes, str):
+831                raise ValueError(f"Expected {kwargs_axes} to be a string")
+832
+833            if any(a not in self.axes for a in kwargs_axes):
+834                raise ValueError("`kwargs.axes` needs to be subset of axes")
 835
-836            if any(a not in self.axes for a in kwargs_axes):
-837                raise ValueError("`kwargs.axes` needs to be subset of axes")
-838
-839        return self
+836        return self
 
    
 
 
@@ -7549,14 +7546,14 @@ 
    Inherited Members
    
 
     
    
     
-            
    845class RunMode(Node):
-846    name: Annotated[
-847        Union[KnownRunMode, str], warn(KnownRunMode, "Unknown run mode '{value}'.")
-848    ]
-849    """Run mode name"""
-850
-851    kwargs: Dict[str, Any] = Field(default_factory=dict)
-852    """Run mode specific key word arguments"""
+            
    842class RunMode(Node):
+843    name: Annotated[
+844        Union[KnownRunMode, str], warn(KnownRunMode, "Unknown run mode '{value}'.")
+845    ]
+846    """Run mode name"""
+847
+848    kwargs: Dict[str, Any] = Field(default_factory=dict)
+849    """Run mode specific key word arguments"""
 
    
 
 
@@ -7566,7 +7563,7 @@ 
    Inherited Members
    
 
                             
    
                                 
    
-            name: Annotated[Union[Literal['deepimagej'], str], AfterWarner(func=<function as_warning.<locals>.wrapper at 0x7f1c131ef740>, severity=30, msg="Unknown run mode '{value}'.", context={'typ': Literal['deepimagej']})]
+            name: Annotated[Union[Literal['deepimagej'], str], AfterWarner(func=<function as_warning.<locals>.wrapper at 0x7afc91ef3060>, severity=30, msg="Unknown run mode '{value}'.", context={'typ': Literal['deepimagej']})]
 
         
     
    
@@ -7677,14 +7674,14 @@ 
    Inherited Members
    
 
     
    
     
-            
    855class LinkedModel(Node):
-856    """Reference to a bioimage.io model."""
+            
    852class LinkedModel(Node):
+853    """Reference to a bioimage.io model."""
+854
+855    id: ModelId
+856    """A valid model `id` from the bioimage.io collection."""
 857
-858    id: ModelId
-859    """A valid model `id` from the bioimage.io collection."""
-860
-861    version_number: Optional[int] = None
-862    """version number (n-th published version, not the semantic version) of linked model"""
+858    version_number: Optional[int] = None
+859    """version number (n-th published version, not the semantic version) of linked model"""
 
    
 
 
@@ -7805,272 +7802,272 @@ 
    Inherited Members
    
 
     
    
     
-            
     865class ModelDescr(GenericModelDescrBase, title="bioimage.io model specification"):
- 866    """Specification of the fields used in a bioimage.io-compliant RDF that describes AI models with pretrained weights.
+            
     862class ModelDescr(GenericModelDescrBase, title="bioimage.io model specification"):
+ 863    """Specification of the fields used in a bioimage.io-compliant RDF that describes AI models with pretrained weights.
+ 864
+ 865    These fields are typically stored in a YAML file which we call a model resource description file (model RDF).
+ 866    """
  867
- 868    These fields are typically stored in a YAML file which we call a model resource description file (model RDF).
- 869    """
- 870
- 871    format_version: Literal["0.4.10",] = "0.4.10"
- 872    """Version of the bioimage.io model description specification used.
- 873    When creating a new model always use the latest micro/patch version described here.
- 874    The `format_version` is important for any consumer software to understand how to parse the fields.
- 875    """
+ 868    format_version: Literal["0.4.10",] = "0.4.10"
+ 869    """Version of the bioimage.io model description specification used.
+ 870    When creating a new model always use the latest micro/patch version described here.
+ 871    The `format_version` is important for any consumer software to understand how to parse the fields.
+ 872    """
+ 873
+ 874    type: Literal["model"] = "model"
+ 875    """Specialized resource type 'model'"""
  876
- 877    type: Literal["model"] = "model"
- 878    """Specialized resource type 'model'"""
+ 877    id: Optional[ModelId] = None
+ 878    """Model zoo (bioimage.io) wide, unique identifier (assigned by bioimage.io)"""
  879
- 880    id: Optional[ModelId] = None
- 881    """Model zoo (bioimage.io) wide, unique identifier (assigned by bioimage.io)"""
+ 880    authors: NotEmpty[List[Author]]
+ 881    """The authors are the creators of the model RDF and the primary points of contact."""
  882
- 883    authors: NotEmpty[List[Author]]
- 884    """The authors are the creators of the model RDF and the primary points of contact."""
- 885
- 886    documentation: Annotated[
- 887        ImportantFileSource,
- 888        Field(
- 889            examples=[
- 890                "https://raw.githubusercontent.com/bioimage-io/spec-bioimage-io/main/example_descriptions/models/unet2d_nuclei_broad/README.md",
- 891                "README.md",
- 892            ],
- 893        ),
- 894    ]
- 895    """∈📦 URL or relative path to a markdown file with additional documentation.
- 896    The recommended documentation file name is `README.md`. An `.md` suffix is mandatory.
- 897    The documentation should include a '[#[#]]# Validation' (sub)section
- 898    with details on how to quantitatively validate the model on unseen data."""
+ 883    documentation: Annotated[
+ 884        ImportantFileSource,
+ 885        Field(
+ 886            examples=[
+ 887                "https://raw.githubusercontent.com/bioimage-io/spec-bioimage-io/main/example_descriptions/models/unet2d_nuclei_broad/README.md",
+ 888                "README.md",
+ 889            ],
+ 890        ),
+ 891    ]
+ 892    """∈📦 URL or relative path to a markdown file with additional documentation.
+ 893    The recommended documentation file name is `README.md`. An `.md` suffix is mandatory.
+ 894    The documentation should include a '[#[#]]# Validation' (sub)section
+ 895    with details on how to quantitatively validate the model on unseen data."""
+ 896
+ 897    inputs: NotEmpty[List[InputTensorDescr]]
+ 898    """Describes the input tensors expected by this model."""
  899
- 900    inputs: NotEmpty[List[InputTensorDescr]]
- 901    """Describes the input tensors expected by this model."""
- 902
- 903    license: Annotated[
- 904        Union[LicenseId, str],
- 905        warn(LicenseId, "Unknown license id '{value}'."),
- 906        Field(examples=["CC-BY-4.0", "MIT", "BSD-2-Clause"]),
- 907    ]
- 908    """A [SPDX license identifier](https://spdx.org/licenses/).
- 909    We do notsupport custom license beyond the SPDX license list, if you need that please
- 910    [open a GitHub issue](https://github.com/bioimage-io/spec-bioimage-io/issues/new/choose
- 911    ) to discuss your intentions with the community."""
- 912
- 913    name: Annotated[
- 914        str,
- 915        MinLen(1),
- 916        warn(MinLen(5), "Name shorter than 5 characters.", INFO),
- 917        warn(MaxLen(64), "Name longer than 64 characters.", INFO),
- 918    ]
- 919    """A human-readable name of this model.
- 920    It should be no longer than 64 characters and only contain letter, number, underscore, minus or space characters."""
+ 900    license: Annotated[
+ 901        Union[LicenseId, str],
+ 902        warn(LicenseId, "Unknown license id '{value}'."),
+ 903        Field(examples=["CC-BY-4.0", "MIT", "BSD-2-Clause"]),
+ 904    ]
+ 905    """A [SPDX license identifier](https://spdx.org/licenses/).
+ 906    We do notsupport custom license beyond the SPDX license list, if you need that please
+ 907    [open a GitHub issue](https://github.com/bioimage-io/spec-bioimage-io/issues/new/choose
+ 908    ) to discuss your intentions with the community."""
+ 909
+ 910    name: Annotated[
+ 911        str,
+ 912        MinLen(1),
+ 913        warn(MinLen(5), "Name shorter than 5 characters.", INFO),
+ 914        warn(MaxLen(64), "Name longer than 64 characters.", INFO),
+ 915    ]
+ 916    """A human-readable name of this model.
+ 917    It should be no longer than 64 characters and only contain letter, number, underscore, minus or space characters."""
+ 918
+ 919    outputs: NotEmpty[List[OutputTensorDescr]]
+ 920    """Describes the output tensors."""
  921
- 922    outputs: NotEmpty[List[OutputTensorDescr]]
- 923    """Describes the output tensors."""
- 924
- 925    @field_validator("inputs", "outputs")
- 926    @classmethod
- 927    def unique_tensor_descr_names(
- 928        cls, value: Sequence[Union[InputTensorDescr, OutputTensorDescr]]
- 929    ) -> Sequence[Union[InputTensorDescr, OutputTensorDescr]]:
- 930        unique_names = {str(v.name) for v in value}
- 931        if len(unique_names) != len(value):
- 932            raise ValueError("Duplicate tensor descriptor names")
- 933
- 934        return value
- 935
- 936    @model_validator(mode="after")
- 937    def unique_io_names(self) -> Self:
- 938        unique_names = {str(ss.name) for s in (self.inputs, self.outputs) for ss in s}
- 939        if len(unique_names) != (len(self.inputs) + len(self.outputs)):
- 940            raise ValueError("Duplicate tensor descriptor names across inputs/outputs")
- 941
- 942        return self
- 943
- 944    @model_validator(mode="after")
- 945    def minimum_shape2valid_output(self) -> Self:
- 946        tensors_by_name: Dict[
- 947            TensorName, Union[InputTensorDescr, OutputTensorDescr]
- 948        ] = {t.name: t for t in self.inputs + self.outputs}
- 949
- 950        for out in self.outputs:
- 951            if isinstance(out.shape, ImplicitOutputShape):
- 952                ndim_ref = len(tensors_by_name[out.shape.reference_tensor].shape)
- 953                ndim_out_ref = len(
- 954                    [scale for scale in out.shape.scale if scale is not None]
- 955                )
- 956                if ndim_ref != ndim_out_ref:
- 957                    expanded_dim_note = (
- 958                        " Note that expanded dimensions (`scale`: null) are not"
- 959                        + f" counted for {out.name}'sdimensionality here."
- 960                        if None in out.shape.scale
- 961                        else ""
- 962                    )
- 963                    raise ValueError(
- 964                        f"Referenced tensor '{out.shape.reference_tensor}' with"
- 965                        + f" {ndim_ref} dimensions does not match output tensor"
- 966                        + f" '{out.name}' with"
- 967                        + f" {ndim_out_ref} dimensions.{expanded_dim_note}"
- 968                    )
- 969
- 970            min_out_shape = self._get_min_shape(out, tensors_by_name)
- 971            if out.halo:
- 972                halo = out.halo
- 973                halo_msg = f" for halo {out.halo}"
- 974            else:
- 975                halo = [0] * len(min_out_shape)
- 976                halo_msg = ""
- 977
- 978            if any([s - 2 * h < 1 for s, h in zip(min_out_shape, halo)]):
- 979                raise ValueError(
- 980                    f"Minimal shape {min_out_shape} of output {out.name} is too"
- 981                    + f" small{halo_msg}."
- 982                )
- 983
- 984        return self
- 985
- 986    @classmethod
- 987    def _get_min_shape(
- 988        cls,
- 989        t: Union[InputTensorDescr, OutputTensorDescr],
- 990        tensors_by_name: Dict[TensorName, Union[InputTensorDescr, OutputTensorDescr]],
- 991    ) -> Sequence[int]:
- 992        """output with subtracted halo has to result in meaningful output even for the minimal input
- 993        see https://github.com/bioimage-io/spec-bioimage-io/issues/392
- 994        """
- 995        if isinstance(t.shape, collections.abc.Sequence):
- 996            return t.shape
- 997        elif isinstance(t.shape, ParameterizedInputShape):
- 998            return t.shape.min
- 999        elif isinstance(t.shape, ImplicitOutputShape):
-1000            pass
-1001        else:
-1002            assert_never(t.shape)
-1003
-1004        ref_shape = cls._get_min_shape(
-1005            tensors_by_name[t.shape.reference_tensor], tensors_by_name
-1006        )
-1007
-1008        if None not in t.shape.scale:
-1009            scale: Sequence[float, ...] = t.shape.scale  # type: ignore
-1010        else:
-1011            expanded_dims = [idx for idx, sc in enumerate(t.shape.scale) if sc is None]
-1012            new_ref_shape: List[int] = []
-1013            for idx in range(len(t.shape.scale)):
-1014                ref_idx = idx - sum(int(exp < idx) for exp in expanded_dims)
-1015                new_ref_shape.append(1 if idx in expanded_dims else ref_shape[ref_idx])
-1016
-1017            ref_shape = new_ref_shape
-1018            assert len(ref_shape) == len(t.shape.scale)
-1019            scale = [0.0 if sc is None else sc for sc in t.shape.scale]
-1020
-1021        offset = t.shape.offset
-1022        assert len(offset) == len(scale)
-1023        return [int(rs * s + 2 * off) for rs, s, off in zip(ref_shape, scale, offset)]
-1024
-1025    @model_validator(mode="after")
-1026    def validate_tensor_references_in_inputs(self) -> Self:
-1027        for t in self.inputs:
-1028            for proc in t.preprocessing:
-1029                if "reference_tensor" not in proc.kwargs:
-1030                    continue
-1031
-1032                ref_tensor = proc.kwargs["reference_tensor"]
-1033                if ref_tensor is not None and str(ref_tensor) not in {
-1034                    str(t.name) for t in self.inputs
-1035                }:
-1036                    raise ValueError(f"'{ref_tensor}' not found in inputs")
-1037
-1038                if ref_tensor == t.name:
-1039                    raise ValueError(
-1040                        f"invalid self reference for preprocessing of tensor {t.name}"
-1041                    )
-1042
-1043        return self
-1044
-1045    @model_validator(mode="after")
-1046    def validate_tensor_references_in_outputs(self) -> Self:
-1047        for t in self.outputs:
-1048            for proc in t.postprocessing:
-1049                if "reference_tensor" not in proc.kwargs:
-1050                    continue
-1051                ref_tensor = proc.kwargs["reference_tensor"]
-1052                if ref_tensor is not None and str(ref_tensor) not in {
-1053                    str(t.name) for t in self.inputs
-1054                }:
-1055                    raise ValueError(f"{ref_tensor} not found in inputs")
-1056
-1057        return self
-1058
-1059    packaged_by: List[Author] = Field(default_factory=list)
-1060    """The persons that have packaged and uploaded this model.
-1061    Only required if those persons differ from the `authors`."""
+ 922    @field_validator("inputs", "outputs")
+ 923    @classmethod
+ 924    def unique_tensor_descr_names(
+ 925        cls, value: Sequence[Union[InputTensorDescr, OutputTensorDescr]]
+ 926    ) -> Sequence[Union[InputTensorDescr, OutputTensorDescr]]:
+ 927        unique_names = {str(v.name) for v in value}
+ 928        if len(unique_names) != len(value):
+ 929            raise ValueError("Duplicate tensor descriptor names")
+ 930
+ 931        return value
+ 932
+ 933    @model_validator(mode="after")
+ 934    def unique_io_names(self) -> Self:
+ 935        unique_names = {str(ss.name) for s in (self.inputs, self.outputs) for ss in s}
+ 936        if len(unique_names) != (len(self.inputs) + len(self.outputs)):
+ 937            raise ValueError("Duplicate tensor descriptor names across inputs/outputs")
+ 938
+ 939        return self
+ 940
+ 941    @model_validator(mode="after")
+ 942    def minimum_shape2valid_output(self) -> Self:
+ 943        tensors_by_name: Dict[
+ 944            TensorName, Union[InputTensorDescr, OutputTensorDescr]
+ 945        ] = {t.name: t for t in self.inputs + self.outputs}
+ 946
+ 947        for out in self.outputs:
+ 948            if isinstance(out.shape, ImplicitOutputShape):
+ 949                ndim_ref = len(tensors_by_name[out.shape.reference_tensor].shape)
+ 950                ndim_out_ref = len(
+ 951                    [scale for scale in out.shape.scale if scale is not None]
+ 952                )
+ 953                if ndim_ref != ndim_out_ref:
+ 954                    expanded_dim_note = (
+ 955                        " Note that expanded dimensions (`scale`: null) are not"
+ 956                        + f" counted for {out.name}'sdimensionality here."
+ 957                        if None in out.shape.scale
+ 958                        else ""
+ 959                    )
+ 960                    raise ValueError(
+ 961                        f"Referenced tensor '{out.shape.reference_tensor}' with"
+ 962                        + f" {ndim_ref} dimensions does not match output tensor"
+ 963                        + f" '{out.name}' with"
+ 964                        + f" {ndim_out_ref} dimensions.{expanded_dim_note}"
+ 965                    )
+ 966
+ 967            min_out_shape = self._get_min_shape(out, tensors_by_name)
+ 968            if out.halo:
+ 969                halo = out.halo
+ 970                halo_msg = f" for halo {out.halo}"
+ 971            else:
+ 972                halo = [0] * len(min_out_shape)
+ 973                halo_msg = ""
+ 974
+ 975            if any([s - 2 * h < 1 for s, h in zip(min_out_shape, halo)]):
+ 976                raise ValueError(
+ 977                    f"Minimal shape {min_out_shape} of output {out.name} is too"
+ 978                    + f" small{halo_msg}."
+ 979                )
+ 980
+ 981        return self
+ 982
+ 983    @classmethod
+ 984    def _get_min_shape(
+ 985        cls,
+ 986        t: Union[InputTensorDescr, OutputTensorDescr],
+ 987        tensors_by_name: Dict[TensorName, Union[InputTensorDescr, OutputTensorDescr]],
+ 988    ) -> Sequence[int]:
+ 989        """output with subtracted halo has to result in meaningful output even for the minimal input
+ 990        see https://github.com/bioimage-io/spec-bioimage-io/issues/392
+ 991        """
+ 992        if isinstance(t.shape, collections.abc.Sequence):
+ 993            return t.shape
+ 994        elif isinstance(t.shape, ParameterizedInputShape):
+ 995            return t.shape.min
+ 996        elif isinstance(t.shape, ImplicitOutputShape):
+ 997            pass
+ 998        else:
+ 999            assert_never(t.shape)
+1000
+1001        ref_shape = cls._get_min_shape(
+1002            tensors_by_name[t.shape.reference_tensor], tensors_by_name
+1003        )
+1004
+1005        if None not in t.shape.scale:
+1006            scale: Sequence[float, ...] = t.shape.scale  # type: ignore
+1007        else:
+1008            expanded_dims = [idx for idx, sc in enumerate(t.shape.scale) if sc is None]
+1009            new_ref_shape: List[int] = []
+1010            for idx in range(len(t.shape.scale)):
+1011                ref_idx = idx - sum(int(exp < idx) for exp in expanded_dims)
+1012                new_ref_shape.append(1 if idx in expanded_dims else ref_shape[ref_idx])
+1013
+1014            ref_shape = new_ref_shape
+1015            assert len(ref_shape) == len(t.shape.scale)
+1016            scale = [0.0 if sc is None else sc for sc in t.shape.scale]
+1017
+1018        offset = t.shape.offset
+1019        assert len(offset) == len(scale)
+1020        return [int(rs * s + 2 * off) for rs, s, off in zip(ref_shape, scale, offset)]
+1021
+1022    @model_validator(mode="after")
+1023    def validate_tensor_references_in_inputs(self) -> Self:
+1024        for t in self.inputs:
+1025            for proc in t.preprocessing:
+1026                if "reference_tensor" not in proc.kwargs:
+1027                    continue
+1028
+1029                ref_tensor = proc.kwargs["reference_tensor"]
+1030                if ref_tensor is not None and str(ref_tensor) not in {
+1031                    str(t.name) for t in self.inputs
+1032                }:
+1033                    raise ValueError(f"'{ref_tensor}' not found in inputs")
+1034
+1035                if ref_tensor == t.name:
+1036                    raise ValueError(
+1037                        f"invalid self reference for preprocessing of tensor {t.name}"
+1038                    )
+1039
+1040        return self
+1041
+1042    @model_validator(mode="after")
+1043    def validate_tensor_references_in_outputs(self) -> Self:
+1044        for t in self.outputs:
+1045            for proc in t.postprocessing:
+1046                if "reference_tensor" not in proc.kwargs:
+1047                    continue
+1048                ref_tensor = proc.kwargs["reference_tensor"]
+1049                if ref_tensor is not None and str(ref_tensor) not in {
+1050                    str(t.name) for t in self.inputs
+1051                }:
+1052                    raise ValueError(f"{ref_tensor} not found in inputs")
+1053
+1054        return self
+1055
+1056    packaged_by: List[Author] = Field(default_factory=list)
+1057    """The persons that have packaged and uploaded this model.
+1058    Only required if those persons differ from the `authors`."""
+1059
+1060    parent: Optional[LinkedModel] = None
+1061    """The model from which this model is derived, e.g. by fine-tuning the weights."""
 1062
-1063    parent: Optional[LinkedModel] = None
-1064    """The model from which this model is derived, e.g. by fine-tuning the weights."""
-1065
-1066    @field_validator("parent", mode="before")
-1067    @classmethod
-1068    def ignore_url_parent(cls, parent: Any):
-1069        if isinstance(parent, dict):
-1070            return None
+1063    @field_validator("parent", mode="before")
+1064    @classmethod
+1065    def ignore_url_parent(cls, parent: Any):
+1066        if isinstance(parent, dict):
+1067            return None
+1068
+1069        else:
+1070            return parent
 1071
-1072        else:
-1073            return parent
-1074
-1075    run_mode: Optional[RunMode] = None
-1076    """Custom run mode for this model: for more complex prediction procedures like test time
-1077    data augmentation that currently cannot be expressed in the specification.
-1078    No standard run modes are defined yet."""
-1079
-1080    sample_inputs: List[ImportantFileSource] = Field(default_factory=list)
-1081    """∈📦 URLs/relative paths to sample inputs to illustrate possible inputs for the model,
-1082    for example stored as PNG or TIFF images.
-1083    The sample files primarily serve to inform a human user about an example use case"""
+1072    run_mode: Optional[RunMode] = None
+1073    """Custom run mode for this model: for more complex prediction procedures like test time
+1074    data augmentation that currently cannot be expressed in the specification.
+1075    No standard run modes are defined yet."""
+1076
+1077    sample_inputs: List[ImportantFileSource] = Field(default_factory=list)
+1078    """∈📦 URLs/relative paths to sample inputs to illustrate possible inputs for the model,
+1079    for example stored as PNG or TIFF images.
+1080    The sample files primarily serve to inform a human user about an example use case"""
+1081
+1082    sample_outputs: List[ImportantFileSource] = Field(default_factory=list)
+1083    """∈📦 URLs/relative paths to sample outputs corresponding to the `sample_inputs`."""
 1084
-1085    sample_outputs: List[ImportantFileSource] = Field(default_factory=list)
-1086    """∈📦 URLs/relative paths to sample outputs corresponding to the `sample_inputs`."""
-1087
-1088    test_inputs: NotEmpty[
-1089        List[Annotated[ImportantFileSource, WithSuffix(".npy", case_sensitive=True)]]
-1090    ]
-1091    """∈📦 Test input tensors compatible with the `inputs` description for a **single test case**.
-1092    This means if your model has more than one input, you should provide one URL/relative path for each input.
-1093    Each test input should be a file with an ndarray in
-1094    [numpy.lib file format](https://numpy.org/doc/stable/reference/generated/numpy.lib.format.html#module-numpy.lib.format).
-1095    The extension must be '.npy'."""
-1096
-1097    test_outputs: NotEmpty[
-1098        List[Annotated[ImportantFileSource, WithSuffix(".npy", case_sensitive=True)]]
-1099    ]
-1100    """∈📦 Analog to `test_inputs`."""
-1101
-1102    timestamp: Datetime
-1103    """Timestamp in [ISO 8601](#https://en.wikipedia.org/wiki/ISO_8601) format
-1104    with a few restrictions listed [here](https://docs.python.org/3/library/datetime.html#datetime.datetime.fromisoformat)."""
+1085    test_inputs: NotEmpty[
+1086        List[Annotated[ImportantFileSource, WithSuffix(".npy", case_sensitive=True)]]
+1087    ]
+1088    """∈📦 Test input tensors compatible with the `inputs` description for a **single test case**.
+1089    This means if your model has more than one input, you should provide one URL/relative path for each input.
+1090    Each test input should be a file with an ndarray in
+1091    [numpy.lib file format](https://numpy.org/doc/stable/reference/generated/numpy.lib.format.html#module-numpy.lib.format).
+1092    The extension must be '.npy'."""
+1093
+1094    test_outputs: NotEmpty[
+1095        List[Annotated[ImportantFileSource, WithSuffix(".npy", case_sensitive=True)]]
+1096    ]
+1097    """∈📦 Analog to `test_inputs`."""
+1098
+1099    timestamp: Datetime
+1100    """Timestamp in [ISO 8601](#https://en.wikipedia.org/wiki/ISO_8601) format
+1101    with a few restrictions listed [here](https://docs.python.org/3/library/datetime.html#datetime.datetime.fromisoformat)."""
+1102
+1103    training_data: Union[LinkedDataset, DatasetDescr, None] = None
+1104    """The dataset used to train this model"""
 1105
-1106    training_data: Union[LinkedDataset, DatasetDescr, None] = None
-1107    """The dataset used to train this model"""
-1108
-1109    weights: WeightsDescr
-1110    """The weights for this model.
-1111    Weights can be given for different formats, but should otherwise be equivalent.
-1112    The available weight formats determine which consumers can use this model."""
-1113
-1114    @model_validator(mode="before")
-1115    @classmethod
-1116    def _convert_from_older_format(
-1117        cls, data: BioimageioYamlContent, /
-1118    ) -> BioimageioYamlContent:
-1119        convert_from_older_format(data)
-1120        return data
-1121
-1122    def get_input_test_arrays(self) -> List[NDArray[Any]]:
-1123        data = [load_array(download(ipt).path) for ipt in self.test_inputs]
-1124        assert all(isinstance(d, np.ndarray) for d in data)
-1125        return data
-1126
-1127    def get_output_test_arrays(self) -> List[NDArray[Any]]:
-1128        data = [load_array(download(out).path) for out in self.test_outputs]
-1129        assert all(isinstance(d, np.ndarray) for d in data)
-1130        return data
+1106    weights: WeightsDescr
+1107    """The weights for this model.
+1108    Weights can be given for different formats, but should otherwise be equivalent.
+1109    The available weight formats determine which consumers can use this model."""
+1110
+1111    @model_validator(mode="before")
+1112    @classmethod
+1113    def _convert_from_older_format(
+1114        cls, data: BioimageioYamlContent, /
+1115    ) -> BioimageioYamlContent:
+1116        convert_from_older_format(data)
+1117        return data
+1118
+1119    def get_input_test_arrays(self) -> List[NDArray[Any]]:
+1120        data = [load_array(download(ipt).path) for ipt in self.test_inputs]
+1121        assert all(isinstance(d, np.ndarray) for d in data)
+1122        return data
+1123
+1124    def get_output_test_arrays(self) -> List[NDArray[Any]]:
+1125        data = [load_array(download(out).path) for out in self.test_outputs]
+1126        assert all(isinstance(d, np.ndarray) for d in data)
+1127        return data
 
    
 
 
@@ -8136,7 +8133,7 @@ 
    Inherited Members
    
                             
    
                             
    
                                 
    
-            documentation: Annotated[Union[Annotated[pathlib.Path, PathType(path_type='file')], bioimageio.spec._internal.io.RelativeFilePath, bioimageio.spec._internal.url.HttpUrl, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator(func=<function wo_special_file_name at 0x7f1c21c3ef20>), PlainSerializer(func=<function _package at 0x7f1c21c782c0>, return_type=PydanticUndefined, when_used='unless-none'), FieldInfo(annotation=NoneType, required=True, examples=['https://raw.githubusercontent.com/bioimage-io/spec-bioimage-io/main/example_descriptions/models/unet2d_nuclei_broad/README.md', 'README.md'])]
+            documentation: Annotated[Union[Annotated[pathlib.Path, PathType(path_type='file')], bioimageio.spec._internal.io.RelativeFilePath, bioimageio.spec._internal.url.HttpUrl, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator(func=<function wo_special_file_name at 0x7afca0d90540>), PlainSerializer(func=<function _package at 0x7afca0d91760>, return_type=PydanticUndefined, when_used='unless-none'), FieldInfo(annotation=NoneType, required=True, examples=['https://raw.githubusercontent.com/bioimage-io/spec-bioimage-io/main/example_descriptions/models/unet2d_nuclei_broad/README.md', 'README.md'])]
 
         
     
    
@@ -8165,7 +8162,7 @@ 
    Inherited Members
    
                             
    
                             
    
                                 
    
-            license: Annotated[Union[bioimageio.spec._internal.license_id.LicenseId, str], AfterWarner(func=<function as_warning.<locals>.wrapper at 0x7f1c131ef880>, severity=30, msg="Unknown license id '{value}'.", context={'typ': <class 'bioimageio.spec._internal.license_id.LicenseId'>}), FieldInfo(annotation=NoneType, required=True, examples=['CC-BY-4.0', 'MIT', 'BSD-2-Clause'])]
+            license: Annotated[Union[bioimageio.spec._internal.license_id.LicenseId, str], AfterWarner(func=<function as_warning.<locals>.wrapper at 0x7afc91ef31a0>, severity=30, msg="Unknown license id '{value}'.", context={'typ': <class 'bioimageio.spec._internal.license_id.LicenseId'>}), FieldInfo(annotation=NoneType, required=True, examples=['CC-BY-4.0', 'MIT', 'BSD-2-Clause'])]
 
         
     
    
@@ -8181,7 +8178,7 @@ 
    Inherited Members
    
                             
    
                             
    
                                 
    
-            name: Annotated[str, MinLen(min_length=1), AfterWarner(func=<function as_warning.<locals>.wrapper at 0x7f1c130fd3a0>, severity=20, msg='Name shorter than 5 characters.', context={'typ': Annotated[Any, MinLen(min_length=5)]}), AfterWarner(func=<function as_warning.<locals>.wrapper at 0x7f1c130ff740>, severity=20, msg='Name longer than 64 characters.', context={'typ': Annotated[Any, MaxLen(max_length=64)]})]
+            name: Annotated[str, MinLen(min_length=1), AfterWarner(func=<function as_warning.<locals>.wrapper at 0x7afc91ef2340>, severity=20, msg='Name shorter than 5 characters.', context={'typ': Annotated[Any, MinLen(min_length=5)]}), AfterWarner(func=<function as_warning.<locals>.wrapper at 0x7afc91ef2160>, severity=20, msg='Name longer than 64 characters.', context={'typ': Annotated[Any, MaxLen(max_length=64)]})]
 
         
     
    
@@ -8219,16 +8216,16 @@ 
    Inherited Members
    
 
     
    
     
-            
    925    @field_validator("inputs", "outputs")
-926    @classmethod
-927    def unique_tensor_descr_names(
-928        cls, value: Sequence[Union[InputTensorDescr, OutputTensorDescr]]
-929    ) -> Sequence[Union[InputTensorDescr, OutputTensorDescr]]:
-930        unique_names = {str(v.name) for v in value}
-931        if len(unique_names) != len(value):
-932            raise ValueError("Duplicate tensor descriptor names")
-933
-934        return value
+            
    922    @field_validator("inputs", "outputs")
+923    @classmethod
+924    def unique_tensor_descr_names(
+925        cls, value: Sequence[Union[InputTensorDescr, OutputTensorDescr]]
+926    ) -> Sequence[Union[InputTensorDescr, OutputTensorDescr]]:
+927        unique_names = {str(v.name) for v in value}
+928        if len(unique_names) != len(value):
+929            raise ValueError("Duplicate tensor descriptor names")
+930
+931        return value
 
    
 
 
@@ -8247,13 +8244,13 @@ 
    Inherited Members
    
 
     
    
     
-            
    936    @model_validator(mode="after")
-937    def unique_io_names(self) -> Self:
-938        unique_names = {str(ss.name) for s in (self.inputs, self.outputs) for ss in s}
-939        if len(unique_names) != (len(self.inputs) + len(self.outputs)):
-940            raise ValueError("Duplicate tensor descriptor names across inputs/outputs")
-941
-942        return self
+            
    933    @model_validator(mode="after")
+934    def unique_io_names(self) -> Self:
+935        unique_names = {str(ss.name) for s in (self.inputs, self.outputs) for ss in s}
+936        if len(unique_names) != (len(self.inputs) + len(self.outputs)):
+937            raise ValueError("Duplicate tensor descriptor names across inputs/outputs")
+938
+939        return self
 
    
 
 
@@ -8272,47 +8269,47 @@ 
    Inherited Members
    
 
     
    
     
-            
    944    @model_validator(mode="after")
-945    def minimum_shape2valid_output(self) -> Self:
-946        tensors_by_name: Dict[
-947            TensorName, Union[InputTensorDescr, OutputTensorDescr]
-948        ] = {t.name: t for t in self.inputs + self.outputs}
-949
-950        for out in self.outputs:
-951            if isinstance(out.shape, ImplicitOutputShape):
-952                ndim_ref = len(tensors_by_name[out.shape.reference_tensor].shape)
-953                ndim_out_ref = len(
-954                    [scale for scale in out.shape.scale if scale is not None]
-955                )
-956                if ndim_ref != ndim_out_ref:
-957                    expanded_dim_note = (
-958                        " Note that expanded dimensions (`scale`: null) are not"
-959                        + f" counted for {out.name}'sdimensionality here."
-960                        if None in out.shape.scale
-961                        else ""
-962                    )
-963                    raise ValueError(
-964                        f"Referenced tensor '{out.shape.reference_tensor}' with"
-965                        + f" {ndim_ref} dimensions does not match output tensor"
-966                        + f" '{out.name}' with"
-967                        + f" {ndim_out_ref} dimensions.{expanded_dim_note}"
-968                    )
-969
-970            min_out_shape = self._get_min_shape(out, tensors_by_name)
-971            if out.halo:
-972                halo = out.halo
-973                halo_msg = f" for halo {out.halo}"
-974            else:
-975                halo = [0] * len(min_out_shape)
-976                halo_msg = ""
-977
-978            if any([s - 2 * h < 1 for s, h in zip(min_out_shape, halo)]):
-979                raise ValueError(
-980                    f"Minimal shape {min_out_shape} of output {out.name} is too"
-981                    + f" small{halo_msg}."
-982                )
-983
-984        return self
+            
    941    @model_validator(mode="after")
+942    def minimum_shape2valid_output(self) -> Self:
+943        tensors_by_name: Dict[
+944            TensorName, Union[InputTensorDescr, OutputTensorDescr]
+945        ] = {t.name: t for t in self.inputs + self.outputs}
+946
+947        for out in self.outputs:
+948            if isinstance(out.shape, ImplicitOutputShape):
+949                ndim_ref = len(tensors_by_name[out.shape.reference_tensor].shape)
+950                ndim_out_ref = len(
+951                    [scale for scale in out.shape.scale if scale is not None]
+952                )
+953                if ndim_ref != ndim_out_ref:
+954                    expanded_dim_note = (
+955                        " Note that expanded dimensions (`scale`: null) are not"
+956                        + f" counted for {out.name}'sdimensionality here."
+957                        if None in out.shape.scale
+958                        else ""
+959                    )
+960                    raise ValueError(
+961                        f"Referenced tensor '{out.shape.reference_tensor}' with"
+962                        + f" {ndim_ref} dimensions does not match output tensor"
+963                        + f" '{out.name}' with"
+964                        + f" {ndim_out_ref} dimensions.{expanded_dim_note}"
+965                    )
+966
+967            min_out_shape = self._get_min_shape(out, tensors_by_name)
+968            if out.halo:
+969                halo = out.halo
+970                halo_msg = f" for halo {out.halo}"
+971            else:
+972                halo = [0] * len(min_out_shape)
+973                halo_msg = ""
+974
+975            if any([s - 2 * h < 1 for s, h in zip(min_out_shape, halo)]):
+976                raise ValueError(
+977                    f"Minimal shape {min_out_shape} of output {out.name} is too"
+978                    + f" small{halo_msg}."
+979                )
+980
+981        return self
 
    
 
 
@@ -8331,25 +8328,25 @@ 
    Inherited Members
    
 
     
    
     
-            
    1025    @model_validator(mode="after")
-1026    def validate_tensor_references_in_inputs(self) -> Self:
-1027        for t in self.inputs:
-1028            for proc in t.preprocessing:
-1029                if "reference_tensor" not in proc.kwargs:
-1030                    continue
-1031
-1032                ref_tensor = proc.kwargs["reference_tensor"]
-1033                if ref_tensor is not None and str(ref_tensor) not in {
-1034                    str(t.name) for t in self.inputs
-1035                }:
-1036                    raise ValueError(f"'{ref_tensor}' not found in inputs")
-1037
-1038                if ref_tensor == t.name:
-1039                    raise ValueError(
-1040                        f"invalid self reference for preprocessing of tensor {t.name}"
-1041                    )
-1042
-1043        return self
+            
    1022    @model_validator(mode="after")
+1023    def validate_tensor_references_in_inputs(self) -> Self:
+1024        for t in self.inputs:
+1025            for proc in t.preprocessing:
+1026                if "reference_tensor" not in proc.kwargs:
+1027                    continue
+1028
+1029                ref_tensor = proc.kwargs["reference_tensor"]
+1030                if ref_tensor is not None and str(ref_tensor) not in {
+1031                    str(t.name) for t in self.inputs
+1032                }:
+1033                    raise ValueError(f"'{ref_tensor}' not found in inputs")
+1034
+1035                if ref_tensor == t.name:
+1036                    raise ValueError(
+1037                        f"invalid self reference for preprocessing of tensor {t.name}"
+1038                    )
+1039
+1040        return self
 
    
 
 
@@ -8368,19 +8365,19 @@ 
    Inherited Members
    
 
     
    
     
-            
    1045    @model_validator(mode="after")
-1046    def validate_tensor_references_in_outputs(self) -> Self:
-1047        for t in self.outputs:
-1048            for proc in t.postprocessing:
-1049                if "reference_tensor" not in proc.kwargs:
-1050                    continue
-1051                ref_tensor = proc.kwargs["reference_tensor"]
-1052                if ref_tensor is not None and str(ref_tensor) not in {
-1053                    str(t.name) for t in self.inputs
-1054                }:
-1055                    raise ValueError(f"{ref_tensor} not found in inputs")
-1056
-1057        return self
+            
    1042    @model_validator(mode="after")
+1043    def validate_tensor_references_in_outputs(self) -> Self:
+1044        for t in self.outputs:
+1045            for proc in t.postprocessing:
+1046                if "reference_tensor" not in proc.kwargs:
+1047                    continue
+1048                ref_tensor = proc.kwargs["reference_tensor"]
+1049                if ref_tensor is not None and str(ref_tensor) not in {
+1050                    str(t.name) for t in self.inputs
+1051                }:
+1052                    raise ValueError(f"{ref_tensor} not found in inputs")
+1053
+1054        return self
 
    
 
 
@@ -8427,14 +8424,14 @@ 
    Inherited Members
    
 
     
    
     
-            
    1066    @field_validator("parent", mode="before")
-1067    @classmethod
-1068    def ignore_url_parent(cls, parent: Any):
-1069        if isinstance(parent, dict):
-1070            return None
-1071
-1072        else:
-1073            return parent
+            
    1063    @field_validator("parent", mode="before")
+1064    @classmethod
+1065    def ignore_url_parent(cls, parent: Any):
+1066        if isinstance(parent, dict):
+1067            return None
+1068
+1069        else:
+1070            return parent
 
    
 
 
@@ -8458,7 +8455,7 @@ 
    Inherited Members
    
                             
    
                             
    
                                 
    
-            sample_inputs: List[Annotated[Union[Annotated[pathlib.Path, PathType(path_type='file')], bioimageio.spec._internal.io.RelativeFilePath, bioimageio.spec._internal.url.HttpUrl, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator(func=<function wo_special_file_name at 0x7f1c21c3ef20>), PlainSerializer(func=<function _package at 0x7f1c21c782c0>, return_type=PydanticUndefined, when_used='unless-none')]]
+            sample_inputs: List[Annotated[Union[Annotated[pathlib.Path, PathType(path_type='file')], bioimageio.spec._internal.io.RelativeFilePath, bioimageio.spec._internal.url.HttpUrl, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator(func=<function wo_special_file_name at 0x7afca0d90540>), PlainSerializer(func=<function _package at 0x7afca0d91760>, return_type=PydanticUndefined, when_used='unless-none')]]
 
         
     
    
@@ -8473,7 +8470,7 @@ 
    Inherited Members
    
                             
    
                             
    
                                 
    
-            sample_outputs: List[Annotated[Union[Annotated[pathlib.Path, PathType(path_type='file')], bioimageio.spec._internal.io.RelativeFilePath, bioimageio.spec._internal.url.HttpUrl, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator(func=<function wo_special_file_name at 0x7f1c21c3ef20>), PlainSerializer(func=<function _package at 0x7f1c21c782c0>, return_type=PydanticUndefined, when_used='unless-none')]]
+            sample_outputs: List[Annotated[Union[Annotated[pathlib.Path, PathType(path_type='file')], bioimageio.spec._internal.io.RelativeFilePath, bioimageio.spec._internal.url.HttpUrl, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator(func=<function wo_special_file_name at 0x7afca0d90540>), PlainSerializer(func=<function _package at 0x7afca0d91760>, return_type=PydanticUndefined, when_used='unless-none')]]
 
         
     
    
@@ -8486,7 +8483,7 @@ 
    Inherited Members
    
                             
    
                             
    
                                 
    
-            test_inputs: Annotated[List[Annotated[Union[Annotated[pathlib.Path, PathType(path_type='file')], bioimageio.spec._internal.io.RelativeFilePath, bioimageio.spec._internal.url.HttpUrl, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator(func=<function wo_special_file_name at 0x7f1c21c3ef20>), PlainSerializer(func=<function _package at 0x7f1c21c782c0>, return_type=PydanticUndefined, when_used='unless-none'), WithSuffix(suffix='.npy', case_sensitive=True)]], MinLen(min_length=1)]
+            test_inputs: Annotated[List[Annotated[Union[Annotated[pathlib.Path, PathType(path_type='file')], bioimageio.spec._internal.io.RelativeFilePath, bioimageio.spec._internal.url.HttpUrl, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator(func=<function wo_special_file_name at 0x7afca0d90540>), PlainSerializer(func=<function _package at 0x7afca0d91760>, return_type=PydanticUndefined, when_used='unless-none'), WithSuffix(suffix='.npy', case_sensitive=True)]], MinLen(min_length=1)]
 
         
     
    
@@ -8503,7 +8500,7 @@ 
    Inherited Members
    
                             
    
                             
    
                                 
    
-            test_outputs: Annotated[List[Annotated[Union[Annotated[pathlib.Path, PathType(path_type='file')], bioimageio.spec._internal.io.RelativeFilePath, bioimageio.spec._internal.url.HttpUrl, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator(func=<function wo_special_file_name at 0x7f1c21c3ef20>), PlainSerializer(func=<function _package at 0x7f1c21c782c0>, return_type=PydanticUndefined, when_used='unless-none'), WithSuffix(suffix='.npy', case_sensitive=True)]], MinLen(min_length=1)]
+            test_outputs: Annotated[List[Annotated[Union[Annotated[pathlib.Path, PathType(path_type='file')], bioimageio.spec._internal.io.RelativeFilePath, bioimageio.spec._internal.url.HttpUrl, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator(func=<function wo_special_file_name at 0x7afca0d90540>), PlainSerializer(func=<function _package at 0x7afca0d91760>, return_type=PydanticUndefined, when_used='unless-none'), WithSuffix(suffix='.npy', case_sensitive=True)]], MinLen(min_length=1)]
 
         
     
    
@@ -8567,10 +8564,10 @@ 
    Inherited Members
    
 
     
    
     
-            
    1122    def get_input_test_arrays(self) -> List[NDArray[Any]]:
-1123        data = [load_array(download(ipt).path) for ipt in self.test_inputs]
-1124        assert all(isinstance(d, np.ndarray) for d in data)
-1125        return data
+            
    1119    def get_input_test_arrays(self) -> List[NDArray[Any]]:
+1120        data = [load_array(download(ipt).path) for ipt in self.test_inputs]
+1121        assert all(isinstance(d, np.ndarray) for d in data)
+1122        return data
 
    
 
 
@@ -8588,10 +8585,10 @@ 
    Inherited Members
    
 
     
    
     
-            
    1127    def get_output_test_arrays(self) -> List[NDArray[Any]]:
-1128        data = [load_array(download(out).path) for out in self.test_outputs]
-1129        assert all(isinstance(d, np.ndarray) for d in data)
-1130        return data
+            
    1124    def get_output_test_arrays(self) -> List[NDArray[Any]]:
+1125        data = [load_array(download(out).path) for out in self.test_outputs]
+1126        assert all(isinstance(d, np.ndarray) for d in data)
+1127        return data
 
    
 
 
diff --git a/bioimageio/spec/model/v0_5.html b/bioimageio/spec/model/v0_5.html
index 7c1921c9d..3dbdeb057 100644
--- a/bioimageio/spec/model/v0_5.html
+++ b/bioimageio/spec/model/v0_5.html
@@ -43,7 +43,13 @@ 
    API Documentation
    
                     TensorId
             
             
  • 
-                    AxisId
+                    AxisId
+                            
+
             
    • 
             
  • 
                     NonBatchAxisId
@@ -1332,2404 +1338,2428 @@ 
    
   34from annotated_types import Ge, Gt, Interval, MaxLen, MinLen, Predicate
   35from imageio.v3 import imread  # pyright: ignore[reportUnknownVariableType]
   36from numpy.typing import NDArray
-  37from pydantic import Field, ValidationInfo, field_validator, model_validator
-  38from typing_extensions import Annotated, LiteralString, Self, assert_never
-  39
-  40from bioimageio.spec._internal.validated_string import ValidatedString
-  41
-  42from .._internal.common_nodes import (
-  43    Converter,
-  44    InvalidDescr,
-  45    Node,
-  46    NodeWithExplicitlySetFields,
+  37from pydantic import (
+  38    Field,
+  39    GetCoreSchemaHandler,
+  40    ValidationInfo,
+  41    field_validator,
+  42    model_validator,
+  43)
+  44from pydantic_core.core_schema import (
+  45    CoreSchema,
+  46    no_info_after_validator_function,
   47)
-  48from .._internal.constants import DTYPE_LIMITS
-  49from .._internal.field_warning import issue_warning, warn
-  50from .._internal.io import BioimageioYamlContent as BioimageioYamlContent
-  51from .._internal.io import FileDescr as FileDescr
-  52from .._internal.io import Sha256 as Sha256
-  53from .._internal.io import WithSuffix, download
-  54from .._internal.io_basics import AbsoluteFilePath as AbsoluteFilePath
-  55from .._internal.io_utils import load_array
-  56from .._internal.types import Datetime as Datetime
-  57from .._internal.types import DeprecatedLicenseId as DeprecatedLicenseId
-  58from .._internal.types import Identifier as Identifier
-  59from .._internal.types import ImportantFileSource, LowerCaseIdentifierAnno, SiUnit
-  60from .._internal.types import LicenseId as LicenseId
-  61from .._internal.types import ModelId as ModelId
-  62from .._internal.types import NotEmpty as NotEmpty
-  63from .._internal.types import ResourceId as ResourceId
-  64from .._internal.url import HttpUrl as HttpUrl
-  65from .._internal.validation_context import validation_context_var
-  66from .._internal.version_type import Version as Version
-  67from .._internal.warning_levels import INFO
-  68from ..dataset.v0_3 import DatasetDescr as DatasetDescr
-  69from ..dataset.v0_3 import LinkedDataset as LinkedDataset
-  70from ..dataset.v0_3 import Uploader as Uploader
-  71from ..generic.v0_3 import Author as Author
-  72from ..generic.v0_3 import BadgeDescr as BadgeDescr
-  73from ..generic.v0_3 import CiteEntry as CiteEntry
-  74from ..generic.v0_3 import (
-  75    DocumentationSource,
-  76    GenericModelDescrBase,
-  77    _author_conv,  # pyright: ignore[reportPrivateUsage]
-  78    _maintainer_conv,  # pyright: ignore[reportPrivateUsage]
-  79)
-  80from ..generic.v0_3 import Doi as Doi
-  81from ..generic.v0_3 import LinkedResource as LinkedResource
-  82from ..generic.v0_3 import Maintainer as Maintainer
-  83from ..generic.v0_3 import OrcidId as OrcidId
-  84from ..generic.v0_3 import RelativeFilePath as RelativeFilePath
-  85from .v0_4 import Author as _Author_v0_4
-  86from .v0_4 import BinarizeDescr as _BinarizeDescr_v0_4
-  87from .v0_4 import BinarizeKwargs as BinarizeKwargs
-  88from .v0_4 import CallableFromDepencency as CallableFromDepencency
-  89from .v0_4 import CallableFromDepencency as _CallableFromDepencency_v0_4
-  90from .v0_4 import CallableFromFile as _CallableFromFile_v0_4
-  91from .v0_4 import ClipDescr as _ClipDescr_v0_4
-  92from .v0_4 import ClipKwargs as ClipKwargs
-  93from .v0_4 import ImplicitOutputShape as _ImplicitOutputShape_v0_4
-  94from .v0_4 import InputTensorDescr as _InputTensorDescr_v0_4
-  95from .v0_4 import KnownRunMode as KnownRunMode
-  96from .v0_4 import ModelDescr as _ModelDescr_v0_4
-  97from .v0_4 import OutputTensorDescr as _OutputTensorDescr_v0_4
-  98from .v0_4 import ParameterizedInputShape as _ParameterizedInputShape_v0_4
-  99from .v0_4 import PostprocessingDescr as _PostprocessingDescr_v0_4
- 100from .v0_4 import PreprocessingDescr as _PreprocessingDescr_v0_4
- 101from .v0_4 import ProcessingKwargs as ProcessingKwargs
- 102from .v0_4 import RunMode as RunMode
- 103from .v0_4 import ScaleLinearDescr as _ScaleLinearDescr_v0_4
- 104from .v0_4 import ScaleMeanVarianceDescr as _ScaleMeanVarianceDescr_v0_4
- 105from .v0_4 import ScaleRangeDescr as _ScaleRangeDescr_v0_4
- 106from .v0_4 import SigmoidDescr as _SigmoidDescr_v0_4
- 107from .v0_4 import TensorName as _TensorName_v0_4
- 108from .v0_4 import WeightsFormat as WeightsFormat
- 109from .v0_4 import ZeroMeanUnitVarianceDescr as _ZeroMeanUnitVarianceDescr_v0_4
- 110
- 111# unit names from https://ngff.openmicroscopy.org/latest/#axes-md
- 112SpaceUnit = Literal[
- 113    "attometer",
- 114    "angstrom",
- 115    "centimeter",
- 116    "decimeter",
- 117    "exameter",
- 118    "femtometer",
- 119    "foot",
- 120    "gigameter",
- 121    "hectometer",
- 122    "inch",
- 123    "kilometer",
- 124    "megameter",
- 125    "meter",
- 126    "micrometer",
- 127    "mile",
- 128    "millimeter",
- 129    "nanometer",
- 130    "parsec",
- 131    "petameter",
- 132    "picometer",
- 133    "terameter",
- 134    "yard",
- 135    "yoctometer",
- 136    "yottameter",
- 137    "zeptometer",
- 138    "zettameter",
- 139]
- 140
- 141TimeUnit = Literal[
- 142    "attosecond",
- 143    "centisecond",
- 144    "day",
- 145    "decisecond",
- 146    "exasecond",
- 147    "femtosecond",
- 148    "gigasecond",
- 149    "hectosecond",
- 150    "hour",
- 151    "kilosecond",
- 152    "megasecond",
- 153    "microsecond",
- 154    "millisecond",
- 155    "minute",
- 156    "nanosecond",
- 157    "petasecond",
- 158    "picosecond",
- 159    "second",
- 160    "terasecond",
- 161    "yoctosecond",
- 162    "yottasecond",
- 163    "zeptosecond",
- 164    "zettasecond",
- 165]
- 166
- 167AxisType = Literal["batch", "channel", "index", "time", "space"]
- 168TensorId = ValidatedString[Annotated[LowerCaseIdentifierAnno, MaxLen(32)]]
- 169AxisId = ValidatedString[Annotated[LowerCaseIdentifierAnno, MaxLen(16)]]
- 170
- 171
- 172NonBatchAxisId = Annotated[AxisId, Predicate(lambda x: x != "batch")]
- 173
- 174PostprocessingId = Literal[
- 175    "binarize",
- 176    "clip",
- 177    "ensure_dtype",
- 178    "fixed_zero_mean_unit_variance",
- 179    "scale_linear",
- 180    "scale_mean_variance",
- 181    "scale_range",
- 182    "sigmoid",
- 183    "zero_mean_unit_variance",
- 184]
- 185PreprocessingId = Literal[
- 186    "binarize",
- 187    "clip",
- 188    "ensure_dtype",
- 189    "scale_linear",
- 190    "sigmoid",
- 191    "zero_mean_unit_variance",
- 192    "scale_range",
- 193]
+  48from typing_extensions import Annotated, LiteralString, Self, assert_never
+  49
+  50from bioimageio.spec._internal.validated_string import ValidatedString
+  51
+  52from .._internal.common_nodes import (
+  53    Converter,
+  54    InvalidDescr,
+  55    Node,
+  56    NodeWithExplicitlySetFields,
+  57)
+  58from .._internal.constants import DTYPE_LIMITS
+  59from .._internal.field_warning import issue_warning, warn
+  60from .._internal.io import BioimageioYamlContent as BioimageioYamlContent
+  61from .._internal.io import FileDescr as FileDescr
+  62from .._internal.io import Sha256 as Sha256
+  63from .._internal.io import WithSuffix, download
+  64from .._internal.io_basics import AbsoluteFilePath as AbsoluteFilePath
+  65from .._internal.io_utils import load_array
+  66from .._internal.types import Datetime as Datetime
+  67from .._internal.types import DeprecatedLicenseId as DeprecatedLicenseId
+  68from .._internal.types import Identifier as Identifier
+  69from .._internal.types import ImportantFileSource, LowerCaseIdentifierAnno, SiUnit
+  70from .._internal.types import LicenseId as LicenseId
+  71from .._internal.types import ModelId as ModelId
+  72from .._internal.types import NotEmpty as NotEmpty
+  73from .._internal.types import ResourceId as ResourceId
+  74from .._internal.url import HttpUrl as HttpUrl
+  75from .._internal.validation_context import validation_context_var
+  76from .._internal.version_type import Version as Version
+  77from .._internal.warning_levels import INFO
+  78from ..dataset.v0_3 import DatasetDescr as DatasetDescr
+  79from ..dataset.v0_3 import LinkedDataset as LinkedDataset
+  80from ..dataset.v0_3 import Uploader as Uploader
+  81from ..generic.v0_3 import Author as Author
+  82from ..generic.v0_3 import BadgeDescr as BadgeDescr
+  83from ..generic.v0_3 import CiteEntry as CiteEntry
+  84from ..generic.v0_3 import (
+  85    DocumentationSource,
+  86    GenericModelDescrBase,
+  87    _author_conv,  # pyright: ignore[reportPrivateUsage]
+  88    _maintainer_conv,  # pyright: ignore[reportPrivateUsage]
+  89)
+  90from ..generic.v0_3 import Doi as Doi
+  91from ..generic.v0_3 import LinkedResource as LinkedResource
+  92from ..generic.v0_3 import Maintainer as Maintainer
+  93from ..generic.v0_3 import OrcidId as OrcidId
+  94from ..generic.v0_3 import RelativeFilePath as RelativeFilePath
+  95from .v0_4 import Author as _Author_v0_4
+  96from .v0_4 import BinarizeDescr as _BinarizeDescr_v0_4
+  97from .v0_4 import BinarizeKwargs as BinarizeKwargs
+  98from .v0_4 import CallableFromDepencency as CallableFromDepencency
+  99from .v0_4 import CallableFromDepencency as _CallableFromDepencency_v0_4
+ 100from .v0_4 import CallableFromFile as _CallableFromFile_v0_4
+ 101from .v0_4 import ClipDescr as _ClipDescr_v0_4
+ 102from .v0_4 import ClipKwargs as ClipKwargs
+ 103from .v0_4 import ImplicitOutputShape as _ImplicitOutputShape_v0_4
+ 104from .v0_4 import InputTensorDescr as _InputTensorDescr_v0_4
+ 105from .v0_4 import KnownRunMode as KnownRunMode
+ 106from .v0_4 import ModelDescr as _ModelDescr_v0_4
+ 107from .v0_4 import OutputTensorDescr as _OutputTensorDescr_v0_4
+ 108from .v0_4 import ParameterizedInputShape as _ParameterizedInputShape_v0_4
+ 109from .v0_4 import PostprocessingDescr as _PostprocessingDescr_v0_4
+ 110from .v0_4 import PreprocessingDescr as _PreprocessingDescr_v0_4
+ 111from .v0_4 import ProcessingKwargs as ProcessingKwargs
+ 112from .v0_4 import RunMode as RunMode
+ 113from .v0_4 import ScaleLinearDescr as _ScaleLinearDescr_v0_4
+ 114from .v0_4 import ScaleMeanVarianceDescr as _ScaleMeanVarianceDescr_v0_4
+ 115from .v0_4 import ScaleRangeDescr as _ScaleRangeDescr_v0_4
+ 116from .v0_4 import SigmoidDescr as _SigmoidDescr_v0_4
+ 117from .v0_4 import TensorName as _TensorName_v0_4
+ 118from .v0_4 import WeightsFormat as WeightsFormat
+ 119from .v0_4 import ZeroMeanUnitVarianceDescr as _ZeroMeanUnitVarianceDescr_v0_4
+ 120
+ 121# unit names from https://ngff.openmicroscopy.org/latest/#axes-md
+ 122SpaceUnit = Literal[
+ 123    "attometer",
+ 124    "angstrom",
+ 125    "centimeter",
+ 126    "decimeter",
+ 127    "exameter",
+ 128    "femtometer",
+ 129    "foot",
+ 130    "gigameter",
+ 131    "hectometer",
+ 132    "inch",
+ 133    "kilometer",
+ 134    "megameter",
+ 135    "meter",
+ 136    "micrometer",
+ 137    "mile",
+ 138    "millimeter",
+ 139    "nanometer",
+ 140    "parsec",
+ 141    "petameter",
+ 142    "picometer",
+ 143    "terameter",
+ 144    "yard",
+ 145    "yoctometer",
+ 146    "yottameter",
+ 147    "zeptometer",
+ 148    "zettameter",
+ 149]
+ 150
+ 151TimeUnit = Literal[
+ 152    "attosecond",
+ 153    "centisecond",
+ 154    "day",
+ 155    "decisecond",
+ 156    "exasecond",
+ 157    "femtosecond",
+ 158    "gigasecond",
+ 159    "hectosecond",
+ 160    "hour",
+ 161    "kilosecond",
+ 162    "megasecond",
+ 163    "microsecond",
+ 164    "millisecond",
+ 165    "minute",
+ 166    "nanosecond",
+ 167    "petasecond",
+ 168    "picosecond",
+ 169    "second",
+ 170    "terasecond",
+ 171    "yoctosecond",
+ 172    "yottasecond",
+ 173    "zeptosecond",
+ 174    "zettasecond",
+ 175]
+ 176
+ 177AxisType = Literal["batch", "channel", "index", "time", "space"]
+ 178TensorId = ValidatedString[Annotated[LowerCaseIdentifierAnno, MaxLen(32)]]
+ 179
+ 180
+ 181class AxisId(str):
+ 182    root_model = ValidatedString[Annotated[LowerCaseIdentifierAnno, MaxLen(16)]]
+ 183
+ 184    @classmethod
+ 185    def __get_pydantic_core_schema__(
+ 186        cls, source_type: Any, handler: GetCoreSchemaHandler
+ 187    ) -> CoreSchema:
+ 188        return no_info_after_validator_function(cls, handler(str))
+ 189
+ 190    @classmethod
+ 191    def _validate(cls, value: str):
+ 192        valid = cls.root_model.model_validate(value)
+ 193        return cls(valid.root)
  194
  195
- 196SAME_AS_TYPE = "<same as type>"
+ 196NonBatchAxisId = Annotated[AxisId, Predicate(lambda x: x != "batch")]
  197
- 198
- 199class ParameterizedSize(Node):
- 200    """Describes a range of valid tensor axis sizes as `size = min + n*step`.
- 201    `n` in this equation is the same for all axis parameterized in this manner across the whole model.
- 202    """
- 203
- 204    N: ClassVar[Type[int]] = int
- 205    """integer to parameterize all axes with a `ParameterizedSize`"""
- 206
- 207    min: Annotated[int, Gt(0)]
- 208    step: Annotated[int, Gt(0)]
- 209
- 210    def validate_size(self, size: int) -> int:
- 211        if size < self.min:
- 212            raise ValueError(f"size {size} < {self.min}")
- 213        if (size - self.min) % self.step != 0:
- 214            raise ValueError(
- 215                f"axis of size {size} is not parameterized by `min + n*step` ="
- 216                + f" `{self.min} + n*{self.step}`"
- 217            )
+ 198PostprocessingId = Literal[
+ 199    "binarize",
+ 200    "clip",
+ 201    "ensure_dtype",
+ 202    "fixed_zero_mean_unit_variance",
+ 203    "scale_linear",
+ 204    "scale_mean_variance",
+ 205    "scale_range",
+ 206    "sigmoid",
+ 207    "zero_mean_unit_variance",
+ 208]
+ 209PreprocessingId = Literal[
+ 210    "binarize",
+ 211    "clip",
+ 212    "ensure_dtype",
+ 213    "scale_linear",
+ 214    "sigmoid",
+ 215    "zero_mean_unit_variance",
+ 216    "scale_range",
+ 217]
  218
- 219        return size
- 220
- 221    def get_size(self, n: ParameterizedSize.N) -> int:
- 222        return self.min + self.step * n
- 223
- 224
- 225class SizeReference(Node):
- 226    """A tensor axis size (extent in pixels/frames) defined in relation to a reference axis.
+ 219
+ 220SAME_AS_TYPE = "<same as type>"
+ 221
+ 222
+ 223class ParameterizedSize(Node):
+ 224    """Describes a range of valid tensor axis sizes as `size = min + n*step`.
+ 225    `n` in this equation is the same for all axis parameterized in this manner across the whole model.
+ 226    """
  227
- 228    `axis.size = reference.size * reference.scale / axis.scale + offset`
- 229
- 230    note:
- 231    1. The axis and the referenced axis need to have the same unit (or no unit).
- 232    2. Batch axes may not be referenced.
- 233    3. Fractions are rounded down.
- 234
- 235    example:
- 236    An unisotropic input image of w*h=100*49 pixels depicts a phsical space of 200*196mm².
- 237    Let's assume that we want to express the image height h in relation to its width w
- 238    instead of only accepting input images of exactly 100*49 pixels
- 239    (for example to express a range of valid image shapes by parametrizing w, see `ParameterizedSize`).
- 240
- 241    >>> w = SpaceInputAxis(id=AxisId("w"), size=100, unit="millimeter", scale=2)
- 242    >>> h = SpaceInputAxis(
- 243    ...     id=AxisId("h"),
- 244    ...     size=SizeReference(tensor_id=TensorId("input"), axis_id=AxisId("w"), offset=-1),
- 245    ...     unit="millimeter",
- 246    ...     scale=4,
- 247    ... )
- 248    >>> print(h.size.compute(h, w))
- 249    49
- 250
- 251    -> h = w * w.scale / h.scale + offset = 100 * 2mm / 4mm - 1 = 49
- 252    """
+ 228    N: ClassVar[Type[int]] = int
+ 229    """integer to parameterize all axes with a `ParameterizedSize`"""
+ 230
+ 231    min: Annotated[int, Gt(0)]
+ 232    step: Annotated[int, Gt(0)]
+ 233
+ 234    def validate_size(self, size: int) -> int:
+ 235        if size < self.min:
+ 236            raise ValueError(f"size {size} < {self.min}")
+ 237        if (size - self.min) % self.step != 0:
+ 238            raise ValueError(
+ 239                f"axis of size {size} is not parameterized by `min + n*step` ="
+ 240                + f" `{self.min} + n*{self.step}`"
+ 241            )
+ 242
+ 243        return size
+ 244
+ 245    def get_size(self, n: ParameterizedSize.N) -> int:
+ 246        return self.min + self.step * n
+ 247
+ 248
+ 249class SizeReference(Node):
+ 250    """A tensor axis size (extent in pixels/frames) defined in relation to a reference axis.
+ 251
+ 252    `axis.size = reference.size * reference.scale / axis.scale + offset`
  253
- 254    tensor_id: TensorId
- 255    """tensor id of the reference axis"""
- 256
- 257    axis_id: AxisId
- 258    """axis id of the reference axis"""
- 259
- 260    offset: int = 0
- 261
- 262    def get_size(
- 263        self,
- 264        axis: Union[
- 265            ChannelAxis,
- 266            IndexAxis,
- 267            TimeInputAxis,
- 268            SpaceInputAxis,
- 269            TimeOutputAxis,
- 270            SpaceOutputAxis,
- 271        ],
- 272        ref_axis: Union[
- 273            ChannelAxis,
- 274            IndexAxis,
- 275            TimeInputAxis,
- 276            SpaceInputAxis,
- 277            TimeOutputAxis,
- 278            SpaceOutputAxis,
- 279        ],
- 280        n: ParameterizedSize.N,
- 281    ):
- 282        """helper method to compute concrete size for a given axis and its reference axis.
- 283        If the reference axis is parameterized, `n` is used to compute the concrete size of it, see `ParameterizedSize`.
- 284        """
- 285        assert (
- 286            axis.size == self
- 287        ), "Given `axis.size` is not defined by this `SizeReference`"
- 288
- 289        assert (
- 290            ref_axis.id == self.axis_id
- 291        ), f"Expected `ref_axis.id` to be {self.axis_id}, but got {ref_axis.id}."
- 292
- 293        assert axis.unit == ref_axis.unit, (
- 294            "`SizeReference` requires `axis` and `ref_axis` to have the same `unit`,"
- 295            f" but {axis.unit}!={ref_axis.unit}"
- 296        )
- 297
- 298        if isinstance(ref_axis.size, (int, float)):
- 299            ref_size = ref_axis.size
- 300        elif isinstance(ref_axis.size, ParameterizedSize):
- 301            ref_size = ref_axis.size.get_size(n)
- 302        elif isinstance(ref_axis.size, SizeReference):
- 303            raise ValueError(
- 304                "Reference axis referenced in `SizeReference` may not be sized by a"
- 305                + " `SizeReference` itself."
- 306            )
- 307        else:
- 308            assert_never(ref_axis.size)
- 309
- 310        return int(ref_size * ref_axis.scale / axis.scale + self.offset)
- 311
- 312    @staticmethod
- 313    def _get_unit(
- 314        axis: Union[
- 315            ChannelAxis,
- 316            IndexAxis,
- 317            TimeInputAxis,
- 318            SpaceInputAxis,
- 319            TimeOutputAxis,
- 320            SpaceOutputAxis,
- 321        ],
- 322    ):
- 323        return axis.unit
- 324
- 325
- 326# this Axis definition is compatible with the NGFF draft from July 10, 2023
- 327# https://ngff.openmicroscopy.org/latest/#axes-md
- 328class AxisBase(NodeWithExplicitlySetFields):
- 329    fields_to_set_explicitly: ClassVar[FrozenSet[LiteralString]] = frozenset({"type"})
- 330
- 331    id: AxisId
- 332    """An axis id unique across all axes of one tensor."""
+ 254    note:
+ 255    1. The axis and the referenced axis need to have the same unit (or no unit).
+ 256    2. Batch axes may not be referenced.
+ 257    3. Fractions are rounded down.
+ 258
+ 259    example:
+ 260    An unisotropic input image of w*h=100*49 pixels depicts a phsical space of 200*196mm².
+ 261    Let's assume that we want to express the image height h in relation to its width w
+ 262    instead of only accepting input images of exactly 100*49 pixels
+ 263    (for example to express a range of valid image shapes by parametrizing w, see `ParameterizedSize`).
+ 264
+ 265    >>> w = SpaceInputAxis(id=AxisId("w"), size=100, unit="millimeter", scale=2)
+ 266    >>> h = SpaceInputAxis(
+ 267    ...     id=AxisId("h"),
+ 268    ...     size=SizeReference(tensor_id=TensorId("input"), axis_id=AxisId("w"), offset=-1),
+ 269    ...     unit="millimeter",
+ 270    ...     scale=4,
+ 271    ... )
+ 272    >>> print(h.size.compute(h, w))
+ 273    49
+ 274
+ 275    -> h = w * w.scale / h.scale + offset = 100 * 2mm / 4mm - 1 = 49
+ 276    """
+ 277
+ 278    tensor_id: TensorId
+ 279    """tensor id of the reference axis"""
+ 280
+ 281    axis_id: AxisId
+ 282    """axis id of the reference axis"""
+ 283
+ 284    offset: int = 0
+ 285
+ 286    def get_size(
+ 287        self,
+ 288        axis: Union[
+ 289            ChannelAxis,
+ 290            IndexAxis,
+ 291            TimeInputAxis,
+ 292            SpaceInputAxis,
+ 293            TimeOutputAxis,
+ 294            SpaceOutputAxis,
+ 295        ],
+ 296        ref_axis: Union[
+ 297            ChannelAxis,
+ 298            IndexAxis,
+ 299            TimeInputAxis,
+ 300            SpaceInputAxis,
+ 301            TimeOutputAxis,
+ 302            SpaceOutputAxis,
+ 303        ],
+ 304        n: ParameterizedSize.N,
+ 305    ):
+ 306        """helper method to compute concrete size for a given axis and its reference axis.
+ 307        If the reference axis is parameterized, `n` is used to compute the concrete size of it, see `ParameterizedSize`.
+ 308        """
+ 309        assert (
+ 310            axis.size == self
+ 311        ), "Given `axis.size` is not defined by this `SizeReference`"
+ 312
+ 313        assert (
+ 314            ref_axis.id == self.axis_id
+ 315        ), f"Expected `ref_axis.id` to be {self.axis_id}, but got {ref_axis.id}."
+ 316
+ 317        assert axis.unit == ref_axis.unit, (
+ 318            "`SizeReference` requires `axis` and `ref_axis` to have the same `unit`,"
+ 319            f" but {axis.unit}!={ref_axis.unit}"
+ 320        )
+ 321
+ 322        if isinstance(ref_axis.size, (int, float)):
+ 323            ref_size = ref_axis.size
+ 324        elif isinstance(ref_axis.size, ParameterizedSize):
+ 325            ref_size = ref_axis.size.get_size(n)
+ 326        elif isinstance(ref_axis.size, SizeReference):
+ 327            raise ValueError(
+ 328                "Reference axis referenced in `SizeReference` may not be sized by a"
+ 329                + " `SizeReference` itself."
+ 330            )
+ 331        else:
+ 332            assert_never(ref_axis.size)
  333
- 334    description: Annotated[str, MaxLen(128)] = ""
+ 334        return int(ref_size * ref_axis.scale / axis.scale + self.offset)
  335
- 336
- 337class WithHalo(Node):
- 338    halo: Annotated[int, Ge(0)] = 0
- 339    """The halo should be cropped from the output tensor to avoid boundary effects.
- 340    It is to be cropped from both sides, i.e. `size_after_crop = size - 2 * halo`.
- 341    To document a halo that is already cropped by the model use `size.offset` instead."""
- 342
- 343
- 344class BatchAxis(AxisBase):
- 345    type: Literal["batch"] = "batch"
- 346    id: Annotated[AxisId, Predicate(lambda x: x == AxisId("batch"))] = AxisId("batch")
- 347    size: Optional[Literal[1]] = None
- 348    """The batch size may be fixed to 1,
- 349    otherwise (the default) it may be chosen arbitrarily depending on available memory"""
- 350
- 351    @property
- 352    def scale(self):
- 353        return 1.0
+ 336    @staticmethod
+ 337    def _get_unit(
+ 338        axis: Union[
+ 339            ChannelAxis,
+ 340            IndexAxis,
+ 341            TimeInputAxis,
+ 342            SpaceInputAxis,
+ 343            TimeOutputAxis,
+ 344            SpaceOutputAxis,
+ 345        ],
+ 346    ):
+ 347        return axis.unit
+ 348
+ 349
+ 350# this Axis definition is compatible with the NGFF draft from July 10, 2023
+ 351# https://ngff.openmicroscopy.org/latest/#axes-md
+ 352class AxisBase(NodeWithExplicitlySetFields):
+ 353    fields_to_set_explicitly: ClassVar[FrozenSet[LiteralString]] = frozenset({"type"})
  354
- 355    @property
- 356    def unit(self):
- 357        return None
- 358
+ 355    id: AxisId
+ 356    """An axis id unique across all axes of one tensor."""
+ 357
+ 358    description: Annotated[str, MaxLen(128)] = ""
  359
- 360class ChannelAxis(AxisBase):
- 361    type: Literal["channel"] = "channel"
- 362    id: NonBatchAxisId = AxisId("channel")
- 363    channel_names: List[Identifier]
- 364
- 365    @property
- 366    def size(self) -> int:
- 367        return len(self.channel_names)
- 368
- 369    @property
- 370    def scale(self) -> float:
- 371        return 1.0
- 372
- 373    @property
- 374    def unit(self):
- 375        return None
- 376
- 377
- 378class IndexTimeSpaceAxisBase(AxisBase):
- 379    size: Annotated[
- 380        Union[Annotated[int, Gt(0)], ParameterizedSize, SizeReference],
- 381        Field(
- 382            examples=[
- 383                10,
- 384                ParameterizedSize(min=32, step=16).model_dump(mode="json"),
- 385                SizeReference(
- 386                    tensor_id=TensorId("t"), axis_id=AxisId("a"), offset=5
- 387                ).model_dump(mode="json"),
- 388            ]
- 389        ),
- 390    ]
- 391    """The size/length of an axis can be specified as
- 392    - fixed integer
- 393    - parameterized series of valid sizes (`ParameterizedSize`)
- 394    - reference to another axis with an optional offset (`SizeReference`)
- 395    """
+ 360
+ 361class WithHalo(Node):
+ 362    halo: Annotated[int, Ge(0)] = 0
+ 363    """The halo should be cropped from the output tensor to avoid boundary effects.
+ 364    It is to be cropped from both sides, i.e. `size_after_crop = size - 2 * halo`.
+ 365    To document a halo that is already cropped by the model use `size.offset` instead."""
+ 366
+ 367
+ 368class BatchAxis(AxisBase):
+ 369    type: Literal["batch"] = "batch"
+ 370    id: Annotated[AxisId, Predicate(lambda x: x == AxisId("batch"))] = AxisId("batch")
+ 371    size: Optional[Literal[1]] = None
+ 372    """The batch size may be fixed to 1,
+ 373    otherwise (the default) it may be chosen arbitrarily depending on available memory"""
+ 374
+ 375    @property
+ 376    def scale(self):
+ 377        return 1.0
+ 378
+ 379    @property
+ 380    def unit(self):
+ 381        return None
+ 382
+ 383
+ 384class ChannelAxis(AxisBase):
+ 385    type: Literal["channel"] = "channel"
+ 386    id: NonBatchAxisId = AxisId("channel")
+ 387    channel_names: List[Identifier]
+ 388
+ 389    @property
+ 390    def size(self) -> int:
+ 391        return len(self.channel_names)
+ 392
+ 393    @property
+ 394    def scale(self) -> float:
+ 395        return 1.0
  396
- 397
- 398class IndexAxis(IndexTimeSpaceAxisBase):
- 399    type: Literal["index"] = "index"
- 400    id: NonBatchAxisId = AxisId("index")
+ 397    @property
+ 398    def unit(self):
+ 399        return None
+ 400
  401
- 402    @property
- 403    def scale(self) -> float:
- 404        return 1.0
- 405
- 406    @property
- 407    def unit(self):
- 408        return None
- 409
- 410
- 411class TimeAxisBase(IndexTimeSpaceAxisBase):
- 412    type: Literal["time"] = "time"
- 413    id: NonBatchAxisId = AxisId("time")
- 414    unit: Optional[TimeUnit] = None
- 415    scale: Annotated[float, Gt(0)] = 1.0
- 416
- 417
- 418class TimeInputAxis(TimeAxisBase):
- 419    pass
+ 402class IndexTimeSpaceAxisBase(AxisBase):
+ 403    size: Annotated[
+ 404        Union[Annotated[int, Gt(0)], ParameterizedSize, SizeReference],
+ 405        Field(
+ 406            examples=[
+ 407                10,
+ 408                ParameterizedSize(min=32, step=16).model_dump(mode="json"),
+ 409                SizeReference(
+ 410                    tensor_id=TensorId("t"), axis_id=AxisId("a"), offset=5
+ 411                ).model_dump(mode="json"),
+ 412            ]
+ 413        ),
+ 414    ]
+ 415    """The size/length of an axis can be specified as
+ 416    - fixed integer
+ 417    - parameterized series of valid sizes (`ParameterizedSize`)
+ 418    - reference to another axis with an optional offset (`SizeReference`)
+ 419    """
  420
  421
- 422class SpaceAxisBase(IndexTimeSpaceAxisBase):
- 423    type: Literal["space"] = "space"
- 424    id: Annotated[NonBatchAxisId, Field(examples=["x", "y", "z"])] = AxisId("x")
- 425    unit: Optional[SpaceUnit] = None
- 426    scale: Annotated[float, Gt(0)] = 1.0
- 427
- 428
- 429class SpaceInputAxis(SpaceAxisBase):
- 430    pass
- 431
- 432
- 433_InputAxisUnion = Union[
- 434    BatchAxis, ChannelAxis, IndexAxis, TimeInputAxis, SpaceInputAxis
- 435]
- 436InputAxis = Annotated[_InputAxisUnion, Field(discriminator="type")]
- 437
- 438
- 439class TimeOutputAxis(TimeAxisBase, WithHalo):
- 440    pass
+ 422class IndexAxis(IndexTimeSpaceAxisBase):
+ 423    type: Literal["index"] = "index"
+ 424    id: NonBatchAxisId = AxisId("index")
+ 425
+ 426    @property
+ 427    def scale(self) -> float:
+ 428        return 1.0
+ 429
+ 430    @property
+ 431    def unit(self):
+ 432        return None
+ 433
+ 434
+ 435class TimeAxisBase(IndexTimeSpaceAxisBase):
+ 436    type: Literal["time"] = "time"
+ 437    id: NonBatchAxisId = AxisId("time")
+ 438    unit: Optional[TimeUnit] = None
+ 439    scale: Annotated[float, Gt(0)] = 1.0
+ 440
  441
- 442
- 443class SpaceOutputAxis(SpaceAxisBase, WithHalo):
- 444    pass
+ 442class TimeInputAxis(TimeAxisBase):
+ 443    pass
+ 444
  445
- 446
- 447_OutputAxisUnion = Union[
- 448    BatchAxis, ChannelAxis, IndexAxis, TimeOutputAxis, SpaceOutputAxis
- 449]
- 450OutputAxis = Annotated[_OutputAxisUnion, Field(discriminator="type")]
+ 446class SpaceAxisBase(IndexTimeSpaceAxisBase):
+ 447    type: Literal["space"] = "space"
+ 448    id: Annotated[NonBatchAxisId, Field(examples=["x", "y", "z"])] = AxisId("x")
+ 449    unit: Optional[SpaceUnit] = None
+ 450    scale: Annotated[float, Gt(0)] = 1.0
  451
- 452AnyAxis = Union[InputAxis, OutputAxis]
- 453
- 454TVs = Union[
- 455    NotEmpty[List[int]],
- 456    NotEmpty[List[float]],
- 457    NotEmpty[List[bool]],
- 458    NotEmpty[List[str]],
+ 452
+ 453class SpaceInputAxis(SpaceAxisBase):
+ 454    pass
+ 455
+ 456
+ 457_InputAxisUnion = Union[
+ 458    BatchAxis, ChannelAxis, IndexAxis, TimeInputAxis, SpaceInputAxis
  459]
- 460
+ 460InputAxis = Annotated[_InputAxisUnion, Field(discriminator="type")]
  461
- 462NominalOrOrdinalDType = Literal[
- 463    "float32",
- 464    "float64",
- 465    "uint8",
- 466    "int8",
- 467    "uint16",
- 468    "int16",
- 469    "uint32",
- 470    "int32",
- 471    "uint64",
- 472    "int64",
- 473    "bool",
- 474]
+ 462
+ 463class TimeOutputAxis(TimeAxisBase, WithHalo):
+ 464    pass
+ 465
+ 466
+ 467class SpaceOutputAxis(SpaceAxisBase, WithHalo):
+ 468    pass
+ 469
+ 470
+ 471_OutputAxisUnion = Union[
+ 472    BatchAxis, ChannelAxis, IndexAxis, TimeOutputAxis, SpaceOutputAxis
+ 473]
+ 474OutputAxis = Annotated[_OutputAxisUnion, Field(discriminator="type")]
  475
- 476
- 477class NominalOrOrdinalDataDescr(Node):
- 478    values: TVs
- 479    """A fixed set of nominal or an ascending sequence of ordinal values.
- 480    In this case `data_type` is required to be an unsigend integer type, e.g. 'uint8'.
- 481    String `values` are interpreted as labels for tensor values 0, ..., N.
- 482    Note: as YAML 1.2 does not natively support a "set" datatype,
- 483    nominal values should be given as a sequence (aka list/array) as well.
- 484    """
+ 476AnyAxis = Union[InputAxis, OutputAxis]
+ 477
+ 478TVs = Union[
+ 479    NotEmpty[List[int]],
+ 480    NotEmpty[List[float]],
+ 481    NotEmpty[List[bool]],
+ 482    NotEmpty[List[str]],
+ 483]
+ 484
  485
- 486    type: Annotated[
- 487        NominalOrOrdinalDType,
- 488        Field(
- 489            examples=[
- 490                "float32",
- 491                "uint8",
- 492                "uint16",
- 493                "int64",
- 494                "bool",
- 495            ],
- 496        ),
- 497    ] = "uint8"
- 498
- 499    @model_validator(mode="after")
- 500    def _validate_values_match_type(
- 501        self,
- 502    ) -> Self:
- 503        incompatible: List[Any] = []
- 504        for v in self.values:
- 505            if self.type == "bool":
- 506                if not isinstance(v, bool):
- 507                    incompatible.append(v)
- 508            elif self.type in DTYPE_LIMITS:
- 509                if (
- 510                    isinstance(v, (int, float))
- 511                    and (
- 512                        v < DTYPE_LIMITS[self.type].min
- 513                        or v > DTYPE_LIMITS[self.type].max
- 514                    )
- 515                    or (isinstance(v, str) and "uint" not in self.type)
- 516                    or (isinstance(v, float) and "int" in self.type)
- 517                ):
- 518                    incompatible.append(v)
- 519            else:
- 520                incompatible.append(v)
- 521
- 522            if len(incompatible) == 5:
- 523                incompatible.append("...")
- 524                break
- 525
- 526        if incompatible:
- 527            raise ValueError(
- 528                f"data type '{self.type}' incompatible with values {incompatible}"
- 529            )
- 530
- 531        return self
- 532
- 533    unit: Optional[Union[Literal["arbitrary unit"], SiUnit]] = None
- 534
- 535    @property
- 536    def range(self):
- 537        if isinstance(self.values[0], str):
- 538            return 0, len(self.values) - 1
- 539        else:
- 540            return min(self.values), max(self.values)
- 541
- 542
- 543IntervalOrRatioDType = Literal[
- 544    "float32",
- 545    "float64",
- 546    "uint8",
- 547    "int8",
- 548    "uint16",
- 549    "int16",
- 550    "uint32",
- 551    "int32",
- 552    "uint64",
- 553    "int64",
- 554]
- 555
+ 486NominalOrOrdinalDType = Literal[
+ 487    "float32",
+ 488    "float64",
+ 489    "uint8",
+ 490    "int8",
+ 491    "uint16",
+ 492    "int16",
+ 493    "uint32",
+ 494    "int32",
+ 495    "uint64",
+ 496    "int64",
+ 497    "bool",
+ 498]
+ 499
+ 500
+ 501class NominalOrOrdinalDataDescr(Node):
+ 502    values: TVs
+ 503    """A fixed set of nominal or an ascending sequence of ordinal values.
+ 504    In this case `data_type` is required to be an unsigend integer type, e.g. 'uint8'.
+ 505    String `values` are interpreted as labels for tensor values 0, ..., N.
+ 506    Note: as YAML 1.2 does not natively support a "set" datatype,
+ 507    nominal values should be given as a sequence (aka list/array) as well.
+ 508    """
+ 509
+ 510    type: Annotated[
+ 511        NominalOrOrdinalDType,
+ 512        Field(
+ 513            examples=[
+ 514                "float32",
+ 515                "uint8",
+ 516                "uint16",
+ 517                "int64",
+ 518                "bool",
+ 519            ],
+ 520        ),
+ 521    ] = "uint8"
+ 522
+ 523    @model_validator(mode="after")
+ 524    def _validate_values_match_type(
+ 525        self,
+ 526    ) -> Self:
+ 527        incompatible: List[Any] = []
+ 528        for v in self.values:
+ 529            if self.type == "bool":
+ 530                if not isinstance(v, bool):
+ 531                    incompatible.append(v)
+ 532            elif self.type in DTYPE_LIMITS:
+ 533                if (
+ 534                    isinstance(v, (int, float))
+ 535                    and (
+ 536                        v < DTYPE_LIMITS[self.type].min
+ 537                        or v > DTYPE_LIMITS[self.type].max
+ 538                    )
+ 539                    or (isinstance(v, str) and "uint" not in self.type)
+ 540                    or (isinstance(v, float) and "int" in self.type)
+ 541                ):
+ 542                    incompatible.append(v)
+ 543            else:
+ 544                incompatible.append(v)
+ 545
+ 546            if len(incompatible) == 5:
+ 547                incompatible.append("...")
+ 548                break
+ 549
+ 550        if incompatible:
+ 551            raise ValueError(
+ 552                f"data type '{self.type}' incompatible with values {incompatible}"
+ 553            )
+ 554
+ 555        return self
  556
- 557class IntervalOrRatioDataDescr(Node):
- 558    type: Annotated[  # todo: rename to dtype
- 559        IntervalOrRatioDType,
- 560        Field(
- 561            examples=["float32", "float64", "uint8", "uint16"],
- 562        ),
- 563    ] = "float32"
- 564    range: Tuple[Optional[float], Optional[float]] = (
- 565        None,
- 566        None,
- 567    )
- 568    """Tuple `(minimum, maximum)` specifying the allowed range of the data in this tensor.
- 569    `None` corresponds to min/max of what can be expressed by `data_type`."""
- 570    unit: Union[Literal["arbitrary unit"], SiUnit] = "arbitrary unit"
- 571    scale: float = 1.0
- 572    """Scale for data on an interval (or ratio) scale."""
- 573    offset: Optional[float] = None
- 574    """Offset for data on a ratio scale."""
- 575
- 576
- 577TensorDataDescr = Union[NominalOrOrdinalDataDescr, IntervalOrRatioDataDescr]
- 578
+ 557    unit: Optional[Union[Literal["arbitrary unit"], SiUnit]] = None
+ 558
+ 559    @property
+ 560    def range(self):
+ 561        if isinstance(self.values[0], str):
+ 562            return 0, len(self.values) - 1
+ 563        else:
+ 564            return min(self.values), max(self.values)
+ 565
+ 566
+ 567IntervalOrRatioDType = Literal[
+ 568    "float32",
+ 569    "float64",
+ 570    "uint8",
+ 571    "int8",
+ 572    "uint16",
+ 573    "int16",
+ 574    "uint32",
+ 575    "int32",
+ 576    "uint64",
+ 577    "int64",
+ 578]
  579
- 580class ProcessingDescrBase(NodeWithExplicitlySetFields, ABC):
- 581    """processing base class"""
- 582
- 583    # id: Literal[PreprocessingId, PostprocessingId]  # make abstract field
- 584    fields_to_set_explicitly: ClassVar[FrozenSet[LiteralString]] = frozenset({"id"})
- 585
- 586
- 587class BinarizeDescr(ProcessingDescrBase):
- 588    """Binarize the tensor with a fixed threshold.
- 589    Values above the threshold will be set to one, values below the threshold to zero.
- 590    """
- 591
- 592    id: Literal["binarize"] = "binarize"
- 593    kwargs: BinarizeKwargs
- 594
- 595
- 596class ClipDescr(ProcessingDescrBase):
- 597    """Set tensor values below min to min and above max to max."""
- 598
- 599    id: Literal["clip"] = "clip"
- 600    kwargs: ClipKwargs
- 601
+ 580
+ 581class IntervalOrRatioDataDescr(Node):
+ 582    type: Annotated[  # todo: rename to dtype
+ 583        IntervalOrRatioDType,
+ 584        Field(
+ 585            examples=["float32", "float64", "uint8", "uint16"],
+ 586        ),
+ 587    ] = "float32"
+ 588    range: Tuple[Optional[float], Optional[float]] = (
+ 589        None,
+ 590        None,
+ 591    )
+ 592    """Tuple `(minimum, maximum)` specifying the allowed range of the data in this tensor.
+ 593    `None` corresponds to min/max of what can be expressed by `data_type`."""
+ 594    unit: Union[Literal["arbitrary unit"], SiUnit] = "arbitrary unit"
+ 595    scale: float = 1.0
+ 596    """Scale for data on an interval (or ratio) scale."""
+ 597    offset: Optional[float] = None
+ 598    """Offset for data on a ratio scale."""
+ 599
+ 600
+ 601TensorDataDescr = Union[NominalOrOrdinalDataDescr, IntervalOrRatioDataDescr]
  602
- 603class EnsureDtypeKwargs(ProcessingKwargs):
- 604    dtype: str
- 605
+ 603
+ 604class ProcessingDescrBase(NodeWithExplicitlySetFields, ABC):
+ 605    """processing base class"""
  606
- 607class EnsureDtypeDescr(ProcessingDescrBase):
- 608    id: Literal["ensure_dtype"] = "ensure_dtype"
- 609    kwargs: EnsureDtypeKwargs
+ 607    # id: Literal[PreprocessingId, PostprocessingId]  # make abstract field
+ 608    fields_to_set_explicitly: ClassVar[FrozenSet[LiteralString]] = frozenset({"id"})
+ 609
  610
- 611
- 612class ScaleLinearKwargs(ProcessingKwargs):
- 613    axis: Annotated[Optional[NonBatchAxisId], Field(examples=["channel"])] = (
- 614        None  # todo: validate existence of axis
- 615    )
- 616    """The axis of non-scalar gains/offsets.
- 617    Invalid for scalar gains/offsets.
- 618    """
+ 611class BinarizeDescr(ProcessingDescrBase):
+ 612    """Binarize the tensor with a fixed threshold.
+ 613    Values above the threshold will be set to one, values below the threshold to zero.
+ 614    """
+ 615
+ 616    id: Literal["binarize"] = "binarize"
+ 617    kwargs: BinarizeKwargs
+ 618
  619
- 620    gain: Union[float, NotEmpty[List[float]]] = 1.0
- 621    """multiplicative factor"""
+ 620class ClipDescr(ProcessingDescrBase):
+ 621    """Set tensor values below min to min and above max to max."""
  622
- 623    offset: Union[float, NotEmpty[List[float]]] = 0.0
- 624    """additive term"""
+ 623    id: Literal["clip"] = "clip"
+ 624    kwargs: ClipKwargs
  625
- 626    @model_validator(mode="after")
- 627    def either_gain_or_offset(self) -> Self:
- 628        if (
- 629            self.gain == 1.0
- 630            or isinstance(self.gain, list)
- 631            and all(g == 1.0 for g in self.gain)
- 632        ) and (
- 633            self.offset == 0.0
- 634            or isinstance(self.offset, list)
- 635            and all(off == 0.0 for off in self.offset)
- 636        ):
- 637            raise ValueError(
- 638                "Redundant linear scaling not allowd. Set `gain` != 1.0 and/or `offset`"
- 639                + " != 0.0."
- 640            )
- 641
- 642        return self
+ 626
+ 627class EnsureDtypeKwargs(ProcessingKwargs):
+ 628    dtype: str
+ 629
+ 630
+ 631class EnsureDtypeDescr(ProcessingDescrBase):
+ 632    id: Literal["ensure_dtype"] = "ensure_dtype"
+ 633    kwargs: EnsureDtypeKwargs
+ 634
+ 635
+ 636class ScaleLinearKwargs(ProcessingKwargs):
+ 637    axis: Annotated[Optional[NonBatchAxisId], Field(examples=["channel"])] = (
+ 638        None  # todo: validate existence of axis
+ 639    )
+ 640    """The axis of non-scalar gains/offsets.
+ 641    Invalid for scalar gains/offsets.
+ 642    """
  643
- 644
- 645class ScaleLinearDescr(ProcessingDescrBase):
- 646    """Fixed linear scaling."""
- 647
- 648    id: Literal["scale_linear"] = "scale_linear"
- 649    kwargs: ScaleLinearKwargs
- 650
- 651
- 652class SigmoidDescr(ProcessingDescrBase):
- 653    """The logistic sigmoid funciton, a.k.a. expit function."""
- 654
- 655    id: Literal["sigmoid"] = "sigmoid"
- 656
- 657    @property
- 658    def kwargs(self) -> ProcessingKwargs:
- 659        """empty kwargs"""
- 660        return ProcessingKwargs()
- 661
- 662
- 663class FixedZeroMeanUnitVarianceKwargs(ProcessingKwargs):
- 664    """Normalize with fixed, precomputed values for mean and variance.
- 665    See `zero_mean_unit_variance` for data dependent normalization."""
- 666
- 667    mean: Annotated[
- 668        Union[float, NotEmpty[Tuple[float, ...]]],
- 669        Field(examples=[3.14, (1.1, -2.2, 3.3)]),
- 670    ]
- 671    """The mean value(s) to normalize with. Specify `axis` for a sequence of `mean` values"""
- 672
- 673    std: Annotated[
- 674        Union[
- 675            Annotated[float, Ge(1e-6)], NotEmpty[Tuple[Annotated[float, Ge(1e-6)], ...]]
- 676        ],
- 677        Field(examples=[1.05, (0.1, 0.2, 0.3)]),
- 678    ]
- 679    """The standard deviation value(s) to normalize with. Size must match `mean` values."""
+ 644    gain: Union[float, NotEmpty[List[float]]] = 1.0
+ 645    """multiplicative factor"""
+ 646
+ 647    offset: Union[float, NotEmpty[List[float]]] = 0.0
+ 648    """additive term"""
+ 649
+ 650    @model_validator(mode="after")
+ 651    def either_gain_or_offset(self) -> Self:
+ 652        if (
+ 653            self.gain == 1.0
+ 654            or isinstance(self.gain, list)
+ 655            and all(g == 1.0 for g in self.gain)
+ 656        ) and (
+ 657            self.offset == 0.0
+ 658            or isinstance(self.offset, list)
+ 659            and all(off == 0.0 for off in self.offset)
+ 660        ):
+ 661            raise ValueError(
+ 662                "Redundant linear scaling not allowd. Set `gain` != 1.0 and/or `offset`"
+ 663                + " != 0.0."
+ 664            )
+ 665
+ 666        return self
+ 667
+ 668
+ 669class ScaleLinearDescr(ProcessingDescrBase):
+ 670    """Fixed linear scaling."""
+ 671
+ 672    id: Literal["scale_linear"] = "scale_linear"
+ 673    kwargs: ScaleLinearKwargs
+ 674
+ 675
+ 676class SigmoidDescr(ProcessingDescrBase):
+ 677    """The logistic sigmoid funciton, a.k.a. expit function."""
+ 678
+ 679    id: Literal["sigmoid"] = "sigmoid"
  680
- 681    axis: Annotated[Optional[NonBatchAxisId], Field(examples=["channel", "index"])] = (
- 682        None  # todo: validate existence of axis
- 683    )
- 684    """The axis of the mean/std values to normalize each entry along that dimension separately.
- 685    Invalid for scalar gains/offsets.
- 686    """
- 687
- 688    @model_validator(mode="after")
- 689    def mean_and_std_match(self) -> Self:
- 690        mean_len = 1 if isinstance(self.mean, (float, int)) else len(self.mean)
- 691        std_len = 1 if isinstance(self.std, (float, int)) else len(self.std)
- 692        if mean_len != std_len:
- 693            raise ValueError(
- 694                "size of `mean` ({mean_len}) and `std` ({std_len}) must match."
- 695            )
+ 681    @property
+ 682    def kwargs(self) -> ProcessingKwargs:
+ 683        """empty kwargs"""
+ 684        return ProcessingKwargs()
+ 685
+ 686
+ 687class FixedZeroMeanUnitVarianceKwargs(ProcessingKwargs):
+ 688    """Normalize with fixed, precomputed values for mean and variance.
+ 689    See `zero_mean_unit_variance` for data dependent normalization."""
+ 690
+ 691    mean: Annotated[
+ 692        Union[float, NotEmpty[Tuple[float, ...]]],
+ 693        Field(examples=[3.14, (1.1, -2.2, 3.3)]),
+ 694    ]
+ 695    """The mean value(s) to normalize with. Specify `axis` for a sequence of `mean` values"""
  696
- 697        return self
- 698
- 699
- 700class FixedZeroMeanUnitVarianceDescr(ProcessingDescrBase):
- 701    """Subtract a given mean and divide by a given variance."""
- 702
- 703    id: Literal["fixed_zero_mean_unit_variance"] = "fixed_zero_mean_unit_variance"
- 704    kwargs: FixedZeroMeanUnitVarianceKwargs
- 705
- 706
- 707class ZeroMeanUnitVarianceKwargs(ProcessingKwargs):
- 708    axes: Annotated[
- 709        Optional[Sequence[AxisId]], Field(examples=[("batch", "x", "y")])
- 710    ] = None
- 711    """The subset of axes to normalize jointly, i.e. axes to reduce to compute mean/std.
- 712    For example to normalize 'batch', 'x' and 'y' jointly in a tensor ('batch', 'channel', 'y', 'x')
- 713    resulting in a tensor of equal shape normalized per channel, specify `axes=('batch', 'x', 'y')`.
- 714    To normalize each sample independently leave out the 'batch' axis.
- 715    Default: Scale all axes jointly."""
- 716
- 717    eps: Annotated[float, Interval(gt=0, le=0.1)] = 1e-6
- 718    """epsilon for numeric stability: `out = (tensor - mean) / (std + eps)`."""
- 719
+ 697    std: Annotated[
+ 698        Union[
+ 699            Annotated[float, Ge(1e-6)], NotEmpty[Tuple[Annotated[float, Ge(1e-6)], ...]]
+ 700        ],
+ 701        Field(examples=[1.05, (0.1, 0.2, 0.3)]),
+ 702    ]
+ 703    """The standard deviation value(s) to normalize with. Size must match `mean` values."""
+ 704
+ 705    axis: Annotated[Optional[NonBatchAxisId], Field(examples=["channel", "index"])] = (
+ 706        None  # todo: validate existence of axis
+ 707    )
+ 708    """The axis of the mean/std values to normalize each entry along that dimension separately.
+ 709    Invalid for scalar gains/offsets.
+ 710    """
+ 711
+ 712    @model_validator(mode="after")
+ 713    def mean_and_std_match(self) -> Self:
+ 714        mean_len = 1 if isinstance(self.mean, (float, int)) else len(self.mean)
+ 715        std_len = 1 if isinstance(self.std, (float, int)) else len(self.std)
+ 716        if mean_len != std_len:
+ 717            raise ValueError(
+ 718                "size of `mean` ({mean_len}) and `std` ({std_len}) must match."
+ 719            )
  720
- 721class ZeroMeanUnitVarianceDescr(ProcessingDescrBase):
- 722    """Subtract mean and divide by variance."""
+ 721        return self
+ 722
  723
- 724    id: Literal["zero_mean_unit_variance"] = "zero_mean_unit_variance"
- 725    kwargs: ZeroMeanUnitVarianceKwargs
+ 724class FixedZeroMeanUnitVarianceDescr(ProcessingDescrBase):
+ 725    """Subtract a given mean and divide by a given variance."""
  726
- 727
- 728class ScaleRangeKwargs(ProcessingKwargs):
- 729    axes: Annotated[
- 730        Optional[Sequence[AxisId]], Field(examples=[("batch", "x", "y")])
- 731    ] = None
- 732    """The subset of axes to normalize jointly, i.e. axes to reduce to compute the min/max percentile value.
- 733    For example to normalize 'batch', 'x' and 'y' jointly in a tensor ('batch', 'channel', 'y', 'x')
- 734    resulting in a tensor of equal shape normalized per channel, specify `axes=('batch', 'x', 'y')`.
- 735    To normalize samples indepdencently, leave out the "batch" axis.
- 736    Default: Scale all axes jointly."""
- 737
- 738    min_percentile: Annotated[float, Interval(ge=0, lt=100)] = 0.0
- 739    """The lower percentile used for normalization."""
+ 727    id: Literal["fixed_zero_mean_unit_variance"] = "fixed_zero_mean_unit_variance"
+ 728    kwargs: FixedZeroMeanUnitVarianceKwargs
+ 729
+ 730
+ 731class ZeroMeanUnitVarianceKwargs(ProcessingKwargs):
+ 732    axes: Annotated[
+ 733        Optional[Sequence[AxisId]], Field(examples=[("batch", "x", "y")])
+ 734    ] = None
+ 735    """The subset of axes to normalize jointly, i.e. axes to reduce to compute mean/std.
+ 736    For example to normalize 'batch', 'x' and 'y' jointly in a tensor ('batch', 'channel', 'y', 'x')
+ 737    resulting in a tensor of equal shape normalized per channel, specify `axes=('batch', 'x', 'y')`.
+ 738    To normalize each sample independently leave out the 'batch' axis.
+ 739    Default: Scale all axes jointly."""
  740
- 741    max_percentile: Annotated[float, Interval(gt=1, le=100)] = 100.0
- 742    """The upper percentile used for normalization
- 743    Has to be bigger than `min_percentile`.
- 744    The range is 1 to 100 instead of 0 to 100 to avoid mistakenly
- 745    accepting percentiles specified in the range 0.0 to 1.0."""
- 746
- 747    eps: Annotated[float, Interval(gt=0, le=0.1)] = 1e-6
- 748    """Epsilon for numeric stability.
- 749    `out = (tensor - v_lower) / (v_upper - v_lower + eps)`;
- 750    with `v_lower,v_upper` values at the respective percentiles."""
+ 741    eps: Annotated[float, Interval(gt=0, le=0.1)] = 1e-6
+ 742    """epsilon for numeric stability: `out = (tensor - mean) / (std + eps)`."""
+ 743
+ 744
+ 745class ZeroMeanUnitVarianceDescr(ProcessingDescrBase):
+ 746    """Subtract mean and divide by variance."""
+ 747
+ 748    id: Literal["zero_mean_unit_variance"] = "zero_mean_unit_variance"
+ 749    kwargs: ZeroMeanUnitVarianceKwargs
+ 750
  751
- 752    reference_tensor: Optional[TensorId] = None
- 753    """Tensor ID to compute the percentiles from. Default: The tensor itself.
- 754    For any tensor in `inputs` only input tensor references are allowed."""
- 755
- 756    @field_validator("max_percentile", mode="after")
- 757    @classmethod
- 758    def min_smaller_max(cls, value: float, info: ValidationInfo) -> float:
- 759        if (min_p := info.data["min_percentile"]) >= value:
- 760            raise ValueError(f"min_percentile {min_p} >= max_percentile {value}")
+ 752class ScaleRangeKwargs(ProcessingKwargs):
+ 753    axes: Annotated[
+ 754        Optional[Sequence[AxisId]], Field(examples=[("batch", "x", "y")])
+ 755    ] = None
+ 756    """The subset of axes to normalize jointly, i.e. axes to reduce to compute the min/max percentile value.
+ 757    For example to normalize 'batch', 'x' and 'y' jointly in a tensor ('batch', 'channel', 'y', 'x')
+ 758    resulting in a tensor of equal shape normalized per channel, specify `axes=('batch', 'x', 'y')`.
+ 759    To normalize samples indepdencently, leave out the "batch" axis.
+ 760    Default: Scale all axes jointly."""
  761
- 762        return value
- 763
+ 762    min_percentile: Annotated[float, Interval(ge=0, lt=100)] = 0.0
+ 763    """The lower percentile used for normalization."""
  764
- 765class ScaleRangeDescr(ProcessingDescrBase):
- 766    """Scale with percentiles."""
- 767
- 768    id: Literal["scale_range"] = "scale_range"
- 769    kwargs: ScaleRangeKwargs
+ 765    max_percentile: Annotated[float, Interval(gt=1, le=100)] = 100.0
+ 766    """The upper percentile used for normalization
+ 767    Has to be bigger than `min_percentile`.
+ 768    The range is 1 to 100 instead of 0 to 100 to avoid mistakenly
+ 769    accepting percentiles specified in the range 0.0 to 1.0."""
  770
- 771
- 772class ScaleMeanVarianceKwargs(ProcessingKwargs):
- 773    """Scale a tensor's data distribution to match another tensor's mean/std.
- 774    `out  = (tensor - mean) / (std + eps) * (ref_std + eps) + ref_mean.`"""
+ 771    eps: Annotated[float, Interval(gt=0, le=0.1)] = 1e-6
+ 772    """Epsilon for numeric stability.
+ 773    `out = (tensor - v_lower) / (v_upper - v_lower + eps)`;
+ 774    with `v_lower,v_upper` values at the respective percentiles."""
  775
- 776    reference_tensor: TensorId
- 777    """Name of tensor to match."""
- 778
- 779    axes: Annotated[
- 780        Optional[Sequence[AxisId]], Field(examples=[("batch", "x", "y")])
- 781    ] = None
- 782    """The subset of axes to normalize jointly, i.e. axes to reduce to compute mean/std.
- 783    For example to normalize 'batch', 'x' and 'y' jointly in a tensor ('batch', 'channel', 'y', 'x')
- 784    resulting in a tensor of equal shape normalized per channel, specify `axes=('batch', 'x', 'y')`.
- 785    To normalize samples independently, leave out the 'batch' axis.
- 786    Default: Scale all axes jointly."""
+ 776    reference_tensor: Optional[TensorId] = None
+ 777    """Tensor ID to compute the percentiles from. Default: The tensor itself.
+ 778    For any tensor in `inputs` only input tensor references are allowed."""
+ 779
+ 780    @field_validator("max_percentile", mode="after")
+ 781    @classmethod
+ 782    def min_smaller_max(cls, value: float, info: ValidationInfo) -> float:
+ 783        if (min_p := info.data["min_percentile"]) >= value:
+ 784            raise ValueError(f"min_percentile {min_p} >= max_percentile {value}")
+ 785
+ 786        return value
  787
- 788    eps: Annotated[float, Interval(gt=0, le=0.1)] = 1e-6
- 789    """Epsilon for numeric stability:
- 790    `out  = (tensor - mean) / (std + eps) * (ref_std + eps) + ref_mean.`"""
+ 788
+ 789class ScaleRangeDescr(ProcessingDescrBase):
+ 790    """Scale with percentiles."""
  791
- 792
- 793class ScaleMeanVarianceDescr(ProcessingDescrBase):
- 794    """Scale the tensor s.t. its mean and variance match a reference tensor."""
+ 792    id: Literal["scale_range"] = "scale_range"
+ 793    kwargs: ScaleRangeKwargs
+ 794
  795
- 796    id: Literal["scale_mean_variance"] = "scale_mean_variance"
- 797    kwargs: ScaleMeanVarianceKwargs
- 798
+ 796class ScaleMeanVarianceKwargs(ProcessingKwargs):
+ 797    """Scale a tensor's data distribution to match another tensor's mean/std.
+ 798    `out  = (tensor - mean) / (std + eps) * (ref_std + eps) + ref_mean.`"""
  799
- 800PreprocessingDescr = Annotated[
- 801    Union[
- 802        BinarizeDescr,
- 803        ClipDescr,
- 804        EnsureDtypeDescr,
- 805        ScaleLinearDescr,
- 806        SigmoidDescr,
- 807        FixedZeroMeanUnitVarianceDescr,
- 808        ZeroMeanUnitVarianceDescr,
- 809        ScaleRangeDescr,
- 810    ],
- 811    Field(discriminator="id"),
- 812]
- 813PostprocessingDescr = Annotated[
- 814    Union[
- 815        BinarizeDescr,
- 816        ClipDescr,
- 817        EnsureDtypeDescr,
- 818        ScaleLinearDescr,
- 819        SigmoidDescr,
- 820        FixedZeroMeanUnitVarianceDescr,
- 821        ZeroMeanUnitVarianceDescr,
- 822        ScaleRangeDescr,
- 823        ScaleMeanVarianceDescr,
- 824    ],
- 825    Field(discriminator="id"),
- 826]
- 827
- 828IO_AxisT = TypeVar("IO_AxisT", InputAxis, OutputAxis)
- 829
- 830
- 831class TensorDescrBase(Node, Generic[IO_AxisT]):
- 832    id: TensorId
- 833    """Tensor id. No duplicates are allowed."""
- 834
- 835    description: Annotated[str, MaxLen(128)] = ""
- 836    """free text description"""
- 837
- 838    axes: NotEmpty[Sequence[IO_AxisT]]
- 839    """tensor axes"""
- 840
- 841    @property
- 842    def shape(self):
- 843        return tuple(a.size for a in self.axes)
- 844
- 845    @field_validator("axes", mode="after", check_fields=False)
- 846    @classmethod
- 847    def _validate_axes(cls, axes: Sequence[AnyAxis]) -> Sequence[AnyAxis]:
- 848        seen_types: Set[str] = set()
- 849        duplicate_axes_types: Set[str] = set()
- 850        for a in axes:
- 851            if a.type in ("time", "space"):
- 852                continue  # duplicates allowed
+ 800    reference_tensor: TensorId
+ 801    """Name of tensor to match."""
+ 802
+ 803    axes: Annotated[
+ 804        Optional[Sequence[AxisId]], Field(examples=[("batch", "x", "y")])
+ 805    ] = None
+ 806    """The subset of axes to normalize jointly, i.e. axes to reduce to compute mean/std.
+ 807    For example to normalize 'batch', 'x' and 'y' jointly in a tensor ('batch', 'channel', 'y', 'x')
+ 808    resulting in a tensor of equal shape normalized per channel, specify `axes=('batch', 'x', 'y')`.
+ 809    To normalize samples independently, leave out the 'batch' axis.
+ 810    Default: Scale all axes jointly."""
+ 811
+ 812    eps: Annotated[float, Interval(gt=0, le=0.1)] = 1e-6
+ 813    """Epsilon for numeric stability:
+ 814    `out  = (tensor - mean) / (std + eps) * (ref_std + eps) + ref_mean.`"""
+ 815
+ 816
+ 817class ScaleMeanVarianceDescr(ProcessingDescrBase):
+ 818    """Scale the tensor s.t. its mean and variance match a reference tensor."""
+ 819
+ 820    id: Literal["scale_mean_variance"] = "scale_mean_variance"
+ 821    kwargs: ScaleMeanVarianceKwargs
+ 822
+ 823
+ 824PreprocessingDescr = Annotated[
+ 825    Union[
+ 826        BinarizeDescr,
+ 827        ClipDescr,
+ 828        EnsureDtypeDescr,
+ 829        ScaleLinearDescr,
+ 830        SigmoidDescr,
+ 831        FixedZeroMeanUnitVarianceDescr,
+ 832        ZeroMeanUnitVarianceDescr,
+ 833        ScaleRangeDescr,
+ 834    ],
+ 835    Field(discriminator="id"),
+ 836]
+ 837PostprocessingDescr = Annotated[
+ 838    Union[
+ 839        BinarizeDescr,
+ 840        ClipDescr,
+ 841        EnsureDtypeDescr,
+ 842        ScaleLinearDescr,
+ 843        SigmoidDescr,
+ 844        FixedZeroMeanUnitVarianceDescr,
+ 845        ZeroMeanUnitVarianceDescr,
+ 846        ScaleRangeDescr,
+ 847        ScaleMeanVarianceDescr,
+ 848    ],
+ 849    Field(discriminator="id"),
+ 850]
+ 851
+ 852IO_AxisT = TypeVar("IO_AxisT", InputAxis, OutputAxis)
  853
- 854            (duplicate_axes_types if a.type in seen_types else seen_types).add(a.type)
- 855
- 856        if duplicate_axes_types:
- 857            raise ValueError(f"Duplicate axis types: {duplicate_axes_types}")
+ 854
+ 855class TensorDescrBase(Node, Generic[IO_AxisT]):
+ 856    id: TensorId
+ 857    """Tensor id. No duplicates are allowed."""
  858
- 859        seen_ids: Set[AxisId] = set()
- 860        duplicate_axes_ids: Set[AxisId] = set()
- 861        for a in axes:
- 862            (duplicate_axes_ids if a.id in seen_ids else seen_ids).add(a.id)
- 863
- 864        if duplicate_axes_ids:
- 865            raise ValueError(f"Duplicate axis ids: {duplicate_axes_ids}")
- 866
- 867        return axes
+ 859    description: Annotated[str, MaxLen(128)] = ""
+ 860    """free text description"""
+ 861
+ 862    axes: NotEmpty[Sequence[IO_AxisT]]
+ 863    """tensor axes"""
+ 864
+ 865    @property
+ 866    def shape(self):
+ 867        return tuple(a.size for a in self.axes)
  868
- 869    test_tensor: FileDescr
- 870    """An example tensor to use for testing.
- 871    Using the model with the test input tensors is expected to yield the test output tensors.
- 872    Each test tensor has be a an ndarray in the
- 873    [numpy.lib file format](https://numpy.org/doc/stable/reference/generated/numpy.lib.format.html#module-numpy.lib.format).
- 874    The file extension must be '.npy'."""
- 875
- 876    sample_tensor: Optional[FileDescr] = None
- 877    """A sample tensor to illustrate a possible input/output for the model,
- 878    The sample image primarily serves to inform a human user about an example use case
- 879    and is typically stored as .hdf5, .png or .tiff.
- 880    It has to be readable by the [imageio library](https://imageio.readthedocs.io/en/stable/formats/index.html#supported-formats)
- 881    (numpy's `.npy` format is not supported).
- 882    The image dimensionality has to match the number of axes specified in this tensor description.
- 883    """
- 884
- 885    @model_validator(mode="after")
- 886    def _validate_sample_tensor(self) -> Self:
- 887        if (
- 888            self.sample_tensor is None
- 889            or not validation_context_var.get().perform_io_checks
- 890        ):
- 891            return self
+ 869    @field_validator("axes", mode="after", check_fields=False)
+ 870    @classmethod
+ 871    def _validate_axes(cls, axes: Sequence[AnyAxis]) -> Sequence[AnyAxis]:
+ 872        seen_types: Set[str] = set()
+ 873        duplicate_axes_types: Set[str] = set()
+ 874        for a in axes:
+ 875            if a.type in ("time", "space"):
+ 876                continue  # duplicates allowed
+ 877
+ 878            (duplicate_axes_types if a.type in seen_types else seen_types).add(a.type)
+ 879
+ 880        if duplicate_axes_types:
+ 881            raise ValueError(f"Duplicate axis types: {duplicate_axes_types}")
+ 882
+ 883        seen_ids: Set[AxisId] = set()
+ 884        duplicate_axes_ids: Set[AxisId] = set()
+ 885        for a in axes:
+ 886            (duplicate_axes_ids if a.id in seen_ids else seen_ids).add(a.id)
+ 887
+ 888        if duplicate_axes_ids:
+ 889            raise ValueError(f"Duplicate axis ids: {duplicate_axes_ids}")
+ 890
+ 891        return axes
  892
- 893        down = download(self.sample_tensor.source, sha256=self.sample_tensor.sha256)
- 894
- 895        local_source = down.path
- 896        tensor: NDArray[Any] = imread(
- 897            local_source, extension=PurePosixPath(down.original_file_name).suffix
- 898        )
- 899        n_dims = len(tensor.squeeze().shape)
- 900        n_dims_min = n_dims_max = len(self.axes)
- 901
- 902        for a in self.axes:
- 903            if isinstance(a, BatchAxis):
- 904                n_dims_min -= 1
- 905            elif isinstance(a.size, int):
- 906                if a.size == 1:
- 907                    n_dims_min -= 1
- 908            elif isinstance(a.size, ParameterizedSize):
- 909                if a.size.min == 1:
- 910                    n_dims_min -= 1
- 911            elif isinstance(a.size, SizeReference):
- 912                if a.size.offset < 2:
- 913                    # size reference may result in singleton axis
- 914                    n_dims_min -= 1
- 915            else:
- 916                assert_never(a.size)
- 917
- 918        n_dims_min = max(0, n_dims_min)
- 919        if n_dims < n_dims_min or n_dims > n_dims_max:
- 920            raise ValueError(
- 921                f"Expected sample tensor to have {n_dims_min} to"
- 922                + f" {n_dims_max} dimensions, but found {n_dims} (shape: {tensor.shape})."
- 923            )
- 924
- 925        return self
- 926
- 927    data: Union[TensorDataDescr, NotEmpty[Sequence[TensorDataDescr]]] = (
- 928        IntervalOrRatioDataDescr()
- 929    )
- 930    """Description of the tensor's data values, optionally per channel.
- 931    If specified per channel, the data `type` needs to match across channels."""
- 932
- 933    @property
- 934    def dtype(
- 935        self,
- 936    ) -> Literal[
- 937        "float32",
- 938        "float64",
- 939        "uint8",
- 940        "int8",
- 941        "uint16",
- 942        "int16",
- 943        "uint32",
- 944        "int32",
- 945        "uint64",
- 946        "int64",
- 947        "bool",
- 948    ]:
- 949        """dtype as specified under `data.type` or `data[i].type`"""
- 950        if isinstance(self.data, collections.abc.Sequence):
- 951            return self.data[0].type
- 952        else:
- 953            return self.data.type
- 954
- 955    @field_validator("data", mode="after")
- 956    @classmethod
- 957    def _check_data_type_across_channels(
- 958        cls, value: Union[TensorDataDescr, NotEmpty[Sequence[TensorDataDescr]]]
- 959    ) -> Union[TensorDataDescr, NotEmpty[Sequence[TensorDataDescr]]]:
- 960        if not isinstance(value, list):
- 961            return value
- 962
- 963        dtypes = {t.type for t in value}
- 964        if len(dtypes) > 1:
- 965            raise ValueError(
- 966                "Tensor data descriptions per channel need to agree in their data"
- 967                + f" `type`, but found {dtypes}."
- 968            )
- 969
- 970        return value
- 971
- 972    @model_validator(mode="after")
- 973    def _check_data_matches_channelaxis(self) -> Self:
- 974        if not isinstance(self.data, (list, tuple)):
- 975            return self
- 976
- 977        for a in self.axes:
- 978            if isinstance(a, ChannelAxis):
- 979                size = a.size
- 980                assert isinstance(size, int)
- 981                break
- 982        else:
- 983            return self
- 984
- 985        if len(self.data) != size:
- 986            raise ValueError(
- 987                f"Got tensor data descriptions for {len(self.data)} channels, but"
- 988                + f" '{a.id}' axis has size {size}."
- 989            )
- 990
- 991        return self
- 992
- 993    def get_axis_sizes_for_array(self, array: NDArray[Any]) -> Dict[AxisId, int]:
- 994        if len(array.shape) != len(self.axes):
- 995            raise ValueError(
- 996                f"Dimension mismatch: array shape {array.shape} (#{len(array.shape)})"
- 997                + f" incompatible with {len(self.axes)} axes."
- 998            )
- 999        return {a.id: array.shape[i] for i, a in enumerate(self.axes)}
+ 893    test_tensor: FileDescr
+ 894    """An example tensor to use for testing.
+ 895    Using the model with the test input tensors is expected to yield the test output tensors.
+ 896    Each test tensor has be a an ndarray in the
+ 897    [numpy.lib file format](https://numpy.org/doc/stable/reference/generated/numpy.lib.format.html#module-numpy.lib.format).
+ 898    The file extension must be '.npy'."""
+ 899
+ 900    sample_tensor: Optional[FileDescr] = None
+ 901    """A sample tensor to illustrate a possible input/output for the model,
+ 902    The sample image primarily serves to inform a human user about an example use case
+ 903    and is typically stored as .hdf5, .png or .tiff.
+ 904    It has to be readable by the [imageio library](https://imageio.readthedocs.io/en/stable/formats/index.html#supported-formats)
+ 905    (numpy's `.npy` format is not supported).
+ 906    The image dimensionality has to match the number of axes specified in this tensor description.
+ 907    """
+ 908
+ 909    @model_validator(mode="after")
+ 910    def _validate_sample_tensor(self) -> Self:
+ 911        if (
+ 912            self.sample_tensor is None
+ 913            or not validation_context_var.get().perform_io_checks
+ 914        ):
+ 915            return self
+ 916
+ 917        down = download(self.sample_tensor.source, sha256=self.sample_tensor.sha256)
+ 918
+ 919        local_source = down.path
+ 920        tensor: NDArray[Any] = imread(
+ 921            local_source, extension=PurePosixPath(down.original_file_name).suffix
+ 922        )
+ 923        n_dims = len(tensor.squeeze().shape)
+ 924        n_dims_min = n_dims_max = len(self.axes)
+ 925
+ 926        for a in self.axes:
+ 927            if isinstance(a, BatchAxis):
+ 928                n_dims_min -= 1
+ 929            elif isinstance(a.size, int):
+ 930                if a.size == 1:
+ 931                    n_dims_min -= 1
+ 932            elif isinstance(a.size, ParameterizedSize):
+ 933                if a.size.min == 1:
+ 934                    n_dims_min -= 1
+ 935            elif isinstance(a.size, SizeReference):
+ 936                if a.size.offset < 2:
+ 937                    # size reference may result in singleton axis
+ 938                    n_dims_min -= 1
+ 939            else:
+ 940                assert_never(a.size)
+ 941
+ 942        n_dims_min = max(0, n_dims_min)
+ 943        if n_dims < n_dims_min or n_dims > n_dims_max:
+ 944            raise ValueError(
+ 945                f"Expected sample tensor to have {n_dims_min} to"
+ 946                + f" {n_dims_max} dimensions, but found {n_dims} (shape: {tensor.shape})."
+ 947            )
+ 948
+ 949        return self
+ 950
+ 951    data: Union[TensorDataDescr, NotEmpty[Sequence[TensorDataDescr]]] = (
+ 952        IntervalOrRatioDataDescr()
+ 953    )
+ 954    """Description of the tensor's data values, optionally per channel.
+ 955    If specified per channel, the data `type` needs to match across channels."""
+ 956
+ 957    @property
+ 958    def dtype(
+ 959        self,
+ 960    ) -> Literal[
+ 961        "float32",
+ 962        "float64",
+ 963        "uint8",
+ 964        "int8",
+ 965        "uint16",
+ 966        "int16",
+ 967        "uint32",
+ 968        "int32",
+ 969        "uint64",
+ 970        "int64",
+ 971        "bool",
+ 972    ]:
+ 973        """dtype as specified under `data.type` or `data[i].type`"""
+ 974        if isinstance(self.data, collections.abc.Sequence):
+ 975            return self.data[0].type
+ 976        else:
+ 977            return self.data.type
+ 978
+ 979    @field_validator("data", mode="after")
+ 980    @classmethod
+ 981    def _check_data_type_across_channels(
+ 982        cls, value: Union[TensorDataDescr, NotEmpty[Sequence[TensorDataDescr]]]
+ 983    ) -> Union[TensorDataDescr, NotEmpty[Sequence[TensorDataDescr]]]:
+ 984        if not isinstance(value, list):
+ 985            return value
+ 986
+ 987        dtypes = {t.type for t in value}
+ 988        if len(dtypes) > 1:
+ 989            raise ValueError(
+ 990                "Tensor data descriptions per channel need to agree in their data"
+ 991                + f" `type`, but found {dtypes}."
+ 992            )
+ 993
+ 994        return value
+ 995
+ 996    @model_validator(mode="after")
+ 997    def _check_data_matches_channelaxis(self) -> Self:
+ 998        if not isinstance(self.data, (list, tuple)):
+ 999            return self
 1000
-1001
-1002class InputTensorDescr(TensorDescrBase[InputAxis]):
-1003    id: TensorId = TensorId("input")
-1004    """Input tensor id.
-1005    No duplicates are allowed across all inputs and outputs."""
-1006
-1007    preprocessing: List[PreprocessingDescr] = Field(default_factory=list)
-1008    """Description of how this input should be preprocessed."""
-1009
-1010    @model_validator(mode="after")
-1011    def _validate_preprocessing_kwargs(self) -> Self:
-1012        axes_ids = [a.id for a in self.axes]
-1013        for p in self.preprocessing:
-1014            kwargs_axes: Union[Any, Sequence[Any]] = p.kwargs.get("axes", ())
-1015            if not isinstance(kwargs_axes, collections.abc.Sequence):
-1016                raise ValueError(
-1017                    f"Expeted `axes` to be a sequence, but got {type(kwargs_axes)}"
-1018                )
-1019
-1020            if any(a not in axes_ids for a in kwargs_axes):
-1021                raise ValueError("`kwargs.axes` needs to be subset of axes ids")
-1022
-1023        return self
+1001        for a in self.axes:
+1002            if isinstance(a, ChannelAxis):
+1003                size = a.size
+1004                assert isinstance(size, int)
+1005                break
+1006        else:
+1007            return self
+1008
+1009        if len(self.data) != size:
+1010            raise ValueError(
+1011                f"Got tensor data descriptions for {len(self.data)} channels, but"
+1012                + f" '{a.id}' axis has size {size}."
+1013            )
+1014
+1015        return self
+1016
+1017    def get_axis_sizes_for_array(self, array: NDArray[Any]) -> Dict[AxisId, int]:
+1018        if len(array.shape) != len(self.axes):
+1019            raise ValueError(
+1020                f"Dimension mismatch: array shape {array.shape} (#{len(array.shape)})"
+1021                + f" incompatible with {len(self.axes)} axes."
+1022            )
+1023        return {a.id: array.shape[i] for i, a in enumerate(self.axes)}
 1024
 1025
-1026def convert_axes(
-1027    axes: str,
-1028    *,
-1029    shape: Union[
-1030        Sequence[int], _ParameterizedInputShape_v0_4, _ImplicitOutputShape_v0_4
-1031    ],
-1032    tensor_type: Literal["input", "output"],
-1033    halo: Optional[Sequence[int]],
-1034    size_refs: Mapping[_TensorName_v0_4, Mapping[str, int]],
-1035):
-1036    ret: List[AnyAxis] = []
-1037    for i, a in enumerate(axes):
-1038        axis_type = _AXIS_TYPE_MAP.get(a, a)
-1039        if axis_type == "batch":
-1040            ret.append(BatchAxis())
-1041            continue
-1042
-1043        scale = 1.0
-1044        if isinstance(shape, _ParameterizedInputShape_v0_4):
-1045            if shape.step[i] == 0:
-1046                size = shape.min[i]
-1047            else:
-1048                size = ParameterizedSize(min=shape.min[i], step=shape.step[i])
-1049        elif isinstance(shape, _ImplicitOutputShape_v0_4):
-1050            ref_t = str(shape.reference_tensor)
-1051            if ref_t.count(".") == 1:
-1052                t_id, orig_a_id = ref_t.split(".")
-1053            else:
-1054                t_id = ref_t
-1055                orig_a_id = a
-1056
-1057            a_id = _AXIS_ID_MAP.get(orig_a_id, a)
-1058            if not (orig_scale := shape.scale[i]):
-1059                # old way to insert a new axis dimension
-1060                size = int(2 * shape.offset[i])
-1061            else:
-1062                scale = 1 / orig_scale
-1063                if axis_type in ("channel", "index"):
-1064                    # these axes no longer have a scale
-1065                    offset_from_scale = orig_scale * size_refs.get(
-1066                        _TensorName_v0_4(t_id), {}
-1067                    ).get(orig_a_id, 0)
-1068                else:
-1069                    offset_from_scale = 0
-1070                size = SizeReference(
-1071                    tensor_id=TensorId(t_id),
-1072                    axis_id=AxisId(a_id),
-1073                    offset=int(offset_from_scale + 2 * shape.offset[i]),
-1074                )
-1075        elif isinstance(shape, collections.abc.Sequence):
-1076            size: Any = shape[i]
-1077            assert isinstance(size, int)
-1078        else:
-1079            assert_never(shape)
+1026class InputTensorDescr(TensorDescrBase[InputAxis]):
+1027    id: TensorId = TensorId("input")
+1028    """Input tensor id.
+1029    No duplicates are allowed across all inputs and outputs."""
+1030
+1031    preprocessing: List[PreprocessingDescr] = Field(default_factory=list)
+1032    """Description of how this input should be preprocessed."""
+1033
+1034    @model_validator(mode="after")
+1035    def _validate_preprocessing_kwargs(self) -> Self:
+1036        axes_ids = [a.id for a in self.axes]
+1037        for p in self.preprocessing:
+1038            kwargs_axes: Union[Any, Sequence[Any]] = p.kwargs.get("axes", ())
+1039            if not isinstance(kwargs_axes, collections.abc.Sequence):
+1040                raise ValueError(
+1041                    f"Expeted `axes` to be a sequence, but got {type(kwargs_axes)}"
+1042                )
+1043
+1044            if any(a not in axes_ids for a in kwargs_axes):
+1045                raise ValueError("`kwargs.axes` needs to be subset of axes ids")
+1046
+1047        return self
+1048
+1049
+1050def convert_axes(
+1051    axes: str,
+1052    *,
+1053    shape: Union[
+1054        Sequence[int], _ParameterizedInputShape_v0_4, _ImplicitOutputShape_v0_4
+1055    ],
+1056    tensor_type: Literal["input", "output"],
+1057    halo: Optional[Sequence[int]],
+1058    size_refs: Mapping[_TensorName_v0_4, Mapping[str, int]],
+1059):
+1060    ret: List[AnyAxis] = []
+1061    for i, a in enumerate(axes):
+1062        axis_type = _AXIS_TYPE_MAP.get(a, a)
+1063        if axis_type == "batch":
+1064            ret.append(BatchAxis())
+1065            continue
+1066
+1067        scale = 1.0
+1068        if isinstance(shape, _ParameterizedInputShape_v0_4):
+1069            if shape.step[i] == 0:
+1070                size = shape.min[i]
+1071            else:
+1072                size = ParameterizedSize(min=shape.min[i], step=shape.step[i])
+1073        elif isinstance(shape, _ImplicitOutputShape_v0_4):
+1074            ref_t = str(shape.reference_tensor)
+1075            if ref_t.count(".") == 1:
+1076                t_id, orig_a_id = ref_t.split(".")
+1077            else:
+1078                t_id = ref_t
+1079                orig_a_id = a
 1080
-1081        if axis_type == "time":
-1082            if tensor_type == "input":
-1083                ret.append(TimeInputAxis(size=size, scale=scale))
-1084            else:
-1085                ret.append(
-1086                    TimeOutputAxis(
-1087                        size=size, scale=scale, halo=0 if halo is None else halo[i]
-1088                    )
-1089                )
-1090        elif axis_type == "index":
-1091            ret.append(IndexAxis(size=size))
-1092        elif axis_type == "channel":
-1093            assert not isinstance(size, ParameterizedSize)
-1094            if isinstance(size, SizeReference):
-1095                warnings.warn(
-1096                    "Conversion of channel size from an implicit output shape may by"
-1097                    + " wrong"
+1081            a_id = _AXIS_ID_MAP.get(orig_a_id, a)
+1082            if not (orig_scale := shape.scale[i]):
+1083                # old way to insert a new axis dimension
+1084                size = int(2 * shape.offset[i])
+1085            else:
+1086                scale = 1 / orig_scale
+1087                if axis_type in ("channel", "index"):
+1088                    # these axes no longer have a scale
+1089                    offset_from_scale = orig_scale * size_refs.get(
+1090                        _TensorName_v0_4(t_id), {}
+1091                    ).get(orig_a_id, 0)
+1092                else:
+1093                    offset_from_scale = 0
+1094                size = SizeReference(
+1095                    tensor_id=TensorId(t_id),
+1096                    axis_id=AxisId(a_id),
+1097                    offset=int(offset_from_scale + 2 * shape.offset[i]),
 1098                )
-1099                ret.append(
-1100                    ChannelAxis(
-1101                        channel_names=[
-1102                            Identifier(f"channel{i}") for i in range(size.offset)
-1103                        ]
-1104                    )
-1105                )
-1106            else:
-1107                ret.append(
-1108                    ChannelAxis(
-1109                        channel_names=[Identifier(f"channel{i}") for i in range(size)]
-1110                    )
-1111                )
-1112        elif axis_type == "space":
-1113            if tensor_type == "input":
-1114                ret.append(SpaceInputAxis(id=AxisId(a), size=size, scale=scale))
-1115            else:
-1116                ret.append(SpaceOutputAxis(id=AxisId(a), size=size, scale=scale))
-1117
-1118    return ret
-1119
-1120
-1121_AXIS_TYPE_MAP = {
-1122    "b": "batch",
-1123    "t": "time",
-1124    "i": "index",
-1125    "c": "channel",
-1126    "x": "space",
-1127    "y": "space",
-1128    "z": "space",
-1129}
-1130
-1131_AXIS_ID_MAP = {
-1132    "b": "batch",
-1133    "t": "time",
-1134    "i": "index",
-1135    "c": "channel",
-1136}
-1137
-1138
-1139def _axes_letters_to_ids(
-1140    axes: Optional[str],
-1141) -> Optional[List[AxisId]]:
-1142    if axes is None:
-1143        return None
-1144    return [AxisId(_AXIS_ID_MAP.get(a, a)) for a in map(str, axes)]
-1145
-1146
-1147def _get_complement_v04_axis(
-1148    tensor_axes: Sequence[str], axes: Optional[Sequence[str]]
-1149) -> Optional[AxisId]:
-1150    if axes is None:
-1151        return None
-1152
-1153    axes_str = str(axes)
-1154    all_axes = set(str(tensor_axes)) | {"b"}
-1155    complement_axes = [a for a in axes_str if a not in all_axes]
-1156    if len(complement_axes) > 1:
-1157        raise ValueError(
-1158            f"Expected none or a single complement axis, but axes '{axes}' "
-1159            + f"for tensor dims '{all_axes}' leave '{complement_axes}'."
-1160        )
+1099        elif isinstance(shape, collections.abc.Sequence):
+1100            size: Any = shape[i]
+1101            assert isinstance(size, int)
+1102        else:
+1103            assert_never(shape)
+1104
+1105        if axis_type == "time":
+1106            if tensor_type == "input":
+1107                ret.append(TimeInputAxis(size=size, scale=scale))
+1108            else:
+1109                ret.append(
+1110                    TimeOutputAxis(
+1111                        size=size, scale=scale, halo=0 if halo is None else halo[i]
+1112                    )
+1113                )
+1114        elif axis_type == "index":
+1115            ret.append(IndexAxis(size=size))
+1116        elif axis_type == "channel":
+1117            assert not isinstance(size, ParameterizedSize)
+1118            if isinstance(size, SizeReference):
+1119                warnings.warn(
+1120                    "Conversion of channel size from an implicit output shape may by"
+1121                    + " wrong"
+1122                )
+1123                ret.append(
+1124                    ChannelAxis(
+1125                        channel_names=[
+1126                            Identifier(f"channel{i}") for i in range(size.offset)
+1127                        ]
+1128                    )
+1129                )
+1130            else:
+1131                ret.append(
+1132                    ChannelAxis(
+1133                        channel_names=[Identifier(f"channel{i}") for i in range(size)]
+1134                    )
+1135                )
+1136        elif axis_type == "space":
+1137            if tensor_type == "input":
+1138                ret.append(SpaceInputAxis(id=AxisId(a), size=size, scale=scale))
+1139            else:
+1140                ret.append(SpaceOutputAxis(id=AxisId(a), size=size, scale=scale))
+1141
+1142    return ret
+1143
+1144
+1145_AXIS_TYPE_MAP = {
+1146    "b": "batch",
+1147    "t": "time",
+1148    "i": "index",
+1149    "c": "channel",
+1150    "x": "space",
+1151    "y": "space",
+1152    "z": "space",
+1153}
+1154
+1155_AXIS_ID_MAP = {
+1156    "b": "batch",
+1157    "t": "time",
+1158    "i": "index",
+1159    "c": "channel",
+1160}
 1161
-1162    return None if not complement_axes else AxisId(complement_axes[0])
-1163
-1164
-1165def _convert_proc(
-1166    p: Union[_PreprocessingDescr_v0_4, _PostprocessingDescr_v0_4],
-1167    tensor_axes: Sequence[str],
-1168) -> Union[PreprocessingDescr, PostprocessingDescr]:
-1169    if isinstance(p, _BinarizeDescr_v0_4):
-1170        return BinarizeDescr(kwargs=BinarizeKwargs(threshold=p.kwargs.threshold))
-1171    elif isinstance(p, _ClipDescr_v0_4):
-1172        return ClipDescr(kwargs=ClipKwargs(min=p.kwargs.min, max=p.kwargs.max))
-1173    elif isinstance(p, _SigmoidDescr_v0_4):
-1174        return SigmoidDescr()
-1175    elif isinstance(p, _ScaleLinearDescr_v0_4):
-1176        axes = _axes_letters_to_ids(p.kwargs.axes)
-1177        if p.kwargs.axes is None:
-1178            axis = None
-1179        else:
-1180            axis = _get_complement_v04_axis(tensor_axes, p.kwargs.axes)
-1181
-1182        return ScaleLinearDescr(
-1183            kwargs=ScaleLinearKwargs(
-1184                axis=axis, gain=p.kwargs.gain, offset=p.kwargs.offset
-1185            )
-1186        )
-1187    elif isinstance(p, _ScaleMeanVarianceDescr_v0_4):
-1188        return ScaleMeanVarianceDescr(
-1189            kwargs=ScaleMeanVarianceKwargs(
-1190                axes=_axes_letters_to_ids(p.kwargs.axes),
-1191                reference_tensor=TensorId(str(p.kwargs.reference_tensor)),
-1192                eps=p.kwargs.eps,
-1193            )
-1194        )
-1195    elif isinstance(p, _ZeroMeanUnitVarianceDescr_v0_4):
-1196        if p.kwargs.mode == "fixed":
-1197            mean = p.kwargs.mean
-1198            assert mean is not None
-1199            if isinstance(mean, list):
-1200                mean = tuple(mean)
-1201
-1202            std = p.kwargs.std
-1203            assert std is not None
-1204            if isinstance(std, list):
-1205                std = tuple(std)
-1206
-1207            return FixedZeroMeanUnitVarianceDescr(
-1208                kwargs=FixedZeroMeanUnitVarianceKwargs(mean=mean, std=std)
+1162
+1163def _axes_letters_to_ids(
+1164    axes: Optional[str],
+1165) -> Optional[List[AxisId]]:
+1166    if axes is None:
+1167        return None
+1168    return [AxisId(_AXIS_ID_MAP.get(a, a)) for a in map(str, axes)]
+1169
+1170
+1171def _get_complement_v04_axis(
+1172    tensor_axes: Sequence[str], axes: Optional[Sequence[str]]
+1173) -> Optional[AxisId]:
+1174    if axes is None:
+1175        return None
+1176
+1177    axes_str = str(axes)
+1178    all_axes = set(str(tensor_axes)) | {"b"}
+1179    complement_axes = [a for a in axes_str if a not in all_axes]
+1180    if len(complement_axes) > 1:
+1181        raise ValueError(
+1182            f"Expected none or a single complement axis, but axes '{axes}' "
+1183            + f"for tensor dims '{all_axes}' leave '{complement_axes}'."
+1184        )
+1185
+1186    return None if not complement_axes else AxisId(complement_axes[0])
+1187
+1188
+1189def _convert_proc(
+1190    p: Union[_PreprocessingDescr_v0_4, _PostprocessingDescr_v0_4],
+1191    tensor_axes: Sequence[str],
+1192) -> Union[PreprocessingDescr, PostprocessingDescr]:
+1193    if isinstance(p, _BinarizeDescr_v0_4):
+1194        return BinarizeDescr(kwargs=BinarizeKwargs(threshold=p.kwargs.threshold))
+1195    elif isinstance(p, _ClipDescr_v0_4):
+1196        return ClipDescr(kwargs=ClipKwargs(min=p.kwargs.min, max=p.kwargs.max))
+1197    elif isinstance(p, _SigmoidDescr_v0_4):
+1198        return SigmoidDescr()
+1199    elif isinstance(p, _ScaleLinearDescr_v0_4):
+1200        axes = _axes_letters_to_ids(p.kwargs.axes)
+1201        if p.kwargs.axes is None:
+1202            axis = None
+1203        else:
+1204            axis = _get_complement_v04_axis(tensor_axes, p.kwargs.axes)
+1205
+1206        return ScaleLinearDescr(
+1207            kwargs=ScaleLinearKwargs(
+1208                axis=axis, gain=p.kwargs.gain, offset=p.kwargs.offset
 1209            )
-1210        else:
-1211            axes = _axes_letters_to_ids(p.kwargs.axes) or []
-1212            if p.kwargs.mode == "per_dataset":
-1213                axes = [AxisId("batch")] + axes
-1214            if not axes:
-1215                axes = None
-1216            return ZeroMeanUnitVarianceDescr(
-1217                kwargs=ZeroMeanUnitVarianceKwargs(axes=axes, eps=p.kwargs.eps)
-1218            )
-1219
-1220    elif isinstance(p, _ScaleRangeDescr_v0_4):
-1221        return ScaleRangeDescr(
-1222            kwargs=ScaleRangeKwargs(
-1223                axes=_axes_letters_to_ids(p.kwargs.axes),
-1224                min_percentile=p.kwargs.min_percentile,
-1225                max_percentile=p.kwargs.max_percentile,
-1226                eps=p.kwargs.eps,
-1227            )
-1228        )
-1229    else:
-1230        assert_never(p)
-1231
-1232
-1233class _InputTensorConv(
-1234    Converter[
-1235        _InputTensorDescr_v0_4,
-1236        InputTensorDescr,
-1237        ImportantFileSource,
-1238        Optional[ImportantFileSource],
-1239        Mapping[_TensorName_v0_4, Mapping[str, int]],
-1240    ]
-1241):
-1242    def _convert(
-1243        self,
-1244        src: _InputTensorDescr_v0_4,
-1245        tgt: "type[InputTensorDescr] | type[dict[str, Any]]",
-1246        test_tensor: ImportantFileSource,
-1247        sample_tensor: Optional[ImportantFileSource],
-1248        size_refs: Mapping[_TensorName_v0_4, Mapping[str, int]],
-1249    ) -> "InputTensorDescr | dict[str, Any]":
-1250        axes: List[InputAxis] = convert_axes(  # pyright: ignore[reportAssignmentType]
-1251            src.axes,
-1252            shape=src.shape,
-1253            tensor_type="input",
-1254            halo=None,
-1255            size_refs=size_refs,
-1256        )
-1257        prep: List[PreprocessingDescr] = []
-1258        for p in src.preprocessing:
-1259            cp = _convert_proc(p, src.axes)
-1260            assert not isinstance(cp, ScaleMeanVarianceDescr)
-1261            prep.append(cp)
-1262
-1263        return tgt(
-1264            axes=axes,
-1265            id=TensorId(str(src.name)),
-1266            test_tensor=FileDescr(source=test_tensor),
-1267            sample_tensor=(
-1268                None if sample_tensor is None else FileDescr(source=sample_tensor)
-1269            ),
-1270            data=dict(type=src.data_type),  # pyright: ignore[reportArgumentType]
-1271            preprocessing=prep,
-1272        )
-1273
-1274
-1275_input_tensor_conv = _InputTensorConv(_InputTensorDescr_v0_4, InputTensorDescr)
-1276
-1277
-1278class OutputTensorDescr(TensorDescrBase[OutputAxis]):
-1279    id: TensorId = TensorId("output")
-1280    """Output tensor id.
-1281    No duplicates are allowed across all inputs and outputs."""
-1282
-1283    postprocessing: List[PostprocessingDescr] = Field(default_factory=list)
-1284    """Description of how this output should be postprocessed."""
-1285
-1286    @model_validator(mode="after")
-1287    def _validate_postprocessing_kwargs(self) -> Self:
-1288        axes_ids = [a.id for a in self.axes]
-1289        for p in self.postprocessing:
-1290            kwargs_axes: Union[Any, Sequence[Any]] = p.kwargs.get("axes", ())
-1291            if not isinstance(kwargs_axes, collections.abc.Sequence):
-1292                raise ValueError(
-1293                    f"expected `axes` sequence, but got {type(kwargs_axes)}"
-1294                )
-1295
-1296            if any(a not in axes_ids for a in kwargs_axes):
-1297                raise ValueError("`kwargs.axes` needs to be subset of axes ids")
+1210        )
+1211    elif isinstance(p, _ScaleMeanVarianceDescr_v0_4):
+1212        return ScaleMeanVarianceDescr(
+1213            kwargs=ScaleMeanVarianceKwargs(
+1214                axes=_axes_letters_to_ids(p.kwargs.axes),
+1215                reference_tensor=TensorId(str(p.kwargs.reference_tensor)),
+1216                eps=p.kwargs.eps,
+1217            )
+1218        )
+1219    elif isinstance(p, _ZeroMeanUnitVarianceDescr_v0_4):
+1220        if p.kwargs.mode == "fixed":
+1221            mean = p.kwargs.mean
+1222            assert mean is not None
+1223            if isinstance(mean, list):
+1224                mean = tuple(mean)
+1225
+1226            std = p.kwargs.std
+1227            assert std is not None
+1228            if isinstance(std, list):
+1229                std = tuple(std)
+1230
+1231            return FixedZeroMeanUnitVarianceDescr(
+1232                kwargs=FixedZeroMeanUnitVarianceKwargs(mean=mean, std=std)
+1233            )
+1234        else:
+1235            axes = _axes_letters_to_ids(p.kwargs.axes) or []
+1236            if p.kwargs.mode == "per_dataset":
+1237                axes = [AxisId("batch")] + axes
+1238            if not axes:
+1239                axes = None
+1240            return ZeroMeanUnitVarianceDescr(
+1241                kwargs=ZeroMeanUnitVarianceKwargs(axes=axes, eps=p.kwargs.eps)
+1242            )
+1243
+1244    elif isinstance(p, _ScaleRangeDescr_v0_4):
+1245        return ScaleRangeDescr(
+1246            kwargs=ScaleRangeKwargs(
+1247                axes=_axes_letters_to_ids(p.kwargs.axes),
+1248                min_percentile=p.kwargs.min_percentile,
+1249                max_percentile=p.kwargs.max_percentile,
+1250                eps=p.kwargs.eps,
+1251            )
+1252        )
+1253    else:
+1254        assert_never(p)
+1255
+1256
+1257class _InputTensorConv(
+1258    Converter[
+1259        _InputTensorDescr_v0_4,
+1260        InputTensorDescr,
+1261        ImportantFileSource,
+1262        Optional[ImportantFileSource],
+1263        Mapping[_TensorName_v0_4, Mapping[str, int]],
+1264    ]
+1265):
+1266    def _convert(
+1267        self,
+1268        src: _InputTensorDescr_v0_4,
+1269        tgt: "type[InputTensorDescr] | type[dict[str, Any]]",
+1270        test_tensor: ImportantFileSource,
+1271        sample_tensor: Optional[ImportantFileSource],
+1272        size_refs: Mapping[_TensorName_v0_4, Mapping[str, int]],
+1273    ) -> "InputTensorDescr | dict[str, Any]":
+1274        axes: List[InputAxis] = convert_axes(  # pyright: ignore[reportAssignmentType]
+1275            src.axes,
+1276            shape=src.shape,
+1277            tensor_type="input",
+1278            halo=None,
+1279            size_refs=size_refs,
+1280        )
+1281        prep: List[PreprocessingDescr] = []
+1282        for p in src.preprocessing:
+1283            cp = _convert_proc(p, src.axes)
+1284            assert not isinstance(cp, ScaleMeanVarianceDescr)
+1285            prep.append(cp)
+1286
+1287        return tgt(
+1288            axes=axes,
+1289            id=TensorId(str(src.name)),
+1290            test_tensor=FileDescr(source=test_tensor),
+1291            sample_tensor=(
+1292                None if sample_tensor is None else FileDescr(source=sample_tensor)
+1293            ),
+1294            data=dict(type=src.data_type),  # pyright: ignore[reportArgumentType]
+1295            preprocessing=prep,
+1296        )
+1297
 1298
-1299        return self
+1299_input_tensor_conv = _InputTensorConv(_InputTensorDescr_v0_4, InputTensorDescr)
 1300
 1301
-1302class _OutputTensorConv(
-1303    Converter[
-1304        _OutputTensorDescr_v0_4,
-1305        OutputTensorDescr,
-1306        ImportantFileSource,
-1307        Optional[ImportantFileSource],
-1308        Mapping[_TensorName_v0_4, Mapping[str, int]],
-1309    ]
-1310):
-1311    def _convert(
-1312        self,
-1313        src: _OutputTensorDescr_v0_4,
-1314        tgt: "type[OutputTensorDescr] | type[dict[str, Any]]",
-1315        test_tensor: ImportantFileSource,
-1316        sample_tensor: Optional[ImportantFileSource],
-1317        size_refs: Mapping[_TensorName_v0_4, Mapping[str, int]],
-1318    ) -> "OutputTensorDescr | dict[str, Any]":
-1319        # TODO: split convert_axes into convert_output_axes and convert_input_axes
-1320        axes: List[OutputAxis] = convert_axes(  # pyright: ignore[reportAssignmentType]
-1321            src.axes,
-1322            shape=src.shape,
-1323            tensor_type="output",
-1324            halo=src.halo,
-1325            size_refs=size_refs,
-1326        )
-1327        data_descr: Dict[str, Any] = dict(type=src.data_type)
-1328        if data_descr["type"] == "bool":
-1329            data_descr["values"] = [False, True]
-1330
-1331        return tgt(
-1332            axes=axes,
-1333            id=TensorId(str(src.name)),
-1334            test_tensor=FileDescr(source=test_tensor),
-1335            sample_tensor=(
-1336                None if sample_tensor is None else FileDescr(source=sample_tensor)
-1337            ),
-1338            data=data_descr,  # pyright: ignore[reportArgumentType]
-1339            postprocessing=[_convert_proc(p, src.axes) for p in src.postprocessing],
-1340        )
-1341
-1342
-1343_output_tensor_conv = _OutputTensorConv(_OutputTensorDescr_v0_4, OutputTensorDescr)
-1344
-1345
-1346TensorDescr = Union[InputTensorDescr, OutputTensorDescr]
-1347
-1348
-1349def validate_tensors(
-1350    tensors: Mapping[TensorId, Tuple[TensorDescr, NDArray[Any]]],
-1351    tensor_origin: str,  # for more precise error messages, e.g. 'test_tensor'
-1352):
-1353    all_tensor_axes: Dict[TensorId, Dict[AxisId, Tuple[AnyAxis, int]]] = {}
+1302class OutputTensorDescr(TensorDescrBase[OutputAxis]):
+1303    id: TensorId = TensorId("output")
+1304    """Output tensor id.
+1305    No duplicates are allowed across all inputs and outputs."""
+1306
+1307    postprocessing: List[PostprocessingDescr] = Field(default_factory=list)
+1308    """Description of how this output should be postprocessed."""
+1309
+1310    @model_validator(mode="after")
+1311    def _validate_postprocessing_kwargs(self) -> Self:
+1312        axes_ids = [a.id for a in self.axes]
+1313        for p in self.postprocessing:
+1314            kwargs_axes: Union[Any, Sequence[Any]] = p.kwargs.get("axes", ())
+1315            if not isinstance(kwargs_axes, collections.abc.Sequence):
+1316                raise ValueError(
+1317                    f"expected `axes` sequence, but got {type(kwargs_axes)}"
+1318                )
+1319
+1320            if any(a not in axes_ids for a in kwargs_axes):
+1321                raise ValueError("`kwargs.axes` needs to be subset of axes ids")
+1322
+1323        return self
+1324
+1325
+1326class _OutputTensorConv(
+1327    Converter[
+1328        _OutputTensorDescr_v0_4,
+1329        OutputTensorDescr,
+1330        ImportantFileSource,
+1331        Optional[ImportantFileSource],
+1332        Mapping[_TensorName_v0_4, Mapping[str, int]],
+1333    ]
+1334):
+1335    def _convert(
+1336        self,
+1337        src: _OutputTensorDescr_v0_4,
+1338        tgt: "type[OutputTensorDescr] | type[dict[str, Any]]",
+1339        test_tensor: ImportantFileSource,
+1340        sample_tensor: Optional[ImportantFileSource],
+1341        size_refs: Mapping[_TensorName_v0_4, Mapping[str, int]],
+1342    ) -> "OutputTensorDescr | dict[str, Any]":
+1343        # TODO: split convert_axes into convert_output_axes and convert_input_axes
+1344        axes: List[OutputAxis] = convert_axes(  # pyright: ignore[reportAssignmentType]
+1345            src.axes,
+1346            shape=src.shape,
+1347            tensor_type="output",
+1348            halo=src.halo,
+1349            size_refs=size_refs,
+1350        )
+1351        data_descr: Dict[str, Any] = dict(type=src.data_type)
+1352        if data_descr["type"] == "bool":
+1353            data_descr["values"] = [False, True]
 1354
-1355    def e_msg(d: TensorDescr):
-1356        return f"{'inputs' if isinstance(d, InputTensorDescr) else 'outputs'}[{d.id}]"
-1357
-1358    for descr, array in tensors.values():
-1359        try:
-1360            axis_sizes = descr.get_axis_sizes_for_array(array)
-1361        except ValueError as e:
-1362            raise ValueError(f"{e_msg(descr)} {e}")
-1363        else:
-1364            all_tensor_axes[descr.id] = {
-1365                a.id: (a, axis_sizes[a.id]) for a in descr.axes
-1366            }
-1367
-1368    for descr, array in tensors.values():
-1369        if array.dtype.name != descr.dtype:
-1370            raise ValueError(
-1371                f"{e_msg(descr)}.{tensor_origin}.dtype '{array.dtype.name}' does not"
-1372                + f" match described dtype '{descr.dtype}'"
-1373            )
-1374
-1375        for a in descr.axes:
-1376            actual_size = all_tensor_axes[descr.id][a.id][1]
-1377            if a.size is None:
-1378                continue
-1379
-1380            if isinstance(a.size, int):
-1381                if actual_size != a.size:
-1382                    raise ValueError(
-1383                        f"{e_msg(descr)}.{tensor_origin}: axis '{a.id}' "
-1384                        + f"has incompatible size {actual_size}, expected {a.size}"
-1385                    )
-1386            elif isinstance(a.size, ParameterizedSize):
-1387                _ = a.size.validate_size(actual_size)
-1388            elif isinstance(a.size, SizeReference):
-1389                ref_tensor_axes = all_tensor_axes.get(a.size.tensor_id)
-1390                if ref_tensor_axes is None:
-1391                    raise ValueError(
-1392                        f"{e_msg(descr)}.axes[{a.id}].size.tensor_id: Unknown tensor"
-1393                        + f" reference '{a.size.tensor_id}'"
-1394                    )
-1395
-1396                ref_axis, ref_size = ref_tensor_axes.get(a.size.axis_id, (None, None))
-1397                if ref_axis is None or ref_size is None:
-1398                    raise ValueError(
-1399                        f"{e_msg(descr)}.axes[{a.id}].size.axis_id: Unknown tensor axis"
-1400                        + f" reference '{a.size.tensor_id}.{a.size.axis_id}"
-1401                    )
-1402
-1403                if a.unit != ref_axis.unit:
-1404                    raise ValueError(
-1405                        f"{e_msg(descr)}.axes[{a.id}].size: `SizeReference` requires"
-1406                        + " axis and reference axis to have the same `unit`, but"
-1407                        + f" {a.unit}!={ref_axis.unit}"
-1408                    )
-1409
-1410                if actual_size != (
-1411                    expected_size := (
-1412                        ref_size * ref_axis.scale / a.scale + a.size.offset
-1413                    )
-1414                ):
+1355        return tgt(
+1356            axes=axes,
+1357            id=TensorId(str(src.name)),
+1358            test_tensor=FileDescr(source=test_tensor),
+1359            sample_tensor=(
+1360                None if sample_tensor is None else FileDescr(source=sample_tensor)
+1361            ),
+1362            data=data_descr,  # pyright: ignore[reportArgumentType]
+1363            postprocessing=[_convert_proc(p, src.axes) for p in src.postprocessing],
+1364        )
+1365
+1366
+1367_output_tensor_conv = _OutputTensorConv(_OutputTensorDescr_v0_4, OutputTensorDescr)
+1368
+1369
+1370TensorDescr = Union[InputTensorDescr, OutputTensorDescr]
+1371
+1372
+1373def validate_tensors(
+1374    tensors: Mapping[TensorId, Tuple[TensorDescr, NDArray[Any]]],
+1375    tensor_origin: str,  # for more precise error messages, e.g. 'test_tensor'
+1376):
+1377    all_tensor_axes: Dict[TensorId, Dict[AxisId, Tuple[AnyAxis, int]]] = {}
+1378
+1379    def e_msg(d: TensorDescr):
+1380        return f"{'inputs' if isinstance(d, InputTensorDescr) else 'outputs'}[{d.id}]"
+1381
+1382    for descr, array in tensors.values():
+1383        try:
+1384            axis_sizes = descr.get_axis_sizes_for_array(array)
+1385        except ValueError as e:
+1386            raise ValueError(f"{e_msg(descr)} {e}")
+1387        else:
+1388            all_tensor_axes[descr.id] = {
+1389                a.id: (a, axis_sizes[a.id]) for a in descr.axes
+1390            }
+1391
+1392    for descr, array in tensors.values():
+1393        if array.dtype.name != descr.dtype:
+1394            raise ValueError(
+1395                f"{e_msg(descr)}.{tensor_origin}.dtype '{array.dtype.name}' does not"
+1396                + f" match described dtype '{descr.dtype}'"
+1397            )
+1398
+1399        for a in descr.axes:
+1400            actual_size = all_tensor_axes[descr.id][a.id][1]
+1401            if a.size is None:
+1402                continue
+1403
+1404            if isinstance(a.size, int):
+1405                if actual_size != a.size:
+1406                    raise ValueError(
+1407                        f"{e_msg(descr)}.{tensor_origin}: axis '{a.id}' "
+1408                        + f"has incompatible size {actual_size}, expected {a.size}"
+1409                    )
+1410            elif isinstance(a.size, ParameterizedSize):
+1411                _ = a.size.validate_size(actual_size)
+1412            elif isinstance(a.size, SizeReference):
+1413                ref_tensor_axes = all_tensor_axes.get(a.size.tensor_id)
+1414                if ref_tensor_axes is None:
 1415                    raise ValueError(
-1416                        f"{e_msg(descr)}.{tensor_origin}: axis '{a.id}' of size"
-1417                        + f" {actual_size} invalid for referenced size {ref_size};"
-1418                        + f" expected {expected_size}"
-1419                    )
-1420            else:
-1421                assert_never(a.size)
-1422
-1423
-1424class EnvironmentFileDescr(FileDescr):
-1425    source: Annotated[
-1426        ImportantFileSource,
-1427        WithSuffix((".yaml", ".yml"), case_sensitive=True),
-1428        Field(
-1429            examples=["environment.yaml"],
-1430        ),
-1431    ]
-1432    """∈📦 Conda environment file.
-1433    Allows to specify custom dependencies, see conda docs:
-1434    - [Exporting an environment file across platforms](https://conda.io/projects/conda/en/latest/user-guide/tasks/manage-environments.html#exporting-an-environment-file-across-platforms)
-1435    - [Creating an environment file manually](https://conda.io/projects/conda/en/latest/user-guide/tasks/manage-environments.html#creating-an-environment-file-manually)
-1436    """
-1437
-1438
-1439class _ArchitectureCallableDescr(Node):
-1440    callable: Annotated[Identifier, Field(examples=["MyNetworkClass", "get_my_model"])]
-1441    """Identifier of the callable that returns a torch.nn.Module instance."""
-1442
-1443    kwargs: Dict[str, Any] = Field(default_factory=dict)
-1444    """key word arguments for the `callable`"""
-1445
+1416                        f"{e_msg(descr)}.axes[{a.id}].size.tensor_id: Unknown tensor"
+1417                        + f" reference '{a.size.tensor_id}'"
+1418                    )
+1419
+1420                ref_axis, ref_size = ref_tensor_axes.get(a.size.axis_id, (None, None))
+1421                if ref_axis is None or ref_size is None:
+1422                    raise ValueError(
+1423                        f"{e_msg(descr)}.axes[{a.id}].size.axis_id: Unknown tensor axis"
+1424                        + f" reference '{a.size.tensor_id}.{a.size.axis_id}"
+1425                    )
+1426
+1427                if a.unit != ref_axis.unit:
+1428                    raise ValueError(
+1429                        f"{e_msg(descr)}.axes[{a.id}].size: `SizeReference` requires"
+1430                        + " axis and reference axis to have the same `unit`, but"
+1431                        + f" {a.unit}!={ref_axis.unit}"
+1432                    )
+1433
+1434                if actual_size != (
+1435                    expected_size := (
+1436                        ref_size * ref_axis.scale / a.scale + a.size.offset
+1437                    )
+1438                ):
+1439                    raise ValueError(
+1440                        f"{e_msg(descr)}.{tensor_origin}: axis '{a.id}' of size"
+1441                        + f" {actual_size} invalid for referenced size {ref_size};"
+1442                        + f" expected {expected_size}"
+1443                    )
+1444            else:
+1445                assert_never(a.size)
 1446
-1447class ArchitectureFromFileDescr(_ArchitectureCallableDescr, FileDescr):
-1448    pass
-1449
-1450
-1451class ArchitectureFromLibraryDescr(_ArchitectureCallableDescr):
-1452    import_from: str
-1453    """Where to import the callable from, i.e. `from <import_from> import <callable>`"""
-1454
-1455
-1456ArchitectureDescr = Union[ArchitectureFromFileDescr, ArchitectureFromLibraryDescr]
-1457
-1458
-1459class _ArchFileConv(
-1460    Converter[
-1461        _CallableFromFile_v0_4,
-1462        ArchitectureFromFileDescr,
-1463        Optional[Sha256],
-1464        Dict[str, Any],
-1465    ]
-1466):
-1467    def _convert(
-1468        self,
-1469        src: _CallableFromFile_v0_4,
-1470        tgt: "type[ArchitectureFromFileDescr | dict[str, Any]]",
-1471        sha256: Optional[Sha256],
-1472        kwargs: Dict[str, Any],
-1473    ) -> "ArchitectureFromFileDescr | dict[str, Any]":
-1474        if src.startswith("http") and src.count(":") == 2:
-1475            http, source, callable_ = src.split(":")
-1476            source = ":".join((http, source))
-1477        elif not src.startswith("http") and src.count(":") == 1:
-1478            source, callable_ = src.split(":")
-1479        else:
-1480            source = str(src)
-1481            callable_ = str(src)
-1482        return tgt(
-1483            callable=Identifier(callable_),
-1484            source=cast(ImportantFileSource, source),
-1485            sha256=sha256,
-1486            kwargs=kwargs,
-1487        )
-1488
-1489
-1490_arch_file_conv = _ArchFileConv(_CallableFromFile_v0_4, ArchitectureFromFileDescr)
-1491
-1492
-1493class _ArchLibConv(
-1494    Converter[
-1495        _CallableFromDepencency_v0_4, ArchitectureFromLibraryDescr, Dict[str, Any]
-1496    ]
-1497):
-1498    def _convert(
-1499        self,
-1500        src: _CallableFromDepencency_v0_4,
-1501        tgt: "type[ArchitectureFromLibraryDescr | dict[str, Any]]",
-1502        kwargs: Dict[str, Any],
-1503    ) -> "ArchitectureFromLibraryDescr | dict[str, Any]":
-1504        *mods, callable_ = src.split(".")
-1505        import_from = ".".join(mods)
+1447
+1448class EnvironmentFileDescr(FileDescr):
+1449    source: Annotated[
+1450        ImportantFileSource,
+1451        WithSuffix((".yaml", ".yml"), case_sensitive=True),
+1452        Field(
+1453            examples=["environment.yaml"],
+1454        ),
+1455    ]
+1456    """∈📦 Conda environment file.
+1457    Allows to specify custom dependencies, see conda docs:
+1458    - [Exporting an environment file across platforms](https://conda.io/projects/conda/en/latest/user-guide/tasks/manage-environments.html#exporting-an-environment-file-across-platforms)
+1459    - [Creating an environment file manually](https://conda.io/projects/conda/en/latest/user-guide/tasks/manage-environments.html#creating-an-environment-file-manually)
+1460    """
+1461
+1462
+1463class _ArchitectureCallableDescr(Node):
+1464    callable: Annotated[Identifier, Field(examples=["MyNetworkClass", "get_my_model"])]
+1465    """Identifier of the callable that returns a torch.nn.Module instance."""
+1466
+1467    kwargs: Dict[str, Any] = Field(default_factory=dict)
+1468    """key word arguments for the `callable`"""
+1469
+1470
+1471class ArchitectureFromFileDescr(_ArchitectureCallableDescr, FileDescr):
+1472    pass
+1473
+1474
+1475class ArchitectureFromLibraryDescr(_ArchitectureCallableDescr):
+1476    import_from: str
+1477    """Where to import the callable from, i.e. `from <import_from> import <callable>`"""
+1478
+1479
+1480ArchitectureDescr = Union[ArchitectureFromFileDescr, ArchitectureFromLibraryDescr]
+1481
+1482
+1483class _ArchFileConv(
+1484    Converter[
+1485        _CallableFromFile_v0_4,
+1486        ArchitectureFromFileDescr,
+1487        Optional[Sha256],
+1488        Dict[str, Any],
+1489    ]
+1490):
+1491    def _convert(
+1492        self,
+1493        src: _CallableFromFile_v0_4,
+1494        tgt: "type[ArchitectureFromFileDescr | dict[str, Any]]",
+1495        sha256: Optional[Sha256],
+1496        kwargs: Dict[str, Any],
+1497    ) -> "ArchitectureFromFileDescr | dict[str, Any]":
+1498        if src.startswith("http") and src.count(":") == 2:
+1499            http, source, callable_ = src.split(":")
+1500            source = ":".join((http, source))
+1501        elif not src.startswith("http") and src.count(":") == 1:
+1502            source, callable_ = src.split(":")
+1503        else:
+1504            source = str(src)
+1505            callable_ = str(src)
 1506        return tgt(
-1507            import_from=import_from, callable=Identifier(callable_), kwargs=kwargs
-1508        )
-1509
-1510
-1511_arch_lib_conv = _ArchLibConv(
-1512    _CallableFromDepencency_v0_4, ArchitectureFromLibraryDescr
-1513)
-1514
+1507            callable=Identifier(callable_),
+1508            source=cast(ImportantFileSource, source),
+1509            sha256=sha256,
+1510            kwargs=kwargs,
+1511        )
+1512
+1513
+1514_arch_file_conv = _ArchFileConv(_CallableFromFile_v0_4, ArchitectureFromFileDescr)
 1515
-1516class WeightsEntryDescrBase(FileDescr):
-1517    type: ClassVar[WeightsFormat]
-1518    weights_format_name: ClassVar[str]  # human readable
-1519
-1520    source: ImportantFileSource
-1521    """∈📦 The weights file."""
-1522
-1523    authors: Optional[List[Author]] = None
-1524    """Authors
-1525    Either the person(s) that have trained this model resulting in the original weights file.
-1526        (If this is the initial weights entry, i.e. it does not have a `parent`)
-1527    Or the person(s) who have converted the weights to this weights format.
-1528        (If this is a child weight, i.e. it has a `parent` field)
-1529    """
-1530
-1531    parent: Annotated[
-1532        Optional[WeightsFormat], Field(examples=["pytorch_state_dict"])
-1533    ] = None
-1534    """The source weights these weights were converted from.
-1535    For example, if a model's weights were converted from the `pytorch_state_dict` format to `torchscript`,
-1536    The `pytorch_state_dict` weights entry has no `parent` and is the parent of the `torchscript` weights.
-1537    All weight entries except one (the initial set of weights resulting from training the model),
-1538    need to have this field."""
+1516
+1517class _ArchLibConv(
+1518    Converter[
+1519        _CallableFromDepencency_v0_4, ArchitectureFromLibraryDescr, Dict[str, Any]
+1520    ]
+1521):
+1522    def _convert(
+1523        self,
+1524        src: _CallableFromDepencency_v0_4,
+1525        tgt: "type[ArchitectureFromLibraryDescr | dict[str, Any]]",
+1526        kwargs: Dict[str, Any],
+1527    ) -> "ArchitectureFromLibraryDescr | dict[str, Any]":
+1528        *mods, callable_ = src.split(".")
+1529        import_from = ".".join(mods)
+1530        return tgt(
+1531            import_from=import_from, callable=Identifier(callable_), kwargs=kwargs
+1532        )
+1533
+1534
+1535_arch_lib_conv = _ArchLibConv(
+1536    _CallableFromDepencency_v0_4, ArchitectureFromLibraryDescr
+1537)
+1538
 1539
-1540    @model_validator(mode="after")
-1541    def check_parent_is_not_self(self) -> Self:
-1542        if self.type == self.parent:
-1543            raise ValueError("Weights entry can't be it's own parent.")
-1544
-1545        return self
+1540class WeightsEntryDescrBase(FileDescr):
+1541    type: ClassVar[WeightsFormat]
+1542    weights_format_name: ClassVar[str]  # human readable
+1543
+1544    source: ImportantFileSource
+1545    """∈📦 The weights file."""
 1546
-1547
-1548class KerasHdf5WeightsDescr(WeightsEntryDescrBase):
-1549    type = "keras_hdf5"
-1550    weights_format_name: ClassVar[str] = "Keras HDF5"
-1551    tensorflow_version: Version
-1552    """TensorFlow version used to create these weights."""
-1553
+1547    authors: Optional[List[Author]] = None
+1548    """Authors
+1549    Either the person(s) that have trained this model resulting in the original weights file.
+1550        (If this is the initial weights entry, i.e. it does not have a `parent`)
+1551    Or the person(s) who have converted the weights to this weights format.
+1552        (If this is a child weight, i.e. it has a `parent` field)
+1553    """
 1554
-1555class OnnxWeightsDescr(WeightsEntryDescrBase):
-1556    type = "onnx"
-1557    weights_format_name: ClassVar[str] = "ONNX"
-1558    opset_version: Annotated[int, Ge(7)]
-1559    """ONNX opset version"""
-1560
-1561
-1562class PytorchStateDictWeightsDescr(WeightsEntryDescrBase):
-1563    type = "pytorch_state_dict"
-1564    weights_format_name: ClassVar[str] = "Pytorch State Dict"
-1565    architecture: ArchitectureDescr
-1566    pytorch_version: Version
-1567    """Version of the PyTorch library used.
-1568    If `architecture.depencencies` is specified it has to include pytorch and any version pinning has to be compatible.
-1569    """
-1570    dependencies: Optional[EnvironmentFileDescr] = None
-1571    """Custom depencies beyond pytorch.
-1572    The conda environment file should include pytorch and any version pinning has to be compatible with
-1573    `pytorch_version`.
-1574    """
-1575
-1576
-1577class TensorflowJsWeightsDescr(WeightsEntryDescrBase):
-1578    type = "tensorflow_js"
-1579    weights_format_name: ClassVar[str] = "Tensorflow.js"
-1580    tensorflow_version: Version
-1581    """Version of the TensorFlow library used."""
-1582
-1583    source: ImportantFileSource
-1584    """∈📦 The multi-file weights.
-1585    All required files/folders should be a zip archive."""
-1586
-1587
-1588class TensorflowSavedModelBundleWeightsDescr(WeightsEntryDescrBase):
-1589    type = "tensorflow_saved_model_bundle"
-1590    weights_format_name: ClassVar[str] = "Tensorflow Saved Model"
-1591    tensorflow_version: Version
-1592    """Version of the TensorFlow library used."""
-1593
+1555    parent: Annotated[
+1556        Optional[WeightsFormat], Field(examples=["pytorch_state_dict"])
+1557    ] = None
+1558    """The source weights these weights were converted from.
+1559    For example, if a model's weights were converted from the `pytorch_state_dict` format to `torchscript`,
+1560    The `pytorch_state_dict` weights entry has no `parent` and is the parent of the `torchscript` weights.
+1561    All weight entries except one (the initial set of weights resulting from training the model),
+1562    need to have this field."""
+1563
+1564    @model_validator(mode="after")
+1565    def check_parent_is_not_self(self) -> Self:
+1566        if self.type == self.parent:
+1567            raise ValueError("Weights entry can't be it's own parent.")
+1568
+1569        return self
+1570
+1571
+1572class KerasHdf5WeightsDescr(WeightsEntryDescrBase):
+1573    type = "keras_hdf5"
+1574    weights_format_name: ClassVar[str] = "Keras HDF5"
+1575    tensorflow_version: Version
+1576    """TensorFlow version used to create these weights."""
+1577
+1578
+1579class OnnxWeightsDescr(WeightsEntryDescrBase):
+1580    type = "onnx"
+1581    weights_format_name: ClassVar[str] = "ONNX"
+1582    opset_version: Annotated[int, Ge(7)]
+1583    """ONNX opset version"""
+1584
+1585
+1586class PytorchStateDictWeightsDescr(WeightsEntryDescrBase):
+1587    type = "pytorch_state_dict"
+1588    weights_format_name: ClassVar[str] = "Pytorch State Dict"
+1589    architecture: ArchitectureDescr
+1590    pytorch_version: Version
+1591    """Version of the PyTorch library used.
+1592    If `architecture.depencencies` is specified it has to include pytorch and any version pinning has to be compatible.
+1593    """
 1594    dependencies: Optional[EnvironmentFileDescr] = None
-1595    """Custom dependencies beyond tensorflow.
-1596    Should include tensorflow and any version pinning has to be compatible with `tensorflow_version`."""
-1597
-1598    source: ImportantFileSource
-1599    """∈📦 The multi-file weights.
-1600    All required files/folders should be a zip archive."""
-1601
-1602
-1603class TorchscriptWeightsDescr(WeightsEntryDescrBase):
-1604    type = "torchscript"
-1605    weights_format_name: ClassVar[str] = "TorchScript"
-1606    pytorch_version: Version
-1607    """Version of the PyTorch library used."""
-1608
-1609
-1610class WeightsDescr(Node):
-1611    keras_hdf5: Optional[KerasHdf5WeightsDescr] = None
-1612    onnx: Optional[OnnxWeightsDescr] = None
-1613    pytorch_state_dict: Optional[PytorchStateDictWeightsDescr] = None
-1614    tensorflow_js: Optional[TensorflowJsWeightsDescr] = None
-1615    tensorflow_saved_model_bundle: Optional[TensorflowSavedModelBundleWeightsDescr] = (
-1616        None
-1617    )
-1618    torchscript: Optional[TorchscriptWeightsDescr] = None
-1619
-1620    @model_validator(mode="after")
-1621    def check_entries(self) -> Self:
-1622        entries = {wtype for wtype, entry in self if entry is not None}
-1623
-1624        if not entries:
-1625            raise ValueError("Missing weights entry")
+1595    """Custom depencies beyond pytorch.
+1596    The conda environment file should include pytorch and any version pinning has to be compatible with
+1597    `pytorch_version`.
+1598    """
+1599
+1600
+1601class TensorflowJsWeightsDescr(WeightsEntryDescrBase):
+1602    type = "tensorflow_js"
+1603    weights_format_name: ClassVar[str] = "Tensorflow.js"
+1604    tensorflow_version: Version
+1605    """Version of the TensorFlow library used."""
+1606
+1607    source: ImportantFileSource
+1608    """∈📦 The multi-file weights.
+1609    All required files/folders should be a zip archive."""
+1610
+1611
+1612class TensorflowSavedModelBundleWeightsDescr(WeightsEntryDescrBase):
+1613    type = "tensorflow_saved_model_bundle"
+1614    weights_format_name: ClassVar[str] = "Tensorflow Saved Model"
+1615    tensorflow_version: Version
+1616    """Version of the TensorFlow library used."""
+1617
+1618    dependencies: Optional[EnvironmentFileDescr] = None
+1619    """Custom dependencies beyond tensorflow.
+1620    Should include tensorflow and any version pinning has to be compatible with `tensorflow_version`."""
+1621
+1622    source: ImportantFileSource
+1623    """∈📦 The multi-file weights.
+1624    All required files/folders should be a zip archive."""
+1625
 1626
-1627        entries_wo_parent = {
-1628            wtype
-1629            for wtype, entry in self
-1630            if entry is not None and hasattr(entry, "parent") and entry.parent is None
-1631        }
-1632        if len(entries_wo_parent) != 1:
-1633            issue_warning(
-1634                "Exactly one weights entry may not specify the `parent` field (got"
-1635                + " {value}).That entry is considered the original set of model weights."
-1636                + " Other weight formats are created through conversion of the orignal or"
-1637                + " already converted weights. They have to reference the weights format"
-1638                + " they were converted from as their `parent`.",
-1639                value=len(entries_wo_parent),
-1640            )
-1641
-1642        for wtype, entry in self:
-1643            if entry is None:
-1644                continue
-1645
-1646            assert hasattr(entry, "type")
-1647            assert hasattr(entry, "parent")
-1648            assert wtype == entry.type
-1649            if (
-1650                entry.parent is not None and entry.parent not in entries
-1651            ):  # self reference checked for `parent` field
-1652                raise ValueError(
-1653                    f"`weights.{wtype}.parent={entry.parent} not in specified weight"
-1654                    + f" formats: {entries}"
-1655                )
-1656
-1657        return self
-1658
-1659
-1660class LinkedModel(Node):
-1661    """Reference to a bioimage.io model."""
-1662
-1663    id: ModelId
-1664    """A valid model `id` from the bioimage.io collection."""
+1627class TorchscriptWeightsDescr(WeightsEntryDescrBase):
+1628    type = "torchscript"
+1629    weights_format_name: ClassVar[str] = "TorchScript"
+1630    pytorch_version: Version
+1631    """Version of the PyTorch library used."""
+1632
+1633
+1634class WeightsDescr(Node):
+1635    keras_hdf5: Optional[KerasHdf5WeightsDescr] = None
+1636    onnx: Optional[OnnxWeightsDescr] = None
+1637    pytorch_state_dict: Optional[PytorchStateDictWeightsDescr] = None
+1638    tensorflow_js: Optional[TensorflowJsWeightsDescr] = None
+1639    tensorflow_saved_model_bundle: Optional[TensorflowSavedModelBundleWeightsDescr] = (
+1640        None
+1641    )
+1642    torchscript: Optional[TorchscriptWeightsDescr] = None
+1643
+1644    @model_validator(mode="after")
+1645    def check_entries(self) -> Self:
+1646        entries = {wtype for wtype, entry in self if entry is not None}
+1647
+1648        if not entries:
+1649            raise ValueError("Missing weights entry")
+1650
+1651        entries_wo_parent = {
+1652            wtype
+1653            for wtype, entry in self
+1654            if entry is not None and hasattr(entry, "parent") and entry.parent is None
+1655        }
+1656        if len(entries_wo_parent) != 1:
+1657            issue_warning(
+1658                "Exactly one weights entry may not specify the `parent` field (got"
+1659                + " {value}).That entry is considered the original set of model weights."
+1660                + " Other weight formats are created through conversion of the orignal or"
+1661                + " already converted weights. They have to reference the weights format"
+1662                + " they were converted from as their `parent`.",
+1663                value=len(entries_wo_parent),
+1664            )
 1665
-1666    version_number: int
-1667    """version number (n-th published version, not the semantic version) of linked model"""
-1668
+1666        for wtype, entry in self:
+1667            if entry is None:
+1668                continue
 1669
-1670class ModelDescr(GenericModelDescrBase, title="bioimage.io model specification"):
-1671    """Specification of the fields used in a bioimage.io-compliant RDF to describe AI models with pretrained weights.
-1672    These fields are typically stored in a YAML file which we call a model resource description file (model RDF).
-1673    """
-1674
-1675    format_version: Literal["0.5.0"] = "0.5.0"
-1676    """Version of the bioimage.io model description specification used.
-1677    When creating a new model always use the latest micro/patch version described here.
-1678    The `format_version` is important for any consumer software to understand how to parse the fields.
-1679    """
+1670            assert hasattr(entry, "type")
+1671            assert hasattr(entry, "parent")
+1672            assert wtype == entry.type
+1673            if (
+1674                entry.parent is not None and entry.parent not in entries
+1675            ):  # self reference checked for `parent` field
+1676                raise ValueError(
+1677                    f"`weights.{wtype}.parent={entry.parent} not in specified weight"
+1678                    + f" formats: {entries}"
+1679                )
 1680
-1681    type: Literal["model"] = "model"
-1682    """Specialized resource type 'model'"""
+1681        return self
+1682
 1683
-1684    id: Optional[ModelId] = None
-1685    """Model zoo (bioimage.io) wide, unique identifier (assigned by bioimage.io)"""
+1684class LinkedModel(Node):
+1685    """Reference to a bioimage.io model."""
 1686
-1687    authors: NotEmpty[List[Author]]
-1688    """The authors are the creators of the model RDF and the primary points of contact."""
+1687    id: ModelId
+1688    """A valid model `id` from the bioimage.io collection."""
 1689
-1690    documentation: Annotated[
-1691        DocumentationSource,
-1692        Field(
-1693            examples=[
-1694                "https://raw.githubusercontent.com/bioimage-io/spec-bioimage-io/main/example_descriptions/models/unet2d_nuclei_broad/README.md",
-1695                "README.md",
-1696            ],
-1697        ),
-1698    ]
-1699    """∈📦 URL or relative path to a markdown file with additional documentation.
-1700    The recommended documentation file name is `README.md`. An `.md` suffix is mandatory.
-1701    The documentation should include a '#[#] Validation' (sub)section
-1702    with details on how to quantitatively validate the model on unseen data."""
-1703
-1704    @field_validator("documentation", mode="after")
-1705    @classmethod
-1706    def _validate_documentation(cls, value: DocumentationSource) -> DocumentationSource:
-1707        if not validation_context_var.get().perform_io_checks:
-1708            return value
-1709
-1710        doc_path = download(value).path
-1711        doc_content = doc_path.read_text()
-1712        if not re.match("#.*[vV]alidation", doc_content):
-1713            issue_warning(
-1714                "No '# Validation' (sub)section found in {value}.", value=value
-1715            )
-1716
-1717        return value
-1718
-1719    inputs: NotEmpty[Sequence[InputTensorDescr]]
-1720    """Describes the input tensors expected by this model."""
-1721
-1722    @field_validator("inputs", mode="after")
-1723    @classmethod
-1724    def _validate_input_axes(
-1725        cls, inputs: Sequence[InputTensorDescr]
-1726    ) -> Sequence[InputTensorDescr]:
-1727        input_size_refs = cls._get_axes_with_independent_size(inputs)
-1728
-1729        for i, ipt in enumerate(inputs):
-1730            valid_independent_refs: Dict[
-1731                Tuple[TensorId, AxisId],
-1732                Tuple[TensorDescr, AnyAxis, Union[int, ParameterizedSize]],
-1733            ] = {
-1734                **{
-1735                    (ipt.id, a.id): (ipt, a, a.size)
-1736                    for a in ipt.axes
-1737                    if not isinstance(a, BatchAxis)
-1738                    and isinstance(a.size, (int, ParameterizedSize))
-1739                },
-1740                **input_size_refs,
-1741            }
-1742            for a, ax in enumerate(ipt.axes):
-1743                cls._validate_axis(
-1744                    "inputs",
-1745                    i=i,
-1746                    tensor_id=ipt.id,
-1747                    a=a,
-1748                    axis=ax,
-1749                    valid_independent_refs=valid_independent_refs,
-1750                )
-1751        return inputs
+1690    version_number: int
+1691    """version number (n-th published version, not the semantic version) of linked model"""
+1692
+1693
+1694class ModelDescr(GenericModelDescrBase, title="bioimage.io model specification"):
+1695    """Specification of the fields used in a bioimage.io-compliant RDF to describe AI models with pretrained weights.
+1696    These fields are typically stored in a YAML file which we call a model resource description file (model RDF).
+1697    """
+1698
+1699    format_version: Literal["0.5.0"] = "0.5.0"
+1700    """Version of the bioimage.io model description specification used.
+1701    When creating a new model always use the latest micro/patch version described here.
+1702    The `format_version` is important for any consumer software to understand how to parse the fields.
+1703    """
+1704
+1705    type: Literal["model"] = "model"
+1706    """Specialized resource type 'model'"""
+1707
+1708    id: Optional[ModelId] = None
+1709    """Model zoo (bioimage.io) wide, unique identifier (assigned by bioimage.io)"""
+1710
+1711    authors: NotEmpty[List[Author]]
+1712    """The authors are the creators of the model RDF and the primary points of contact."""
+1713
+1714    documentation: Annotated[
+1715        DocumentationSource,
+1716        Field(
+1717            examples=[
+1718                "https://raw.githubusercontent.com/bioimage-io/spec-bioimage-io/main/example_descriptions/models/unet2d_nuclei_broad/README.md",
+1719                "README.md",
+1720            ],
+1721        ),
+1722    ]
+1723    """∈📦 URL or relative path to a markdown file with additional documentation.
+1724    The recommended documentation file name is `README.md`. An `.md` suffix is mandatory.
+1725    The documentation should include a '#[#] Validation' (sub)section
+1726    with details on how to quantitatively validate the model on unseen data."""
+1727
+1728    @field_validator("documentation", mode="after")
+1729    @classmethod
+1730    def _validate_documentation(cls, value: DocumentationSource) -> DocumentationSource:
+1731        if not validation_context_var.get().perform_io_checks:
+1732            return value
+1733
+1734        doc_path = download(value).path
+1735        doc_content = doc_path.read_text()
+1736        if not re.match("#.*[vV]alidation", doc_content):
+1737            issue_warning(
+1738                "No '# Validation' (sub)section found in {value}.", value=value
+1739            )
+1740
+1741        return value
+1742
+1743    inputs: NotEmpty[Sequence[InputTensorDescr]]
+1744    """Describes the input tensors expected by this model."""
+1745
+1746    @field_validator("inputs", mode="after")
+1747    @classmethod
+1748    def _validate_input_axes(
+1749        cls, inputs: Sequence[InputTensorDescr]
+1750    ) -> Sequence[InputTensorDescr]:
+1751        input_size_refs = cls._get_axes_with_independent_size(inputs)
 1752
-1753    @staticmethod
-1754    def _validate_axis(
-1755        field_name: str,
-1756        i: int,
-1757        tensor_id: TensorId,
-1758        a: int,
-1759        axis: AnyAxis,
-1760        valid_independent_refs: Dict[
-1761            Tuple[TensorId, AxisId],
-1762            Tuple[TensorDescr, AnyAxis, Union[int, ParameterizedSize]],
-1763        ],
-1764    ):
-1765        if isinstance(axis, BatchAxis) or isinstance(axis.size, int):
-1766            return
-1767
-1768        if isinstance(axis.size, ParameterizedSize):
-1769            if isinstance(axis, WithHalo) and (axis.size.min - 2 * axis.halo) < 1:
-1770                raise ValueError(
-1771                    f"axis {axis.id} with minimum size {axis.size.min} is too small for"
-1772                    + f" halo {axis.halo}."
-1773                )
-1774
-1775        elif isinstance(axis.size, SizeReference):
-1776            ref = (axis.size.tensor_id, axis.size.axis_id)
-1777            if ref not in valid_independent_refs:
-1778                raise ValueError(
-1779                    "Invalid tensor axis reference at"
-1780                    + f" {field_name}[{i}].axes[{a}].size: {axis.size}."
-1781                )
-1782            if ref == (tensor_id, axis.id):
-1783                raise ValueError(
-1784                    "Self-referencing not allowed for"
-1785                    + f" {field_name}[{i}].axes[{a}].size: {axis.size}"
-1786                )
-1787            if axis.type == "channel":
-1788                if valid_independent_refs[ref][1].type != "channel":
-1789                    raise ValueError(
-1790                        "A channel axis' size may only reference another fixed size"
-1791                        + " channel axis."
-1792                    )
-1793                if isinstance(axis.channel_names, str) and "{i}" in axis.channel_names:
-1794                    ref_size = valid_independent_refs[ref][2]
-1795                    assert isinstance(ref_size, int), (
-1796                        "channel axis ref (another channel axis) has to specify fixed"
-1797                        + " size"
-1798                    )
-1799                    generated_channel_names = [
-1800                        Identifier(axis.channel_names.format(i=i))
-1801                        for i in range(1, ref_size + 1)
-1802                    ]
-1803                    axis.channel_names = generated_channel_names
-1804
-1805            if (ax_unit := getattr(axis, "unit", None)) != (
-1806                ref_unit := getattr(valid_independent_refs[ref][1], "unit", None)
-1807            ):
-1808                raise ValueError(
-1809                    "The units of an axis and its reference axis need to match, but"
-1810                    + f" '{ax_unit}' != '{ref_unit}'."
-1811                )
-1812            min_size = valid_independent_refs[ref][2]
-1813            if isinstance(min_size, ParameterizedSize):
-1814                min_size = min_size.min
-1815
-1816            if isinstance(axis, WithHalo) and (min_size - 2 * axis.halo) < 1:
-1817                raise ValueError(
-1818                    f"axis {axis.id} with minimum size {min_size} is too small for halo"
-1819                    + f" {axis.halo}."
-1820                )
-1821
-1822        else:
-1823            assert_never(axis.size)
-1824
-1825    @model_validator(mode="after")
-1826    def _validate_test_tensors(self) -> Self:
-1827        if not validation_context_var.get().perform_io_checks:
-1828            return self
-1829
-1830        test_arrays = [
-1831            load_array(descr.test_tensor.download().path)
-1832            for descr in chain(self.inputs, self.outputs)
-1833        ]
-1834        tensors = {
-1835            descr.id: (descr, array)
-1836            for descr, array in zip(chain(self.inputs, self.outputs), test_arrays)
-1837        }
-1838        validate_tensors(tensors, tensor_origin="test_tensor")
-1839        return self
-1840
-1841    @model_validator(mode="after")
-1842    def _validate_tensor_references_in_proc_kwargs(self, info: ValidationInfo) -> Self:
-1843        ipt_refs = {t.id for t in self.inputs}
-1844        out_refs = {t.id for t in self.outputs}
-1845        for ipt in self.inputs:
-1846            for p in ipt.preprocessing:
-1847                ref = p.kwargs.get("reference_tensor")
-1848                if ref is None:
-1849                    continue
-1850                if ref not in ipt_refs:
-1851                    raise ValueError(
-1852                        f"`reference_tensor` '{ref}' not found. Valid input tensor"
-1853                        + f" references are: {ipt_refs}."
-1854                    )
-1855
-1856        for out in self.outputs:
-1857            for p in out.postprocessing:
-1858                ref = p.kwargs.get("reference_tensor")
-1859                if ref is None:
-1860                    continue
-1861
-1862                if ref not in ipt_refs and ref not in out_refs:
-1863                    raise ValueError(
-1864                        f"`reference_tensor` '{ref}' not found. Valid tensor references"
-1865                        + f" are: {ipt_refs | out_refs}."
-1866                    )
-1867
-1868        return self
-1869
-1870    # TODO: use validate funcs in validate_test_tensors
-1871    # def validate_inputs(self, input_tensors: Mapping[TensorId, NDArray[Any]]) -> Mapping[TensorId, NDArray[Any]]:
-1872
-1873    name: Annotated[
-1874        str,
-1875        MinLen(5),
-1876        warn(MaxLen(64), "Name longer than 64 characters.", INFO),
-1877    ]
-1878    """A human-readable name of this model.
-1879    It should be no longer than 64 characters
-1880    and may only contain letter, number, underscore, minus or space characters.
-1881    We recommend to chose a name that refers to the model's task and image modality.
-1882    """
-1883
-1884    outputs: NotEmpty[Sequence[OutputTensorDescr]]
-1885    """Describes the output tensors."""
-1886
-1887    @field_validator("outputs", mode="after")
-1888    @classmethod
-1889    def _validate_tensor_ids(
-1890        cls, outputs: Sequence[OutputTensorDescr], info: ValidationInfo
-1891    ) -> Sequence[OutputTensorDescr]:
-1892        tensor_ids = [
-1893            t.id for t in info.data.get("inputs", []) + info.data.get("outputs", [])
-1894        ]
-1895        duplicate_tensor_ids: List[str] = []
-1896        seen: Set[str] = set()
-1897        for t in tensor_ids:
-1898            if t in seen:
-1899                duplicate_tensor_ids.append(t)
-1900
-1901            seen.add(t)
-1902
-1903        if duplicate_tensor_ids:
-1904            raise ValueError(f"Duplicate tensor ids: {duplicate_tensor_ids}")
-1905
-1906        return outputs
+1753        for i, ipt in enumerate(inputs):
+1754            valid_independent_refs: Dict[
+1755                Tuple[TensorId, AxisId],
+1756                Tuple[TensorDescr, AnyAxis, Union[int, ParameterizedSize]],
+1757            ] = {
+1758                **{
+1759                    (ipt.id, a.id): (ipt, a, a.size)
+1760                    for a in ipt.axes
+1761                    if not isinstance(a, BatchAxis)
+1762                    and isinstance(a.size, (int, ParameterizedSize))
+1763                },
+1764                **input_size_refs,
+1765            }
+1766            for a, ax in enumerate(ipt.axes):
+1767                cls._validate_axis(
+1768                    "inputs",
+1769                    i=i,
+1770                    tensor_id=ipt.id,
+1771                    a=a,
+1772                    axis=ax,
+1773                    valid_independent_refs=valid_independent_refs,
+1774                )
+1775        return inputs
+1776
+1777    @staticmethod
+1778    def _validate_axis(
+1779        field_name: str,
+1780        i: int,
+1781        tensor_id: TensorId,
+1782        a: int,
+1783        axis: AnyAxis,
+1784        valid_independent_refs: Dict[
+1785            Tuple[TensorId, AxisId],
+1786            Tuple[TensorDescr, AnyAxis, Union[int, ParameterizedSize]],
+1787        ],
+1788    ):
+1789        if isinstance(axis, BatchAxis) or isinstance(axis.size, int):
+1790            return
+1791
+1792        if isinstance(axis.size, ParameterizedSize):
+1793            if isinstance(axis, WithHalo) and (axis.size.min - 2 * axis.halo) < 1:
+1794                raise ValueError(
+1795                    f"axis {axis.id} with minimum size {axis.size.min} is too small for"
+1796                    + f" halo {axis.halo}."
+1797                )
+1798
+1799        elif isinstance(axis.size, SizeReference):
+1800            ref = (axis.size.tensor_id, axis.size.axis_id)
+1801            if ref not in valid_independent_refs:
+1802                raise ValueError(
+1803                    "Invalid tensor axis reference at"
+1804                    + f" {field_name}[{i}].axes[{a}].size: {axis.size}."
+1805                )
+1806            if ref == (tensor_id, axis.id):
+1807                raise ValueError(
+1808                    "Self-referencing not allowed for"
+1809                    + f" {field_name}[{i}].axes[{a}].size: {axis.size}"
+1810                )
+1811            if axis.type == "channel":
+1812                if valid_independent_refs[ref][1].type != "channel":
+1813                    raise ValueError(
+1814                        "A channel axis' size may only reference another fixed size"
+1815                        + " channel axis."
+1816                    )
+1817                if isinstance(axis.channel_names, str) and "{i}" in axis.channel_names:
+1818                    ref_size = valid_independent_refs[ref][2]
+1819                    assert isinstance(ref_size, int), (
+1820                        "channel axis ref (another channel axis) has to specify fixed"
+1821                        + " size"
+1822                    )
+1823                    generated_channel_names = [
+1824                        Identifier(axis.channel_names.format(i=i))
+1825                        for i in range(1, ref_size + 1)
+1826                    ]
+1827                    axis.channel_names = generated_channel_names
+1828
+1829            if (ax_unit := getattr(axis, "unit", None)) != (
+1830                ref_unit := getattr(valid_independent_refs[ref][1], "unit", None)
+1831            ):
+1832                raise ValueError(
+1833                    "The units of an axis and its reference axis need to match, but"
+1834                    + f" '{ax_unit}' != '{ref_unit}'."
+1835                )
+1836            min_size = valid_independent_refs[ref][2]
+1837            if isinstance(min_size, ParameterizedSize):
+1838                min_size = min_size.min
+1839
+1840            if isinstance(axis, WithHalo) and (min_size - 2 * axis.halo) < 1:
+1841                raise ValueError(
+1842                    f"axis {axis.id} with minimum size {min_size} is too small for halo"
+1843                    + f" {axis.halo}."
+1844                )
+1845
+1846        else:
+1847            assert_never(axis.size)
+1848
+1849    @model_validator(mode="after")
+1850    def _validate_test_tensors(self) -> Self:
+1851        if not validation_context_var.get().perform_io_checks:
+1852            return self
+1853
+1854        test_arrays = [
+1855            load_array(descr.test_tensor.download().path)
+1856            for descr in chain(self.inputs, self.outputs)
+1857        ]
+1858        tensors = {
+1859            descr.id: (descr, array)
+1860            for descr, array in zip(chain(self.inputs, self.outputs), test_arrays)
+1861        }
+1862        validate_tensors(tensors, tensor_origin="test_tensor")
+1863        return self
+1864
+1865    @model_validator(mode="after")
+1866    def _validate_tensor_references_in_proc_kwargs(self, info: ValidationInfo) -> Self:
+1867        ipt_refs = {t.id for t in self.inputs}
+1868        out_refs = {t.id for t in self.outputs}
+1869        for ipt in self.inputs:
+1870            for p in ipt.preprocessing:
+1871                ref = p.kwargs.get("reference_tensor")
+1872                if ref is None:
+1873                    continue
+1874                if ref not in ipt_refs:
+1875                    raise ValueError(
+1876                        f"`reference_tensor` '{ref}' not found. Valid input tensor"
+1877                        + f" references are: {ipt_refs}."
+1878                    )
+1879
+1880        for out in self.outputs:
+1881            for p in out.postprocessing:
+1882                ref = p.kwargs.get("reference_tensor")
+1883                if ref is None:
+1884                    continue
+1885
+1886                if ref not in ipt_refs and ref not in out_refs:
+1887                    raise ValueError(
+1888                        f"`reference_tensor` '{ref}' not found. Valid tensor references"
+1889                        + f" are: {ipt_refs | out_refs}."
+1890                    )
+1891
+1892        return self
+1893
+1894    # TODO: use validate funcs in validate_test_tensors
+1895    # def validate_inputs(self, input_tensors: Mapping[TensorId, NDArray[Any]]) -> Mapping[TensorId, NDArray[Any]]:
+1896
+1897    name: Annotated[
+1898        str,
+1899        MinLen(5),
+1900        warn(MaxLen(64), "Name longer than 64 characters.", INFO),
+1901    ]
+1902    """A human-readable name of this model.
+1903    It should be no longer than 64 characters
+1904    and may only contain letter, number, underscore, minus or space characters.
+1905    We recommend to chose a name that refers to the model's task and image modality.
+1906    """
 1907
-1908    @staticmethod
-1909    def _get_axes_with_parameterized_size(
-1910        io: Union[Sequence[InputTensorDescr], Sequence[OutputTensorDescr]],
-1911    ):
-1912        return {
-1913            f"{t.id}.{a.id}": (t, a, a.size)
-1914            for t in io
-1915            for a in t.axes
-1916            if not isinstance(a, BatchAxis) and isinstance(a.size, ParameterizedSize)
-1917        }
-1918
-1919    @staticmethod
-1920    def _get_axes_with_independent_size(
-1921        io: Union[Sequence[InputTensorDescr], Sequence[OutputTensorDescr]],
-1922    ):
-1923        return {
-1924            (t.id, a.id): (t, a, a.size)
-1925            for t in io
-1926            for a in t.axes
-1927            if not isinstance(a, BatchAxis)
-1928            and isinstance(a.size, (int, ParameterizedSize))
-1929        }
-1930
-1931    @field_validator("outputs", mode="after")
-1932    @classmethod
-1933    def _validate_output_axes(
-1934        cls, outputs: List[OutputTensorDescr], info: ValidationInfo
-1935    ) -> List[OutputTensorDescr]:
-1936        input_size_refs = cls._get_axes_with_independent_size(
-1937            info.data.get("inputs", [])
-1938        )
-1939        output_size_refs = cls._get_axes_with_independent_size(outputs)
-1940
-1941        for i, out in enumerate(outputs):
-1942            valid_independent_refs: Dict[
-1943                Tuple[TensorId, AxisId],
-1944                Tuple[TensorDescr, AnyAxis, Union[int, ParameterizedSize]],
-1945            ] = {
-1946                **{
-1947                    (out.id, a.id): (out, a, a.size)
-1948                    for a in out.axes
-1949                    if not isinstance(a, BatchAxis)
-1950                    and isinstance(a.size, (int, ParameterizedSize))
-1951                },
-1952                **input_size_refs,
-1953                **output_size_refs,
-1954            }
-1955            for a, ax in enumerate(out.axes):
-1956                cls._validate_axis(
-1957                    "outputs",
-1958                    i,
-1959                    out.id,
-1960                    a,
-1961                    ax,
-1962                    valid_independent_refs=valid_independent_refs,
-1963                )
+1908    outputs: NotEmpty[Sequence[OutputTensorDescr]]
+1909    """Describes the output tensors."""
+1910
+1911    @field_validator("outputs", mode="after")
+1912    @classmethod
+1913    def _validate_tensor_ids(
+1914        cls, outputs: Sequence[OutputTensorDescr], info: ValidationInfo
+1915    ) -> Sequence[OutputTensorDescr]:
+1916        tensor_ids = [
+1917            t.id for t in info.data.get("inputs", []) + info.data.get("outputs", [])
+1918        ]
+1919        duplicate_tensor_ids: List[str] = []
+1920        seen: Set[str] = set()
+1921        for t in tensor_ids:
+1922            if t in seen:
+1923                duplicate_tensor_ids.append(t)
+1924
+1925            seen.add(t)
+1926
+1927        if duplicate_tensor_ids:
+1928            raise ValueError(f"Duplicate tensor ids: {duplicate_tensor_ids}")
+1929
+1930        return outputs
+1931
+1932    @staticmethod
+1933    def _get_axes_with_parameterized_size(
+1934        io: Union[Sequence[InputTensorDescr], Sequence[OutputTensorDescr]],
+1935    ):
+1936        return {
+1937            f"{t.id}.{a.id}": (t, a, a.size)
+1938            for t in io
+1939            for a in t.axes
+1940            if not isinstance(a, BatchAxis) and isinstance(a.size, ParameterizedSize)
+1941        }
+1942
+1943    @staticmethod
+1944    def _get_axes_with_independent_size(
+1945        io: Union[Sequence[InputTensorDescr], Sequence[OutputTensorDescr]],
+1946    ):
+1947        return {
+1948            (t.id, a.id): (t, a, a.size)
+1949            for t in io
+1950            for a in t.axes
+1951            if not isinstance(a, BatchAxis)
+1952            and isinstance(a.size, (int, ParameterizedSize))
+1953        }
+1954
+1955    @field_validator("outputs", mode="after")
+1956    @classmethod
+1957    def _validate_output_axes(
+1958        cls, outputs: List[OutputTensorDescr], info: ValidationInfo
+1959    ) -> List[OutputTensorDescr]:
+1960        input_size_refs = cls._get_axes_with_independent_size(
+1961            info.data.get("inputs", [])
+1962        )
+1963        output_size_refs = cls._get_axes_with_independent_size(outputs)
 1964
-1965        return outputs
-1966
-1967    packaged_by: List[Author] = Field(default_factory=list)
-1968    """The persons that have packaged and uploaded this model.
-1969    Only required if those persons differ from the `authors`."""
-1970
-1971    parent: Optional[LinkedModel] = None
-1972    """The model from which this model is derived, e.g. by fine-tuning the weights."""
-1973
-1974    # todo: add parent self check once we have `id`
-1975    # @model_validator(mode="after")
-1976    # def validate_parent_is_not_self(self) -> Self:
-1977    #     if self.parent is not None and self.parent == self.id:
-1978    #         raise ValueError("The model may not reference itself as parent model")
-1979
-1980    #     return self
-1981
-1982    run_mode: Annotated[
-1983        Optional[RunMode],
-1984        warn(None, "Run mode '{value}' has limited support across consumer softwares."),
-1985    ] = None
-1986    """Custom run mode for this model: for more complex prediction procedures like test time
-1987    data augmentation that currently cannot be expressed in the specification.
-1988    No standard run modes are defined yet."""
-1989
-1990    timestamp: Datetime = Datetime(datetime.now())
-1991    """Timestamp in [ISO 8601](#https://en.wikipedia.org/wiki/ISO_8601) format
-1992    with a few restrictions listed [here](https://docs.python.org/3/library/datetime.html#datetime.datetime.fromisoformat).
-1993    (In Python a datetime object is valid, too)."""
+1965        for i, out in enumerate(outputs):
+1966            valid_independent_refs: Dict[
+1967                Tuple[TensorId, AxisId],
+1968                Tuple[TensorDescr, AnyAxis, Union[int, ParameterizedSize]],
+1969            ] = {
+1970                **{
+1971                    (out.id, a.id): (out, a, a.size)
+1972                    for a in out.axes
+1973                    if not isinstance(a, BatchAxis)
+1974                    and isinstance(a.size, (int, ParameterizedSize))
+1975                },
+1976                **input_size_refs,
+1977                **output_size_refs,
+1978            }
+1979            for a, ax in enumerate(out.axes):
+1980                cls._validate_axis(
+1981                    "outputs",
+1982                    i,
+1983                    out.id,
+1984                    a,
+1985                    ax,
+1986                    valid_independent_refs=valid_independent_refs,
+1987                )
+1988
+1989        return outputs
+1990
+1991    packaged_by: List[Author] = Field(default_factory=list)
+1992    """The persons that have packaged and uploaded this model.
+1993    Only required if those persons differ from the `authors`."""
 1994
-1995    training_data: Union[LinkedDataset, DatasetDescr, None] = None
-1996    """The dataset used to train this model"""
+1995    parent: Optional[LinkedModel] = None
+1996    """The model from which this model is derived, e.g. by fine-tuning the weights."""
 1997
-1998    weights: WeightsDescr
-1999    """The weights for this model.
-2000    Weights can be given for different formats, but should otherwise be equivalent.
-2001    The available weight formats determine which consumers can use this model."""
-2002
-2003    @model_validator(mode="after")
-2004    def _add_default_cover(self) -> Self:
-2005        if not validation_context_var.get().perform_io_checks or self.covers:
-2006            return self
-2007
-2008        try:
-2009            generated_covers = generate_covers(
-2010                [(t, load_array(t.test_tensor.download().path)) for t in self.inputs],
-2011                [(t, load_array(t.test_tensor.download().path)) for t in self.outputs],
-2012            )
-2013        except Exception as e:
-2014            issue_warning(
-2015                "Failed to generate cover image(s): {e}",
-2016                value=self.covers,
-2017                msg_context=dict(e=e),
-2018            )
-2019        else:
-2020            self.covers.extend(generated_covers)
+1998    # todo: add parent self check once we have `id`
+1999    # @model_validator(mode="after")
+2000    # def validate_parent_is_not_self(self) -> Self:
+2001    #     if self.parent is not None and self.parent == self.id:
+2002    #         raise ValueError("The model may not reference itself as parent model")
+2003
+2004    #     return self
+2005
+2006    run_mode: Annotated[
+2007        Optional[RunMode],
+2008        warn(None, "Run mode '{value}' has limited support across consumer softwares."),
+2009    ] = None
+2010    """Custom run mode for this model: for more complex prediction procedures like test time
+2011    data augmentation that currently cannot be expressed in the specification.
+2012    No standard run modes are defined yet."""
+2013
+2014    timestamp: Datetime = Datetime(datetime.now())
+2015    """Timestamp in [ISO 8601](#https://en.wikipedia.org/wiki/ISO_8601) format
+2016    with a few restrictions listed [here](https://docs.python.org/3/library/datetime.html#datetime.datetime.fromisoformat).
+2017    (In Python a datetime object is valid, too)."""
+2018
+2019    training_data: Union[LinkedDataset, DatasetDescr, None] = None
+2020    """The dataset used to train this model"""
 2021
-2022        return self
-2023
-2024    def get_input_test_arrays(self) -> List[NDArray[Any]]:
-2025        data = [load_array(ipt.test_tensor.download().path) for ipt in self.inputs]
-2026        assert all(isinstance(d, np.ndarray) for d in data)
-2027        return data
-2028
-2029    def get_output_test_arrays(self) -> List[NDArray[Any]]:
-2030        data = [load_array(out.test_tensor.download().path) for out in self.outputs]
-2031        assert all(isinstance(d, np.ndarray) for d in data)
-2032        return data
-2033
-2034    def get_tensor_sizes(
-2035        self, n: ParameterizedSize.N, batch_size: int
-2036    ) -> Dict[TensorId, Dict[AxisId, int]]:
-2037        all_axes = {
-2038            t.id: {a.id: a for a in t.axes} for t in chain(self.inputs, self.outputs)
-2039        }
-2040
-2041        ret: Dict[TensorId, Dict[AxisId, int]] = {}
-2042        for t_descr in chain(self.inputs, self.outputs):
-2043            ret[t_descr.id] = {}
-2044            for a in t_descr.axes:
-2045                if a.size is None:
-2046                    assert isinstance(a, BatchAxis)
-2047                    s = batch_size
-2048                elif isinstance(a.size, int):
-2049                    s = a.size
-2050                elif isinstance(a.size, ParameterizedSize):
-2051                    s = a.size.get_size(n)
-2052                elif isinstance(a.size, SizeReference):
-2053                    assert not isinstance(a, BatchAxis)
-2054                    ref_axis = all_axes[a.size.tensor_id][a.size.axis_id]
-2055                    assert not isinstance(ref_axis, BatchAxis)
-2056                    s = a.size.get_size(axis=a, ref_axis=ref_axis, n=n)
-2057                else:
-2058                    assert_never(a.size)
-2059
-2060                ret[t_descr.id][a.id] = s
-2061
-2062        return ret
-2063
-2064    @model_validator(mode="before")
-2065    @classmethod
-2066    def _convert(cls, data: Dict[str, Any]) -> Dict[str, Any]:
-2067        if (
-2068            data.get("type") == "model"
-2069            and isinstance(fv := data.get("format_version"), str)
-2070            and (fv.startswith("0.3.") or fv.startswith("0.4."))
-2071        ):
-2072            m04 = _ModelDescr_v0_4.load(data)
-2073            if not isinstance(m04, InvalidDescr):
-2074                return _model_conv.convert_as_dict(m04)
-2075
-2076        return data
-2077
-2078
-2079class _ModelConv(Converter[_ModelDescr_v0_4, ModelDescr]):
-2080    def _convert(
-2081        self, src: _ModelDescr_v0_4, tgt: "type[ModelDescr] | type[dict[str, Any]]"
-2082    ) -> "ModelDescr | dict[str, Any]":
-2083        def conv_authors(auths: Optional[Sequence[_Author_v0_4]]):
-2084            conv = (
-2085                _author_conv.convert if TYPE_CHECKING else _author_conv.convert_as_dict
-2086            )
-2087            return None if auths is None else [conv(a) for a in auths]
-2088
-2089        if TYPE_CHECKING:
-2090            arch_file_conv = _arch_file_conv.convert
-2091            arch_lib_conv = _arch_lib_conv.convert
-2092        else:
-2093            arch_file_conv = _arch_file_conv.convert_as_dict
-2094            arch_lib_conv = _arch_lib_conv.convert_as_dict
-2095
-2096        input_size_refs = {
-2097            ipt.name: {
-2098                a: s
-2099                for a, s in zip(
-2100                    ipt.axes,
-2101                    (
-2102                        ipt.shape.min
-2103                        if isinstance(ipt.shape, _ParameterizedInputShape_v0_4)
-2104                        else ipt.shape
-2105                    ),
-2106                )
-2107            }
-2108            for ipt in src.inputs
-2109            if ipt.shape
-2110        }
-2111        output_size_refs = {
-2112            **{
-2113                out.name: {a: s for a, s in zip(out.axes, out.shape)}
-2114                for out in src.outputs
-2115                if not isinstance(out.shape, _ImplicitOutputShape_v0_4)
-2116            },
-2117            **input_size_refs,
-2118        }
+2022    weights: WeightsDescr
+2023    """The weights for this model.
+2024    Weights can be given for different formats, but should otherwise be equivalent.
+2025    The available weight formats determine which consumers can use this model."""
+2026
+2027    @model_validator(mode="after")
+2028    def _add_default_cover(self) -> Self:
+2029        if not validation_context_var.get().perform_io_checks or self.covers:
+2030            return self
+2031
+2032        try:
+2033            generated_covers = generate_covers(
+2034                [(t, load_array(t.test_tensor.download().path)) for t in self.inputs],
+2035                [(t, load_array(t.test_tensor.download().path)) for t in self.outputs],
+2036            )
+2037        except Exception as e:
+2038            issue_warning(
+2039                "Failed to generate cover image(s): {e}",
+2040                value=self.covers,
+2041                msg_context=dict(e=e),
+2042            )
+2043        else:
+2044            self.covers.extend(generated_covers)
+2045
+2046        return self
+2047
+2048    def get_input_test_arrays(self) -> List[NDArray[Any]]:
+2049        data = [load_array(ipt.test_tensor.download().path) for ipt in self.inputs]
+2050        assert all(isinstance(d, np.ndarray) for d in data)
+2051        return data
+2052
+2053    def get_output_test_arrays(self) -> List[NDArray[Any]]:
+2054        data = [load_array(out.test_tensor.download().path) for out in self.outputs]
+2055        assert all(isinstance(d, np.ndarray) for d in data)
+2056        return data
+2057
+2058    def get_tensor_sizes(
+2059        self, n: ParameterizedSize.N, batch_size: int
+2060    ) -> Dict[TensorId, Dict[AxisId, int]]:
+2061        all_axes = {
+2062            t.id: {a.id: a for a in t.axes} for t in chain(self.inputs, self.outputs)
+2063        }
+2064
+2065        ret: Dict[TensorId, Dict[AxisId, int]] = {}
+2066        for t_descr in chain(self.inputs, self.outputs):
+2067            ret[t_descr.id] = {}
+2068            for a in t_descr.axes:
+2069                if a.size is None:
+2070                    assert isinstance(a, BatchAxis)
+2071                    s = batch_size
+2072                elif isinstance(a.size, int):
+2073                    s = a.size
+2074                elif isinstance(a.size, ParameterizedSize):
+2075                    s = a.size.get_size(n)
+2076                elif isinstance(a.size, SizeReference):
+2077                    assert not isinstance(a, BatchAxis)
+2078                    ref_axis = all_axes[a.size.tensor_id][a.size.axis_id]
+2079                    assert not isinstance(ref_axis, BatchAxis)
+2080                    s = a.size.get_size(axis=a, ref_axis=ref_axis, n=n)
+2081                else:
+2082                    assert_never(a.size)
+2083
+2084                ret[t_descr.id][a.id] = s
+2085
+2086        return ret
+2087
+2088    @model_validator(mode="before")
+2089    @classmethod
+2090    def _convert(cls, data: Dict[str, Any]) -> Dict[str, Any]:
+2091        if (
+2092            data.get("type") == "model"
+2093            and isinstance(fv := data.get("format_version"), str)
+2094            and (fv.startswith("0.3.") or fv.startswith("0.4."))
+2095        ):
+2096            m04 = _ModelDescr_v0_4.load(data)
+2097            if not isinstance(m04, InvalidDescr):
+2098                return _model_conv.convert_as_dict(m04)
+2099
+2100        return data
+2101
+2102
+2103class _ModelConv(Converter[_ModelDescr_v0_4, ModelDescr]):
+2104    def _convert(
+2105        self, src: _ModelDescr_v0_4, tgt: "type[ModelDescr] | type[dict[str, Any]]"
+2106    ) -> "ModelDescr | dict[str, Any]":
+2107        def conv_authors(auths: Optional[Sequence[_Author_v0_4]]):
+2108            conv = (
+2109                _author_conv.convert if TYPE_CHECKING else _author_conv.convert_as_dict
+2110            )
+2111            return None if auths is None else [conv(a) for a in auths]
+2112
+2113        if TYPE_CHECKING:
+2114            arch_file_conv = _arch_file_conv.convert
+2115            arch_lib_conv = _arch_lib_conv.convert
+2116        else:
+2117            arch_file_conv = _arch_file_conv.convert_as_dict
+2118            arch_lib_conv = _arch_lib_conv.convert_as_dict
 2119
-2120        return tgt(
-2121            attachments=(
-2122                []
-2123                if src.attachments is None
-2124                else [FileDescr(source=f) for f in src.attachments.files]
-2125            ),
-2126            authors=[
-2127                _author_conv.convert_as_dict(a) for a in src.authors
-2128            ],  # pyright: ignore[reportArgumentType]
-2129            cite=[
-2130                {"text": c.text, "doi": c.doi, "url": c.url} for c in src.cite
-2131            ],  # pyright: ignore[reportArgumentType]
-2132            config=src.config,
-2133            covers=src.covers,
-2134            description=src.description,
-2135            documentation=src.documentation,  # pyright: ignore[reportArgumentType]
-2136            format_version="0.5.0",
-2137            git_repo=src.git_repo,  # pyright: ignore[reportArgumentType]
-2138            icon=src.icon,
-2139            id=src.id,
-2140            id_emoji=src.id_emoji,
-2141            license=src.license,  # type: ignore
-2142            links=src.links,
-2143            maintainers=[
-2144                _maintainer_conv.convert_as_dict(m) for m in src.maintainers
-2145            ],  # pyright: ignore[reportArgumentType]
-2146            name=src.name,
-2147            tags=src.tags,
-2148            type=src.type,
-2149            uploader=src.uploader,
-2150            version=src.version,
-2151            inputs=[  # pyright: ignore[reportArgumentType]
-2152                _input_tensor_conv.convert_as_dict(ipt, tt, st, input_size_refs)
-2153                for ipt, tt, st, in zip(
-2154                    src.inputs,
-2155                    src.test_inputs,
-2156                    src.sample_inputs or [None] * len(src.test_inputs),
-2157                )
-2158            ],
-2159            outputs=[  # pyright: ignore[reportArgumentType]
-2160                _output_tensor_conv.convert_as_dict(out, tt, st, output_size_refs)
-2161                for out, tt, st, in zip(
-2162                    src.outputs,
-2163                    src.test_outputs,
-2164                    src.sample_outputs or [None] * len(src.test_outputs),
-2165                )
-2166            ],
-2167            weights=(WeightsDescr if TYPE_CHECKING else dict)(
-2168                keras_hdf5=(w := src.weights.keras_hdf5)
-2169                and (KerasHdf5WeightsDescr if TYPE_CHECKING else dict)(
-2170                    authors=conv_authors(w.authors),
-2171                    source=w.source,
-2172                    tensorflow_version=w.tensorflow_version or Version("1.15"),
-2173                    parent=w.parent,
-2174                ),
-2175                onnx=(w := src.weights.onnx)
-2176                and (OnnxWeightsDescr if TYPE_CHECKING else dict)(
-2177                    source=w.source,
-2178                    authors=conv_authors(w.authors),
-2179                    parent=w.parent,
-2180                    opset_version=w.opset_version or 15,
-2181                ),
-2182                pytorch_state_dict=(w := src.weights.pytorch_state_dict)
-2183                and (PytorchStateDictWeightsDescr if TYPE_CHECKING else dict)(
-2184                    source=w.source,
-2185                    authors=conv_authors(w.authors),
-2186                    parent=w.parent,
-2187                    architecture=(
-2188                        arch_file_conv(
-2189                            w.architecture,
-2190                            w.architecture_sha256,
-2191                            w.kwargs,
-2192                        )
-2193                        if isinstance(w.architecture, _CallableFromFile_v0_4)
-2194                        else arch_lib_conv(w.architecture, w.kwargs)
-2195                    ),
-2196                    pytorch_version=w.pytorch_version or Version("1.10"),
-2197                    dependencies=(
-2198                        None
-2199                        if w.dependencies is None
-2200                        else (EnvironmentFileDescr if TYPE_CHECKING else dict)(
-2201                            source=cast(
-2202                                ImportantFileSource,
-2203                                str(deps := w.dependencies)[
-2204                                    (
-2205                                        len("conda:")
-2206                                        if str(deps).startswith("conda:")
-2207                                        else 0
-2208                                    ) :
-2209                                ],
-2210                            )
-2211                        )
-2212                    ),
-2213                ),
-2214                tensorflow_js=(w := src.weights.tensorflow_js)
-2215                and (TensorflowJsWeightsDescr if TYPE_CHECKING else dict)(
-2216                    source=w.source,
-2217                    authors=conv_authors(w.authors),
-2218                    parent=w.parent,
-2219                    tensorflow_version=w.tensorflow_version or Version("1.15"),
-2220                ),
-2221                tensorflow_saved_model_bundle=(
-2222                    w := src.weights.tensorflow_saved_model_bundle
-2223                )
-2224                and (TensorflowSavedModelBundleWeightsDescr if TYPE_CHECKING else dict)(
-2225                    authors=conv_authors(w.authors),
-2226                    parent=w.parent,
-2227                    source=w.source,
-2228                    tensorflow_version=w.tensorflow_version or Version("1.15"),
-2229                    dependencies=(
-2230                        None
-2231                        if w.dependencies is None
-2232                        else (EnvironmentFileDescr if TYPE_CHECKING else dict)(
-2233                            source=cast(
-2234                                ImportantFileSource,
-2235                                (
-2236                                    str(w.dependencies)[len("conda:") :]
-2237                                    if str(w.dependencies).startswith("conda:")
-2238                                    else str(w.dependencies)
-2239                                ),
-2240                            )
-2241                        )
-2242                    ),
-2243                ),
-2244                torchscript=(w := src.weights.torchscript)
-2245                and (TorchscriptWeightsDescr if TYPE_CHECKING else dict)(
-2246                    source=w.source,
-2247                    authors=conv_authors(w.authors),
-2248                    parent=w.parent,
-2249                    pytorch_version=w.pytorch_version or Version("1.10"),
-2250                ),
-2251            ),
-2252        )
-2253
-2254
-2255_model_conv = _ModelConv(_ModelDescr_v0_4, ModelDescr)
-2256
-2257
-2258# create better cover images for 3d data and non-image outputs
-2259def generate_covers(
-2260    inputs: Sequence[Tuple[InputTensorDescr, NDArray[Any]]],
-2261    outputs: Sequence[Tuple[OutputTensorDescr, NDArray[Any]]],
-2262) -> List[Path]:
-2263    def squeeze(
-2264        data: NDArray[Any], axes: Sequence[AnyAxis]
-2265    ) -> Tuple[NDArray[Any], List[AnyAxis]]:
-2266        """apply numpy.ndarray.squeeze while keeping track of the axis descriptions remaining"""
-2267        if data.ndim != len(axes):
-2268            raise ValueError(
-2269                f"tensor shape {data.shape} does not match described axes"
-2270                + f" {[a.id for a in axes]}"
-2271            )
-2272
-2273        axes = [deepcopy(a) for a, s in zip(axes, data.shape) if s != 1]
-2274        return data.squeeze(), axes
-2275
-2276    def normalize(
-2277        data: NDArray[Any], axis: Optional[Tuple[int, ...]], eps: float = 1e-7
-2278    ) -> NDArray[np.float32]:
-2279        data = data.astype("float32")
-2280        data -= data.min(axis=axis, keepdims=True)
-2281        data /= data.max(axis=axis, keepdims=True) + eps
-2282        return data
-2283
-2284    def to_2d_image(data: NDArray[Any], axes: Sequence[AnyAxis]):
-2285        original_shape = data.shape
-2286        data, axes = squeeze(data, axes)
-2287
-2288        # take slice fom any batch or index axis if needed
-2289        # and convert the first channel axis and take a slice from any additional channel axes
-2290        slices: Tuple[slice, ...] = ()
-2291        ndim = data.ndim
-2292        ndim_need = 3 if any(isinstance(a, ChannelAxis) for a in axes) else 2
-2293        has_c_axis = False
-2294        for i, a in enumerate(axes):
-2295            s = data.shape[i]
-2296            assert s > 1
-2297            if isinstance(a, (BatchAxis, IndexAxis)) and ndim > ndim_need:
-2298                data = data[slices + (slice(s // 2 - 1, s // 2),)]
-2299                ndim -= 1
-2300            elif isinstance(a, ChannelAxis):
-2301                if has_c_axis:
-2302                    # second channel axis
-2303                    data = data[slices + (slice(0, 1),)]
-2304                    ndim -= 1
-2305                else:
-2306                    has_c_axis = True
-2307                    if s == 2:
-2308                        # visualize two channels with cyan and magenta
-2309                        data = np.concatenate(
-2310                            [
-2311                                data[slices + (slice(1, 2),)],
-2312                                data[slices + (slice(0, 1),)],
-2313                                (
-2314                                    data[slices + (slice(0, 1),)]
-2315                                    + data[slices + (slice(1, 2),)]
-2316                                )
-2317                                / 2,  # TODO: take maximum instead?
-2318                            ],
-2319                            axis=i,
-2320                        )
-2321                    elif data.shape[i] == 3:
-2322                        pass  # visualize 3 channels as RGB
-2323                    else:
-2324                        # visualize first 3 channels as RGB
-2325                        data = data[slices + (slice(3),)]
-2326
-2327                    assert data.shape[i] == 3
-2328
-2329            slices += (slice(None),)  # type: ignore
-2330
-2331        data, axes = squeeze(data, axes)
-2332        assert len(axes) == ndim
-2333        # take slice from z axis if needed
-2334        slices = ()
-2335        if ndim > ndim_need:
-2336            for i, a in enumerate(axes):
-2337                s = data.shape[i]
-2338                if a.id.root == "z":
-2339                    data = data[slices + (slice(s // 2 - 1, s // 2),)]
-2340                    data, axes = squeeze(data, axes)
-2341                    ndim -= 1
-2342                    break
-2343
-2344            slices += (slice(None),)
-2345
-2346        # take slice from any space or time axis
-2347        slices = ()
-2348
-2349        for i, a in enumerate(axes):
-2350            if ndim <= ndim_need:
-2351                break
+2120        input_size_refs = {
+2121            ipt.name: {
+2122                a: s
+2123                for a, s in zip(
+2124                    ipt.axes,
+2125                    (
+2126                        ipt.shape.min
+2127                        if isinstance(ipt.shape, _ParameterizedInputShape_v0_4)
+2128                        else ipt.shape
+2129                    ),
+2130                )
+2131            }
+2132            for ipt in src.inputs
+2133            if ipt.shape
+2134        }
+2135        output_size_refs = {
+2136            **{
+2137                out.name: {a: s for a, s in zip(out.axes, out.shape)}
+2138                for out in src.outputs
+2139                if not isinstance(out.shape, _ImplicitOutputShape_v0_4)
+2140            },
+2141            **input_size_refs,
+2142        }
+2143
+2144        return tgt(
+2145            attachments=(
+2146                []
+2147                if src.attachments is None
+2148                else [FileDescr(source=f) for f in src.attachments.files]
+2149            ),
+2150            authors=[
+2151                _author_conv.convert_as_dict(a) for a in src.authors
+2152            ],  # pyright: ignore[reportArgumentType]
+2153            cite=[
+2154                {"text": c.text, "doi": c.doi, "url": c.url} for c in src.cite
+2155            ],  # pyright: ignore[reportArgumentType]
+2156            config=src.config,
+2157            covers=src.covers,
+2158            description=src.description,
+2159            documentation=src.documentation,  # pyright: ignore[reportArgumentType]
+2160            format_version="0.5.0",
+2161            git_repo=src.git_repo,  # pyright: ignore[reportArgumentType]
+2162            icon=src.icon,
+2163            id=src.id,
+2164            id_emoji=src.id_emoji,
+2165            license=src.license,  # type: ignore
+2166            links=src.links,
+2167            maintainers=[
+2168                _maintainer_conv.convert_as_dict(m) for m in src.maintainers
+2169            ],  # pyright: ignore[reportArgumentType]
+2170            name=src.name,
+2171            tags=src.tags,
+2172            type=src.type,
+2173            uploader=src.uploader,
+2174            version=src.version,
+2175            inputs=[  # pyright: ignore[reportArgumentType]
+2176                _input_tensor_conv.convert_as_dict(ipt, tt, st, input_size_refs)
+2177                for ipt, tt, st, in zip(
+2178                    src.inputs,
+2179                    src.test_inputs,
+2180                    src.sample_inputs or [None] * len(src.test_inputs),
+2181                )
+2182            ],
+2183            outputs=[  # pyright: ignore[reportArgumentType]
+2184                _output_tensor_conv.convert_as_dict(out, tt, st, output_size_refs)
+2185                for out, tt, st, in zip(
+2186                    src.outputs,
+2187                    src.test_outputs,
+2188                    src.sample_outputs or [None] * len(src.test_outputs),
+2189                )
+2190            ],
+2191            weights=(WeightsDescr if TYPE_CHECKING else dict)(
+2192                keras_hdf5=(w := src.weights.keras_hdf5)
+2193                and (KerasHdf5WeightsDescr if TYPE_CHECKING else dict)(
+2194                    authors=conv_authors(w.authors),
+2195                    source=w.source,
+2196                    tensorflow_version=w.tensorflow_version or Version("1.15"),
+2197                    parent=w.parent,
+2198                ),
+2199                onnx=(w := src.weights.onnx)
+2200                and (OnnxWeightsDescr if TYPE_CHECKING else dict)(
+2201                    source=w.source,
+2202                    authors=conv_authors(w.authors),
+2203                    parent=w.parent,
+2204                    opset_version=w.opset_version or 15,
+2205                ),
+2206                pytorch_state_dict=(w := src.weights.pytorch_state_dict)
+2207                and (PytorchStateDictWeightsDescr if TYPE_CHECKING else dict)(
+2208                    source=w.source,
+2209                    authors=conv_authors(w.authors),
+2210                    parent=w.parent,
+2211                    architecture=(
+2212                        arch_file_conv(
+2213                            w.architecture,
+2214                            w.architecture_sha256,
+2215                            w.kwargs,
+2216                        )
+2217                        if isinstance(w.architecture, _CallableFromFile_v0_4)
+2218                        else arch_lib_conv(w.architecture, w.kwargs)
+2219                    ),
+2220                    pytorch_version=w.pytorch_version or Version("1.10"),
+2221                    dependencies=(
+2222                        None
+2223                        if w.dependencies is None
+2224                        else (EnvironmentFileDescr if TYPE_CHECKING else dict)(
+2225                            source=cast(
+2226                                ImportantFileSource,
+2227                                str(deps := w.dependencies)[
+2228                                    (
+2229                                        len("conda:")
+2230                                        if str(deps).startswith("conda:")
+2231                                        else 0
+2232                                    ) :
+2233                                ],
+2234                            )
+2235                        )
+2236                    ),
+2237                ),
+2238                tensorflow_js=(w := src.weights.tensorflow_js)
+2239                and (TensorflowJsWeightsDescr if TYPE_CHECKING else dict)(
+2240                    source=w.source,
+2241                    authors=conv_authors(w.authors),
+2242                    parent=w.parent,
+2243                    tensorflow_version=w.tensorflow_version or Version("1.15"),
+2244                ),
+2245                tensorflow_saved_model_bundle=(
+2246                    w := src.weights.tensorflow_saved_model_bundle
+2247                )
+2248                and (TensorflowSavedModelBundleWeightsDescr if TYPE_CHECKING else dict)(
+2249                    authors=conv_authors(w.authors),
+2250                    parent=w.parent,
+2251                    source=w.source,
+2252                    tensorflow_version=w.tensorflow_version or Version("1.15"),
+2253                    dependencies=(
+2254                        None
+2255                        if w.dependencies is None
+2256                        else (EnvironmentFileDescr if TYPE_CHECKING else dict)(
+2257                            source=cast(
+2258                                ImportantFileSource,
+2259                                (
+2260                                    str(w.dependencies)[len("conda:") :]
+2261                                    if str(w.dependencies).startswith("conda:")
+2262                                    else str(w.dependencies)
+2263                                ),
+2264                            )
+2265                        )
+2266                    ),
+2267                ),
+2268                torchscript=(w := src.weights.torchscript)
+2269                and (TorchscriptWeightsDescr if TYPE_CHECKING else dict)(
+2270                    source=w.source,
+2271                    authors=conv_authors(w.authors),
+2272                    parent=w.parent,
+2273                    pytorch_version=w.pytorch_version or Version("1.10"),
+2274                ),
+2275            ),
+2276        )
+2277
+2278
+2279_model_conv = _ModelConv(_ModelDescr_v0_4, ModelDescr)
+2280
+2281
+2282# create better cover images for 3d data and non-image outputs
+2283def generate_covers(
+2284    inputs: Sequence[Tuple[InputTensorDescr, NDArray[Any]]],
+2285    outputs: Sequence[Tuple[OutputTensorDescr, NDArray[Any]]],
+2286) -> List[Path]:
+2287    def squeeze(
+2288        data: NDArray[Any], axes: Sequence[AnyAxis]
+2289    ) -> Tuple[NDArray[Any], List[AnyAxis]]:
+2290        """apply numpy.ndarray.squeeze while keeping track of the axis descriptions remaining"""
+2291        if data.ndim != len(axes):
+2292            raise ValueError(
+2293                f"tensor shape {data.shape} does not match described axes"
+2294                + f" {[a.id for a in axes]}"
+2295            )
+2296
+2297        axes = [deepcopy(a) for a, s in zip(axes, data.shape) if s != 1]
+2298        return data.squeeze(), axes
+2299
+2300    def normalize(
+2301        data: NDArray[Any], axis: Optional[Tuple[int, ...]], eps: float = 1e-7
+2302    ) -> NDArray[np.float32]:
+2303        data = data.astype("float32")
+2304        data -= data.min(axis=axis, keepdims=True)
+2305        data /= data.max(axis=axis, keepdims=True) + eps
+2306        return data
+2307
+2308    def to_2d_image(data: NDArray[Any], axes: Sequence[AnyAxis]):
+2309        original_shape = data.shape
+2310        data, axes = squeeze(data, axes)
+2311
+2312        # take slice fom any batch or index axis if needed
+2313        # and convert the first channel axis and take a slice from any additional channel axes
+2314        slices: Tuple[slice, ...] = ()
+2315        ndim = data.ndim
+2316        ndim_need = 3 if any(isinstance(a, ChannelAxis) for a in axes) else 2
+2317        has_c_axis = False
+2318        for i, a in enumerate(axes):
+2319            s = data.shape[i]
+2320            assert s > 1
+2321            if isinstance(a, (BatchAxis, IndexAxis)) and ndim > ndim_need:
+2322                data = data[slices + (slice(s // 2 - 1, s // 2),)]
+2323                ndim -= 1
+2324            elif isinstance(a, ChannelAxis):
+2325                if has_c_axis:
+2326                    # second channel axis
+2327                    data = data[slices + (slice(0, 1),)]
+2328                    ndim -= 1
+2329                else:
+2330                    has_c_axis = True
+2331                    if s == 2:
+2332                        # visualize two channels with cyan and magenta
+2333                        data = np.concatenate(
+2334                            [
+2335                                data[slices + (slice(1, 2),)],
+2336                                data[slices + (slice(0, 1),)],
+2337                                (
+2338                                    data[slices + (slice(0, 1),)]
+2339                                    + data[slices + (slice(1, 2),)]
+2340                                )
+2341                                / 2,  # TODO: take maximum instead?
+2342                            ],
+2343                            axis=i,
+2344                        )
+2345                    elif data.shape[i] == 3:
+2346                        pass  # visualize 3 channels as RGB
+2347                    else:
+2348                        # visualize first 3 channels as RGB
+2349                        data = data[slices + (slice(3),)]
+2350
+2351                    assert data.shape[i] == 3
 2352
-2353            s = data.shape[i]
-2354            assert s > 1
-2355            if isinstance(
-2356                a, (SpaceInputAxis, SpaceOutputAxis, TimeInputAxis, TimeOutputAxis)
-2357            ):
-2358                data = data[slices + (slice(s // 2 - 1, s // 2),)]
-2359                ndim -= 1
-2360
-2361            slices += (slice(None),)  # type: ignore
-2362
-2363        del slices
-2364        data, axes = squeeze(data, axes)
-2365        assert len(axes) == ndim
-2366
-2367        if (has_c_axis and ndim != 3) or ndim != 2:
-2368            raise ValueError(
-2369                f"Failed to construct cover image from shape {original_shape}"
-2370            )
-2371
-2372        if not has_c_axis:
-2373            assert ndim == 2
-2374            data = np.repeat(data[:, :, None], 3, axis=2)
-2375            axes.append(ChannelAxis(channel_names=list(map(Identifier, "RGB"))))
-2376            ndim += 1
-2377
-2378        assert ndim == 3
-2379
-2380        # transpose axis order such that longest axis comes first...
-2381        axis_order = list(np.argsort(list(data.shape)))
-2382        axis_order.reverse()
-2383        # ... and channel axis is last
-2384        c = [i for i in range(3) if isinstance(axes[i], ChannelAxis)][0]
-2385        axis_order.append(axis_order.pop(c))
-2386        axes = [axes[ao] for ao in axis_order]
-2387        data = data.transpose(axis_order)
-2388
-2389        # h, w = data.shape[:2]
-2390        # if h / w  in (1.0 or 2.0):
-2391        #     pass
-2392        # elif h / w < 2:
-2393        # TODO: enforce 2:1 or 1:1 aspect ratio for generated cover images
-2394
-2395        norm_along = (
-2396            tuple(i for i, a in enumerate(axes) if a.type in ("space", "time")) or None
-2397        )
-2398        # normalize the data and map to 8 bit
-2399        data = normalize(data, norm_along)
-2400        data = (data * 255).astype("uint8")
+2353            slices += (slice(None),)  # type: ignore
+2354
+2355        data, axes = squeeze(data, axes)
+2356        assert len(axes) == ndim
+2357        # take slice from z axis if needed
+2358        slices = ()
+2359        if ndim > ndim_need:
+2360            for i, a in enumerate(axes):
+2361                s = data.shape[i]
+2362                if a.id == AxisId("z"):
+2363                    data = data[slices + (slice(s // 2 - 1, s // 2),)]
+2364                    data, axes = squeeze(data, axes)
+2365                    ndim -= 1
+2366                    break
+2367
+2368            slices += (slice(None),)
+2369
+2370        # take slice from any space or time axis
+2371        slices = ()
+2372
+2373        for i, a in enumerate(axes):
+2374            if ndim <= ndim_need:
+2375                break
+2376
+2377            s = data.shape[i]
+2378            assert s > 1
+2379            if isinstance(
+2380                a, (SpaceInputAxis, SpaceOutputAxis, TimeInputAxis, TimeOutputAxis)
+2381            ):
+2382                data = data[slices + (slice(s // 2 - 1, s // 2),)]
+2383                ndim -= 1
+2384
+2385            slices += (slice(None),)  # type: ignore
+2386
+2387        del slices
+2388        data, axes = squeeze(data, axes)
+2389        assert len(axes) == ndim
+2390
+2391        if (has_c_axis and ndim != 3) or ndim != 2:
+2392            raise ValueError(
+2393                f"Failed to construct cover image from shape {original_shape}"
+2394            )
+2395
+2396        if not has_c_axis:
+2397            assert ndim == 2
+2398            data = np.repeat(data[:, :, None], 3, axis=2)
+2399            axes.append(ChannelAxis(channel_names=list(map(Identifier, "RGB"))))
+2400            ndim += 1
 2401
-2402        return data
+2402        assert ndim == 3
 2403
-2404    def create_diagonal_split_image(im0: NDArray[Any], im1: NDArray[Any]):
-2405        assert im0.dtype == im1.dtype == np.uint8
-2406        assert im0.shape == im1.shape
-2407        assert im0.ndim == 3
-2408        N, M, C = im0.shape
-2409        assert C == 3
-2410        out = np.ones((N, M, C), dtype="uint8")
-2411        for c in range(C):
-2412            outc = np.tril(im0[..., c])
-2413            mask = outc == 0
-2414            outc[mask] = np.triu(im1[..., c])[mask]
-2415            out[..., c] = outc
-2416
-2417        return out
+2404        # transpose axis order such that longest axis comes first...
+2405        axis_order = list(np.argsort(list(data.shape)))
+2406        axis_order.reverse()
+2407        # ... and channel axis is last
+2408        c = [i for i in range(3) if isinstance(axes[i], ChannelAxis)][0]
+2409        axis_order.append(axis_order.pop(c))
+2410        axes = [axes[ao] for ao in axis_order]
+2411        data = data.transpose(axis_order)
+2412
+2413        # h, w = data.shape[:2]
+2414        # if h / w  in (1.0 or 2.0):
+2415        #     pass
+2416        # elif h / w < 2:
+2417        # TODO: enforce 2:1 or 1:1 aspect ratio for generated cover images
 2418
-2419    ipt_descr, ipt = inputs[0]
-2420    out_descr, out = outputs[0]
-2421
-2422    ipt_img = to_2d_image(ipt, ipt_descr.axes)
-2423    out_img = to_2d_image(out, out_descr.axes)
-2424
-2425    cover_folder = Path(mkdtemp())
-2426    if ipt_img.shape == out_img.shape:
-2427        covers = [cover_folder / "cover.png"]
-2428        imageio.imwrite(covers[0], create_diagonal_split_image(ipt_img, out_img))
-2429    else:
-2430        covers = [cover_folder / "input.png", cover_folder / "output.png"]
-2431        imageio.imwrite(covers[0], ipt_img)
-2432        imageio.imwrite(covers[1], out_img)
-2433
-2434    return covers
+2419        norm_along = (
+2420            tuple(i for i, a in enumerate(axes) if a.type in ("space", "time")) or None
+2421        )
+2422        # normalize the data and map to 8 bit
+2423        data = normalize(data, norm_along)
+2424        data = (data * 255).astype("uint8")
+2425
+2426        return data
+2427
+2428    def create_diagonal_split_image(im0: NDArray[Any], im1: NDArray[Any]):
+2429        assert im0.dtype == im1.dtype == np.uint8
+2430        assert im0.shape == im1.shape
+2431        assert im0.ndim == 3
+2432        N, M, C = im0.shape
+2433        assert C == 3
+2434        out = np.ones((N, M, C), dtype="uint8")
+2435        for c in range(C):
+2436            outc = np.tril(im0[..., c])
+2437            mask = outc == 0
+2438            outc[mask] = np.triu(im1[..., c])[mask]
+2439            out[..., c] = outc
+2440
+2441        return out
+2442
+2443    ipt_descr, ipt = inputs[0]
+2444    out_descr, out = outputs[0]
+2445
+2446    ipt_img = to_2d_image(ipt, ipt_descr.axes)
+2447    out_img = to_2d_image(out, out_descr.axes)
+2448
+2449    cover_folder = Path(mkdtemp())
+2450    if ipt_img.shape == out_img.shape:
+2451        covers = [cover_folder / "cover.png"]
+2452        imageio.imwrite(covers[0], create_diagonal_split_image(ipt_img, out_img))
+2453    else:
+2454        covers = [cover_folder / "input.png", cover_folder / "output.png"]
+2455        imageio.imwrite(covers[0], ipt_img)
+2456        imageio.imwrite(covers[1], out_img)
+2457
+2458    return covers
 
    • 
 
 
@@ -3786,23 +3816,118 @@ 
    
 
                 
                 
    
-                    
    
-            AxisId        =
-
-            <class 'bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]'>
+                            
+
    
+            
+    class
+    AxisId(builtins.str):
+
+                
 
-        
     
    
     
+            
    182class AxisId(str):
+183    root_model = ValidatedString[Annotated[LowerCaseIdentifierAnno, MaxLen(16)]]
+184
+185    @classmethod
+186    def __get_pydantic_core_schema__(
+187        cls, source_type: Any, handler: GetCoreSchemaHandler
+188    ) -> CoreSchema:
+189        return no_info_after_validator_function(cls, handler(str))
+190
+191    @classmethod
+192    def _validate(cls, value: str):
+193        valid = cls.root_model.model_validate(value)
+194        return cls(valid.root)
+
    
+
+
+            
    str(object='') -> str
+str(bytes_or_buffer[, encoding[, errors]]) -> str
    
+
+
    Create a new string object from the given object. If encoding or
+errors is specified, then the object must expose a data buffer
+that will be decoded using the given encoding and error handler.
+Otherwise, returns the result of object.__str__() (if defined)
+or repr(object).
+encoding defaults to sys.getdefaultencoding().
+errors defaults to 'strict'.
    
+
    
+
+
+                            
    
+                                
    
+            root_model        =
+
+            <class 'bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]'>
+
+        
+    
    
+    
     
     
 
+                            
    
+                            
    
+                                
    Inherited Members
    
+                                
    
+                                    
    builtins.str
    
+                                
    encode
    
+                
    replace
    
+                
    split
    
+                
    rsplit
    
+                
    join
    
+                
    capitalize
    
+                
    casefold
    
+                
    title
    
+                
    center
    
+                
    count
    
+                
    expandtabs
    
+                
    find
    
+                
    partition
    
+                
    index
    
+                
    ljust
    
+                
    lower
    
+                
    lstrip
    
+                
    rfind
    
+                
    rindex
    
+                
    rjust
    
+                
    rstrip
    
+                
    rpartition
    
+                
    splitlines
    
+                
    strip
    
+                
    swapcase
    
+                
    translate
    
+                
    upper
    
+                
    startswith
    
+                
    endswith
    
+                
    removeprefix
    
+                
    removesuffix
    
+                
    isascii
    
+                
    islower
    
+                
    isupper
    
+                
    istitle
    
+                
    isspace
    
+                
    isdecimal
    
+                
    isdigit
    
+                
    isnumeric
    
+                
    isalpha
    
+                
    isalnum
    
+                
    isidentifier
    
+                
    isprintable
    
+                
    zfill
    
+                
    format
    
+                
    format_map
    
+                
    maketrans
    
+
+            
    
+                                
    
+                            
    
                 
    
                 
    
                     
    
             NonBatchAxisId        =
-
-            typing.Annotated[bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]], Predicate(func=<function <lambda>>)]
+typing.Annotated[AxisId, Predicate(func=<function <lambda>>)]
 
         
     
    
@@ -3860,30 +3985,30 @@ 
    
 
     
    
     
-            
    200class ParameterizedSize(Node):
-201    """Describes a range of valid tensor axis sizes as `size = min + n*step`.
-202    `n` in this equation is the same for all axis parameterized in this manner across the whole model.
-203    """
-204
-205    N: ClassVar[Type[int]] = int
-206    """integer to parameterize all axes with a `ParameterizedSize`"""
-207
-208    min: Annotated[int, Gt(0)]
-209    step: Annotated[int, Gt(0)]
-210
-211    def validate_size(self, size: int) -> int:
-212        if size < self.min:
-213            raise ValueError(f"size {size} < {self.min}")
-214        if (size - self.min) % self.step != 0:
-215            raise ValueError(
-216                f"axis of size {size} is not parameterized by `min + n*step` ="
-217                + f" `{self.min} + n*{self.step}`"
-218            )
-219
-220        return size
-221
-222    def get_size(self, n: ParameterizedSize.N) -> int:
-223        return self.min + self.step * n
+            
    224class ParameterizedSize(Node):
+225    """Describes a range of valid tensor axis sizes as `size = min + n*step`.
+226    `n` in this equation is the same for all axis parameterized in this manner across the whole model.
+227    """
+228
+229    N: ClassVar[Type[int]] = int
+230    """integer to parameterize all axes with a `ParameterizedSize`"""
+231
+232    min: Annotated[int, Gt(0)]
+233    step: Annotated[int, Gt(0)]
+234
+235    def validate_size(self, size: int) -> int:
+236        if size < self.min:
+237            raise ValueError(f"size {size} < {self.min}")
+238        if (size - self.min) % self.step != 0:
+239            raise ValueError(
+240                f"axis of size {size} is not parameterized by `min + n*step` ="
+241                + f" `{self.min} + n*{self.step}`"
+242            )
+243
+244        return size
+245
+246    def get_size(self, n: ParameterizedSize.N) -> int:
+247        return self.min + self.step * n
 
    
 
 
@@ -3939,16 +4064,16 @@ 
    
 
     
    
     
-            
    211    def validate_size(self, size: int) -> int:
-212        if size < self.min:
-213            raise ValueError(f"size {size} < {self.min}")
-214        if (size - self.min) % self.step != 0:
-215            raise ValueError(
-216                f"axis of size {size} is not parameterized by `min + n*step` ="
-217                + f" `{self.min} + n*{self.step}`"
-218            )
-219
-220        return size
+            
    235    def validate_size(self, size: int) -> int:
+236        if size < self.min:
+237            raise ValueError(f"size {size} < {self.min}")
+238        if (size - self.min) % self.step != 0:
+239            raise ValueError(
+240                f"axis of size {size} is not parameterized by `min + n*step` ="
+241                + f" `{self.min} + n*{self.step}`"
+242            )
+243
+244        return size
 
    
 
 
@@ -3966,8 +4091,8 @@ 
    
 
     
    
     
-            
    222    def get_size(self, n: ParameterizedSize.N) -> int:
-223        return self.min + self.step * n
+            
    246    def get_size(self, n: ParameterizedSize.N) -> int:
+247        return self.min + self.step * n
 
    
 
 
@@ -4061,105 +4186,105 @@ 
    Inherited Members
    
 
     
    
     
-            
    226class SizeReference(Node):
-227    """A tensor axis size (extent in pixels/frames) defined in relation to a reference axis.
-228
-229    `axis.size = reference.size * reference.scale / axis.scale + offset`
-230
-231    note:
-232    1. The axis and the referenced axis need to have the same unit (or no unit).
-233    2. Batch axes may not be referenced.
-234    3. Fractions are rounded down.
-235
-236    example:
-237    An unisotropic input image of w*h=100*49 pixels depicts a phsical space of 200*196mm².
-238    Let's assume that we want to express the image height h in relation to its width w
-239    instead of only accepting input images of exactly 100*49 pixels
-240    (for example to express a range of valid image shapes by parametrizing w, see `ParameterizedSize`).
-241
-242    >>> w = SpaceInputAxis(id=AxisId("w"), size=100, unit="millimeter", scale=2)
-243    >>> h = SpaceInputAxis(
-244    ...     id=AxisId("h"),
-245    ...     size=SizeReference(tensor_id=TensorId("input"), axis_id=AxisId("w"), offset=-1),
-246    ...     unit="millimeter",
-247    ...     scale=4,
-248    ... )
-249    >>> print(h.size.compute(h, w))
-250    49
-251
-252    -> h = w * w.scale / h.scale + offset = 100 * 2mm / 4mm - 1 = 49
-253    """
+            
    250class SizeReference(Node):
+251    """A tensor axis size (extent in pixels/frames) defined in relation to a reference axis.
+252
+253    `axis.size = reference.size * reference.scale / axis.scale + offset`
 254
-255    tensor_id: TensorId
-256    """tensor id of the reference axis"""
-257
-258    axis_id: AxisId
-259    """axis id of the reference axis"""
-260
-261    offset: int = 0
-262
-263    def get_size(
-264        self,
-265        axis: Union[
-266            ChannelAxis,
-267            IndexAxis,
-268            TimeInputAxis,
-269            SpaceInputAxis,
-270            TimeOutputAxis,
-271            SpaceOutputAxis,
-272        ],
-273        ref_axis: Union[
-274            ChannelAxis,
-275            IndexAxis,
-276            TimeInputAxis,
-277            SpaceInputAxis,
-278            TimeOutputAxis,
-279            SpaceOutputAxis,
-280        ],
-281        n: ParameterizedSize.N,
-282    ):
-283        """helper method to compute concrete size for a given axis and its reference axis.
-284        If the reference axis is parameterized, `n` is used to compute the concrete size of it, see `ParameterizedSize`.
-285        """
-286        assert (
-287            axis.size == self
-288        ), "Given `axis.size` is not defined by this `SizeReference`"
-289
-290        assert (
-291            ref_axis.id == self.axis_id
-292        ), f"Expected `ref_axis.id` to be {self.axis_id}, but got {ref_axis.id}."
-293
-294        assert axis.unit == ref_axis.unit, (
-295            "`SizeReference` requires `axis` and `ref_axis` to have the same `unit`,"
-296            f" but {axis.unit}!={ref_axis.unit}"
-297        )
-298
-299        if isinstance(ref_axis.size, (int, float)):
-300            ref_size = ref_axis.size
-301        elif isinstance(ref_axis.size, ParameterizedSize):
-302            ref_size = ref_axis.size.get_size(n)
-303        elif isinstance(ref_axis.size, SizeReference):
-304            raise ValueError(
-305                "Reference axis referenced in `SizeReference` may not be sized by a"
-306                + " `SizeReference` itself."
-307            )
-308        else:
-309            assert_never(ref_axis.size)
-310
-311        return int(ref_size * ref_axis.scale / axis.scale + self.offset)
-312
-313    @staticmethod
-314    def _get_unit(
-315        axis: Union[
-316            ChannelAxis,
-317            IndexAxis,
-318            TimeInputAxis,
-319            SpaceInputAxis,
-320            TimeOutputAxis,
-321            SpaceOutputAxis,
-322        ],
-323    ):
-324        return axis.unit
+255    note:
+256    1. The axis and the referenced axis need to have the same unit (or no unit).
+257    2. Batch axes may not be referenced.
+258    3. Fractions are rounded down.
+259
+260    example:
+261    An unisotropic input image of w*h=100*49 pixels depicts a phsical space of 200*196mm².
+262    Let's assume that we want to express the image height h in relation to its width w
+263    instead of only accepting input images of exactly 100*49 pixels
+264    (for example to express a range of valid image shapes by parametrizing w, see `ParameterizedSize`).
+265
+266    >>> w = SpaceInputAxis(id=AxisId("w"), size=100, unit="millimeter", scale=2)
+267    >>> h = SpaceInputAxis(
+268    ...     id=AxisId("h"),
+269    ...     size=SizeReference(tensor_id=TensorId("input"), axis_id=AxisId("w"), offset=-1),
+270    ...     unit="millimeter",
+271    ...     scale=4,
+272    ... )
+273    >>> print(h.size.compute(h, w))
+274    49
+275
+276    -> h = w * w.scale / h.scale + offset = 100 * 2mm / 4mm - 1 = 49
+277    """
+278
+279    tensor_id: TensorId
+280    """tensor id of the reference axis"""
+281
+282    axis_id: AxisId
+283    """axis id of the reference axis"""
+284
+285    offset: int = 0
+286
+287    def get_size(
+288        self,
+289        axis: Union[
+290            ChannelAxis,
+291            IndexAxis,
+292            TimeInputAxis,
+293            SpaceInputAxis,
+294            TimeOutputAxis,
+295            SpaceOutputAxis,
+296        ],
+297        ref_axis: Union[
+298            ChannelAxis,
+299            IndexAxis,
+300            TimeInputAxis,
+301            SpaceInputAxis,
+302            TimeOutputAxis,
+303            SpaceOutputAxis,
+304        ],
+305        n: ParameterizedSize.N,
+306    ):
+307        """helper method to compute concrete size for a given axis and its reference axis.
+308        If the reference axis is parameterized, `n` is used to compute the concrete size of it, see `ParameterizedSize`.
+309        """
+310        assert (
+311            axis.size == self
+312        ), "Given `axis.size` is not defined by this `SizeReference`"
+313
+314        assert (
+315            ref_axis.id == self.axis_id
+316        ), f"Expected `ref_axis.id` to be {self.axis_id}, but got {ref_axis.id}."
+317
+318        assert axis.unit == ref_axis.unit, (
+319            "`SizeReference` requires `axis` and `ref_axis` to have the same `unit`,"
+320            f" but {axis.unit}!={ref_axis.unit}"
+321        )
+322
+323        if isinstance(ref_axis.size, (int, float)):
+324            ref_size = ref_axis.size
+325        elif isinstance(ref_axis.size, ParameterizedSize):
+326            ref_size = ref_axis.size.get_size(n)
+327        elif isinstance(ref_axis.size, SizeReference):
+328            raise ValueError(
+329                "Reference axis referenced in `SizeReference` may not be sized by a"
+330                + " `SizeReference` itself."
+331            )
+332        else:
+333            assert_never(ref_axis.size)
+334
+335        return int(ref_size * ref_axis.scale / axis.scale + self.offset)
+336
+337    @staticmethod
+338    def _get_unit(
+339        axis: Union[
+340            ChannelAxis,
+341            IndexAxis,
+342            TimeInputAxis,
+343            SpaceInputAxis,
+344            TimeOutputAxis,
+345            SpaceOutputAxis,
+346        ],
+347    ):
+348        return axis.unit
 
    
 
 
@@ -4213,7 +4338,7 @@ 
    Inherited Members
    
                             
    
                             
    
                                 
    
-            axis_id: bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]
+            axis_id: AxisId
 
         
     
    
@@ -4246,55 +4371,55 @@ 
    Inherited Members
    
 
     
    
     
-            
    263    def get_size(
-264        self,
-265        axis: Union[
-266            ChannelAxis,
-267            IndexAxis,
-268            TimeInputAxis,
-269            SpaceInputAxis,
-270            TimeOutputAxis,
-271            SpaceOutputAxis,
-272        ],
-273        ref_axis: Union[
-274            ChannelAxis,
-275            IndexAxis,
-276            TimeInputAxis,
-277            SpaceInputAxis,
-278            TimeOutputAxis,
-279            SpaceOutputAxis,
-280        ],
-281        n: ParameterizedSize.N,
-282    ):
-283        """helper method to compute concrete size for a given axis and its reference axis.
-284        If the reference axis is parameterized, `n` is used to compute the concrete size of it, see `ParameterizedSize`.
-285        """
-286        assert (
-287            axis.size == self
-288        ), "Given `axis.size` is not defined by this `SizeReference`"
-289
-290        assert (
-291            ref_axis.id == self.axis_id
-292        ), f"Expected `ref_axis.id` to be {self.axis_id}, but got {ref_axis.id}."
-293
-294        assert axis.unit == ref_axis.unit, (
-295            "`SizeReference` requires `axis` and `ref_axis` to have the same `unit`,"
-296            f" but {axis.unit}!={ref_axis.unit}"
-297        )
-298
-299        if isinstance(ref_axis.size, (int, float)):
-300            ref_size = ref_axis.size
-301        elif isinstance(ref_axis.size, ParameterizedSize):
-302            ref_size = ref_axis.size.get_size(n)
-303        elif isinstance(ref_axis.size, SizeReference):
-304            raise ValueError(
-305                "Reference axis referenced in `SizeReference` may not be sized by a"
-306                + " `SizeReference` itself."
-307            )
-308        else:
-309            assert_never(ref_axis.size)
-310
-311        return int(ref_size * ref_axis.scale / axis.scale + self.offset)
+            
    287    def get_size(
+288        self,
+289        axis: Union[
+290            ChannelAxis,
+291            IndexAxis,
+292            TimeInputAxis,
+293            SpaceInputAxis,
+294            TimeOutputAxis,
+295            SpaceOutputAxis,
+296        ],
+297        ref_axis: Union[
+298            ChannelAxis,
+299            IndexAxis,
+300            TimeInputAxis,
+301            SpaceInputAxis,
+302            TimeOutputAxis,
+303            SpaceOutputAxis,
+304        ],
+305        n: ParameterizedSize.N,
+306    ):
+307        """helper method to compute concrete size for a given axis and its reference axis.
+308        If the reference axis is parameterized, `n` is used to compute the concrete size of it, see `ParameterizedSize`.
+309        """
+310        assert (
+311            axis.size == self
+312        ), "Given `axis.size` is not defined by this `SizeReference`"
+313
+314        assert (
+315            ref_axis.id == self.axis_id
+316        ), f"Expected `ref_axis.id` to be {self.axis_id}, but got {ref_axis.id}."
+317
+318        assert axis.unit == ref_axis.unit, (
+319            "`SizeReference` requires `axis` and `ref_axis` to have the same `unit`,"
+320            f" but {axis.unit}!={ref_axis.unit}"
+321        )
+322
+323        if isinstance(ref_axis.size, (int, float)):
+324            ref_size = ref_axis.size
+325        elif isinstance(ref_axis.size, ParameterizedSize):
+326            ref_size = ref_axis.size.get_size(n)
+327        elif isinstance(ref_axis.size, SizeReference):
+328            raise ValueError(
+329                "Reference axis referenced in `SizeReference` may not be sized by a"
+330                + " `SizeReference` itself."
+331            )
+332        else:
+333            assert_never(ref_axis.size)
+334
+335        return int(ref_size * ref_axis.scale / axis.scale + self.offset)
 
    
 
 
@@ -4321,7 +4446,7 @@ 
    Inherited Members
    
                                 
    
             model_fields        =
 
-            {'tensor_id': FieldInfo(annotation=ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]], required=True), 'axis_id': FieldInfo(annotation=ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]], required=True), 'offset': FieldInfo(annotation=int, required=False, default=0)}
+            {'tensor_id': FieldInfo(annotation=ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]], required=True), 'axis_id': FieldInfo(annotation=AxisId, required=True), 'offset': FieldInfo(annotation=int, required=False, default=0)}
 
         
     
    
@@ -4391,13 +4516,13 @@ 
    Inherited Members
    
 
     
    
     
-            
    329class AxisBase(NodeWithExplicitlySetFields):
-330    fields_to_set_explicitly: ClassVar[FrozenSet[LiteralString]] = frozenset({"type"})
-331
-332    id: AxisId
-333    """An axis id unique across all axes of one tensor."""
-334
-335    description: Annotated[str, MaxLen(128)] = ""
+            
    353class AxisBase(NodeWithExplicitlySetFields):
+354    fields_to_set_explicitly: ClassVar[FrozenSet[LiteralString]] = frozenset({"type"})
+355
+356    id: AxisId
+357    """An axis id unique across all axes of one tensor."""
+358
+359    description: Annotated[str, MaxLen(128)] = ""
 
    
 
 
@@ -4422,7 +4547,7 @@ 
    Inherited Members
    
                             
    
                             
    
                                 
    
-            id: bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]
+            id: AxisId
 
         
     
    
@@ -4461,7 +4586,7 @@ 
    Inherited Members
    
                                 
    
             model_fields        =
 
-            {'id': FieldInfo(annotation=ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]], required=True), 'description': FieldInfo(annotation=str, required=False, default='', metadata=[MaxLen(max_length=128)])}
+            {'id': FieldInfo(annotation=AxisId, required=True), 'description': FieldInfo(annotation=str, required=False, default='', metadata=[MaxLen(max_length=128)])}
 
         
     
    
@@ -4535,11 +4660,11 @@ 
    Inherited Members
    
 
     
    
     
-            
    338class WithHalo(Node):
-339    halo: Annotated[int, Ge(0)] = 0
-340    """The halo should be cropped from the output tensor to avoid boundary effects.
-341    It is to be cropped from both sides, i.e. `size_after_crop = size - 2 * halo`.
-342    To document a halo that is already cropped by the model use `size.offset` instead."""
+            
    362class WithHalo(Node):
+363    halo: Annotated[int, Ge(0)] = 0
+364    """The halo should be cropped from the output tensor to avoid boundary effects.
+365    It is to be cropped from both sides, i.e. `size_after_crop = size - 2 * halo`.
+366    To document a halo that is already cropped by the model use `size.offset` instead."""
 
    
 
 
@@ -4648,20 +4773,20 @@ 
    Inherited Members
    
 
     
    
     
-            
    345class BatchAxis(AxisBase):
-346    type: Literal["batch"] = "batch"
-347    id: Annotated[AxisId, Predicate(lambda x: x == AxisId("batch"))] = AxisId("batch")
-348    size: Optional[Literal[1]] = None
-349    """The batch size may be fixed to 1,
-350    otherwise (the default) it may be chosen arbitrarily depending on available memory"""
-351
-352    @property
-353    def scale(self):
-354        return 1.0
-355
-356    @property
-357    def unit(self):
-358        return None
+            
    369class BatchAxis(AxisBase):
+370    type: Literal["batch"] = "batch"
+371    id: Annotated[AxisId, Predicate(lambda x: x == AxisId("batch"))] = AxisId("batch")
+372    size: Optional[Literal[1]] = None
+373    """The batch size may be fixed to 1,
+374    otherwise (the default) it may be chosen arbitrarily depending on available memory"""
+375
+376    @property
+377    def scale(self):
+378        return 1.0
+379
+380    @property
+381    def unit(self):
+382        return None
 
    
 
 
@@ -4682,7 +4807,7 @@ 
    Inherited Members
    
                             
    
                             
    
                                 
    
-            id: Annotated[bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]], Predicate(func=<function <lambda> at 0x7f1c1306d4e0>)]
+            id: Annotated[AxisId, Predicate(func=<function <lambda> at 0x7afc933b6b60>)]
 
         
     
    
@@ -4716,9 +4841,9 @@ 
    Inherited Members
    
 
     
    
     
-            
    352    @property
-353    def scale(self):
-354        return 1.0
+            
    376    @property
+377    def scale(self):
+378        return 1.0
 
    
 
 
@@ -4734,9 +4859,9 @@ 
    Inherited Members
    
 
     
    
     
-            
    356    @property
-357    def unit(self):
-358        return None
+            
    380    @property
+381    def unit(self):
+382        return None
 
    
 
 
@@ -4760,7 +4885,7 @@ 
    Inherited Members
    
                                 
    
             model_fields        =
 
-            {'id': FieldInfo(annotation=ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]], required=False, default=ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]](root='batch'), metadata=[Predicate(func=<function <lambda>>)]), 'description': FieldInfo(annotation=str, required=False, default='', metadata=[MaxLen(max_length=128)]), 'type': FieldInfo(annotation=Literal['batch'], required=False, default='batch'), 'size': FieldInfo(annotation=Union[Literal[1], NoneType], required=False)}
+            {'id': FieldInfo(annotation=AxisId, required=False, default='batch', metadata=[Predicate(func=<function <lambda>>)]), 'description': FieldInfo(annotation=str, required=False, default='', metadata=[MaxLen(max_length=128)]), 'type': FieldInfo(annotation=Literal['batch'], required=False, default='batch'), 'size': FieldInfo(annotation=Union[Literal[1], NoneType], required=False)}
 
         
     
    
@@ -4839,22 +4964,22 @@ 
    Inherited Members
    
 
     
    
     
-            
    361class ChannelAxis(AxisBase):
-362    type: Literal["channel"] = "channel"
-363    id: NonBatchAxisId = AxisId("channel")
-364    channel_names: List[Identifier]
-365
-366    @property
-367    def size(self) -> int:
-368        return len(self.channel_names)
-369
-370    @property
-371    def scale(self) -> float:
-372        return 1.0
-373
-374    @property
-375    def unit(self):
-376        return None
+            
    385class ChannelAxis(AxisBase):
+386    type: Literal["channel"] = "channel"
+387    id: NonBatchAxisId = AxisId("channel")
+388    channel_names: List[Identifier]
+389
+390    @property
+391    def size(self) -> int:
+392        return len(self.channel_names)
+393
+394    @property
+395    def scale(self) -> float:
+396        return 1.0
+397
+398    @property
+399    def unit(self):
+400        return None
 
    
 
 
@@ -4875,7 +5000,7 @@ 
    Inherited Members
    
                             
    
                             
    
                                 
    
-            id: Annotated[bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]], Predicate(func=<function <lambda> at 0x7f1c1523f380>)]
+            id: Annotated[AxisId, Predicate(func=<function <lambda> at 0x7afc943332e0>)]
 
         
     
    
@@ -4906,9 +5031,9 @@ 
    Inherited Members
    
 
     
    
     
-            
    366    @property
-367    def size(self) -> int:
-368        return len(self.channel_names)
+            
    390    @property
+391    def size(self) -> int:
+392        return len(self.channel_names)
 
    
 
 
@@ -4924,9 +5049,9 @@ 
    Inherited Members
    
 
     
    
     
-            
    370    @property
-371    def scale(self) -> float:
-372        return 1.0
+            
    394    @property
+395    def scale(self) -> float:
+396        return 1.0
 
    
 
 
@@ -4942,9 +5067,9 @@ 
    Inherited Members
    
 
     
    
     
-            
    374    @property
-375    def unit(self):
-376        return None
+            
    398    @property
+399    def unit(self):
+400        return None
 
    
 
 
@@ -4968,7 +5093,7 @@ 
    Inherited Members
    
                                 
    
             model_fields        =
 
-            {'id': FieldInfo(annotation=ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]], required=False, default=ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]](root='channel'), metadata=[Predicate(func=<function <lambda>>)]), 'description': FieldInfo(annotation=str, required=False, default='', metadata=[MaxLen(max_length=128)]), 'type': FieldInfo(annotation=Literal['channel'], required=False, default='channel'), 'channel_names': FieldInfo(annotation=List[ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator]]], required=True)}
+            {'id': FieldInfo(annotation=AxisId, required=False, default='channel', metadata=[Predicate(func=<function <lambda>>)]), 'description': FieldInfo(annotation=str, required=False, default='', metadata=[MaxLen(max_length=128)]), 'type': FieldInfo(annotation=Literal['channel'], required=False, default='channel'), 'channel_names': FieldInfo(annotation=List[ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator]]], required=True)}
 
         
     
    
@@ -5047,24 +5172,24 @@ 
    Inherited Members
    
 
     
    
     
-            
    379class IndexTimeSpaceAxisBase(AxisBase):
-380    size: Annotated[
-381        Union[Annotated[int, Gt(0)], ParameterizedSize, SizeReference],
-382        Field(
-383            examples=[
-384                10,
-385                ParameterizedSize(min=32, step=16).model_dump(mode="json"),
-386                SizeReference(
-387                    tensor_id=TensorId("t"), axis_id=AxisId("a"), offset=5
-388                ).model_dump(mode="json"),
-389            ]
-390        ),
-391    ]
-392    """The size/length of an axis can be specified as
-393    - fixed integer
-394    - parameterized series of valid sizes (`ParameterizedSize`)
-395    - reference to another axis with an optional offset (`SizeReference`)
-396    """
+            
    403class IndexTimeSpaceAxisBase(AxisBase):
+404    size: Annotated[
+405        Union[Annotated[int, Gt(0)], ParameterizedSize, SizeReference],
+406        Field(
+407            examples=[
+408                10,
+409                ParameterizedSize(min=32, step=16).model_dump(mode="json"),
+410                SizeReference(
+411                    tensor_id=TensorId("t"), axis_id=AxisId("a"), offset=5
+412                ).model_dump(mode="json"),
+413            ]
+414        ),
+415    ]
+416    """The size/length of an axis can be specified as
+417    - fixed integer
+418    - parameterized series of valid sizes (`ParameterizedSize`)
+419    - reference to another axis with an optional offset (`SizeReference`)
+420    """
 
    
 
 
@@ -5108,7 +5233,7 @@ 
    Inherited Members
    
                                 
    
             model_fields        =
 
-            {'id': FieldInfo(annotation=ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]], required=True), 'description': FieldInfo(annotation=str, required=False, default='', metadata=[MaxLen(max_length=128)]), 'size': FieldInfo(annotation=Union[Annotated[int, Gt], ParameterizedSize, SizeReference], required=True, examples=[10, {'min': 32, 'step': 16}, {'tensor_id': 't', 'axis_id': 'a', 'offset': 5}])}
+            {'id': FieldInfo(annotation=AxisId, required=True), 'description': FieldInfo(annotation=str, required=False, default='', metadata=[MaxLen(max_length=128)]), 'size': FieldInfo(annotation=Union[Annotated[int, Gt], ParameterizedSize, SizeReference], required=True, examples=[10, {'min': 32, 'step': 16}, {'tensor_id': 't', 'axis_id': 'a', 'offset': 5}])}
 
         
     
    
@@ -5188,17 +5313,17 @@ 
    Inherited Members
    
 
     
    
     
-            
    399class IndexAxis(IndexTimeSpaceAxisBase):
-400    type: Literal["index"] = "index"
-401    id: NonBatchAxisId = AxisId("index")
-402
-403    @property
-404    def scale(self) -> float:
-405        return 1.0
-406
-407    @property
-408    def unit(self):
-409        return None
+            
    423class IndexAxis(IndexTimeSpaceAxisBase):
+424    type: Literal["index"] = "index"
+425    id: NonBatchAxisId = AxisId("index")
+426
+427    @property
+428    def scale(self) -> float:
+429        return 1.0
+430
+431    @property
+432    def unit(self):
+433        return None
 
    
 
 
@@ -5219,7 +5344,7 @@ 
    Inherited Members
    
                             
    
                             
    
                                 
    
-            id: Annotated[bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]], Predicate(func=<function <lambda> at 0x7f1c1523f380>)]
+            id: Annotated[AxisId, Predicate(func=<function <lambda> at 0x7afc943332e0>)]
 
         
     
    
@@ -5239,9 +5364,9 @@ 
    Inherited Members
    
 
     
    
     
-            
    403    @property
-404    def scale(self) -> float:
-405        return 1.0
+            
    427    @property
+428    def scale(self) -> float:
+429        return 1.0
 
    
 
 
@@ -5257,9 +5382,9 @@ 
    Inherited Members
    
 
     
    
     
-            
    407    @property
-408    def unit(self):
-409        return None
+            
    431    @property
+432    def unit(self):
+433        return None
 
    
 
 
@@ -5283,7 +5408,7 @@ 
    Inherited Members
    
                                 
    
             model_fields        =
 
-            {'id': FieldInfo(annotation=ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]], required=False, default=ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]](root='index'), metadata=[Predicate(func=<function <lambda>>)]), 'description': FieldInfo(annotation=str, required=False, default='', metadata=[MaxLen(max_length=128)]), 'size': FieldInfo(annotation=Union[Annotated[int, Gt], ParameterizedSize, SizeReference], required=True, examples=[10, {'min': 32, 'step': 16}, {'tensor_id': 't', 'axis_id': 'a', 'offset': 5}]), 'type': FieldInfo(annotation=Literal['index'], required=False, default='index')}
+            {'id': FieldInfo(annotation=AxisId, required=False, default='index', metadata=[Predicate(func=<function <lambda>>)]), 'description': FieldInfo(annotation=str, required=False, default='', metadata=[MaxLen(max_length=128)]), 'size': FieldInfo(annotation=Union[Annotated[int, Gt], ParameterizedSize, SizeReference], required=True, examples=[10, {'min': 32, 'step': 16}, {'tensor_id': 't', 'axis_id': 'a', 'offset': 5}]), 'type': FieldInfo(annotation=Literal['index'], required=False, default='index')}
 
         
     
    
@@ -5366,11 +5491,11 @@ 
    Inherited Members
    
 
     
    
     
-            
    412class TimeAxisBase(IndexTimeSpaceAxisBase):
-413    type: Literal["time"] = "time"
-414    id: NonBatchAxisId = AxisId("time")
-415    unit: Optional[TimeUnit] = None
-416    scale: Annotated[float, Gt(0)] = 1.0
+            
    436class TimeAxisBase(IndexTimeSpaceAxisBase):
+437    type: Literal["time"] = "time"
+438    id: NonBatchAxisId = AxisId("time")
+439    unit: Optional[TimeUnit] = None
+440    scale: Annotated[float, Gt(0)] = 1.0
 
    
 
 
@@ -5391,7 +5516,7 @@ 
    Inherited Members
    
                             
    
                             
    
                                 
    
-            id: Annotated[bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]], Predicate(func=<function <lambda> at 0x7f1c1523f380>)]
+            id: Annotated[AxisId, Predicate(func=<function <lambda> at 0x7afc943332e0>)]
 
         
     
    
@@ -5441,7 +5566,7 @@ 
    Inherited Members
    
                                 
    
             model_fields        =
 
-            {'id': FieldInfo(annotation=ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]], required=False, default=ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]](root='time'), metadata=[Predicate(func=<function <lambda>>)]), 'description': FieldInfo(annotation=str, required=False, default='', metadata=[MaxLen(max_length=128)]), 'size': FieldInfo(annotation=Union[Annotated[int, Gt], ParameterizedSize, SizeReference], required=True, examples=[10, {'min': 32, 'step': 16}, {'tensor_id': 't', 'axis_id': 'a', 'offset': 5}]), 'type': FieldInfo(annotation=Literal['time'], required=False, default='time'), 'unit': FieldInfo(annotation=Union[Literal['attosecond', 'centisecond', 'day', 'decisecond', 'exasecond', 'femtosecond', 'gigasecond', 'hectosecond', 'hour', 'kilosecond', 'megasecond', 'microsecond', 'millisecond', 'minute', 'nanosecond', 'petasecond', 'picosecond', 'second', 'terasecond', 'yoctosecond', 'yottasecond', 'zeptosecond', 'zettasecond'], NoneType], required=False), 'scale': FieldInfo(annotation=float, required=False, default=1.0, metadata=[Gt(gt=0)])}
+            {'id': FieldInfo(annotation=AxisId, required=False, default='time', metadata=[Predicate(func=<function <lambda>>)]), 'description': FieldInfo(annotation=str, required=False, default='', metadata=[MaxLen(max_length=128)]), 'size': FieldInfo(annotation=Union[Annotated[int, Gt], ParameterizedSize, SizeReference], required=True, examples=[10, {'min': 32, 'step': 16}, {'tensor_id': 't', 'axis_id': 'a', 'offset': 5}]), 'type': FieldInfo(annotation=Literal['time'], required=False, default='time'), 'unit': FieldInfo(annotation=Union[Literal['attosecond', 'centisecond', 'day', 'decisecond', 'exasecond', 'femtosecond', 'gigasecond', 'hectosecond', 'hour', 'kilosecond', 'megasecond', 'microsecond', 'millisecond', 'minute', 'nanosecond', 'petasecond', 'picosecond', 'second', 'terasecond', 'yoctosecond', 'yottasecond', 'zeptosecond', 'zettasecond'], NoneType], required=False), 'scale': FieldInfo(annotation=float, required=False, default=1.0, metadata=[Gt(gt=0)])}
 
         
     
    
@@ -5524,8 +5649,8 @@ 
    Inherited Members
    
 
     
    
     
-            
    419class TimeInputAxis(TimeAxisBase):
-420    pass
+            
    443class TimeInputAxis(TimeAxisBase):
+444    pass
 
    
 
 
@@ -5550,7 +5675,7 @@ 
    Inherited Members
    
                                 
    
             model_fields        =
 
-            {'id': FieldInfo(annotation=ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]], required=False, default=ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]](root='time'), metadata=[Predicate(func=<function <lambda>>)]), 'description': FieldInfo(annotation=str, required=False, default='', metadata=[MaxLen(max_length=128)]), 'size': FieldInfo(annotation=Union[Annotated[int, Gt], ParameterizedSize, SizeReference], required=True, examples=[10, {'min': 32, 'step': 16}, {'tensor_id': 't', 'axis_id': 'a', 'offset': 5}]), 'type': FieldInfo(annotation=Literal['time'], required=False, default='time'), 'unit': FieldInfo(annotation=Union[Literal['attosecond', 'centisecond', 'day', 'decisecond', 'exasecond', 'femtosecond', 'gigasecond', 'hectosecond', 'hour', 'kilosecond', 'megasecond', 'microsecond', 'millisecond', 'minute', 'nanosecond', 'petasecond', 'picosecond', 'second', 'terasecond', 'yoctosecond', 'yottasecond', 'zeptosecond', 'zettasecond'], NoneType], required=False), 'scale': FieldInfo(annotation=float, required=False, default=1.0, metadata=[Gt(gt=0)])}
+            {'id': FieldInfo(annotation=AxisId, required=False, default='time', metadata=[Predicate(func=<function <lambda>>)]), 'description': FieldInfo(annotation=str, required=False, default='', metadata=[MaxLen(max_length=128)]), 'size': FieldInfo(annotation=Union[Annotated[int, Gt], ParameterizedSize, SizeReference], required=True, examples=[10, {'min': 32, 'step': 16}, {'tensor_id': 't', 'axis_id': 'a', 'offset': 5}]), 'type': FieldInfo(annotation=Literal['time'], required=False, default='time'), 'unit': FieldInfo(annotation=Union[Literal['attosecond', 'centisecond', 'day', 'decisecond', 'exasecond', 'femtosecond', 'gigasecond', 'hectosecond', 'hour', 'kilosecond', 'megasecond', 'microsecond', 'millisecond', 'minute', 'nanosecond', 'petasecond', 'picosecond', 'second', 'terasecond', 'yoctosecond', 'yottasecond', 'zeptosecond', 'zettasecond'], NoneType], required=False), 'scale': FieldInfo(annotation=float, required=False, default=1.0, metadata=[Gt(gt=0)])}
 
         
     
    
@@ -5640,11 +5765,11 @@ 
    Inherited Members
    
 
     
    
     
-            
    423class SpaceAxisBase(IndexTimeSpaceAxisBase):
-424    type: Literal["space"] = "space"
-425    id: Annotated[NonBatchAxisId, Field(examples=["x", "y", "z"])] = AxisId("x")
-426    unit: Optional[SpaceUnit] = None
-427    scale: Annotated[float, Gt(0)] = 1.0
+            
    447class SpaceAxisBase(IndexTimeSpaceAxisBase):
+448    type: Literal["space"] = "space"
+449    id: Annotated[NonBatchAxisId, Field(examples=["x", "y", "z"])] = AxisId("x")
+450    unit: Optional[SpaceUnit] = None
+451    scale: Annotated[float, Gt(0)] = 1.0
 
    
 
 
@@ -5665,7 +5790,7 @@ 
    Inherited Members
    
                             
    
                             
    
                                 
    
-            id: Annotated[bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]], Predicate(func=<function <lambda> at 0x7f1c1523f380>), FieldInfo(annotation=NoneType, required=True, examples=['x', 'y', 'z'])]
+            id: Annotated[AxisId, Predicate(func=<function <lambda> at 0x7afc943332e0>), FieldInfo(annotation=NoneType, required=True, examples=['x', 'y', 'z'])]
 
         
     
    
@@ -5715,7 +5840,7 @@ 
    Inherited Members
    
                                 
    
             model_fields        =
 
-            {'id': FieldInfo(annotation=ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]], required=False, default=ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]](root='x'), examples=['x', 'y', 'z'], metadata=[Predicate(func=<function <lambda>>)]), 'description': FieldInfo(annotation=str, required=False, default='', metadata=[MaxLen(max_length=128)]), 'size': FieldInfo(annotation=Union[Annotated[int, Gt], ParameterizedSize, SizeReference], required=True, examples=[10, {'min': 32, 'step': 16}, {'tensor_id': 't', 'axis_id': 'a', 'offset': 5}]), 'type': FieldInfo(annotation=Literal['space'], required=False, default='space'), 'unit': FieldInfo(annotation=Union[Literal['attometer', 'angstrom', 'centimeter', 'decimeter', 'exameter', 'femtometer', 'foot', 'gigameter', 'hectometer', 'inch', 'kilometer', 'megameter', 'meter', 'micrometer', 'mile', 'millimeter', 'nanometer', 'parsec', 'petameter', 'picometer', 'terameter', 'yard', 'yoctometer', 'yottameter', 'zeptometer', 'zettameter'], NoneType], required=False), 'scale': FieldInfo(annotation=float, required=False, default=1.0, metadata=[Gt(gt=0)])}
+            {'id': FieldInfo(annotation=AxisId, required=False, default='x', examples=['x', 'y', 'z'], metadata=[Predicate(func=<function <lambda>>)]), 'description': FieldInfo(annotation=str, required=False, default='', metadata=[MaxLen(max_length=128)]), 'size': FieldInfo(annotation=Union[Annotated[int, Gt], ParameterizedSize, SizeReference], required=True, examples=[10, {'min': 32, 'step': 16}, {'tensor_id': 't', 'axis_id': 'a', 'offset': 5}]), 'type': FieldInfo(annotation=Literal['space'], required=False, default='space'), 'unit': FieldInfo(annotation=Union[Literal['attometer', 'angstrom', 'centimeter', 'decimeter', 'exameter', 'femtometer', 'foot', 'gigameter', 'hectometer', 'inch', 'kilometer', 'megameter', 'meter', 'micrometer', 'mile', 'millimeter', 'nanometer', 'parsec', 'petameter', 'picometer', 'terameter', 'yard', 'yoctometer', 'yottameter', 'zeptometer', 'zettameter'], NoneType], required=False), 'scale': FieldInfo(annotation=float, required=False, default=1.0, metadata=[Gt(gt=0)])}
 
         
     
    
@@ -5798,8 +5923,8 @@ 
    Inherited Members
    
 
     
    
     
-            
    430class SpaceInputAxis(SpaceAxisBase):
-431    pass
+            
    454class SpaceInputAxis(SpaceAxisBase):
+455    pass
 
    
 
 
@@ -5824,7 +5949,7 @@ 
    Inherited Members
    
                                 
    
             model_fields        =
 
-            {'id': FieldInfo(annotation=ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]], required=False, default=ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]](root='x'), examples=['x', 'y', 'z'], metadata=[Predicate(func=<function <lambda>>)]), 'description': FieldInfo(annotation=str, required=False, default='', metadata=[MaxLen(max_length=128)]), 'size': FieldInfo(annotation=Union[Annotated[int, Gt], ParameterizedSize, SizeReference], required=True, examples=[10, {'min': 32, 'step': 16}, {'tensor_id': 't', 'axis_id': 'a', 'offset': 5}]), 'type': FieldInfo(annotation=Literal['space'], required=False, default='space'), 'unit': FieldInfo(annotation=Union[Literal['attometer', 'angstrom', 'centimeter', 'decimeter', 'exameter', 'femtometer', 'foot', 'gigameter', 'hectometer', 'inch', 'kilometer', 'megameter', 'meter', 'micrometer', 'mile', 'millimeter', 'nanometer', 'parsec', 'petameter', 'picometer', 'terameter', 'yard', 'yoctometer', 'yottameter', 'zeptometer', 'zettameter'], NoneType], required=False), 'scale': FieldInfo(annotation=float, required=False, default=1.0, metadata=[Gt(gt=0)])}
+            {'id': FieldInfo(annotation=AxisId, required=False, default='x', examples=['x', 'y', 'z'], metadata=[Predicate(func=<function <lambda>>)]), 'description': FieldInfo(annotation=str, required=False, default='', metadata=[MaxLen(max_length=128)]), 'size': FieldInfo(annotation=Union[Annotated[int, Gt], ParameterizedSize, SizeReference], required=True, examples=[10, {'min': 32, 'step': 16}, {'tensor_id': 't', 'axis_id': 'a', 'offset': 5}]), 'type': FieldInfo(annotation=Literal['space'], required=False, default='space'), 'unit': FieldInfo(annotation=Union[Literal['attometer', 'angstrom', 'centimeter', 'decimeter', 'exameter', 'femtometer', 'foot', 'gigameter', 'hectometer', 'inch', 'kilometer', 'megameter', 'meter', 'micrometer', 'mile', 'millimeter', 'nanometer', 'parsec', 'petameter', 'picometer', 'terameter', 'yard', 'yoctometer', 'yottameter', 'zeptometer', 'zettameter'], NoneType], required=False), 'scale': FieldInfo(annotation=float, required=False, default=1.0, metadata=[Gt(gt=0)])}
 
         
     
    
@@ -5927,8 +6052,8 @@ 
    Inherited Members
    
 
     
    
     
-            
    440class TimeOutputAxis(TimeAxisBase, WithHalo):
-441    pass
+            
    464class TimeOutputAxis(TimeAxisBase, WithHalo):
+465    pass
 
    
 
 
@@ -5953,7 +6078,7 @@ 
    Inherited Members
    
                                 
    
             model_fields        =
 
-            {'halo': FieldInfo(annotation=int, required=False, default=0, metadata=[Ge(ge=0)]), 'id': FieldInfo(annotation=ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]], required=False, default=ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]](root='time'), metadata=[Predicate(func=<function <lambda>>)]), 'description': FieldInfo(annotation=str, required=False, default='', metadata=[MaxLen(max_length=128)]), 'size': FieldInfo(annotation=Union[Annotated[int, Gt], ParameterizedSize, SizeReference], required=True, examples=[10, {'min': 32, 'step': 16}, {'tensor_id': 't', 'axis_id': 'a', 'offset': 5}]), 'type': FieldInfo(annotation=Literal['time'], required=False, default='time'), 'unit': FieldInfo(annotation=Union[Literal['attosecond', 'centisecond', 'day', 'decisecond', 'exasecond', 'femtosecond', 'gigasecond', 'hectosecond', 'hour', 'kilosecond', 'megasecond', 'microsecond', 'millisecond', 'minute', 'nanosecond', 'petasecond', 'picosecond', 'second', 'terasecond', 'yoctosecond', 'yottasecond', 'zeptosecond', 'zettasecond'], NoneType], required=False), 'scale': FieldInfo(annotation=float, required=False, default=1.0, metadata=[Gt(gt=0)])}
+            {'halo': FieldInfo(annotation=int, required=False, default=0, metadata=[Ge(ge=0)]), 'id': FieldInfo(annotation=AxisId, required=False, default='time', metadata=[Predicate(func=<function <lambda>>)]), 'description': FieldInfo(annotation=str, required=False, default='', metadata=[MaxLen(max_length=128)]), 'size': FieldInfo(annotation=Union[Annotated[int, Gt], ParameterizedSize, SizeReference], required=True, examples=[10, {'min': 32, 'step': 16}, {'tensor_id': 't', 'axis_id': 'a', 'offset': 5}]), 'type': FieldInfo(annotation=Literal['time'], required=False, default='time'), 'unit': FieldInfo(annotation=Union[Literal['attosecond', 'centisecond', 'day', 'decisecond', 'exasecond', 'femtosecond', 'gigasecond', 'hectosecond', 'hour', 'kilosecond', 'megasecond', 'microsecond', 'millisecond', 'minute', 'nanosecond', 'petasecond', 'picosecond', 'second', 'terasecond', 'yoctosecond', 'yottasecond', 'zeptosecond', 'zettasecond'], NoneType], required=False), 'scale': FieldInfo(annotation=float, required=False, default=1.0, metadata=[Gt(gt=0)])}
 
         
     
    
@@ -6047,8 +6172,8 @@ 
    Inherited Members
    
 
     
    
     
-            
    444class SpaceOutputAxis(SpaceAxisBase, WithHalo):
-445    pass
+            
    468class SpaceOutputAxis(SpaceAxisBase, WithHalo):
+469    pass
 
    
 
 
@@ -6073,7 +6198,7 @@ 
    Inherited Members
    
                                 
    
             model_fields        =
 
-            {'halo': FieldInfo(annotation=int, required=False, default=0, metadata=[Ge(ge=0)]), 'id': FieldInfo(annotation=ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]], required=False, default=ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]](root='x'), examples=['x', 'y', 'z'], metadata=[Predicate(func=<function <lambda>>)]), 'description': FieldInfo(annotation=str, required=False, default='', metadata=[MaxLen(max_length=128)]), 'size': FieldInfo(annotation=Union[Annotated[int, Gt], ParameterizedSize, SizeReference], required=True, examples=[10, {'min': 32, 'step': 16}, {'tensor_id': 't', 'axis_id': 'a', 'offset': 5}]), 'type': FieldInfo(annotation=Literal['space'], required=False, default='space'), 'unit': FieldInfo(annotation=Union[Literal['attometer', 'angstrom', 'centimeter', 'decimeter', 'exameter', 'femtometer', 'foot', 'gigameter', 'hectometer', 'inch', 'kilometer', 'megameter', 'meter', 'micrometer', 'mile', 'millimeter', 'nanometer', 'parsec', 'petameter', 'picometer', 'terameter', 'yard', 'yoctometer', 'yottameter', 'zeptometer', 'zettameter'], NoneType], required=False), 'scale': FieldInfo(annotation=float, required=False, default=1.0, metadata=[Gt(gt=0)])}
+            {'halo': FieldInfo(annotation=int, required=False, default=0, metadata=[Ge(ge=0)]), 'id': FieldInfo(annotation=AxisId, required=False, default='x', examples=['x', 'y', 'z'], metadata=[Predicate(func=<function <lambda>>)]), 'description': FieldInfo(annotation=str, required=False, default='', metadata=[MaxLen(max_length=128)]), 'size': FieldInfo(annotation=Union[Annotated[int, Gt], ParameterizedSize, SizeReference], required=True, examples=[10, {'min': 32, 'step': 16}, {'tensor_id': 't', 'axis_id': 'a', 'offset': 5}]), 'type': FieldInfo(annotation=Literal['space'], required=False, default='space'), 'unit': FieldInfo(annotation=Union[Literal['attometer', 'angstrom', 'centimeter', 'decimeter', 'exameter', 'femtometer', 'foot', 'gigameter', 'hectometer', 'inch', 'kilometer', 'megameter', 'meter', 'micrometer', 'mile', 'millimeter', 'nanometer', 'parsec', 'petameter', 'picometer', 'terameter', 'yard', 'yoctometer', 'yottameter', 'zeptometer', 'zettameter'], NoneType], required=False), 'scale': FieldInfo(annotation=float, required=False, default=1.0, metadata=[Gt(gt=0)])}
 
         
     
    
@@ -6219,70 +6344,70 @@ 
    Inherited Members
    
 
     
    
     
-            
    478class NominalOrOrdinalDataDescr(Node):
-479    values: TVs
-480    """A fixed set of nominal or an ascending sequence of ordinal values.
-481    In this case `data_type` is required to be an unsigend integer type, e.g. 'uint8'.
-482    String `values` are interpreted as labels for tensor values 0, ..., N.
-483    Note: as YAML 1.2 does not natively support a "set" datatype,
-484    nominal values should be given as a sequence (aka list/array) as well.
-485    """
-486
-487    type: Annotated[
-488        NominalOrOrdinalDType,
-489        Field(
-490            examples=[
-491                "float32",
-492                "uint8",
-493                "uint16",
-494                "int64",
-495                "bool",
-496            ],
-497        ),
-498    ] = "uint8"
-499
-500    @model_validator(mode="after")
-501    def _validate_values_match_type(
-502        self,
-503    ) -> Self:
-504        incompatible: List[Any] = []
-505        for v in self.values:
-506            if self.type == "bool":
-507                if not isinstance(v, bool):
-508                    incompatible.append(v)
-509            elif self.type in DTYPE_LIMITS:
-510                if (
-511                    isinstance(v, (int, float))
-512                    and (
-513                        v < DTYPE_LIMITS[self.type].min
-514                        or v > DTYPE_LIMITS[self.type].max
-515                    )
-516                    or (isinstance(v, str) and "uint" not in self.type)
-517                    or (isinstance(v, float) and "int" in self.type)
-518                ):
-519                    incompatible.append(v)
-520            else:
-521                incompatible.append(v)
-522
-523            if len(incompatible) == 5:
-524                incompatible.append("...")
-525                break
-526
-527        if incompatible:
-528            raise ValueError(
-529                f"data type '{self.type}' incompatible with values {incompatible}"
-530            )
-531
-532        return self
-533
-534    unit: Optional[Union[Literal["arbitrary unit"], SiUnit]] = None
-535
-536    @property
-537    def range(self):
-538        if isinstance(self.values[0], str):
-539            return 0, len(self.values) - 1
-540        else:
-541            return min(self.values), max(self.values)
+            
    502class NominalOrOrdinalDataDescr(Node):
+503    values: TVs
+504    """A fixed set of nominal or an ascending sequence of ordinal values.
+505    In this case `data_type` is required to be an unsigend integer type, e.g. 'uint8'.
+506    String `values` are interpreted as labels for tensor values 0, ..., N.
+507    Note: as YAML 1.2 does not natively support a "set" datatype,
+508    nominal values should be given as a sequence (aka list/array) as well.
+509    """
+510
+511    type: Annotated[
+512        NominalOrOrdinalDType,
+513        Field(
+514            examples=[
+515                "float32",
+516                "uint8",
+517                "uint16",
+518                "int64",
+519                "bool",
+520            ],
+521        ),
+522    ] = "uint8"
+523
+524    @model_validator(mode="after")
+525    def _validate_values_match_type(
+526        self,
+527    ) -> Self:
+528        incompatible: List[Any] = []
+529        for v in self.values:
+530            if self.type == "bool":
+531                if not isinstance(v, bool):
+532                    incompatible.append(v)
+533            elif self.type in DTYPE_LIMITS:
+534                if (
+535                    isinstance(v, (int, float))
+536                    and (
+537                        v < DTYPE_LIMITS[self.type].min
+538                        or v > DTYPE_LIMITS[self.type].max
+539                    )
+540                    or (isinstance(v, str) and "uint" not in self.type)
+541                    or (isinstance(v, float) and "int" in self.type)
+542                ):
+543                    incompatible.append(v)
+544            else:
+545                incompatible.append(v)
+546
+547            if len(incompatible) == 5:
+548                incompatible.append("...")
+549                break
+550
+551        if incompatible:
+552            raise ValueError(
+553                f"data type '{self.type}' incompatible with values {incompatible}"
+554            )
+555
+556        return self
+557
+558    unit: Optional[Union[Literal["arbitrary unit"], SiUnit]] = None
+559
+560    @property
+561    def range(self):
+562        if isinstance(self.values[0], str):
+563            return 0, len(self.values) - 1
+564        else:
+565            return min(self.values), max(self.values)
 
    
 
 
@@ -6338,12 +6463,12 @@ 
    Inherited Members
    
 
     
    
     
-            
    536    @property
-537    def range(self):
-538        if isinstance(self.values[0], str):
-539            return 0, len(self.values) - 1
-540        else:
-541            return min(self.values), max(self.values)
+            
    560    @property
+561    def range(self):
+562        if isinstance(self.values[0], str):
+563            return 0, len(self.values) - 1
+564        else:
+565            return min(self.values), max(self.values)
 
    
 
 
@@ -6450,24 +6575,24 @@ 
    Inherited Members
    
 
     
    
     
-            
    558class IntervalOrRatioDataDescr(Node):
-559    type: Annotated[  # todo: rename to dtype
-560        IntervalOrRatioDType,
-561        Field(
-562            examples=["float32", "float64", "uint8", "uint16"],
-563        ),
-564    ] = "float32"
-565    range: Tuple[Optional[float], Optional[float]] = (
-566        None,
-567        None,
-568    )
-569    """Tuple `(minimum, maximum)` specifying the allowed range of the data in this tensor.
-570    `None` corresponds to min/max of what can be expressed by `data_type`."""
-571    unit: Union[Literal["arbitrary unit"], SiUnit] = "arbitrary unit"
-572    scale: float = 1.0
-573    """Scale for data on an interval (or ratio) scale."""
-574    offset: Optional[float] = None
-575    """Offset for data on a ratio scale."""
+            
    582class IntervalOrRatioDataDescr(Node):
+583    type: Annotated[  # todo: rename to dtype
+584        IntervalOrRatioDType,
+585        Field(
+586            examples=["float32", "float64", "uint8", "uint16"],
+587        ),
+588    ] = "float32"
+589    range: Tuple[Optional[float], Optional[float]] = (
+590        None,
+591        None,
+592    )
+593    """Tuple `(minimum, maximum)` specifying the allowed range of the data in this tensor.
+594    `None` corresponds to min/max of what can be expressed by `data_type`."""
+595    unit: Union[Literal["arbitrary unit"], SiUnit] = "arbitrary unit"
+596    scale: float = 1.0
+597    """Scale for data on an interval (or ratio) scale."""
+598    offset: Optional[float] = None
+599    """Offset for data on a ratio scale."""
 
    
 
 
@@ -6637,11 +6762,11 @@ 
    Inherited Members
    
 
     
    
     
-            
    581class ProcessingDescrBase(NodeWithExplicitlySetFields, ABC):
-582    """processing base class"""
-583
-584    # id: Literal[PreprocessingId, PostprocessingId]  # make abstract field
-585    fields_to_set_explicitly: ClassVar[FrozenSet[LiteralString]] = frozenset({"id"})
+            
    605class ProcessingDescrBase(NodeWithExplicitlySetFields, ABC):
+606    """processing base class"""
+607
+608    # id: Literal[PreprocessingId, PostprocessingId]  # make abstract field
+609    fields_to_set_explicitly: ClassVar[FrozenSet[LiteralString]] = frozenset({"id"})
 
    
 
 
@@ -6754,13 +6879,13 @@ 
    Inherited Members
    
 
     
    
     
-            
    588class BinarizeDescr(ProcessingDescrBase):
-589    """Binarize the tensor with a fixed threshold.
-590    Values above the threshold will be set to one, values below the threshold to zero.
-591    """
-592
-593    id: Literal["binarize"] = "binarize"
-594    kwargs: BinarizeKwargs
+            
    612class BinarizeDescr(ProcessingDescrBase):
+613    """Binarize the tensor with a fixed threshold.
+614    Values above the threshold will be set to one, values below the threshold to zero.
+615    """
+616
+617    id: Literal["binarize"] = "binarize"
+618    kwargs: BinarizeKwargs
 
    
 
 
@@ -6886,11 +7011,11 @@ 
    Inherited Members
    
 
     
    
     
-            
    597class ClipDescr(ProcessingDescrBase):
-598    """Set tensor values below min to min and above max to max."""
-599
-600    id: Literal["clip"] = "clip"
-601    kwargs: ClipKwargs
+            
    621class ClipDescr(ProcessingDescrBase):
+622    """Set tensor values below min to min and above max to max."""
+623
+624    id: Literal["clip"] = "clip"
+625    kwargs: ClipKwargs
 
    
 
 
@@ -7015,8 +7140,8 @@ 
    Inherited Members
    
 
     
    
     
-            
    604class EnsureDtypeKwargs(ProcessingKwargs):
-605    dtype: str
+            
    628class EnsureDtypeKwargs(ProcessingKwargs):
+629    dtype: str
 
    
 
 
@@ -7125,9 +7250,9 @@ 
    Inherited Members
    
 
     
    
     
-            
    608class EnsureDtypeDescr(ProcessingDescrBase):
-609    id: Literal["ensure_dtype"] = "ensure_dtype"
-610    kwargs: EnsureDtypeKwargs
+            
    632class EnsureDtypeDescr(ProcessingDescrBase):
+633    id: Literal["ensure_dtype"] = "ensure_dtype"
+634    kwargs: EnsureDtypeKwargs
 
    
 
 
@@ -7252,37 +7377,37 @@ 
    Inherited Members
    
 
     
    
     
-            
    613class ScaleLinearKwargs(ProcessingKwargs):
-614    axis: Annotated[Optional[NonBatchAxisId], Field(examples=["channel"])] = (
-615        None  # todo: validate existence of axis
-616    )
-617    """The axis of non-scalar gains/offsets.
-618    Invalid for scalar gains/offsets.
-619    """
-620
-621    gain: Union[float, NotEmpty[List[float]]] = 1.0
-622    """multiplicative factor"""
-623
-624    offset: Union[float, NotEmpty[List[float]]] = 0.0
-625    """additive term"""
-626
-627    @model_validator(mode="after")
-628    def either_gain_or_offset(self) -> Self:
-629        if (
-630            self.gain == 1.0
-631            or isinstance(self.gain, list)
-632            and all(g == 1.0 for g in self.gain)
-633        ) and (
-634            self.offset == 0.0
-635            or isinstance(self.offset, list)
-636            and all(off == 0.0 for off in self.offset)
-637        ):
-638            raise ValueError(
-639                "Redundant linear scaling not allowd. Set `gain` != 1.0 and/or `offset`"
-640                + " != 0.0."
-641            )
-642
-643        return self
+            
    637class ScaleLinearKwargs(ProcessingKwargs):
+638    axis: Annotated[Optional[NonBatchAxisId], Field(examples=["channel"])] = (
+639        None  # todo: validate existence of axis
+640    )
+641    """The axis of non-scalar gains/offsets.
+642    Invalid for scalar gains/offsets.
+643    """
+644
+645    gain: Union[float, NotEmpty[List[float]]] = 1.0
+646    """multiplicative factor"""
+647
+648    offset: Union[float, NotEmpty[List[float]]] = 0.0
+649    """additive term"""
+650
+651    @model_validator(mode="after")
+652    def either_gain_or_offset(self) -> Self:
+653        if (
+654            self.gain == 1.0
+655            or isinstance(self.gain, list)
+656            and all(g == 1.0 for g in self.gain)
+657        ) and (
+658            self.offset == 0.0
+659            or isinstance(self.offset, list)
+660            and all(off == 0.0 for off in self.offset)
+661        ):
+662            raise ValueError(
+663                "Redundant linear scaling not allowd. Set `gain` != 1.0 and/or `offset`"
+664                + " != 0.0."
+665            )
+666
+667        return self
 
    
 
 
@@ -7292,7 +7417,7 @@ 
    Inherited Members
    
 
                             
    
                                 
    
-            axis: Annotated[Optional[Annotated[bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]], Predicate(func=<function <lambda> at 0x7f1c1523f380>)]], FieldInfo(annotation=NoneType, required=True, examples=['channel'])]
+            axis: Annotated[Optional[Annotated[AxisId, Predicate(func=<function <lambda> at 0x7afc943332e0>)]], FieldInfo(annotation=NoneType, required=True, examples=['channel'])]
 
         
     
    
@@ -7342,23 +7467,23 @@ 
    Inherited Members
    
 
     
    
     
-            
    627    @model_validator(mode="after")
-628    def either_gain_or_offset(self) -> Self:
-629        if (
-630            self.gain == 1.0
-631            or isinstance(self.gain, list)
-632            and all(g == 1.0 for g in self.gain)
-633        ) and (
-634            self.offset == 0.0
-635            or isinstance(self.offset, list)
-636            and all(off == 0.0 for off in self.offset)
-637        ):
-638            raise ValueError(
-639                "Redundant linear scaling not allowd. Set `gain` != 1.0 and/or `offset`"
-640                + " != 0.0."
-641            )
-642
-643        return self
+            
    651    @model_validator(mode="after")
+652    def either_gain_or_offset(self) -> Self:
+653        if (
+654            self.gain == 1.0
+655            or isinstance(self.gain, list)
+656            and all(g == 1.0 for g in self.gain)
+657        ) and (
+658            self.offset == 0.0
+659            or isinstance(self.offset, list)
+660            and all(off == 0.0 for off in self.offset)
+661        ):
+662            raise ValueError(
+663                "Redundant linear scaling not allowd. Set `gain` != 1.0 and/or `offset`"
+664                + " != 0.0."
+665            )
+666
+667        return self
 
    
 
 
@@ -7382,7 +7507,7 @@ 
    Inherited Members
    
                                 
    
             model_fields        =
 
-            {'axis': FieldInfo(annotation=Union[Annotated[ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]], Predicate], NoneType], required=False, examples=['channel']), 'gain': FieldInfo(annotation=Union[float, Annotated[List[float], MinLen]], required=False, default=1.0), 'offset': FieldInfo(annotation=Union[float, Annotated[List[float], MinLen]], required=False, default=0.0)}
+            {'axis': FieldInfo(annotation=Union[Annotated[AxisId, Predicate], NoneType], required=False, examples=['channel']), 'gain': FieldInfo(annotation=Union[float, Annotated[List[float], MinLen]], required=False, default=1.0), 'offset': FieldInfo(annotation=Union[float, Annotated[List[float], MinLen]], required=False, default=0.0)}
 
         
     
    
@@ -7456,11 +7581,11 @@ 
    Inherited Members
    
 
     
    
     
-            
    646class ScaleLinearDescr(ProcessingDescrBase):
-647    """Fixed linear scaling."""
-648
-649    id: Literal["scale_linear"] = "scale_linear"
-650    kwargs: ScaleLinearKwargs
+            
    670class ScaleLinearDescr(ProcessingDescrBase):
+671    """Fixed linear scaling."""
+672
+673    id: Literal["scale_linear"] = "scale_linear"
+674    kwargs: ScaleLinearKwargs
 
    
 
 
@@ -7585,15 +7710,15 @@ 
    Inherited Members
    
 
     
    
     
-            
    653class SigmoidDescr(ProcessingDescrBase):
-654    """The logistic sigmoid funciton, a.k.a. expit function."""
-655
-656    id: Literal["sigmoid"] = "sigmoid"
-657
-658    @property
-659    def kwargs(self) -> ProcessingKwargs:
-660        """empty kwargs"""
-661        return ProcessingKwargs()
+            
    677class SigmoidDescr(ProcessingDescrBase):
+678    """The logistic sigmoid funciton, a.k.a. expit function."""
+679
+680    id: Literal["sigmoid"] = "sigmoid"
+681
+682    @property
+683    def kwargs(self) -> ProcessingKwargs:
+684        """empty kwargs"""
+685        return ProcessingKwargs()
 
    
 
 
@@ -7621,10 +7746,10 @@ 
    Inherited Members
    
 
     
    
     
-            
    658    @property
-659    def kwargs(self) -> ProcessingKwargs:
-660        """empty kwargs"""
-661        return ProcessingKwargs()
+            
    682    @property
+683    def kwargs(self) -> ProcessingKwargs:
+684        """empty kwargs"""
+685        return ProcessingKwargs()
 
    
 
 
@@ -7727,41 +7852,41 @@ 
    Inherited Members
    
 
     
    
     
-            
    664class FixedZeroMeanUnitVarianceKwargs(ProcessingKwargs):
-665    """Normalize with fixed, precomputed values for mean and variance.
-666    See `zero_mean_unit_variance` for data dependent normalization."""
-667
-668    mean: Annotated[
-669        Union[float, NotEmpty[Tuple[float, ...]]],
-670        Field(examples=[3.14, (1.1, -2.2, 3.3)]),
-671    ]
-672    """The mean value(s) to normalize with. Specify `axis` for a sequence of `mean` values"""
-673
-674    std: Annotated[
-675        Union[
-676            Annotated[float, Ge(1e-6)], NotEmpty[Tuple[Annotated[float, Ge(1e-6)], ...]]
-677        ],
-678        Field(examples=[1.05, (0.1, 0.2, 0.3)]),
-679    ]
-680    """The standard deviation value(s) to normalize with. Size must match `mean` values."""
-681
-682    axis: Annotated[Optional[NonBatchAxisId], Field(examples=["channel", "index"])] = (
-683        None  # todo: validate existence of axis
-684    )
-685    """The axis of the mean/std values to normalize each entry along that dimension separately.
-686    Invalid for scalar gains/offsets.
-687    """
-688
-689    @model_validator(mode="after")
-690    def mean_and_std_match(self) -> Self:
-691        mean_len = 1 if isinstance(self.mean, (float, int)) else len(self.mean)
-692        std_len = 1 if isinstance(self.std, (float, int)) else len(self.std)
-693        if mean_len != std_len:
-694            raise ValueError(
-695                "size of `mean` ({mean_len}) and `std` ({std_len}) must match."
-696            )
+            
    688class FixedZeroMeanUnitVarianceKwargs(ProcessingKwargs):
+689    """Normalize with fixed, precomputed values for mean and variance.
+690    See `zero_mean_unit_variance` for data dependent normalization."""
+691
+692    mean: Annotated[
+693        Union[float, NotEmpty[Tuple[float, ...]]],
+694        Field(examples=[3.14, (1.1, -2.2, 3.3)]),
+695    ]
+696    """The mean value(s) to normalize with. Specify `axis` for a sequence of `mean` values"""
 697
-698        return self
+698    std: Annotated[
+699        Union[
+700            Annotated[float, Ge(1e-6)], NotEmpty[Tuple[Annotated[float, Ge(1e-6)], ...]]
+701        ],
+702        Field(examples=[1.05, (0.1, 0.2, 0.3)]),
+703    ]
+704    """The standard deviation value(s) to normalize with. Size must match `mean` values."""
+705
+706    axis: Annotated[Optional[NonBatchAxisId], Field(examples=["channel", "index"])] = (
+707        None  # todo: validate existence of axis
+708    )
+709    """The axis of the mean/std values to normalize each entry along that dimension separately.
+710    Invalid for scalar gains/offsets.
+711    """
+712
+713    @model_validator(mode="after")
+714    def mean_and_std_match(self) -> Self:
+715        mean_len = 1 if isinstance(self.mean, (float, int)) else len(self.mean)
+716        std_len = 1 if isinstance(self.std, (float, int)) else len(self.std)
+717        if mean_len != std_len:
+718            raise ValueError(
+719                "size of `mean` ({mean_len}) and `std` ({std_len}) must match."
+720            )
+721
+722        return self
 
    
 
 
@@ -7798,7 +7923,7 @@ 
    Inherited Members
    
                             
    
                             
    
                                 
    
-            axis: Annotated[Optional[Annotated[bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]], Predicate(func=<function <lambda> at 0x7f1c1523f380>)]], FieldInfo(annotation=NoneType, required=True, examples=['channel', 'index'])]
+            axis: Annotated[Optional[Annotated[AxisId, Predicate(func=<function <lambda> at 0x7afc943332e0>)]], FieldInfo(annotation=NoneType, required=True, examples=['channel', 'index'])]
 
         
     
    
@@ -7822,16 +7947,16 @@ 
    Inherited Members
    
 
     
    
     
-            
    689    @model_validator(mode="after")
-690    def mean_and_std_match(self) -> Self:
-691        mean_len = 1 if isinstance(self.mean, (float, int)) else len(self.mean)
-692        std_len = 1 if isinstance(self.std, (float, int)) else len(self.std)
-693        if mean_len != std_len:
-694            raise ValueError(
-695                "size of `mean` ({mean_len}) and `std` ({std_len}) must match."
-696            )
-697
-698        return self
+            
    713    @model_validator(mode="after")
+714    def mean_and_std_match(self) -> Self:
+715        mean_len = 1 if isinstance(self.mean, (float, int)) else len(self.mean)
+716        std_len = 1 if isinstance(self.std, (float, int)) else len(self.std)
+717        if mean_len != std_len:
+718            raise ValueError(
+719                "size of `mean` ({mean_len}) and `std` ({std_len}) must match."
+720            )
+721
+722        return self
 
    
 
 
@@ -7855,7 +7980,7 @@ 
    Inherited Members
    
                                 
    
             model_fields        =
 
-            {'mean': FieldInfo(annotation=Union[float, Annotated[Tuple[float, ...], MinLen]], required=True, examples=[3.14, (1.1, -2.2, 3.3)]), 'std': FieldInfo(annotation=Union[Annotated[float, Ge], Annotated[Tuple[Annotated[float, Ge], ...], MinLen]], required=True, examples=[1.05, (0.1, 0.2, 0.3)]), 'axis': FieldInfo(annotation=Union[Annotated[ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]], Predicate], NoneType], required=False, examples=['channel', 'index'])}
+            {'mean': FieldInfo(annotation=Union[float, Annotated[Tuple[float, ...], MinLen]], required=True, examples=[3.14, (1.1, -2.2, 3.3)]), 'std': FieldInfo(annotation=Union[Annotated[float, Ge], Annotated[Tuple[Annotated[float, Ge], ...], MinLen]], required=True, examples=[1.05, (0.1, 0.2, 0.3)]), 'axis': FieldInfo(annotation=Union[Annotated[AxisId, Predicate], NoneType], required=False, examples=['channel', 'index'])}
 
         
     
    
@@ -7929,11 +8054,11 @@ 
    Inherited Members
    
 
     
    
     
-            
    701class FixedZeroMeanUnitVarianceDescr(ProcessingDescrBase):
-702    """Subtract a given mean and divide by a given variance."""
-703
-704    id: Literal["fixed_zero_mean_unit_variance"] = "fixed_zero_mean_unit_variance"
-705    kwargs: FixedZeroMeanUnitVarianceKwargs
+            
    725class FixedZeroMeanUnitVarianceDescr(ProcessingDescrBase):
+726    """Subtract a given mean and divide by a given variance."""
+727
+728    id: Literal["fixed_zero_mean_unit_variance"] = "fixed_zero_mean_unit_variance"
+729    kwargs: FixedZeroMeanUnitVarianceKwargs
 
    
 
 
@@ -8058,18 +8183,18 @@ 
    Inherited Members
    
 
     
    
     
-            
    708class ZeroMeanUnitVarianceKwargs(ProcessingKwargs):
-709    axes: Annotated[
-710        Optional[Sequence[AxisId]], Field(examples=[("batch", "x", "y")])
-711    ] = None
-712    """The subset of axes to normalize jointly, i.e. axes to reduce to compute mean/std.
-713    For example to normalize 'batch', 'x' and 'y' jointly in a tensor ('batch', 'channel', 'y', 'x')
-714    resulting in a tensor of equal shape normalized per channel, specify `axes=('batch', 'x', 'y')`.
-715    To normalize each sample independently leave out the 'batch' axis.
-716    Default: Scale all axes jointly."""
-717
-718    eps: Annotated[float, Interval(gt=0, le=0.1)] = 1e-6
-719    """epsilon for numeric stability: `out = (tensor - mean) / (std + eps)`."""
+            
    732class ZeroMeanUnitVarianceKwargs(ProcessingKwargs):
+733    axes: Annotated[
+734        Optional[Sequence[AxisId]], Field(examples=[("batch", "x", "y")])
+735    ] = None
+736    """The subset of axes to normalize jointly, i.e. axes to reduce to compute mean/std.
+737    For example to normalize 'batch', 'x' and 'y' jointly in a tensor ('batch', 'channel', 'y', 'x')
+738    resulting in a tensor of equal shape normalized per channel, specify `axes=('batch', 'x', 'y')`.
+739    To normalize each sample independently leave out the 'batch' axis.
+740    Default: Scale all axes jointly."""
+741
+742    eps: Annotated[float, Interval(gt=0, le=0.1)] = 1e-6
+743    """epsilon for numeric stability: `out = (tensor - mean) / (std + eps)`."""
 
    
 
 
@@ -8079,7 +8204,7 @@ 
    Inherited Members
    
 
                             
    
                                 
    
-            axes: Annotated[Optional[Sequence[bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]]], FieldInfo(annotation=NoneType, required=True, examples=[('batch', 'x', 'y')])]
+            axes: Annotated[Optional[Sequence[AxisId]], FieldInfo(annotation=NoneType, required=True, examples=[('batch', 'x', 'y')])]
 
         
     
    
@@ -8124,7 +8249,7 @@ 
    Inherited Members
    
                                 
    
             model_fields        =
 
-            {'axes': FieldInfo(annotation=Union[Sequence[ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]], NoneType], required=False, examples=[('batch', 'x', 'y')]), 'eps': FieldInfo(annotation=float, required=False, default=1e-06, metadata=[Interval(gt=0, ge=None, lt=None, le=0.1)])}
+            {'axes': FieldInfo(annotation=Union[Sequence[AxisId], NoneType], required=False, examples=[('batch', 'x', 'y')]), 'eps': FieldInfo(annotation=float, required=False, default=1e-06, metadata=[Interval(gt=0, ge=None, lt=None, le=0.1)])}
 
         
     
    
@@ -8198,11 +8323,11 @@ 
    Inherited Members
    
 
     
    
     
-            
    722class ZeroMeanUnitVarianceDescr(ProcessingDescrBase):
-723    """Subtract mean and divide by variance."""
-724
-725    id: Literal["zero_mean_unit_variance"] = "zero_mean_unit_variance"
-726    kwargs: ZeroMeanUnitVarianceKwargs
+            
    746class ZeroMeanUnitVarianceDescr(ProcessingDescrBase):
+747    """Subtract mean and divide by variance."""
+748
+749    id: Literal["zero_mean_unit_variance"] = "zero_mean_unit_variance"
+750    kwargs: ZeroMeanUnitVarianceKwargs
 
    
 
 
@@ -8327,41 +8452,41 @@ 
    Inherited Members
    
 
     
    
     
-            
    729class ScaleRangeKwargs(ProcessingKwargs):
-730    axes: Annotated[
-731        Optional[Sequence[AxisId]], Field(examples=[("batch", "x", "y")])
-732    ] = None
-733    """The subset of axes to normalize jointly, i.e. axes to reduce to compute the min/max percentile value.
-734    For example to normalize 'batch', 'x' and 'y' jointly in a tensor ('batch', 'channel', 'y', 'x')
-735    resulting in a tensor of equal shape normalized per channel, specify `axes=('batch', 'x', 'y')`.
-736    To normalize samples indepdencently, leave out the "batch" axis.
-737    Default: Scale all axes jointly."""
-738
-739    min_percentile: Annotated[float, Interval(ge=0, lt=100)] = 0.0
-740    """The lower percentile used for normalization."""
-741
-742    max_percentile: Annotated[float, Interval(gt=1, le=100)] = 100.0
-743    """The upper percentile used for normalization
-744    Has to be bigger than `min_percentile`.
-745    The range is 1 to 100 instead of 0 to 100 to avoid mistakenly
-746    accepting percentiles specified in the range 0.0 to 1.0."""
-747
-748    eps: Annotated[float, Interval(gt=0, le=0.1)] = 1e-6
-749    """Epsilon for numeric stability.
-750    `out = (tensor - v_lower) / (v_upper - v_lower + eps)`;
-751    with `v_lower,v_upper` values at the respective percentiles."""
-752
-753    reference_tensor: Optional[TensorId] = None
-754    """Tensor ID to compute the percentiles from. Default: The tensor itself.
-755    For any tensor in `inputs` only input tensor references are allowed."""
-756
-757    @field_validator("max_percentile", mode="after")
-758    @classmethod
-759    def min_smaller_max(cls, value: float, info: ValidationInfo) -> float:
-760        if (min_p := info.data["min_percentile"]) >= value:
-761            raise ValueError(f"min_percentile {min_p} >= max_percentile {value}")
+            
    753class ScaleRangeKwargs(ProcessingKwargs):
+754    axes: Annotated[
+755        Optional[Sequence[AxisId]], Field(examples=[("batch", "x", "y")])
+756    ] = None
+757    """The subset of axes to normalize jointly, i.e. axes to reduce to compute the min/max percentile value.
+758    For example to normalize 'batch', 'x' and 'y' jointly in a tensor ('batch', 'channel', 'y', 'x')
+759    resulting in a tensor of equal shape normalized per channel, specify `axes=('batch', 'x', 'y')`.
+760    To normalize samples indepdencently, leave out the "batch" axis.
+761    Default: Scale all axes jointly."""
 762
-763        return value
+763    min_percentile: Annotated[float, Interval(ge=0, lt=100)] = 0.0
+764    """The lower percentile used for normalization."""
+765
+766    max_percentile: Annotated[float, Interval(gt=1, le=100)] = 100.0
+767    """The upper percentile used for normalization
+768    Has to be bigger than `min_percentile`.
+769    The range is 1 to 100 instead of 0 to 100 to avoid mistakenly
+770    accepting percentiles specified in the range 0.0 to 1.0."""
+771
+772    eps: Annotated[float, Interval(gt=0, le=0.1)] = 1e-6
+773    """Epsilon for numeric stability.
+774    `out = (tensor - v_lower) / (v_upper - v_lower + eps)`;
+775    with `v_lower,v_upper` values at the respective percentiles."""
+776
+777    reference_tensor: Optional[TensorId] = None
+778    """Tensor ID to compute the percentiles from. Default: The tensor itself.
+779    For any tensor in `inputs` only input tensor references are allowed."""
+780
+781    @field_validator("max_percentile", mode="after")
+782    @classmethod
+783    def min_smaller_max(cls, value: float, info: ValidationInfo) -> float:
+784        if (min_p := info.data["min_percentile"]) >= value:
+785            raise ValueError(f"min_percentile {min_p} >= max_percentile {value}")
+786
+787        return value
 
    
 
 
@@ -8371,7 +8496,7 @@ 
    Inherited Members
    
 
                             
    
                                 
    
-            axes: Annotated[Optional[Sequence[bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]]], FieldInfo(annotation=NoneType, required=True, examples=[('batch', 'x', 'y')])]
+            axes: Annotated[Optional[Sequence[AxisId]], FieldInfo(annotation=NoneType, required=True, examples=[('batch', 'x', 'y')])]
 
         
     
    
@@ -8457,13 +8582,13 @@ 
    Inherited Members
    
 
     
    
     
-            
    757    @field_validator("max_percentile", mode="after")
-758    @classmethod
-759    def min_smaller_max(cls, value: float, info: ValidationInfo) -> float:
-760        if (min_p := info.data["min_percentile"]) >= value:
-761            raise ValueError(f"min_percentile {min_p} >= max_percentile {value}")
-762
-763        return value
+            
    781    @field_validator("max_percentile", mode="after")
+782    @classmethod
+783    def min_smaller_max(cls, value: float, info: ValidationInfo) -> float:
+784        if (min_p := info.data["min_percentile"]) >= value:
+785            raise ValueError(f"min_percentile {min_p} >= max_percentile {value}")
+786
+787        return value
 
    
 
 
@@ -8487,7 +8612,7 @@ 
    Inherited Members
    
                                 
    
             model_fields        =
 
-            {'axes': FieldInfo(annotation=Union[Sequence[ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]], NoneType], required=False, examples=[('batch', 'x', 'y')]), 'min_percentile': FieldInfo(annotation=float, required=False, default=0.0, metadata=[Interval(gt=None, ge=0, lt=100, le=None)]), 'max_percentile': FieldInfo(annotation=float, required=False, default=100.0, metadata=[Interval(gt=1, ge=None, lt=None, le=100)]), 'eps': FieldInfo(annotation=float, required=False, default=1e-06, metadata=[Interval(gt=0, ge=None, lt=None, le=0.1)]), 'reference_tensor': FieldInfo(annotation=Union[ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]], NoneType], required=False)}
+            {'axes': FieldInfo(annotation=Union[Sequence[AxisId], NoneType], required=False, examples=[('batch', 'x', 'y')]), 'min_percentile': FieldInfo(annotation=float, required=False, default=0.0, metadata=[Interval(gt=None, ge=0, lt=100, le=None)]), 'max_percentile': FieldInfo(annotation=float, required=False, default=100.0, metadata=[Interval(gt=1, ge=None, lt=None, le=100)]), 'eps': FieldInfo(annotation=float, required=False, default=1e-06, metadata=[Interval(gt=0, ge=None, lt=None, le=0.1)]), 'reference_tensor': FieldInfo(annotation=Union[ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]], NoneType], required=False)}
 
         
     
    
@@ -8561,11 +8686,11 @@ 
    Inherited Members
    
 
     
    
     
-            
    766class ScaleRangeDescr(ProcessingDescrBase):
-767    """Scale with percentiles."""
-768
-769    id: Literal["scale_range"] = "scale_range"
-770    kwargs: ScaleRangeKwargs
+            
    790class ScaleRangeDescr(ProcessingDescrBase):
+791    """Scale with percentiles."""
+792
+793    id: Literal["scale_range"] = "scale_range"
+794    kwargs: ScaleRangeKwargs
 
    
 
 
@@ -8690,25 +8815,25 @@ 
    Inherited Members
    
 
     
    
     
-            
    773class ScaleMeanVarianceKwargs(ProcessingKwargs):
-774    """Scale a tensor's data distribution to match another tensor's mean/std.
-775    `out  = (tensor - mean) / (std + eps) * (ref_std + eps) + ref_mean.`"""
-776
-777    reference_tensor: TensorId
-778    """Name of tensor to match."""
-779
-780    axes: Annotated[
-781        Optional[Sequence[AxisId]], Field(examples=[("batch", "x", "y")])
-782    ] = None
-783    """The subset of axes to normalize jointly, i.e. axes to reduce to compute mean/std.
-784    For example to normalize 'batch', 'x' and 'y' jointly in a tensor ('batch', 'channel', 'y', 'x')
-785    resulting in a tensor of equal shape normalized per channel, specify `axes=('batch', 'x', 'y')`.
-786    To normalize samples independently, leave out the 'batch' axis.
-787    Default: Scale all axes jointly."""
-788
-789    eps: Annotated[float, Interval(gt=0, le=0.1)] = 1e-6
-790    """Epsilon for numeric stability:
-791    `out  = (tensor - mean) / (std + eps) * (ref_std + eps) + ref_mean.`"""
+            
    797class ScaleMeanVarianceKwargs(ProcessingKwargs):
+798    """Scale a tensor's data distribution to match another tensor's mean/std.
+799    `out  = (tensor - mean) / (std + eps) * (ref_std + eps) + ref_mean.`"""
+800
+801    reference_tensor: TensorId
+802    """Name of tensor to match."""
+803
+804    axes: Annotated[
+805        Optional[Sequence[AxisId]], Field(examples=[("batch", "x", "y")])
+806    ] = None
+807    """The subset of axes to normalize jointly, i.e. axes to reduce to compute mean/std.
+808    For example to normalize 'batch', 'x' and 'y' jointly in a tensor ('batch', 'channel', 'y', 'x')
+809    resulting in a tensor of equal shape normalized per channel, specify `axes=('batch', 'x', 'y')`.
+810    To normalize samples independently, leave out the 'batch' axis.
+811    Default: Scale all axes jointly."""
+812
+813    eps: Annotated[float, Interval(gt=0, le=0.1)] = 1e-6
+814    """Epsilon for numeric stability:
+815    `out  = (tensor - mean) / (std + eps) * (ref_std + eps) + ref_mean.`"""
 
    
 
 
@@ -8732,7 +8857,7 @@ 
    Inherited Members
    
                             
    
                             
    
                                 
    
-            axes: Annotated[Optional[Sequence[bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]]], FieldInfo(annotation=NoneType, required=True, examples=[('batch', 'x', 'y')])]
+            axes: Annotated[Optional[Sequence[AxisId]], FieldInfo(annotation=NoneType, required=True, examples=[('batch', 'x', 'y')])]
 
         
     
    
@@ -8778,7 +8903,7 @@ 
    Inherited Members
    
                                 
    
             model_fields        =
 
-            {'reference_tensor': FieldInfo(annotation=ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]], required=True), 'axes': FieldInfo(annotation=Union[Sequence[ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]], NoneType], required=False, examples=[('batch', 'x', 'y')]), 'eps': FieldInfo(annotation=float, required=False, default=1e-06, metadata=[Interval(gt=0, ge=None, lt=None, le=0.1)])}
+            {'reference_tensor': FieldInfo(annotation=ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]], required=True), 'axes': FieldInfo(annotation=Union[Sequence[AxisId], NoneType], required=False, examples=[('batch', 'x', 'y')]), 'eps': FieldInfo(annotation=float, required=False, default=1e-06, metadata=[Interval(gt=0, ge=None, lt=None, le=0.1)])}
 
         
     
    
@@ -8852,11 +8977,11 @@ 
    Inherited Members
    
 
     
    
     
-            
    794class ScaleMeanVarianceDescr(ProcessingDescrBase):
-795    """Scale the tensor s.t. its mean and variance match a reference tensor."""
-796
-797    id: Literal["scale_mean_variance"] = "scale_mean_variance"
-798    kwargs: ScaleMeanVarianceKwargs
+            
    818class ScaleMeanVarianceDescr(ProcessingDescrBase):
+819    """Scale the tensor s.t. its mean and variance match a reference tensor."""
+820
+821    id: Literal["scale_mean_variance"] = "scale_mean_variance"
+822    kwargs: ScaleMeanVarianceKwargs
 
    
 
 
@@ -9007,175 +9132,175 @@ 
    Inherited Members
    
 
     
    
     
-            
     832class TensorDescrBase(Node, Generic[IO_AxisT]):
- 833    id: TensorId
- 834    """Tensor id. No duplicates are allowed."""
- 835
- 836    description: Annotated[str, MaxLen(128)] = ""
- 837    """free text description"""
- 838
- 839    axes: NotEmpty[Sequence[IO_AxisT]]
- 840    """tensor axes"""
- 841
- 842    @property
- 843    def shape(self):
- 844        return tuple(a.size for a in self.axes)
- 845
- 846    @field_validator("axes", mode="after", check_fields=False)
- 847    @classmethod
- 848    def _validate_axes(cls, axes: Sequence[AnyAxis]) -> Sequence[AnyAxis]:
- 849        seen_types: Set[str] = set()
- 850        duplicate_axes_types: Set[str] = set()
- 851        for a in axes:
- 852            if a.type in ("time", "space"):
- 853                continue  # duplicates allowed
- 854
- 855            (duplicate_axes_types if a.type in seen_types else seen_types).add(a.type)
- 856
- 857        if duplicate_axes_types:
- 858            raise ValueError(f"Duplicate axis types: {duplicate_axes_types}")
+            
     856class TensorDescrBase(Node, Generic[IO_AxisT]):
+ 857    id: TensorId
+ 858    """Tensor id. No duplicates are allowed."""
  859
- 860        seen_ids: Set[AxisId] = set()
- 861        duplicate_axes_ids: Set[AxisId] = set()
- 862        for a in axes:
- 863            (duplicate_axes_ids if a.id in seen_ids else seen_ids).add(a.id)
- 864
- 865        if duplicate_axes_ids:
- 866            raise ValueError(f"Duplicate axis ids: {duplicate_axes_ids}")
- 867
- 868        return axes
+ 860    description: Annotated[str, MaxLen(128)] = ""
+ 861    """free text description"""
+ 862
+ 863    axes: NotEmpty[Sequence[IO_AxisT]]
+ 864    """tensor axes"""
+ 865
+ 866    @property
+ 867    def shape(self):
+ 868        return tuple(a.size for a in self.axes)
  869
- 870    test_tensor: FileDescr
- 871    """An example tensor to use for testing.
- 872    Using the model with the test input tensors is expected to yield the test output tensors.
- 873    Each test tensor has be a an ndarray in the
- 874    [numpy.lib file format](https://numpy.org/doc/stable/reference/generated/numpy.lib.format.html#module-numpy.lib.format).
- 875    The file extension must be '.npy'."""
- 876
- 877    sample_tensor: Optional[FileDescr] = None
- 878    """A sample tensor to illustrate a possible input/output for the model,
- 879    The sample image primarily serves to inform a human user about an example use case
- 880    and is typically stored as .hdf5, .png or .tiff.
- 881    It has to be readable by the [imageio library](https://imageio.readthedocs.io/en/stable/formats/index.html#supported-formats)
- 882    (numpy's `.npy` format is not supported).
- 883    The image dimensionality has to match the number of axes specified in this tensor description.
- 884    """
- 885
- 886    @model_validator(mode="after")
- 887    def _validate_sample_tensor(self) -> Self:
- 888        if (
- 889            self.sample_tensor is None
- 890            or not validation_context_var.get().perform_io_checks
- 891        ):
- 892            return self
+ 870    @field_validator("axes", mode="after", check_fields=False)
+ 871    @classmethod
+ 872    def _validate_axes(cls, axes: Sequence[AnyAxis]) -> Sequence[AnyAxis]:
+ 873        seen_types: Set[str] = set()
+ 874        duplicate_axes_types: Set[str] = set()
+ 875        for a in axes:
+ 876            if a.type in ("time", "space"):
+ 877                continue  # duplicates allowed
+ 878
+ 879            (duplicate_axes_types if a.type in seen_types else seen_types).add(a.type)
+ 880
+ 881        if duplicate_axes_types:
+ 882            raise ValueError(f"Duplicate axis types: {duplicate_axes_types}")
+ 883
+ 884        seen_ids: Set[AxisId] = set()
+ 885        duplicate_axes_ids: Set[AxisId] = set()
+ 886        for a in axes:
+ 887            (duplicate_axes_ids if a.id in seen_ids else seen_ids).add(a.id)
+ 888
+ 889        if duplicate_axes_ids:
+ 890            raise ValueError(f"Duplicate axis ids: {duplicate_axes_ids}")
+ 891
+ 892        return axes
  893
- 894        down = download(self.sample_tensor.source, sha256=self.sample_tensor.sha256)
- 895
- 896        local_source = down.path
- 897        tensor: NDArray[Any] = imread(
- 898            local_source, extension=PurePosixPath(down.original_file_name).suffix
- 899        )
- 900        n_dims = len(tensor.squeeze().shape)
- 901        n_dims_min = n_dims_max = len(self.axes)
- 902
- 903        for a in self.axes:
- 904            if isinstance(a, BatchAxis):
- 905                n_dims_min -= 1
- 906            elif isinstance(a.size, int):
- 907                if a.size == 1:
- 908                    n_dims_min -= 1
- 909            elif isinstance(a.size, ParameterizedSize):
- 910                if a.size.min == 1:
- 911                    n_dims_min -= 1
- 912            elif isinstance(a.size, SizeReference):
- 913                if a.size.offset < 2:
- 914                    # size reference may result in singleton axis
- 915                    n_dims_min -= 1
- 916            else:
- 917                assert_never(a.size)
- 918
- 919        n_dims_min = max(0, n_dims_min)
- 920        if n_dims < n_dims_min or n_dims > n_dims_max:
- 921            raise ValueError(
- 922                f"Expected sample tensor to have {n_dims_min} to"
- 923                + f" {n_dims_max} dimensions, but found {n_dims} (shape: {tensor.shape})."
- 924            )
- 925
- 926        return self
- 927
- 928    data: Union[TensorDataDescr, NotEmpty[Sequence[TensorDataDescr]]] = (
- 929        IntervalOrRatioDataDescr()
- 930    )
- 931    """Description of the tensor's data values, optionally per channel.
- 932    If specified per channel, the data `type` needs to match across channels."""
- 933
- 934    @property
- 935    def dtype(
- 936        self,
- 937    ) -> Literal[
- 938        "float32",
- 939        "float64",
- 940        "uint8",
- 941        "int8",
- 942        "uint16",
- 943        "int16",
- 944        "uint32",
- 945        "int32",
- 946        "uint64",
- 947        "int64",
- 948        "bool",
- 949    ]:
- 950        """dtype as specified under `data.type` or `data[i].type`"""
- 951        if isinstance(self.data, collections.abc.Sequence):
- 952            return self.data[0].type
- 953        else:
- 954            return self.data.type
- 955
- 956    @field_validator("data", mode="after")
- 957    @classmethod
- 958    def _check_data_type_across_channels(
- 959        cls, value: Union[TensorDataDescr, NotEmpty[Sequence[TensorDataDescr]]]
- 960    ) -> Union[TensorDataDescr, NotEmpty[Sequence[TensorDataDescr]]]:
- 961        if not isinstance(value, list):
- 962            return value
- 963
- 964        dtypes = {t.type for t in value}
- 965        if len(dtypes) > 1:
- 966            raise ValueError(
- 967                "Tensor data descriptions per channel need to agree in their data"
- 968                + f" `type`, but found {dtypes}."
- 969            )
- 970
- 971        return value
- 972
- 973    @model_validator(mode="after")
- 974    def _check_data_matches_channelaxis(self) -> Self:
- 975        if not isinstance(self.data, (list, tuple)):
- 976            return self
- 977
- 978        for a in self.axes:
- 979            if isinstance(a, ChannelAxis):
- 980                size = a.size
- 981                assert isinstance(size, int)
- 982                break
- 983        else:
- 984            return self
- 985
- 986        if len(self.data) != size:
- 987            raise ValueError(
- 988                f"Got tensor data descriptions for {len(self.data)} channels, but"
- 989                + f" '{a.id}' axis has size {size}."
- 990            )
- 991
- 992        return self
- 993
- 994    def get_axis_sizes_for_array(self, array: NDArray[Any]) -> Dict[AxisId, int]:
- 995        if len(array.shape) != len(self.axes):
- 996            raise ValueError(
- 997                f"Dimension mismatch: array shape {array.shape} (#{len(array.shape)})"
- 998                + f" incompatible with {len(self.axes)} axes."
- 999            )
-1000        return {a.id: array.shape[i] for i, a in enumerate(self.axes)}
+ 894    test_tensor: FileDescr
+ 895    """An example tensor to use for testing.
+ 896    Using the model with the test input tensors is expected to yield the test output tensors.
+ 897    Each test tensor has be a an ndarray in the
+ 898    [numpy.lib file format](https://numpy.org/doc/stable/reference/generated/numpy.lib.format.html#module-numpy.lib.format).
+ 899    The file extension must be '.npy'."""
+ 900
+ 901    sample_tensor: Optional[FileDescr] = None
+ 902    """A sample tensor to illustrate a possible input/output for the model,
+ 903    The sample image primarily serves to inform a human user about an example use case
+ 904    and is typically stored as .hdf5, .png or .tiff.
+ 905    It has to be readable by the [imageio library](https://imageio.readthedocs.io/en/stable/formats/index.html#supported-formats)
+ 906    (numpy's `.npy` format is not supported).
+ 907    The image dimensionality has to match the number of axes specified in this tensor description.
+ 908    """
+ 909
+ 910    @model_validator(mode="after")
+ 911    def _validate_sample_tensor(self) -> Self:
+ 912        if (
+ 913            self.sample_tensor is None
+ 914            or not validation_context_var.get().perform_io_checks
+ 915        ):
+ 916            return self
+ 917
+ 918        down = download(self.sample_tensor.source, sha256=self.sample_tensor.sha256)
+ 919
+ 920        local_source = down.path
+ 921        tensor: NDArray[Any] = imread(
+ 922            local_source, extension=PurePosixPath(down.original_file_name).suffix
+ 923        )
+ 924        n_dims = len(tensor.squeeze().shape)
+ 925        n_dims_min = n_dims_max = len(self.axes)
+ 926
+ 927        for a in self.axes:
+ 928            if isinstance(a, BatchAxis):
+ 929                n_dims_min -= 1
+ 930            elif isinstance(a.size, int):
+ 931                if a.size == 1:
+ 932                    n_dims_min -= 1
+ 933            elif isinstance(a.size, ParameterizedSize):
+ 934                if a.size.min == 1:
+ 935                    n_dims_min -= 1
+ 936            elif isinstance(a.size, SizeReference):
+ 937                if a.size.offset < 2:
+ 938                    # size reference may result in singleton axis
+ 939                    n_dims_min -= 1
+ 940            else:
+ 941                assert_never(a.size)
+ 942
+ 943        n_dims_min = max(0, n_dims_min)
+ 944        if n_dims < n_dims_min or n_dims > n_dims_max:
+ 945            raise ValueError(
+ 946                f"Expected sample tensor to have {n_dims_min} to"
+ 947                + f" {n_dims_max} dimensions, but found {n_dims} (shape: {tensor.shape})."
+ 948            )
+ 949
+ 950        return self
+ 951
+ 952    data: Union[TensorDataDescr, NotEmpty[Sequence[TensorDataDescr]]] = (
+ 953        IntervalOrRatioDataDescr()
+ 954    )
+ 955    """Description of the tensor's data values, optionally per channel.
+ 956    If specified per channel, the data `type` needs to match across channels."""
+ 957
+ 958    @property
+ 959    def dtype(
+ 960        self,
+ 961    ) -> Literal[
+ 962        "float32",
+ 963        "float64",
+ 964        "uint8",
+ 965        "int8",
+ 966        "uint16",
+ 967        "int16",
+ 968        "uint32",
+ 969        "int32",
+ 970        "uint64",
+ 971        "int64",
+ 972        "bool",
+ 973    ]:
+ 974        """dtype as specified under `data.type` or `data[i].type`"""
+ 975        if isinstance(self.data, collections.abc.Sequence):
+ 976            return self.data[0].type
+ 977        else:
+ 978            return self.data.type
+ 979
+ 980    @field_validator("data", mode="after")
+ 981    @classmethod
+ 982    def _check_data_type_across_channels(
+ 983        cls, value: Union[TensorDataDescr, NotEmpty[Sequence[TensorDataDescr]]]
+ 984    ) -> Union[TensorDataDescr, NotEmpty[Sequence[TensorDataDescr]]]:
+ 985        if not isinstance(value, list):
+ 986            return value
+ 987
+ 988        dtypes = {t.type for t in value}
+ 989        if len(dtypes) > 1:
+ 990            raise ValueError(
+ 991                "Tensor data descriptions per channel need to agree in their data"
+ 992                + f" `type`, but found {dtypes}."
+ 993            )
+ 994
+ 995        return value
+ 996
+ 997    @model_validator(mode="after")
+ 998    def _check_data_matches_channelaxis(self) -> Self:
+ 999        if not isinstance(self.data, (list, tuple)):
+1000            return self
+1001
+1002        for a in self.axes:
+1003            if isinstance(a, ChannelAxis):
+1004                size = a.size
+1005                assert isinstance(size, int)
+1006                break
+1007        else:
+1008            return self
+1009
+1010        if len(self.data) != size:
+1011            raise ValueError(
+1012                f"Got tensor data descriptions for {len(self.data)} channels, but"
+1013                + f" '{a.id}' axis has size {size}."
+1014            )
+1015
+1016        return self
+1017
+1018    def get_axis_sizes_for_array(self, array: NDArray[Any]) -> Dict[AxisId, int]:
+1019        if len(array.shape) != len(self.axes):
+1020            raise ValueError(
+1021                f"Dimension mismatch: array shape {array.shape} (#{len(array.shape)})"
+1022                + f" incompatible with {len(self.axes)} axes."
+1023            )
+1024        return {a.id: array.shape[i] for i, a in enumerate(self.axes)}
 
    
 
 
@@ -9231,9 +9356,9 @@ 
    Inherited Members
    
 
     
    
     
-            
    842    @property
-843    def shape(self):
-844        return tuple(a.size for a in self.axes)
+            
    866    @property
+867    def shape(self):
+868        return tuple(a.size for a in self.axes)
 
    
 
 
@@ -9298,27 +9423,27 @@ 
    Inherited Members
    
 
     
    
     
-            
    934    @property
-935    def dtype(
-936        self,
-937    ) -> Literal[
-938        "float32",
-939        "float64",
-940        "uint8",
-941        "int8",
-942        "uint16",
-943        "int16",
-944        "uint32",
-945        "int32",
-946        "uint64",
-947        "int64",
-948        "bool",
-949    ]:
-950        """dtype as specified under `data.type` or `data[i].type`"""
-951        if isinstance(self.data, collections.abc.Sequence):
-952            return self.data[0].type
-953        else:
-954            return self.data.type
+            
    958    @property
+959    def dtype(
+960        self,
+961    ) -> Literal[
+962        "float32",
+963        "float64",
+964        "uint8",
+965        "int8",
+966        "uint16",
+967        "int16",
+968        "uint32",
+969        "int32",
+970        "uint64",
+971        "int64",
+972        "bool",
+973    ]:
+974        """dtype as specified under `data.type` or `data[i].type`"""
+975        if isinstance(self.data, collections.abc.Sequence):
+976            return self.data[0].type
+977        else:
+978            return self.data.type
 
    
 
 
@@ -9332,19 +9457,19 @@ 
    Inherited Members
    
 
    
             
         def
-        get_axis_sizes_for_array(	self,	array: numpy.ndarray[typing.Any, numpy.dtype[typing.Any]]) -> Dict[bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]], int]:
+        get_axis_sizes_for_array(	self,	array: numpy.ndarray[typing.Any, numpy.dtype[typing.Any]]) -> Dict[AxisId, int]:
 
                 
 
     
    
     
-            
     994    def get_axis_sizes_for_array(self, array: NDArray[Any]) -> Dict[AxisId, int]:
- 995        if len(array.shape) != len(self.axes):
- 996            raise ValueError(
- 997                f"Dimension mismatch: array shape {array.shape} (#{len(array.shape)})"
- 998                + f" incompatible with {len(self.axes)} axes."
- 999            )
-1000        return {a.id: array.shape[i] for i, a in enumerate(self.axes)}
+            
    1018    def get_axis_sizes_for_array(self, array: NDArray[Any]) -> Dict[AxisId, int]:
+1019        if len(array.shape) != len(self.axes):
+1020            raise ValueError(
+1021                f"Dimension mismatch: array shape {array.shape} (#{len(array.shape)})"
+1022                + f" incompatible with {len(self.axes)} axes."
+1023            )
+1024        return {a.id: array.shape[i] for i, a in enumerate(self.axes)}
 
    
 
 
@@ -9403,28 +9528,28 @@ 
    Inherited Members
    
 
     
    
     
-            
    1003class InputTensorDescr(TensorDescrBase[InputAxis]):
-1004    id: TensorId = TensorId("input")
-1005    """Input tensor id.
-1006    No duplicates are allowed across all inputs and outputs."""
-1007
-1008    preprocessing: List[PreprocessingDescr] = Field(default_factory=list)
-1009    """Description of how this input should be preprocessed."""
-1010
-1011    @model_validator(mode="after")
-1012    def _validate_preprocessing_kwargs(self) -> Self:
-1013        axes_ids = [a.id for a in self.axes]
-1014        for p in self.preprocessing:
-1015            kwargs_axes: Union[Any, Sequence[Any]] = p.kwargs.get("axes", ())
-1016            if not isinstance(kwargs_axes, collections.abc.Sequence):
-1017                raise ValueError(
-1018                    f"Expeted `axes` to be a sequence, but got {type(kwargs_axes)}"
-1019                )
-1020
-1021            if any(a not in axes_ids for a in kwargs_axes):
-1022                raise ValueError("`kwargs.axes` needs to be subset of axes ids")
-1023
-1024        return self
+            
    1027class InputTensorDescr(TensorDescrBase[InputAxis]):
+1028    id: TensorId = TensorId("input")
+1029    """Input tensor id.
+1030    No duplicates are allowed across all inputs and outputs."""
+1031
+1032    preprocessing: List[PreprocessingDescr] = Field(default_factory=list)
+1033    """Description of how this input should be preprocessed."""
+1034
+1035    @model_validator(mode="after")
+1036    def _validate_preprocessing_kwargs(self) -> Self:
+1037        axes_ids = [a.id for a in self.axes]
+1038        for p in self.preprocessing:
+1039            kwargs_axes: Union[Any, Sequence[Any]] = p.kwargs.get("axes", ())
+1040            if not isinstance(kwargs_axes, collections.abc.Sequence):
+1041                raise ValueError(
+1042                    f"Expeted `axes` to be a sequence, but got {type(kwargs_axes)}"
+1043                )
+1044
+1045            if any(a not in axes_ids for a in kwargs_axes):
+1046                raise ValueError("`kwargs.axes` needs to be subset of axes ids")
+1047
+1048        return self
 
    
 
 
@@ -9522,99 +9647,99 @@ 
    Inherited Members
    
 
     
    
     
-            
    1027def convert_axes(
-1028    axes: str,
-1029    *,
-1030    shape: Union[
-1031        Sequence[int], _ParameterizedInputShape_v0_4, _ImplicitOutputShape_v0_4
-1032    ],
-1033    tensor_type: Literal["input", "output"],
-1034    halo: Optional[Sequence[int]],
-1035    size_refs: Mapping[_TensorName_v0_4, Mapping[str, int]],
-1036):
-1037    ret: List[AnyAxis] = []
-1038    for i, a in enumerate(axes):
-1039        axis_type = _AXIS_TYPE_MAP.get(a, a)
-1040        if axis_type == "batch":
-1041            ret.append(BatchAxis())
-1042            continue
-1043
-1044        scale = 1.0
-1045        if isinstance(shape, _ParameterizedInputShape_v0_4):
-1046            if shape.step[i] == 0:
-1047                size = shape.min[i]
-1048            else:
-1049                size = ParameterizedSize(min=shape.min[i], step=shape.step[i])
-1050        elif isinstance(shape, _ImplicitOutputShape_v0_4):
-1051            ref_t = str(shape.reference_tensor)
-1052            if ref_t.count(".") == 1:
-1053                t_id, orig_a_id = ref_t.split(".")
-1054            else:
-1055                t_id = ref_t
-1056                orig_a_id = a
-1057
-1058            a_id = _AXIS_ID_MAP.get(orig_a_id, a)
-1059            if not (orig_scale := shape.scale[i]):
-1060                # old way to insert a new axis dimension
-1061                size = int(2 * shape.offset[i])
-1062            else:
-1063                scale = 1 / orig_scale
-1064                if axis_type in ("channel", "index"):
-1065                    # these axes no longer have a scale
-1066                    offset_from_scale = orig_scale * size_refs.get(
-1067                        _TensorName_v0_4(t_id), {}
-1068                    ).get(orig_a_id, 0)
-1069                else:
-1070                    offset_from_scale = 0
-1071                size = SizeReference(
-1072                    tensor_id=TensorId(t_id),
-1073                    axis_id=AxisId(a_id),
-1074                    offset=int(offset_from_scale + 2 * shape.offset[i]),
-1075                )
-1076        elif isinstance(shape, collections.abc.Sequence):
-1077            size: Any = shape[i]
-1078            assert isinstance(size, int)
-1079        else:
-1080            assert_never(shape)
+            
    1051def convert_axes(
+1052    axes: str,
+1053    *,
+1054    shape: Union[
+1055        Sequence[int], _ParameterizedInputShape_v0_4, _ImplicitOutputShape_v0_4
+1056    ],
+1057    tensor_type: Literal["input", "output"],
+1058    halo: Optional[Sequence[int]],
+1059    size_refs: Mapping[_TensorName_v0_4, Mapping[str, int]],
+1060):
+1061    ret: List[AnyAxis] = []
+1062    for i, a in enumerate(axes):
+1063        axis_type = _AXIS_TYPE_MAP.get(a, a)
+1064        if axis_type == "batch":
+1065            ret.append(BatchAxis())
+1066            continue
+1067
+1068        scale = 1.0
+1069        if isinstance(shape, _ParameterizedInputShape_v0_4):
+1070            if shape.step[i] == 0:
+1071                size = shape.min[i]
+1072            else:
+1073                size = ParameterizedSize(min=shape.min[i], step=shape.step[i])
+1074        elif isinstance(shape, _ImplicitOutputShape_v0_4):
+1075            ref_t = str(shape.reference_tensor)
+1076            if ref_t.count(".") == 1:
+1077                t_id, orig_a_id = ref_t.split(".")
+1078            else:
+1079                t_id = ref_t
+1080                orig_a_id = a
 1081
-1082        if axis_type == "time":
-1083            if tensor_type == "input":
-1084                ret.append(TimeInputAxis(size=size, scale=scale))
-1085            else:
-1086                ret.append(
-1087                    TimeOutputAxis(
-1088                        size=size, scale=scale, halo=0 if halo is None else halo[i]
-1089                    )
-1090                )
-1091        elif axis_type == "index":
-1092            ret.append(IndexAxis(size=size))
-1093        elif axis_type == "channel":
-1094            assert not isinstance(size, ParameterizedSize)
-1095            if isinstance(size, SizeReference):
-1096                warnings.warn(
-1097                    "Conversion of channel size from an implicit output shape may by"
-1098                    + " wrong"
+1082            a_id = _AXIS_ID_MAP.get(orig_a_id, a)
+1083            if not (orig_scale := shape.scale[i]):
+1084                # old way to insert a new axis dimension
+1085                size = int(2 * shape.offset[i])
+1086            else:
+1087                scale = 1 / orig_scale
+1088                if axis_type in ("channel", "index"):
+1089                    # these axes no longer have a scale
+1090                    offset_from_scale = orig_scale * size_refs.get(
+1091                        _TensorName_v0_4(t_id), {}
+1092                    ).get(orig_a_id, 0)
+1093                else:
+1094                    offset_from_scale = 0
+1095                size = SizeReference(
+1096                    tensor_id=TensorId(t_id),
+1097                    axis_id=AxisId(a_id),
+1098                    offset=int(offset_from_scale + 2 * shape.offset[i]),
 1099                )
-1100                ret.append(
-1101                    ChannelAxis(
-1102                        channel_names=[
-1103                            Identifier(f"channel{i}") for i in range(size.offset)
-1104                        ]
-1105                    )
-1106                )
-1107            else:
-1108                ret.append(
-1109                    ChannelAxis(
-1110                        channel_names=[Identifier(f"channel{i}") for i in range(size)]
-1111                    )
-1112                )
-1113        elif axis_type == "space":
-1114            if tensor_type == "input":
-1115                ret.append(SpaceInputAxis(id=AxisId(a), size=size, scale=scale))
-1116            else:
-1117                ret.append(SpaceOutputAxis(id=AxisId(a), size=size, scale=scale))
-1118
-1119    return ret
+1100        elif isinstance(shape, collections.abc.Sequence):
+1101            size: Any = shape[i]
+1102            assert isinstance(size, int)
+1103        else:
+1104            assert_never(shape)
+1105
+1106        if axis_type == "time":
+1107            if tensor_type == "input":
+1108                ret.append(TimeInputAxis(size=size, scale=scale))
+1109            else:
+1110                ret.append(
+1111                    TimeOutputAxis(
+1112                        size=size, scale=scale, halo=0 if halo is None else halo[i]
+1113                    )
+1114                )
+1115        elif axis_type == "index":
+1116            ret.append(IndexAxis(size=size))
+1117        elif axis_type == "channel":
+1118            assert not isinstance(size, ParameterizedSize)
+1119            if isinstance(size, SizeReference):
+1120                warnings.warn(
+1121                    "Conversion of channel size from an implicit output shape may by"
+1122                    + " wrong"
+1123                )
+1124                ret.append(
+1125                    ChannelAxis(
+1126                        channel_names=[
+1127                            Identifier(f"channel{i}") for i in range(size.offset)
+1128                        ]
+1129                    )
+1130                )
+1131            else:
+1132                ret.append(
+1133                    ChannelAxis(
+1134                        channel_names=[Identifier(f"channel{i}") for i in range(size)]
+1135                    )
+1136                )
+1137        elif axis_type == "space":
+1138            if tensor_type == "input":
+1139                ret.append(SpaceInputAxis(id=AxisId(a), size=size, scale=scale))
+1140            else:
+1141                ret.append(SpaceOutputAxis(id=AxisId(a), size=size, scale=scale))
+1142
+1143    return ret
 
    
 
 
@@ -9632,28 +9757,28 @@ 
    Inherited Members
    
 
     
    
     
-            
    1279class OutputTensorDescr(TensorDescrBase[OutputAxis]):
-1280    id: TensorId = TensorId("output")
-1281    """Output tensor id.
-1282    No duplicates are allowed across all inputs and outputs."""
-1283
-1284    postprocessing: List[PostprocessingDescr] = Field(default_factory=list)
-1285    """Description of how this output should be postprocessed."""
-1286
-1287    @model_validator(mode="after")
-1288    def _validate_postprocessing_kwargs(self) -> Self:
-1289        axes_ids = [a.id for a in self.axes]
-1290        for p in self.postprocessing:
-1291            kwargs_axes: Union[Any, Sequence[Any]] = p.kwargs.get("axes", ())
-1292            if not isinstance(kwargs_axes, collections.abc.Sequence):
-1293                raise ValueError(
-1294                    f"expected `axes` sequence, but got {type(kwargs_axes)}"
-1295                )
-1296
-1297            if any(a not in axes_ids for a in kwargs_axes):
-1298                raise ValueError("`kwargs.axes` needs to be subset of axes ids")
-1299
-1300        return self
+            
    1303class OutputTensorDescr(TensorDescrBase[OutputAxis]):
+1304    id: TensorId = TensorId("output")
+1305    """Output tensor id.
+1306    No duplicates are allowed across all inputs and outputs."""
+1307
+1308    postprocessing: List[PostprocessingDescr] = Field(default_factory=list)
+1309    """Description of how this output should be postprocessed."""
+1310
+1311    @model_validator(mode="after")
+1312    def _validate_postprocessing_kwargs(self) -> Self:
+1313        axes_ids = [a.id for a in self.axes]
+1314        for p in self.postprocessing:
+1315            kwargs_axes: Union[Any, Sequence[Any]] = p.kwargs.get("axes", ())
+1316            if not isinstance(kwargs_axes, collections.abc.Sequence):
+1317                raise ValueError(
+1318                    f"expected `axes` sequence, but got {type(kwargs_axes)}"
+1319                )
+1320
+1321            if any(a not in axes_ids for a in kwargs_axes):
+1322                raise ValueError("`kwargs.axes` needs to be subset of axes ids")
+1323
+1324        return self
 
    
 
 
@@ -9764,79 +9889,79 @@ 
    Inherited Members
    
 
     
    
     
-            
    1350def validate_tensors(
-1351    tensors: Mapping[TensorId, Tuple[TensorDescr, NDArray[Any]]],
-1352    tensor_origin: str,  # for more precise error messages, e.g. 'test_tensor'
-1353):
-1354    all_tensor_axes: Dict[TensorId, Dict[AxisId, Tuple[AnyAxis, int]]] = {}
-1355
-1356    def e_msg(d: TensorDescr):
-1357        return f"{'inputs' if isinstance(d, InputTensorDescr) else 'outputs'}[{d.id}]"
-1358
-1359    for descr, array in tensors.values():
-1360        try:
-1361            axis_sizes = descr.get_axis_sizes_for_array(array)
-1362        except ValueError as e:
-1363            raise ValueError(f"{e_msg(descr)} {e}")
-1364        else:
-1365            all_tensor_axes[descr.id] = {
-1366                a.id: (a, axis_sizes[a.id]) for a in descr.axes
-1367            }
-1368
-1369    for descr, array in tensors.values():
-1370        if array.dtype.name != descr.dtype:
-1371            raise ValueError(
-1372                f"{e_msg(descr)}.{tensor_origin}.dtype '{array.dtype.name}' does not"
-1373                + f" match described dtype '{descr.dtype}'"
-1374            )
-1375
-1376        for a in descr.axes:
-1377            actual_size = all_tensor_axes[descr.id][a.id][1]
-1378            if a.size is None:
-1379                continue
-1380
-1381            if isinstance(a.size, int):
-1382                if actual_size != a.size:
-1383                    raise ValueError(
-1384                        f"{e_msg(descr)}.{tensor_origin}: axis '{a.id}' "
-1385                        + f"has incompatible size {actual_size}, expected {a.size}"
-1386                    )
-1387            elif isinstance(a.size, ParameterizedSize):
-1388                _ = a.size.validate_size(actual_size)
-1389            elif isinstance(a.size, SizeReference):
-1390                ref_tensor_axes = all_tensor_axes.get(a.size.tensor_id)
-1391                if ref_tensor_axes is None:
-1392                    raise ValueError(
-1393                        f"{e_msg(descr)}.axes[{a.id}].size.tensor_id: Unknown tensor"
-1394                        + f" reference '{a.size.tensor_id}'"
-1395                    )
-1396
-1397                ref_axis, ref_size = ref_tensor_axes.get(a.size.axis_id, (None, None))
-1398                if ref_axis is None or ref_size is None:
-1399                    raise ValueError(
-1400                        f"{e_msg(descr)}.axes[{a.id}].size.axis_id: Unknown tensor axis"
-1401                        + f" reference '{a.size.tensor_id}.{a.size.axis_id}"
-1402                    )
-1403
-1404                if a.unit != ref_axis.unit:
-1405                    raise ValueError(
-1406                        f"{e_msg(descr)}.axes[{a.id}].size: `SizeReference` requires"
-1407                        + " axis and reference axis to have the same `unit`, but"
-1408                        + f" {a.unit}!={ref_axis.unit}"
-1409                    )
-1410
-1411                if actual_size != (
-1412                    expected_size := (
-1413                        ref_size * ref_axis.scale / a.scale + a.size.offset
-1414                    )
-1415                ):
+            
    1374def validate_tensors(
+1375    tensors: Mapping[TensorId, Tuple[TensorDescr, NDArray[Any]]],
+1376    tensor_origin: str,  # for more precise error messages, e.g. 'test_tensor'
+1377):
+1378    all_tensor_axes: Dict[TensorId, Dict[AxisId, Tuple[AnyAxis, int]]] = {}
+1379
+1380    def e_msg(d: TensorDescr):
+1381        return f"{'inputs' if isinstance(d, InputTensorDescr) else 'outputs'}[{d.id}]"
+1382
+1383    for descr, array in tensors.values():
+1384        try:
+1385            axis_sizes = descr.get_axis_sizes_for_array(array)
+1386        except ValueError as e:
+1387            raise ValueError(f"{e_msg(descr)} {e}")
+1388        else:
+1389            all_tensor_axes[descr.id] = {
+1390                a.id: (a, axis_sizes[a.id]) for a in descr.axes
+1391            }
+1392
+1393    for descr, array in tensors.values():
+1394        if array.dtype.name != descr.dtype:
+1395            raise ValueError(
+1396                f"{e_msg(descr)}.{tensor_origin}.dtype '{array.dtype.name}' does not"
+1397                + f" match described dtype '{descr.dtype}'"
+1398            )
+1399
+1400        for a in descr.axes:
+1401            actual_size = all_tensor_axes[descr.id][a.id][1]
+1402            if a.size is None:
+1403                continue
+1404
+1405            if isinstance(a.size, int):
+1406                if actual_size != a.size:
+1407                    raise ValueError(
+1408                        f"{e_msg(descr)}.{tensor_origin}: axis '{a.id}' "
+1409                        + f"has incompatible size {actual_size}, expected {a.size}"
+1410                    )
+1411            elif isinstance(a.size, ParameterizedSize):
+1412                _ = a.size.validate_size(actual_size)
+1413            elif isinstance(a.size, SizeReference):
+1414                ref_tensor_axes = all_tensor_axes.get(a.size.tensor_id)
+1415                if ref_tensor_axes is None:
 1416                    raise ValueError(
-1417                        f"{e_msg(descr)}.{tensor_origin}: axis '{a.id}' of size"
-1418                        + f" {actual_size} invalid for referenced size {ref_size};"
-1419                        + f" expected {expected_size}"
-1420                    )
-1421            else:
-1422                assert_never(a.size)
+1417                        f"{e_msg(descr)}.axes[{a.id}].size.tensor_id: Unknown tensor"
+1418                        + f" reference '{a.size.tensor_id}'"
+1419                    )
+1420
+1421                ref_axis, ref_size = ref_tensor_axes.get(a.size.axis_id, (None, None))
+1422                if ref_axis is None or ref_size is None:
+1423                    raise ValueError(
+1424                        f"{e_msg(descr)}.axes[{a.id}].size.axis_id: Unknown tensor axis"
+1425                        + f" reference '{a.size.tensor_id}.{a.size.axis_id}"
+1426                    )
+1427
+1428                if a.unit != ref_axis.unit:
+1429                    raise ValueError(
+1430                        f"{e_msg(descr)}.axes[{a.id}].size: `SizeReference` requires"
+1431                        + " axis and reference axis to have the same `unit`, but"
+1432                        + f" {a.unit}!={ref_axis.unit}"
+1433                    )
+1434
+1435                if actual_size != (
+1436                    expected_size := (
+1437                        ref_size * ref_axis.scale / a.scale + a.size.offset
+1438                    )
+1439                ):
+1440                    raise ValueError(
+1441                        f"{e_msg(descr)}.{tensor_origin}: axis '{a.id}' of size"
+1442                        + f" {actual_size} invalid for referenced size {ref_size};"
+1443                        + f" expected {expected_size}"
+1444                    )
+1445            else:
+1446                assert_never(a.size)
 
    
 
 
@@ -9854,19 +9979,19 @@ 
    Inherited Members
    
 
     
    
     
-            
    1425class EnvironmentFileDescr(FileDescr):
-1426    source: Annotated[
-1427        ImportantFileSource,
-1428        WithSuffix((".yaml", ".yml"), case_sensitive=True),
-1429        Field(
-1430            examples=["environment.yaml"],
-1431        ),
-1432    ]
-1433    """∈📦 Conda environment file.
-1434    Allows to specify custom dependencies, see conda docs:
-1435    - [Exporting an environment file across platforms](https://conda.io/projects/conda/en/latest/user-guide/tasks/manage-environments.html#exporting-an-environment-file-across-platforms)
-1436    - [Creating an environment file manually](https://conda.io/projects/conda/en/latest/user-guide/tasks/manage-environments.html#creating-an-environment-file-manually)
-1437    """
+            
    1449class EnvironmentFileDescr(FileDescr):
+1450    source: Annotated[
+1451        ImportantFileSource,
+1452        WithSuffix((".yaml", ".yml"), case_sensitive=True),
+1453        Field(
+1454            examples=["environment.yaml"],
+1455        ),
+1456    ]
+1457    """∈📦 Conda environment file.
+1458    Allows to specify custom dependencies, see conda docs:
+1459    - [Exporting an environment file across platforms](https://conda.io/projects/conda/en/latest/user-guide/tasks/manage-environments.html#exporting-an-environment-file-across-platforms)
+1460    - [Creating an environment file manually](https://conda.io/projects/conda/en/latest/user-guide/tasks/manage-environments.html#creating-an-environment-file-manually)
+1461    """
 
    
 
 
@@ -9876,7 +10001,7 @@ 
    Inherited Members
    
 
                             
    
                                 
    
-            source: Annotated[Union[Annotated[pathlib.Path, PathType(path_type='file')], bioimageio.spec._internal.io.RelativeFilePath, bioimageio.spec._internal.url.HttpUrl, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator(func=<function wo_special_file_name at 0x7f1c21c3ef20>), PlainSerializer(func=<function _package at 0x7f1c21c782c0>, return_type=PydanticUndefined, when_used='unless-none'), WithSuffix(suffix=('.yaml', '.yml'), case_sensitive=True), FieldInfo(annotation=NoneType, required=True, examples=['environment.yaml'])]
+            source: Annotated[Union[Annotated[pathlib.Path, PathType(path_type='file')], bioimageio.spec._internal.io.RelativeFilePath, bioimageio.spec._internal.url.HttpUrl, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator(func=<function wo_special_file_name at 0x7afca0d90540>), PlainSerializer(func=<function _package at 0x7afca0d91760>, return_type=PydanticUndefined, when_used='unless-none'), WithSuffix(suffix=('.yaml', '.yml'), case_sensitive=True), FieldInfo(annotation=NoneType, required=True, examples=['environment.yaml'])]
 
         
     
    
@@ -9986,8 +10111,8 @@ 
    Inherited Members
    
 
     
    
     
-            
    1448class ArchitectureFromFileDescr(_ArchitectureCallableDescr, FileDescr):
-1449    pass
+            
    1472class ArchitectureFromFileDescr(_ArchitectureCallableDescr, FileDescr):
+1473    pass
 
    
 
 
@@ -10094,9 +10219,9 @@ 
    Inherited Members
    
 
     
    
     
-            
    1452class ArchitectureFromLibraryDescr(_ArchitectureCallableDescr):
-1453    import_from: str
-1454    """Where to import the callable from, i.e. `from <import_from> import <callable>`"""
+            
    1476class ArchitectureFromLibraryDescr(_ArchitectureCallableDescr):
+1477    import_from: str
+1478    """Where to import the callable from, i.e. `from <import_from> import <callable>`"""
 
    
 
 
@@ -10222,36 +10347,36 @@ 
    Inherited Members
    
 
     
    
     
-            
    1517class WeightsEntryDescrBase(FileDescr):
-1518    type: ClassVar[WeightsFormat]
-1519    weights_format_name: ClassVar[str]  # human readable
-1520
-1521    source: ImportantFileSource
-1522    """∈📦 The weights file."""
-1523
-1524    authors: Optional[List[Author]] = None
-1525    """Authors
-1526    Either the person(s) that have trained this model resulting in the original weights file.
-1527        (If this is the initial weights entry, i.e. it does not have a `parent`)
-1528    Or the person(s) who have converted the weights to this weights format.
-1529        (If this is a child weight, i.e. it has a `parent` field)
-1530    """
-1531
-1532    parent: Annotated[
-1533        Optional[WeightsFormat], Field(examples=["pytorch_state_dict"])
-1534    ] = None
-1535    """The source weights these weights were converted from.
-1536    For example, if a model's weights were converted from the `pytorch_state_dict` format to `torchscript`,
-1537    The `pytorch_state_dict` weights entry has no `parent` and is the parent of the `torchscript` weights.
-1538    All weight entries except one (the initial set of weights resulting from training the model),
-1539    need to have this field."""
-1540
-1541    @model_validator(mode="after")
-1542    def check_parent_is_not_self(self) -> Self:
-1543        if self.type == self.parent:
-1544            raise ValueError("Weights entry can't be it's own parent.")
-1545
-1546        return self
+            
    1541class WeightsEntryDescrBase(FileDescr):
+1542    type: ClassVar[WeightsFormat]
+1543    weights_format_name: ClassVar[str]  # human readable
+1544
+1545    source: ImportantFileSource
+1546    """∈📦 The weights file."""
+1547
+1548    authors: Optional[List[Author]] = None
+1549    """Authors
+1550    Either the person(s) that have trained this model resulting in the original weights file.
+1551        (If this is the initial weights entry, i.e. it does not have a `parent`)
+1552    Or the person(s) who have converted the weights to this weights format.
+1553        (If this is a child weight, i.e. it has a `parent` field)
+1554    """
+1555
+1556    parent: Annotated[
+1557        Optional[WeightsFormat], Field(examples=["pytorch_state_dict"])
+1558    ] = None
+1559    """The source weights these weights were converted from.
+1560    For example, if a model's weights were converted from the `pytorch_state_dict` format to `torchscript`,
+1561    The `pytorch_state_dict` weights entry has no `parent` and is the parent of the `torchscript` weights.
+1562    All weight entries except one (the initial set of weights resulting from training the model),
+1563    need to have this field."""
+1564
+1565    @model_validator(mode="after")
+1566    def check_parent_is_not_self(self) -> Self:
+1567        if self.type == self.parent:
+1568            raise ValueError("Weights entry can't be it's own parent.")
+1569
+1570        return self
 
    
 
 
@@ -10283,7 +10408,7 @@ 
    Inherited Members
    
                             
    
                             
    
                                 
    
-            source: Annotated[Union[Annotated[pathlib.Path, PathType(path_type='file')], bioimageio.spec._internal.io.RelativeFilePath, bioimageio.spec._internal.url.HttpUrl, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator(func=<function wo_special_file_name at 0x7f1c21c3ef20>), PlainSerializer(func=<function _package at 0x7f1c21c782c0>, return_type=PydanticUndefined, when_used='unless-none')]
+            source: Annotated[Union[Annotated[pathlib.Path, PathType(path_type='file')], bioimageio.spec._internal.io.RelativeFilePath, bioimageio.spec._internal.url.HttpUrl, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator(func=<function wo_special_file_name at 0x7afca0d90540>), PlainSerializer(func=<function _package at 0x7afca0d91760>, return_type=PydanticUndefined, when_used='unless-none')]
 
         
     
    
@@ -10340,12 +10465,12 @@ 
    Inherited Members
    
 
     
    
     
-            
    1541    @model_validator(mode="after")
-1542    def check_parent_is_not_self(self) -> Self:
-1543        if self.type == self.parent:
-1544            raise ValueError("Weights entry can't be it's own parent.")
-1545
-1546        return self
+            
    1565    @model_validator(mode="after")
+1566    def check_parent_is_not_self(self) -> Self:
+1567        if self.type == self.parent:
+1568            raise ValueError("Weights entry can't be it's own parent.")
+1569
+1570        return self
 
    
 
 
@@ -10445,11 +10570,11 @@ 
    Inherited Members
    
 
     
    
     
-            
    1549class KerasHdf5WeightsDescr(WeightsEntryDescrBase):
-1550    type = "keras_hdf5"
-1551    weights_format_name: ClassVar[str] = "Keras HDF5"
-1552    tensorflow_version: Version
-1553    """TensorFlow version used to create these weights."""
+            
    1573class KerasHdf5WeightsDescr(WeightsEntryDescrBase):
+1574    type = "keras_hdf5"
+1575    weights_format_name: ClassVar[str] = "Keras HDF5"
+1576    tensorflow_version: Version
+1577    """TensorFlow version used to create these weights."""
 
    
 
 
@@ -10594,11 +10719,11 @@ 
    Inherited Members
    
 
     
    
     
-            
    1556class OnnxWeightsDescr(WeightsEntryDescrBase):
-1557    type = "onnx"
-1558    weights_format_name: ClassVar[str] = "ONNX"
-1559    opset_version: Annotated[int, Ge(7)]
-1560    """ONNX opset version"""
+            
    1580class OnnxWeightsDescr(WeightsEntryDescrBase):
+1581    type = "onnx"
+1582    weights_format_name: ClassVar[str] = "ONNX"
+1583    opset_version: Annotated[int, Ge(7)]
+1584    """ONNX opset version"""
 
    
 
 
@@ -10743,19 +10868,19 @@ 
    Inherited Members
    
 
     
    
     
-            
    1563class PytorchStateDictWeightsDescr(WeightsEntryDescrBase):
-1564    type = "pytorch_state_dict"
-1565    weights_format_name: ClassVar[str] = "Pytorch State Dict"
-1566    architecture: ArchitectureDescr
-1567    pytorch_version: Version
-1568    """Version of the PyTorch library used.
-1569    If `architecture.depencencies` is specified it has to include pytorch and any version pinning has to be compatible.
-1570    """
-1571    dependencies: Optional[EnvironmentFileDescr] = None
-1572    """Custom depencies beyond pytorch.
-1573    The conda environment file should include pytorch and any version pinning has to be compatible with
-1574    `pytorch_version`.
-1575    """
+            
    1587class PytorchStateDictWeightsDescr(WeightsEntryDescrBase):
+1588    type = "pytorch_state_dict"
+1589    weights_format_name: ClassVar[str] = "Pytorch State Dict"
+1590    architecture: ArchitectureDescr
+1591    pytorch_version: Version
+1592    """Version of the PyTorch library used.
+1593    If `architecture.depencencies` is specified it has to include pytorch and any version pinning has to be compatible.
+1594    """
+1595    dependencies: Optional[EnvironmentFileDescr] = None
+1596    """Custom depencies beyond pytorch.
+1597    The conda environment file should include pytorch and any version pinning has to be compatible with
+1598    `pytorch_version`.
+1599    """
 
    
 
 
@@ -10927,15 +11052,15 @@ 
    Inherited Members
    
 
     
    
     
-            
    1578class TensorflowJsWeightsDescr(WeightsEntryDescrBase):
-1579    type = "tensorflow_js"
-1580    weights_format_name: ClassVar[str] = "Tensorflow.js"
-1581    tensorflow_version: Version
-1582    """Version of the TensorFlow library used."""
-1583
-1584    source: ImportantFileSource
-1585    """∈📦 The multi-file weights.
-1586    All required files/folders should be a zip archive."""
+            
    1602class TensorflowJsWeightsDescr(WeightsEntryDescrBase):
+1603    type = "tensorflow_js"
+1604    weights_format_name: ClassVar[str] = "Tensorflow.js"
+1605    tensorflow_version: Version
+1606    """Version of the TensorFlow library used."""
+1607
+1608    source: ImportantFileSource
+1609    """∈📦 The multi-file weights.
+1610    All required files/folders should be a zip archive."""
 
    
 
 
@@ -10982,7 +11107,7 @@ 
    Inherited Members
    
                             
    
                             
    
                                 
    
-            source: Annotated[Union[Annotated[pathlib.Path, PathType(path_type='file')], bioimageio.spec._internal.io.RelativeFilePath, bioimageio.spec._internal.url.HttpUrl, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator(func=<function wo_special_file_name at 0x7f1c21c3ef20>), PlainSerializer(func=<function _package at 0x7f1c21c782c0>, return_type=PydanticUndefined, when_used='unless-none')]
+            source: Annotated[Union[Annotated[pathlib.Path, PathType(path_type='file')], bioimageio.spec._internal.io.RelativeFilePath, bioimageio.spec._internal.url.HttpUrl, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator(func=<function wo_special_file_name at 0x7afca0d90540>), PlainSerializer(func=<function _package at 0x7afca0d91760>, return_type=PydanticUndefined, when_used='unless-none')]
 
         
     
    
@@ -11093,19 +11218,19 @@ 
    Inherited Members
    
 
     
    
     
-            
    1589class TensorflowSavedModelBundleWeightsDescr(WeightsEntryDescrBase):
-1590    type = "tensorflow_saved_model_bundle"
-1591    weights_format_name: ClassVar[str] = "Tensorflow Saved Model"
-1592    tensorflow_version: Version
-1593    """Version of the TensorFlow library used."""
-1594
-1595    dependencies: Optional[EnvironmentFileDescr] = None
-1596    """Custom dependencies beyond tensorflow.
-1597    Should include tensorflow and any version pinning has to be compatible with `tensorflow_version`."""
-1598
-1599    source: ImportantFileSource
-1600    """∈📦 The multi-file weights.
-1601    All required files/folders should be a zip archive."""
+            
    1613class TensorflowSavedModelBundleWeightsDescr(WeightsEntryDescrBase):
+1614    type = "tensorflow_saved_model_bundle"
+1615    weights_format_name: ClassVar[str] = "Tensorflow Saved Model"
+1616    tensorflow_version: Version
+1617    """Version of the TensorFlow library used."""
+1618
+1619    dependencies: Optional[EnvironmentFileDescr] = None
+1620    """Custom dependencies beyond tensorflow.
+1621    Should include tensorflow and any version pinning has to be compatible with `tensorflow_version`."""
+1622
+1623    source: ImportantFileSource
+1624    """∈📦 The multi-file weights.
+1625    All required files/folders should be a zip archive."""
 
    
 
 
@@ -11166,7 +11291,7 @@ 
    Inherited Members
    
                             
    
                             
    
                                 
    
-            source: Annotated[Union[Annotated[pathlib.Path, PathType(path_type='file')], bioimageio.spec._internal.io.RelativeFilePath, bioimageio.spec._internal.url.HttpUrl, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator(func=<function wo_special_file_name at 0x7f1c21c3ef20>), PlainSerializer(func=<function _package at 0x7f1c21c782c0>, return_type=PydanticUndefined, when_used='unless-none')]
+            source: Annotated[Union[Annotated[pathlib.Path, PathType(path_type='file')], bioimageio.spec._internal.io.RelativeFilePath, bioimageio.spec._internal.url.HttpUrl, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator(func=<function wo_special_file_name at 0x7afca0d90540>), PlainSerializer(func=<function _package at 0x7afca0d91760>, return_type=PydanticUndefined, when_used='unless-none')]
 
         
     
    
@@ -11277,11 +11402,11 @@ 
    Inherited Members
    
 
     
    
     
-            
    1604class TorchscriptWeightsDescr(WeightsEntryDescrBase):
-1605    type = "torchscript"
-1606    weights_format_name: ClassVar[str] = "TorchScript"
-1607    pytorch_version: Version
-1608    """Version of the PyTorch library used."""
+            
    1628class TorchscriptWeightsDescr(WeightsEntryDescrBase):
+1629    type = "torchscript"
+1630    weights_format_name: ClassVar[str] = "TorchScript"
+1631    pytorch_version: Version
+1632    """Version of the PyTorch library used."""
 
    
 
 
@@ -11426,54 +11551,54 @@ 
    Inherited Members
    
 
     
    
     
-            
    1611class WeightsDescr(Node):
-1612    keras_hdf5: Optional[KerasHdf5WeightsDescr] = None
-1613    onnx: Optional[OnnxWeightsDescr] = None
-1614    pytorch_state_dict: Optional[PytorchStateDictWeightsDescr] = None
-1615    tensorflow_js: Optional[TensorflowJsWeightsDescr] = None
-1616    tensorflow_saved_model_bundle: Optional[TensorflowSavedModelBundleWeightsDescr] = (
-1617        None
-1618    )
-1619    torchscript: Optional[TorchscriptWeightsDescr] = None
-1620
-1621    @model_validator(mode="after")
-1622    def check_entries(self) -> Self:
-1623        entries = {wtype for wtype, entry in self if entry is not None}
-1624
-1625        if not entries:
-1626            raise ValueError("Missing weights entry")
-1627
-1628        entries_wo_parent = {
-1629            wtype
-1630            for wtype, entry in self
-1631            if entry is not None and hasattr(entry, "parent") and entry.parent is None
-1632        }
-1633        if len(entries_wo_parent) != 1:
-1634            issue_warning(
-1635                "Exactly one weights entry may not specify the `parent` field (got"
-1636                + " {value}).That entry is considered the original set of model weights."
-1637                + " Other weight formats are created through conversion of the orignal or"
-1638                + " already converted weights. They have to reference the weights format"
-1639                + " they were converted from as their `parent`.",
-1640                value=len(entries_wo_parent),
-1641            )
-1642
-1643        for wtype, entry in self:
-1644            if entry is None:
-1645                continue
-1646
-1647            assert hasattr(entry, "type")
-1648            assert hasattr(entry, "parent")
-1649            assert wtype == entry.type
-1650            if (
-1651                entry.parent is not None and entry.parent not in entries
-1652            ):  # self reference checked for `parent` field
-1653                raise ValueError(
-1654                    f"`weights.{wtype}.parent={entry.parent} not in specified weight"
-1655                    + f" formats: {entries}"
-1656                )
-1657
-1658        return self
+            
    1635class WeightsDescr(Node):
+1636    keras_hdf5: Optional[KerasHdf5WeightsDescr] = None
+1637    onnx: Optional[OnnxWeightsDescr] = None
+1638    pytorch_state_dict: Optional[PytorchStateDictWeightsDescr] = None
+1639    tensorflow_js: Optional[TensorflowJsWeightsDescr] = None
+1640    tensorflow_saved_model_bundle: Optional[TensorflowSavedModelBundleWeightsDescr] = (
+1641        None
+1642    )
+1643    torchscript: Optional[TorchscriptWeightsDescr] = None
+1644
+1645    @model_validator(mode="after")
+1646    def check_entries(self) -> Self:
+1647        entries = {wtype for wtype, entry in self if entry is not None}
+1648
+1649        if not entries:
+1650            raise ValueError("Missing weights entry")
+1651
+1652        entries_wo_parent = {
+1653            wtype
+1654            for wtype, entry in self
+1655            if entry is not None and hasattr(entry, "parent") and entry.parent is None
+1656        }
+1657        if len(entries_wo_parent) != 1:
+1658            issue_warning(
+1659                "Exactly one weights entry may not specify the `parent` field (got"
+1660                + " {value}).That entry is considered the original set of model weights."
+1661                + " Other weight formats are created through conversion of the orignal or"
+1662                + " already converted weights. They have to reference the weights format"
+1663                + " they were converted from as their `parent`.",
+1664                value=len(entries_wo_parent),
+1665            )
+1666
+1667        for wtype, entry in self:
+1668            if entry is None:
+1669                continue
+1670
+1671            assert hasattr(entry, "type")
+1672            assert hasattr(entry, "parent")
+1673            assert wtype == entry.type
+1674            if (
+1675                entry.parent is not None and entry.parent not in entries
+1676            ):  # self reference checked for `parent` field
+1677                raise ValueError(
+1678                    f"`weights.{wtype}.parent={entry.parent} not in specified weight"
+1679                    + f" formats: {entries}"
+1680                )
+1681
+1682        return self
 
    
 
 
@@ -11559,44 +11684,44 @@ 
    Inherited Members
    
 
     
    
     
-            
    1621    @model_validator(mode="after")
-1622    def check_entries(self) -> Self:
-1623        entries = {wtype for wtype, entry in self if entry is not None}
-1624
-1625        if not entries:
-1626            raise ValueError("Missing weights entry")
-1627
-1628        entries_wo_parent = {
-1629            wtype
-1630            for wtype, entry in self
-1631            if entry is not None and hasattr(entry, "parent") and entry.parent is None
-1632        }
-1633        if len(entries_wo_parent) != 1:
-1634            issue_warning(
-1635                "Exactly one weights entry may not specify the `parent` field (got"
-1636                + " {value}).That entry is considered the original set of model weights."
-1637                + " Other weight formats are created through conversion of the orignal or"
-1638                + " already converted weights. They have to reference the weights format"
-1639                + " they were converted from as their `parent`.",
-1640                value=len(entries_wo_parent),
-1641            )
-1642
-1643        for wtype, entry in self:
-1644            if entry is None:
-1645                continue
-1646
-1647            assert hasattr(entry, "type")
-1648            assert hasattr(entry, "parent")
-1649            assert wtype == entry.type
-1650            if (
-1651                entry.parent is not None and entry.parent not in entries
-1652            ):  # self reference checked for `parent` field
-1653                raise ValueError(
-1654                    f"`weights.{wtype}.parent={entry.parent} not in specified weight"
-1655                    + f" formats: {entries}"
-1656                )
-1657
-1658        return self
+            
    1645    @model_validator(mode="after")
+1646    def check_entries(self) -> Self:
+1647        entries = {wtype for wtype, entry in self if entry is not None}
+1648
+1649        if not entries:
+1650            raise ValueError("Missing weights entry")
+1651
+1652        entries_wo_parent = {
+1653            wtype
+1654            for wtype, entry in self
+1655            if entry is not None and hasattr(entry, "parent") and entry.parent is None
+1656        }
+1657        if len(entries_wo_parent) != 1:
+1658            issue_warning(
+1659                "Exactly one weights entry may not specify the `parent` field (got"
+1660                + " {value}).That entry is considered the original set of model weights."
+1661                + " Other weight formats are created through conversion of the orignal or"
+1662                + " already converted weights. They have to reference the weights format"
+1663                + " they were converted from as their `parent`.",
+1664                value=len(entries_wo_parent),
+1665            )
+1666
+1667        for wtype, entry in self:
+1668            if entry is None:
+1669                continue
+1670
+1671            assert hasattr(entry, "type")
+1672            assert hasattr(entry, "parent")
+1673            assert wtype == entry.type
+1674            if (
+1675                entry.parent is not None and entry.parent not in entries
+1676            ):  # self reference checked for `parent` field
+1677                raise ValueError(
+1678                    f"`weights.{wtype}.parent={entry.parent} not in specified weight"
+1679                    + f" formats: {entries}"
+1680                )
+1681
+1682        return self
 
    
 
 
@@ -11690,14 +11815,14 @@ 
    Inherited Members
    
 
     
    
     
-            
    1661class LinkedModel(Node):
-1662    """Reference to a bioimage.io model."""
-1663
-1664    id: ModelId
-1665    """A valid model `id` from the bioimage.io collection."""
-1666
-1667    version_number: int
-1668    """version number (n-th published version, not the semantic version) of linked model"""
+            
    1685class LinkedModel(Node):
+1686    """Reference to a bioimage.io model."""
+1687
+1688    id: ModelId
+1689    """A valid model `id` from the bioimage.io collection."""
+1690
+1691    version_number: int
+1692    """version number (n-th published version, not the semantic version) of linked model"""
 
    
 
 
@@ -11818,413 +11943,413 @@ 
    Inherited Members
    
 
     
    
     
-            
    1671class ModelDescr(GenericModelDescrBase, title="bioimage.io model specification"):
-1672    """Specification of the fields used in a bioimage.io-compliant RDF to describe AI models with pretrained weights.
-1673    These fields are typically stored in a YAML file which we call a model resource description file (model RDF).
-1674    """
-1675
-1676    format_version: Literal["0.5.0"] = "0.5.0"
-1677    """Version of the bioimage.io model description specification used.
-1678    When creating a new model always use the latest micro/patch version described here.
-1679    The `format_version` is important for any consumer software to understand how to parse the fields.
-1680    """
-1681
-1682    type: Literal["model"] = "model"
-1683    """Specialized resource type 'model'"""
-1684
-1685    id: Optional[ModelId] = None
-1686    """Model zoo (bioimage.io) wide, unique identifier (assigned by bioimage.io)"""
-1687
-1688    authors: NotEmpty[List[Author]]
-1689    """The authors are the creators of the model RDF and the primary points of contact."""
-1690
-1691    documentation: Annotated[
-1692        DocumentationSource,
-1693        Field(
-1694            examples=[
-1695                "https://raw.githubusercontent.com/bioimage-io/spec-bioimage-io/main/example_descriptions/models/unet2d_nuclei_broad/README.md",
-1696                "README.md",
-1697            ],
-1698        ),
-1699    ]
-1700    """∈📦 URL or relative path to a markdown file with additional documentation.
-1701    The recommended documentation file name is `README.md`. An `.md` suffix is mandatory.
-1702    The documentation should include a '#[#] Validation' (sub)section
-1703    with details on how to quantitatively validate the model on unseen data."""
-1704
-1705    @field_validator("documentation", mode="after")
-1706    @classmethod
-1707    def _validate_documentation(cls, value: DocumentationSource) -> DocumentationSource:
-1708        if not validation_context_var.get().perform_io_checks:
-1709            return value
-1710
-1711        doc_path = download(value).path
-1712        doc_content = doc_path.read_text()
-1713        if not re.match("#.*[vV]alidation", doc_content):
-1714            issue_warning(
-1715                "No '# Validation' (sub)section found in {value}.", value=value
-1716            )
-1717
-1718        return value
-1719
-1720    inputs: NotEmpty[Sequence[InputTensorDescr]]
-1721    """Describes the input tensors expected by this model."""
-1722
-1723    @field_validator("inputs", mode="after")
-1724    @classmethod
-1725    def _validate_input_axes(
-1726        cls, inputs: Sequence[InputTensorDescr]
-1727    ) -> Sequence[InputTensorDescr]:
-1728        input_size_refs = cls._get_axes_with_independent_size(inputs)
-1729
-1730        for i, ipt in enumerate(inputs):
-1731            valid_independent_refs: Dict[
-1732                Tuple[TensorId, AxisId],
-1733                Tuple[TensorDescr, AnyAxis, Union[int, ParameterizedSize]],
-1734            ] = {
-1735                **{
-1736                    (ipt.id, a.id): (ipt, a, a.size)
-1737                    for a in ipt.axes
-1738                    if not isinstance(a, BatchAxis)
-1739                    and isinstance(a.size, (int, ParameterizedSize))
-1740                },
-1741                **input_size_refs,
-1742            }
-1743            for a, ax in enumerate(ipt.axes):
-1744                cls._validate_axis(
-1745                    "inputs",
-1746                    i=i,
-1747                    tensor_id=ipt.id,
-1748                    a=a,
-1749                    axis=ax,
-1750                    valid_independent_refs=valid_independent_refs,
-1751                )
-1752        return inputs
+            
    1695class ModelDescr(GenericModelDescrBase, title="bioimage.io model specification"):
+1696    """Specification of the fields used in a bioimage.io-compliant RDF to describe AI models with pretrained weights.
+1697    These fields are typically stored in a YAML file which we call a model resource description file (model RDF).
+1698    """
+1699
+1700    format_version: Literal["0.5.0"] = "0.5.0"
+1701    """Version of the bioimage.io model description specification used.
+1702    When creating a new model always use the latest micro/patch version described here.
+1703    The `format_version` is important for any consumer software to understand how to parse the fields.
+1704    """
+1705
+1706    type: Literal["model"] = "model"
+1707    """Specialized resource type 'model'"""
+1708
+1709    id: Optional[ModelId] = None
+1710    """Model zoo (bioimage.io) wide, unique identifier (assigned by bioimage.io)"""
+1711
+1712    authors: NotEmpty[List[Author]]
+1713    """The authors are the creators of the model RDF and the primary points of contact."""
+1714
+1715    documentation: Annotated[
+1716        DocumentationSource,
+1717        Field(
+1718            examples=[
+1719                "https://raw.githubusercontent.com/bioimage-io/spec-bioimage-io/main/example_descriptions/models/unet2d_nuclei_broad/README.md",
+1720                "README.md",
+1721            ],
+1722        ),
+1723    ]
+1724    """∈📦 URL or relative path to a markdown file with additional documentation.
+1725    The recommended documentation file name is `README.md`. An `.md` suffix is mandatory.
+1726    The documentation should include a '#[#] Validation' (sub)section
+1727    with details on how to quantitatively validate the model on unseen data."""
+1728
+1729    @field_validator("documentation", mode="after")
+1730    @classmethod
+1731    def _validate_documentation(cls, value: DocumentationSource) -> DocumentationSource:
+1732        if not validation_context_var.get().perform_io_checks:
+1733            return value
+1734
+1735        doc_path = download(value).path
+1736        doc_content = doc_path.read_text()
+1737        if not re.match("#.*[vV]alidation", doc_content):
+1738            issue_warning(
+1739                "No '# Validation' (sub)section found in {value}.", value=value
+1740            )
+1741
+1742        return value
+1743
+1744    inputs: NotEmpty[Sequence[InputTensorDescr]]
+1745    """Describes the input tensors expected by this model."""
+1746
+1747    @field_validator("inputs", mode="after")
+1748    @classmethod
+1749    def _validate_input_axes(
+1750        cls, inputs: Sequence[InputTensorDescr]
+1751    ) -> Sequence[InputTensorDescr]:
+1752        input_size_refs = cls._get_axes_with_independent_size(inputs)
 1753
-1754    @staticmethod
-1755    def _validate_axis(
-1756        field_name: str,
-1757        i: int,
-1758        tensor_id: TensorId,
-1759        a: int,
-1760        axis: AnyAxis,
-1761        valid_independent_refs: Dict[
-1762            Tuple[TensorId, AxisId],
-1763            Tuple[TensorDescr, AnyAxis, Union[int, ParameterizedSize]],
-1764        ],
-1765    ):
-1766        if isinstance(axis, BatchAxis) or isinstance(axis.size, int):
-1767            return
-1768
-1769        if isinstance(axis.size, ParameterizedSize):
-1770            if isinstance(axis, WithHalo) and (axis.size.min - 2 * axis.halo) < 1:
-1771                raise ValueError(
-1772                    f"axis {axis.id} with minimum size {axis.size.min} is too small for"
-1773                    + f" halo {axis.halo}."
-1774                )
-1775
-1776        elif isinstance(axis.size, SizeReference):
-1777            ref = (axis.size.tensor_id, axis.size.axis_id)
-1778            if ref not in valid_independent_refs:
-1779                raise ValueError(
-1780                    "Invalid tensor axis reference at"
-1781                    + f" {field_name}[{i}].axes[{a}].size: {axis.size}."
-1782                )
-1783            if ref == (tensor_id, axis.id):
-1784                raise ValueError(
-1785                    "Self-referencing not allowed for"
-1786                    + f" {field_name}[{i}].axes[{a}].size: {axis.size}"
-1787                )
-1788            if axis.type == "channel":
-1789                if valid_independent_refs[ref][1].type != "channel":
-1790                    raise ValueError(
-1791                        "A channel axis' size may only reference another fixed size"
-1792                        + " channel axis."
-1793                    )
-1794                if isinstance(axis.channel_names, str) and "{i}" in axis.channel_names:
-1795                    ref_size = valid_independent_refs[ref][2]
-1796                    assert isinstance(ref_size, int), (
-1797                        "channel axis ref (another channel axis) has to specify fixed"
-1798                        + " size"
-1799                    )
-1800                    generated_channel_names = [
-1801                        Identifier(axis.channel_names.format(i=i))
-1802                        for i in range(1, ref_size + 1)
-1803                    ]
-1804                    axis.channel_names = generated_channel_names
-1805
-1806            if (ax_unit := getattr(axis, "unit", None)) != (
-1807                ref_unit := getattr(valid_independent_refs[ref][1], "unit", None)
-1808            ):
-1809                raise ValueError(
-1810                    "The units of an axis and its reference axis need to match, but"
-1811                    + f" '{ax_unit}' != '{ref_unit}'."
-1812                )
-1813            min_size = valid_independent_refs[ref][2]
-1814            if isinstance(min_size, ParameterizedSize):
-1815                min_size = min_size.min
-1816
-1817            if isinstance(axis, WithHalo) and (min_size - 2 * axis.halo) < 1:
-1818                raise ValueError(
-1819                    f"axis {axis.id} with minimum size {min_size} is too small for halo"
-1820                    + f" {axis.halo}."
-1821                )
-1822
-1823        else:
-1824            assert_never(axis.size)
-1825
-1826    @model_validator(mode="after")
-1827    def _validate_test_tensors(self) -> Self:
-1828        if not validation_context_var.get().perform_io_checks:
-1829            return self
-1830
-1831        test_arrays = [
-1832            load_array(descr.test_tensor.download().path)
-1833            for descr in chain(self.inputs, self.outputs)
-1834        ]
-1835        tensors = {
-1836            descr.id: (descr, array)
-1837            for descr, array in zip(chain(self.inputs, self.outputs), test_arrays)
-1838        }
-1839        validate_tensors(tensors, tensor_origin="test_tensor")
-1840        return self
-1841
-1842    @model_validator(mode="after")
-1843    def _validate_tensor_references_in_proc_kwargs(self, info: ValidationInfo) -> Self:
-1844        ipt_refs = {t.id for t in self.inputs}
-1845        out_refs = {t.id for t in self.outputs}
-1846        for ipt in self.inputs:
-1847            for p in ipt.preprocessing:
-1848                ref = p.kwargs.get("reference_tensor")
-1849                if ref is None:
-1850                    continue
-1851                if ref not in ipt_refs:
-1852                    raise ValueError(
-1853                        f"`reference_tensor` '{ref}' not found. Valid input tensor"
-1854                        + f" references are: {ipt_refs}."
-1855                    )
-1856
-1857        for out in self.outputs:
-1858            for p in out.postprocessing:
-1859                ref = p.kwargs.get("reference_tensor")
-1860                if ref is None:
-1861                    continue
-1862
-1863                if ref not in ipt_refs and ref not in out_refs:
-1864                    raise ValueError(
-1865                        f"`reference_tensor` '{ref}' not found. Valid tensor references"
-1866                        + f" are: {ipt_refs | out_refs}."
-1867                    )
-1868
-1869        return self
-1870
-1871    # TODO: use validate funcs in validate_test_tensors
-1872    # def validate_inputs(self, input_tensors: Mapping[TensorId, NDArray[Any]]) -> Mapping[TensorId, NDArray[Any]]:
-1873
-1874    name: Annotated[
-1875        str,
-1876        MinLen(5),
-1877        warn(MaxLen(64), "Name longer than 64 characters.", INFO),
-1878    ]
-1879    """A human-readable name of this model.
-1880    It should be no longer than 64 characters
-1881    and may only contain letter, number, underscore, minus or space characters.
-1882    We recommend to chose a name that refers to the model's task and image modality.
-1883    """
-1884
-1885    outputs: NotEmpty[Sequence[OutputTensorDescr]]
-1886    """Describes the output tensors."""
-1887
-1888    @field_validator("outputs", mode="after")
-1889    @classmethod
-1890    def _validate_tensor_ids(
-1891        cls, outputs: Sequence[OutputTensorDescr], info: ValidationInfo
-1892    ) -> Sequence[OutputTensorDescr]:
-1893        tensor_ids = [
-1894            t.id for t in info.data.get("inputs", []) + info.data.get("outputs", [])
-1895        ]
-1896        duplicate_tensor_ids: List[str] = []
-1897        seen: Set[str] = set()
-1898        for t in tensor_ids:
-1899            if t in seen:
-1900                duplicate_tensor_ids.append(t)
-1901
-1902            seen.add(t)
-1903
-1904        if duplicate_tensor_ids:
-1905            raise ValueError(f"Duplicate tensor ids: {duplicate_tensor_ids}")
-1906
-1907        return outputs
+1754        for i, ipt in enumerate(inputs):
+1755            valid_independent_refs: Dict[
+1756                Tuple[TensorId, AxisId],
+1757                Tuple[TensorDescr, AnyAxis, Union[int, ParameterizedSize]],
+1758            ] = {
+1759                **{
+1760                    (ipt.id, a.id): (ipt, a, a.size)
+1761                    for a in ipt.axes
+1762                    if not isinstance(a, BatchAxis)
+1763                    and isinstance(a.size, (int, ParameterizedSize))
+1764                },
+1765                **input_size_refs,
+1766            }
+1767            for a, ax in enumerate(ipt.axes):
+1768                cls._validate_axis(
+1769                    "inputs",
+1770                    i=i,
+1771                    tensor_id=ipt.id,
+1772                    a=a,
+1773                    axis=ax,
+1774                    valid_independent_refs=valid_independent_refs,
+1775                )
+1776        return inputs
+1777
+1778    @staticmethod
+1779    def _validate_axis(
+1780        field_name: str,
+1781        i: int,
+1782        tensor_id: TensorId,
+1783        a: int,
+1784        axis: AnyAxis,
+1785        valid_independent_refs: Dict[
+1786            Tuple[TensorId, AxisId],
+1787            Tuple[TensorDescr, AnyAxis, Union[int, ParameterizedSize]],
+1788        ],
+1789    ):
+1790        if isinstance(axis, BatchAxis) or isinstance(axis.size, int):
+1791            return
+1792
+1793        if isinstance(axis.size, ParameterizedSize):
+1794            if isinstance(axis, WithHalo) and (axis.size.min - 2 * axis.halo) < 1:
+1795                raise ValueError(
+1796                    f"axis {axis.id} with minimum size {axis.size.min} is too small for"
+1797                    + f" halo {axis.halo}."
+1798                )
+1799
+1800        elif isinstance(axis.size, SizeReference):
+1801            ref = (axis.size.tensor_id, axis.size.axis_id)
+1802            if ref not in valid_independent_refs:
+1803                raise ValueError(
+1804                    "Invalid tensor axis reference at"
+1805                    + f" {field_name}[{i}].axes[{a}].size: {axis.size}."
+1806                )
+1807            if ref == (tensor_id, axis.id):
+1808                raise ValueError(
+1809                    "Self-referencing not allowed for"
+1810                    + f" {field_name}[{i}].axes[{a}].size: {axis.size}"
+1811                )
+1812            if axis.type == "channel":
+1813                if valid_independent_refs[ref][1].type != "channel":
+1814                    raise ValueError(
+1815                        "A channel axis' size may only reference another fixed size"
+1816                        + " channel axis."
+1817                    )
+1818                if isinstance(axis.channel_names, str) and "{i}" in axis.channel_names:
+1819                    ref_size = valid_independent_refs[ref][2]
+1820                    assert isinstance(ref_size, int), (
+1821                        "channel axis ref (another channel axis) has to specify fixed"
+1822                        + " size"
+1823                    )
+1824                    generated_channel_names = [
+1825                        Identifier(axis.channel_names.format(i=i))
+1826                        for i in range(1, ref_size + 1)
+1827                    ]
+1828                    axis.channel_names = generated_channel_names
+1829
+1830            if (ax_unit := getattr(axis, "unit", None)) != (
+1831                ref_unit := getattr(valid_independent_refs[ref][1], "unit", None)
+1832            ):
+1833                raise ValueError(
+1834                    "The units of an axis and its reference axis need to match, but"
+1835                    + f" '{ax_unit}' != '{ref_unit}'."
+1836                )
+1837            min_size = valid_independent_refs[ref][2]
+1838            if isinstance(min_size, ParameterizedSize):
+1839                min_size = min_size.min
+1840
+1841            if isinstance(axis, WithHalo) and (min_size - 2 * axis.halo) < 1:
+1842                raise ValueError(
+1843                    f"axis {axis.id} with minimum size {min_size} is too small for halo"
+1844                    + f" {axis.halo}."
+1845                )
+1846
+1847        else:
+1848            assert_never(axis.size)
+1849
+1850    @model_validator(mode="after")
+1851    def _validate_test_tensors(self) -> Self:
+1852        if not validation_context_var.get().perform_io_checks:
+1853            return self
+1854
+1855        test_arrays = [
+1856            load_array(descr.test_tensor.download().path)
+1857            for descr in chain(self.inputs, self.outputs)
+1858        ]
+1859        tensors = {
+1860            descr.id: (descr, array)
+1861            for descr, array in zip(chain(self.inputs, self.outputs), test_arrays)
+1862        }
+1863        validate_tensors(tensors, tensor_origin="test_tensor")
+1864        return self
+1865
+1866    @model_validator(mode="after")
+1867    def _validate_tensor_references_in_proc_kwargs(self, info: ValidationInfo) -> Self:
+1868        ipt_refs = {t.id for t in self.inputs}
+1869        out_refs = {t.id for t in self.outputs}
+1870        for ipt in self.inputs:
+1871            for p in ipt.preprocessing:
+1872                ref = p.kwargs.get("reference_tensor")
+1873                if ref is None:
+1874                    continue
+1875                if ref not in ipt_refs:
+1876                    raise ValueError(
+1877                        f"`reference_tensor` '{ref}' not found. Valid input tensor"
+1878                        + f" references are: {ipt_refs}."
+1879                    )
+1880
+1881        for out in self.outputs:
+1882            for p in out.postprocessing:
+1883                ref = p.kwargs.get("reference_tensor")
+1884                if ref is None:
+1885                    continue
+1886
+1887                if ref not in ipt_refs and ref not in out_refs:
+1888                    raise ValueError(
+1889                        f"`reference_tensor` '{ref}' not found. Valid tensor references"
+1890                        + f" are: {ipt_refs | out_refs}."
+1891                    )
+1892
+1893        return self
+1894
+1895    # TODO: use validate funcs in validate_test_tensors
+1896    # def validate_inputs(self, input_tensors: Mapping[TensorId, NDArray[Any]]) -> Mapping[TensorId, NDArray[Any]]:
+1897
+1898    name: Annotated[
+1899        str,
+1900        MinLen(5),
+1901        warn(MaxLen(64), "Name longer than 64 characters.", INFO),
+1902    ]
+1903    """A human-readable name of this model.
+1904    It should be no longer than 64 characters
+1905    and may only contain letter, number, underscore, minus or space characters.
+1906    We recommend to chose a name that refers to the model's task and image modality.
+1907    """
 1908
-1909    @staticmethod
-1910    def _get_axes_with_parameterized_size(
-1911        io: Union[Sequence[InputTensorDescr], Sequence[OutputTensorDescr]],
-1912    ):
-1913        return {
-1914            f"{t.id}.{a.id}": (t, a, a.size)
-1915            for t in io
-1916            for a in t.axes
-1917            if not isinstance(a, BatchAxis) and isinstance(a.size, ParameterizedSize)
-1918        }
-1919
-1920    @staticmethod
-1921    def _get_axes_with_independent_size(
-1922        io: Union[Sequence[InputTensorDescr], Sequence[OutputTensorDescr]],
-1923    ):
-1924        return {
-1925            (t.id, a.id): (t, a, a.size)
-1926            for t in io
-1927            for a in t.axes
-1928            if not isinstance(a, BatchAxis)
-1929            and isinstance(a.size, (int, ParameterizedSize))
-1930        }
-1931
-1932    @field_validator("outputs", mode="after")
-1933    @classmethod
-1934    def _validate_output_axes(
-1935        cls, outputs: List[OutputTensorDescr], info: ValidationInfo
-1936    ) -> List[OutputTensorDescr]:
-1937        input_size_refs = cls._get_axes_with_independent_size(
-1938            info.data.get("inputs", [])
-1939        )
-1940        output_size_refs = cls._get_axes_with_independent_size(outputs)
-1941
-1942        for i, out in enumerate(outputs):
-1943            valid_independent_refs: Dict[
-1944                Tuple[TensorId, AxisId],
-1945                Tuple[TensorDescr, AnyAxis, Union[int, ParameterizedSize]],
-1946            ] = {
-1947                **{
-1948                    (out.id, a.id): (out, a, a.size)
-1949                    for a in out.axes
-1950                    if not isinstance(a, BatchAxis)
-1951                    and isinstance(a.size, (int, ParameterizedSize))
-1952                },
-1953                **input_size_refs,
-1954                **output_size_refs,
-1955            }
-1956            for a, ax in enumerate(out.axes):
-1957                cls._validate_axis(
-1958                    "outputs",
-1959                    i,
-1960                    out.id,
-1961                    a,
-1962                    ax,
-1963                    valid_independent_refs=valid_independent_refs,
-1964                )
+1909    outputs: NotEmpty[Sequence[OutputTensorDescr]]
+1910    """Describes the output tensors."""
+1911
+1912    @field_validator("outputs", mode="after")
+1913    @classmethod
+1914    def _validate_tensor_ids(
+1915        cls, outputs: Sequence[OutputTensorDescr], info: ValidationInfo
+1916    ) -> Sequence[OutputTensorDescr]:
+1917        tensor_ids = [
+1918            t.id for t in info.data.get("inputs", []) + info.data.get("outputs", [])
+1919        ]
+1920        duplicate_tensor_ids: List[str] = []
+1921        seen: Set[str] = set()
+1922        for t in tensor_ids:
+1923            if t in seen:
+1924                duplicate_tensor_ids.append(t)
+1925
+1926            seen.add(t)
+1927
+1928        if duplicate_tensor_ids:
+1929            raise ValueError(f"Duplicate tensor ids: {duplicate_tensor_ids}")
+1930
+1931        return outputs
+1932
+1933    @staticmethod
+1934    def _get_axes_with_parameterized_size(
+1935        io: Union[Sequence[InputTensorDescr], Sequence[OutputTensorDescr]],
+1936    ):
+1937        return {
+1938            f"{t.id}.{a.id}": (t, a, a.size)
+1939            for t in io
+1940            for a in t.axes
+1941            if not isinstance(a, BatchAxis) and isinstance(a.size, ParameterizedSize)
+1942        }
+1943
+1944    @staticmethod
+1945    def _get_axes_with_independent_size(
+1946        io: Union[Sequence[InputTensorDescr], Sequence[OutputTensorDescr]],
+1947    ):
+1948        return {
+1949            (t.id, a.id): (t, a, a.size)
+1950            for t in io
+1951            for a in t.axes
+1952            if not isinstance(a, BatchAxis)
+1953            and isinstance(a.size, (int, ParameterizedSize))
+1954        }
+1955
+1956    @field_validator("outputs", mode="after")
+1957    @classmethod
+1958    def _validate_output_axes(
+1959        cls, outputs: List[OutputTensorDescr], info: ValidationInfo
+1960    ) -> List[OutputTensorDescr]:
+1961        input_size_refs = cls._get_axes_with_independent_size(
+1962            info.data.get("inputs", [])
+1963        )
+1964        output_size_refs = cls._get_axes_with_independent_size(outputs)
 1965
-1966        return outputs
-1967
-1968    packaged_by: List[Author] = Field(default_factory=list)
-1969    """The persons that have packaged and uploaded this model.
-1970    Only required if those persons differ from the `authors`."""
-1971
-1972    parent: Optional[LinkedModel] = None
-1973    """The model from which this model is derived, e.g. by fine-tuning the weights."""
-1974
-1975    # todo: add parent self check once we have `id`
-1976    # @model_validator(mode="after")
-1977    # def validate_parent_is_not_self(self) -> Self:
-1978    #     if self.parent is not None and self.parent == self.id:
-1979    #         raise ValueError("The model may not reference itself as parent model")
-1980
-1981    #     return self
-1982
-1983    run_mode: Annotated[
-1984        Optional[RunMode],
-1985        warn(None, "Run mode '{value}' has limited support across consumer softwares."),
-1986    ] = None
-1987    """Custom run mode for this model: for more complex prediction procedures like test time
-1988    data augmentation that currently cannot be expressed in the specification.
-1989    No standard run modes are defined yet."""
-1990
-1991    timestamp: Datetime = Datetime(datetime.now())
-1992    """Timestamp in [ISO 8601](#https://en.wikipedia.org/wiki/ISO_8601) format
-1993    with a few restrictions listed [here](https://docs.python.org/3/library/datetime.html#datetime.datetime.fromisoformat).
-1994    (In Python a datetime object is valid, too)."""
+1966        for i, out in enumerate(outputs):
+1967            valid_independent_refs: Dict[
+1968                Tuple[TensorId, AxisId],
+1969                Tuple[TensorDescr, AnyAxis, Union[int, ParameterizedSize]],
+1970            ] = {
+1971                **{
+1972                    (out.id, a.id): (out, a, a.size)
+1973                    for a in out.axes
+1974                    if not isinstance(a, BatchAxis)
+1975                    and isinstance(a.size, (int, ParameterizedSize))
+1976                },
+1977                **input_size_refs,
+1978                **output_size_refs,
+1979            }
+1980            for a, ax in enumerate(out.axes):
+1981                cls._validate_axis(
+1982                    "outputs",
+1983                    i,
+1984                    out.id,
+1985                    a,
+1986                    ax,
+1987                    valid_independent_refs=valid_independent_refs,
+1988                )
+1989
+1990        return outputs
+1991
+1992    packaged_by: List[Author] = Field(default_factory=list)
+1993    """The persons that have packaged and uploaded this model.
+1994    Only required if those persons differ from the `authors`."""
 1995
-1996    training_data: Union[LinkedDataset, DatasetDescr, None] = None
-1997    """The dataset used to train this model"""
+1996    parent: Optional[LinkedModel] = None
+1997    """The model from which this model is derived, e.g. by fine-tuning the weights."""
 1998
-1999    weights: WeightsDescr
-2000    """The weights for this model.
-2001    Weights can be given for different formats, but should otherwise be equivalent.
-2002    The available weight formats determine which consumers can use this model."""
-2003
-2004    @model_validator(mode="after")
-2005    def _add_default_cover(self) -> Self:
-2006        if not validation_context_var.get().perform_io_checks or self.covers:
-2007            return self
-2008
-2009        try:
-2010            generated_covers = generate_covers(
-2011                [(t, load_array(t.test_tensor.download().path)) for t in self.inputs],
-2012                [(t, load_array(t.test_tensor.download().path)) for t in self.outputs],
-2013            )
-2014        except Exception as e:
-2015            issue_warning(
-2016                "Failed to generate cover image(s): {e}",
-2017                value=self.covers,
-2018                msg_context=dict(e=e),
-2019            )
-2020        else:
-2021            self.covers.extend(generated_covers)
+1999    # todo: add parent self check once we have `id`
+2000    # @model_validator(mode="after")
+2001    # def validate_parent_is_not_self(self) -> Self:
+2002    #     if self.parent is not None and self.parent == self.id:
+2003    #         raise ValueError("The model may not reference itself as parent model")
+2004
+2005    #     return self
+2006
+2007    run_mode: Annotated[
+2008        Optional[RunMode],
+2009        warn(None, "Run mode '{value}' has limited support across consumer softwares."),
+2010    ] = None
+2011    """Custom run mode for this model: for more complex prediction procedures like test time
+2012    data augmentation that currently cannot be expressed in the specification.
+2013    No standard run modes are defined yet."""
+2014
+2015    timestamp: Datetime = Datetime(datetime.now())
+2016    """Timestamp in [ISO 8601](#https://en.wikipedia.org/wiki/ISO_8601) format
+2017    with a few restrictions listed [here](https://docs.python.org/3/library/datetime.html#datetime.datetime.fromisoformat).
+2018    (In Python a datetime object is valid, too)."""
+2019
+2020    training_data: Union[LinkedDataset, DatasetDescr, None] = None
+2021    """The dataset used to train this model"""
 2022
-2023        return self
-2024
-2025    def get_input_test_arrays(self) -> List[NDArray[Any]]:
-2026        data = [load_array(ipt.test_tensor.download().path) for ipt in self.inputs]
-2027        assert all(isinstance(d, np.ndarray) for d in data)
-2028        return data
-2029
-2030    def get_output_test_arrays(self) -> List[NDArray[Any]]:
-2031        data = [load_array(out.test_tensor.download().path) for out in self.outputs]
-2032        assert all(isinstance(d, np.ndarray) for d in data)
-2033        return data
-2034
-2035    def get_tensor_sizes(
-2036        self, n: ParameterizedSize.N, batch_size: int
-2037    ) -> Dict[TensorId, Dict[AxisId, int]]:
-2038        all_axes = {
-2039            t.id: {a.id: a for a in t.axes} for t in chain(self.inputs, self.outputs)
-2040        }
-2041
-2042        ret: Dict[TensorId, Dict[AxisId, int]] = {}
-2043        for t_descr in chain(self.inputs, self.outputs):
-2044            ret[t_descr.id] = {}
-2045            for a in t_descr.axes:
-2046                if a.size is None:
-2047                    assert isinstance(a, BatchAxis)
-2048                    s = batch_size
-2049                elif isinstance(a.size, int):
-2050                    s = a.size
-2051                elif isinstance(a.size, ParameterizedSize):
-2052                    s = a.size.get_size(n)
-2053                elif isinstance(a.size, SizeReference):
-2054                    assert not isinstance(a, BatchAxis)
-2055                    ref_axis = all_axes[a.size.tensor_id][a.size.axis_id]
-2056                    assert not isinstance(ref_axis, BatchAxis)
-2057                    s = a.size.get_size(axis=a, ref_axis=ref_axis, n=n)
-2058                else:
-2059                    assert_never(a.size)
-2060
-2061                ret[t_descr.id][a.id] = s
-2062
-2063        return ret
-2064
-2065    @model_validator(mode="before")
-2066    @classmethod
-2067    def _convert(cls, data: Dict[str, Any]) -> Dict[str, Any]:
-2068        if (
-2069            data.get("type") == "model"
-2070            and isinstance(fv := data.get("format_version"), str)
-2071            and (fv.startswith("0.3.") or fv.startswith("0.4."))
-2072        ):
-2073            m04 = _ModelDescr_v0_4.load(data)
-2074            if not isinstance(m04, InvalidDescr):
-2075                return _model_conv.convert_as_dict(m04)
-2076
-2077        return data
+2023    weights: WeightsDescr
+2024    """The weights for this model.
+2025    Weights can be given for different formats, but should otherwise be equivalent.
+2026    The available weight formats determine which consumers can use this model."""
+2027
+2028    @model_validator(mode="after")
+2029    def _add_default_cover(self) -> Self:
+2030        if not validation_context_var.get().perform_io_checks or self.covers:
+2031            return self
+2032
+2033        try:
+2034            generated_covers = generate_covers(
+2035                [(t, load_array(t.test_tensor.download().path)) for t in self.inputs],
+2036                [(t, load_array(t.test_tensor.download().path)) for t in self.outputs],
+2037            )
+2038        except Exception as e:
+2039            issue_warning(
+2040                "Failed to generate cover image(s): {e}",
+2041                value=self.covers,
+2042                msg_context=dict(e=e),
+2043            )
+2044        else:
+2045            self.covers.extend(generated_covers)
+2046
+2047        return self
+2048
+2049    def get_input_test_arrays(self) -> List[NDArray[Any]]:
+2050        data = [load_array(ipt.test_tensor.download().path) for ipt in self.inputs]
+2051        assert all(isinstance(d, np.ndarray) for d in data)
+2052        return data
+2053
+2054    def get_output_test_arrays(self) -> List[NDArray[Any]]:
+2055        data = [load_array(out.test_tensor.download().path) for out in self.outputs]
+2056        assert all(isinstance(d, np.ndarray) for d in data)
+2057        return data
+2058
+2059    def get_tensor_sizes(
+2060        self, n: ParameterizedSize.N, batch_size: int
+2061    ) -> Dict[TensorId, Dict[AxisId, int]]:
+2062        all_axes = {
+2063            t.id: {a.id: a for a in t.axes} for t in chain(self.inputs, self.outputs)
+2064        }
+2065
+2066        ret: Dict[TensorId, Dict[AxisId, int]] = {}
+2067        for t_descr in chain(self.inputs, self.outputs):
+2068            ret[t_descr.id] = {}
+2069            for a in t_descr.axes:
+2070                if a.size is None:
+2071                    assert isinstance(a, BatchAxis)
+2072                    s = batch_size
+2073                elif isinstance(a.size, int):
+2074                    s = a.size
+2075                elif isinstance(a.size, ParameterizedSize):
+2076                    s = a.size.get_size(n)
+2077                elif isinstance(a.size, SizeReference):
+2078                    assert not isinstance(a, BatchAxis)
+2079                    ref_axis = all_axes[a.size.tensor_id][a.size.axis_id]
+2080                    assert not isinstance(ref_axis, BatchAxis)
+2081                    s = a.size.get_size(axis=a, ref_axis=ref_axis, n=n)
+2082                else:
+2083                    assert_never(a.size)
+2084
+2085                ret[t_descr.id][a.id] = s
+2086
+2087        return ret
+2088
+2089    @model_validator(mode="before")
+2090    @classmethod
+2091    def _convert(cls, data: Dict[str, Any]) -> Dict[str, Any]:
+2092        if (
+2093            data.get("type") == "model"
+2094            and isinstance(fv := data.get("format_version"), str)
+2095            and (fv.startswith("0.3.") or fv.startswith("0.4."))
+2096        ):
+2097            m04 = _ModelDescr_v0_4.load(data)
+2098            if not isinstance(m04, InvalidDescr):
+2099                return _model_conv.convert_as_dict(m04)
+2100
+2101        return data
 
    
 
 
@@ -12289,7 +12414,7 @@ 
    Inherited Members
    
                             
    
                             
    
                                 
    
-            documentation: Annotated[Union[Annotated[pathlib.Path, PathType(path_type='file'), Predicate(func=<function PurePath.is_absolute at 0x7f1c25245940>)], bioimageio.spec._internal.io.RelativeFilePath, bioimageio.spec._internal.url.HttpUrl], AfterValidator(func=<function _validate_md_suffix at 0x7f1c21d1afc0>), PlainSerializer(func=<function _package at 0x7f1c21c782c0>, return_type=PydanticUndefined, when_used='unless-none'), FieldInfo(annotation=NoneType, required=True, examples=['https://raw.githubusercontent.com/bioimage-io/spec-bioimage-io/main/example_descriptions/models/unet2d_nuclei_broad/README.md', 'README.md'])]
+            documentation: Annotated[Union[Annotated[pathlib.Path, PathType(path_type='file'), Predicate(func=<function PurePath.is_absolute at 0x7afca4145940>)], bioimageio.spec._internal.io.RelativeFilePath, bioimageio.spec._internal.url.HttpUrl], AfterValidator(func=<function _validate_md_suffix at 0x7afca0c06ca0>), PlainSerializer(func=<function _package at 0x7afca0d91760>, return_type=PydanticUndefined, when_used='unless-none'), FieldInfo(annotation=NoneType, required=True, examples=['https://raw.githubusercontent.com/bioimage-io/spec-bioimage-io/main/example_descriptions/models/unet2d_nuclei_broad/README.md', 'README.md'])]
 
         
     
    
@@ -12318,7 +12443,7 @@ 
    Inherited Members
    
                             
    
                             
    
                                 
    
-            name: Annotated[str, MinLen(min_length=5), AfterWarner(func=<function as_warning.<locals>.wrapper at 0x7f1c138bd300>, severity=20, msg='Name longer than 64 characters.', context={'typ': Annotated[Any, MaxLen(max_length=64)]})]
+            name: Annotated[str, MinLen(min_length=5), AfterWarner(func=<function as_warning.<locals>.wrapper at 0x7afc93e7bf60>, severity=20, msg='Name longer than 64 characters.', context={'typ': Annotated[Any, MaxLen(max_length=64)]})]
 
         
     
    
@@ -12374,7 +12499,7 @@ 
    Inherited Members
    
                             
    
                             
    
                                 
    
-            run_mode: Annotated[Optional[bioimageio.spec.model.v0_4.RunMode], AfterWarner(func=<function as_warning.<locals>.wrapper at 0x7f1c1336a0c0>, severity=30, msg="Run mode '{value}' has limited support across consumer softwares.", context={'typ': None})]
+            run_mode: Annotated[Optional[bioimageio.spec.model.v0_4.RunMode], AfterWarner(func=<function as_warning.<locals>.wrapper at 0x7afc91dd7a60>, severity=30, msg="Run mode '{value}' has limited support across consumer softwares.", context={'typ': None})]
 
         
     
    
@@ -12441,10 +12566,10 @@ 
    Inherited Members
    
 
     
    
     
-            
    2025    def get_input_test_arrays(self) -> List[NDArray[Any]]:
-2026        data = [load_array(ipt.test_tensor.download().path) for ipt in self.inputs]
-2027        assert all(isinstance(d, np.ndarray) for d in data)
-2028        return data
+            
    2049    def get_input_test_arrays(self) -> List[NDArray[Any]]:
+2050        data = [load_array(ipt.test_tensor.download().path) for ipt in self.inputs]
+2051        assert all(isinstance(d, np.ndarray) for d in data)
+2052        return data
 
    
 
 
@@ -12462,10 +12587,10 @@ 
    Inherited Members
    
 
     
    
     
-            
    2030    def get_output_test_arrays(self) -> List[NDArray[Any]]:
-2031        data = [load_array(out.test_tensor.download().path) for out in self.outputs]
-2032        assert all(isinstance(d, np.ndarray) for d in data)
-2033        return data
+            
    2054    def get_output_test_arrays(self) -> List[NDArray[Any]]:
+2055        data = [load_array(out.test_tensor.download().path) for out in self.outputs]
+2056        assert all(isinstance(d, np.ndarray) for d in data)
+2057        return data
 
    
 
 
@@ -12477,41 +12602,41 @@ 
    Inherited Members
    
 
    
             
         def
-        get_tensor_sizes(	self,	n: int,	batch_size: int) -> Dict[bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]], Dict[bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]], int]]:
+        get_tensor_sizes(	self,	n: int,	batch_size: int) -> Dict[bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]], Dict[AxisId, int]]:
 
                 
 
     
    
     
-            
    2035    def get_tensor_sizes(
-2036        self, n: ParameterizedSize.N, batch_size: int
-2037    ) -> Dict[TensorId, Dict[AxisId, int]]:
-2038        all_axes = {
-2039            t.id: {a.id: a for a in t.axes} for t in chain(self.inputs, self.outputs)
-2040        }
-2041
-2042        ret: Dict[TensorId, Dict[AxisId, int]] = {}
-2043        for t_descr in chain(self.inputs, self.outputs):
-2044            ret[t_descr.id] = {}
-2045            for a in t_descr.axes:
-2046                if a.size is None:
-2047                    assert isinstance(a, BatchAxis)
-2048                    s = batch_size
-2049                elif isinstance(a.size, int):
-2050                    s = a.size
-2051                elif isinstance(a.size, ParameterizedSize):
-2052                    s = a.size.get_size(n)
-2053                elif isinstance(a.size, SizeReference):
-2054                    assert not isinstance(a, BatchAxis)
-2055                    ref_axis = all_axes[a.size.tensor_id][a.size.axis_id]
-2056                    assert not isinstance(ref_axis, BatchAxis)
-2057                    s = a.size.get_size(axis=a, ref_axis=ref_axis, n=n)
-2058                else:
-2059                    assert_never(a.size)
-2060
-2061                ret[t_descr.id][a.id] = s
-2062
-2063        return ret
+            
    2059    def get_tensor_sizes(
+2060        self, n: ParameterizedSize.N, batch_size: int
+2061    ) -> Dict[TensorId, Dict[AxisId, int]]:
+2062        all_axes = {
+2063            t.id: {a.id: a for a in t.axes} for t in chain(self.inputs, self.outputs)
+2064        }
+2065
+2066        ret: Dict[TensorId, Dict[AxisId, int]] = {}
+2067        for t_descr in chain(self.inputs, self.outputs):
+2068            ret[t_descr.id] = {}
+2069            for a in t_descr.axes:
+2070                if a.size is None:
+2071                    assert isinstance(a, BatchAxis)
+2072                    s = batch_size
+2073                elif isinstance(a.size, int):
+2074                    s = a.size
+2075                elif isinstance(a.size, ParameterizedSize):
+2076                    s = a.size.get_size(n)
+2077                elif isinstance(a.size, SizeReference):
+2078                    assert not isinstance(a, BatchAxis)
+2079                    ref_axis = all_axes[a.size.tensor_id][a.size.axis_id]
+2080                    assert not isinstance(ref_axis, BatchAxis)
+2081                    s = a.size.get_size(axis=a, ref_axis=ref_axis, n=n)
+2082                else:
+2083                    assert_never(a.size)
+2084
+2085                ret[t_descr.id][a.id] = s
+2086
+2087        return ret
 
    
 
 
@@ -12559,7 +12684,7 @@ 
    Inherited Members
    
                                 
    
             model_fields        =
 
-            {'name': FieldInfo(annotation=str, required=True, metadata=[MinLen(min_length=5), AfterWarner(func=<function as_warning.<locals>.wrapper>, severity=20, msg='Name longer than 64 characters.', context={'typ': typing.Annotated[typing.Any, MaxLen(max_length=64)]})]), 'description': FieldInfo(annotation=str, required=True, metadata=[MaxLen(max_length=1024), AfterWarner(func=<function as_warning.<locals>.wrapper>, severity=30, msg='Description longer than 512 characters.', context={'typ': typing.Annotated[typing.Any, MaxLen(max_length=512)]})]), 'covers': FieldInfo(annotation=List[Annotated[Union[HttpUrl, Annotated[Path, PathType, Predicate], RelativeFilePath], WithSuffix, PlainSerializer]], required=False, default_factory=list, description="Cover images. Please use an image smaller than 500KB and an aspect ratio width to height of 2:1 or 1:1.\nThe supported image formats are: ('.gif', '.jpeg', '.jpg', '.png', '.svg')", examples=[]), 'id_emoji': FieldInfo(annotation=Union[Annotated[str, Len], NoneType], required=False), 'authors': FieldInfo(annotation=List[Author], required=True, metadata=[MinLen(min_length=1)]), 'attachments': FieldInfo(annotation=List[FileDescr], required=False, default_factory=list), 'cite': FieldInfo(annotation=List[CiteEntry], required=True, metadata=[MinLen(min_length=1)]), 'license': FieldInfo(annotation=Union[LicenseId, DeprecatedLicenseId], required=True, examples=['CC-BY-4.0', 'MIT', 'BSD-2-Clause'], metadata=[AfterWarner(func=<function as_warning.<locals>.wrapper>, severity=30, msg='{value} is deprecated, see https://spdx.org/licenses/{value}.html', context={'typ': <class 'bioimageio.spec._internal.license_id.LicenseId'>})]), 'config': FieldInfo(annotation=Dict[str, YamlValue], required=False, default_factory=dict, examples=[{'bioimageio': {'my_custom_key': 3837283, 'another_key': {'nested': 'value'}}, 'imagej': {'macro_dir': 'path/to/macro/file'}}]), 'git_repo': FieldInfo(annotation=Union[HttpUrl, NoneType], required=False, examples=['https://github.com/bioimage-io/spec-bioimage-io/tree/main/example_descriptions/models/unet2d_nuclei_broad']), 'icon': FieldInfo(annotation=Union[Annotated[Union[Annotated[Path, PathType], RelativeFilePath, HttpUrl, Annotated[Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator, PlainSerializer], Annotated[str, Len], NoneType], required=False), 'links': FieldInfo(annotation=List[str], required=False, default_factory=list, examples=[('ilastik/ilastik', 'deepimagej/deepimagej', 'zero/notebook_u-net_3d_zerocostdl4mic')]), 'uploader': FieldInfo(annotation=Union[Uploader, NoneType], required=False), 'maintainers': FieldInfo(annotation=List[Maintainer], required=False, default_factory=list), 'tags': FieldInfo(annotation=List[str], required=False, default_factory=list, examples=[('unet2d', 'pytorch', 'nucleus', 'segmentation', 'dsb2018')]), 'version': FieldInfo(annotation=Union[Version, NoneType], required=False), 'version_number': FieldInfo(annotation=Union[int, NoneType], required=False), 'format_version': FieldInfo(annotation=Literal['0.5.0'], required=False, default='0.5.0'), 'type': FieldInfo(annotation=Literal['model'], required=False, default='model'), 'id': FieldInfo(annotation=Union[ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]], NoneType], required=False), 'documentation': FieldInfo(annotation=Union[Annotated[Path, PathType, Predicate], RelativeFilePath, HttpUrl], required=True, examples=['https://raw.githubusercontent.com/bioimage-io/spec-bioimage-io/main/example_descriptions/models/unet2d_nuclei_broad/README.md', 'README.md'], metadata=[AfterValidator(func=<function _validate_md_suffix>), PlainSerializer(func=<function _package>, return_type=PydanticUndefined, when_used='unless-none')]), 'inputs': FieldInfo(annotation=Sequence[InputTensorDescr], required=True, metadata=[MinLen(min_length=1)]), 'outputs': FieldInfo(annotation=Sequence[OutputTensorDescr], required=True, metadata=[MinLen(min_length=1)]), 'packaged_by': FieldInfo(annotation=List[Author], required=False, default_factory=list), 'parent': FieldInfo(annotation=Union[LinkedModel, NoneType], required=False), 'run_mode': FieldInfo(annotation=Union[RunMode, NoneType], required=False, metadata=[AfterWarner(func=<function as_warning.<locals>.wrapper>, severity=30, msg="Run mode '{value}' has limited support across consumer softwares.", context={'typ': None})]), 'timestamp': FieldInfo(annotation=Datetime, required=False, default=Datetime(root=datetime.datetime(2024, 3, 13, 14, 32, 43, 966760))), 'training_data': FieldInfo(annotation=Union[LinkedDataset, DatasetDescr, NoneType], required=False), 'weights': FieldInfo(annotation=WeightsDescr, required=True)}
+            {'name': FieldInfo(annotation=str, required=True, metadata=[MinLen(min_length=5), AfterWarner(func=<function as_warning.<locals>.wrapper>, severity=20, msg='Name longer than 64 characters.', context={'typ': typing.Annotated[typing.Any, MaxLen(max_length=64)]})]), 'description': FieldInfo(annotation=str, required=True, metadata=[MaxLen(max_length=1024), AfterWarner(func=<function as_warning.<locals>.wrapper>, severity=30, msg='Description longer than 512 characters.', context={'typ': typing.Annotated[typing.Any, MaxLen(max_length=512)]})]), 'covers': FieldInfo(annotation=List[Annotated[Union[HttpUrl, Annotated[Path, PathType, Predicate], RelativeFilePath], WithSuffix, PlainSerializer]], required=False, default_factory=list, description="Cover images. Please use an image smaller than 500KB and an aspect ratio width to height of 2:1 or 1:1.\nThe supported image formats are: ('.gif', '.jpeg', '.jpg', '.png', '.svg')", examples=[]), 'id_emoji': FieldInfo(annotation=Union[Annotated[str, Len], NoneType], required=False), 'authors': FieldInfo(annotation=List[Author], required=True, metadata=[MinLen(min_length=1)]), 'attachments': FieldInfo(annotation=List[FileDescr], required=False, default_factory=list), 'cite': FieldInfo(annotation=List[CiteEntry], required=True, metadata=[MinLen(min_length=1)]), 'license': FieldInfo(annotation=Union[LicenseId, DeprecatedLicenseId], required=True, examples=['CC-BY-4.0', 'MIT', 'BSD-2-Clause'], metadata=[AfterWarner(func=<function as_warning.<locals>.wrapper>, severity=30, msg='{value} is deprecated, see https://spdx.org/licenses/{value}.html', context={'typ': <class 'bioimageio.spec._internal.license_id.LicenseId'>})]), 'config': FieldInfo(annotation=Dict[str, YamlValue], required=False, default_factory=dict, examples=[{'bioimageio': {'my_custom_key': 3837283, 'another_key': {'nested': 'value'}}, 'imagej': {'macro_dir': 'path/to/macro/file'}}]), 'git_repo': FieldInfo(annotation=Union[HttpUrl, NoneType], required=False, examples=['https://github.com/bioimage-io/spec-bioimage-io/tree/main/example_descriptions/models/unet2d_nuclei_broad']), 'icon': FieldInfo(annotation=Union[Annotated[Union[Annotated[Path, PathType], RelativeFilePath, HttpUrl, Annotated[Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator, PlainSerializer], Annotated[str, Len], NoneType], required=False), 'links': FieldInfo(annotation=List[str], required=False, default_factory=list, examples=[('ilastik/ilastik', 'deepimagej/deepimagej', 'zero/notebook_u-net_3d_zerocostdl4mic')]), 'uploader': FieldInfo(annotation=Union[Uploader, NoneType], required=False), 'maintainers': FieldInfo(annotation=List[Maintainer], required=False, default_factory=list), 'tags': FieldInfo(annotation=List[str], required=False, default_factory=list, examples=[('unet2d', 'pytorch', 'nucleus', 'segmentation', 'dsb2018')]), 'version': FieldInfo(annotation=Union[Version, NoneType], required=False), 'version_number': FieldInfo(annotation=Union[int, NoneType], required=False), 'format_version': FieldInfo(annotation=Literal['0.5.0'], required=False, default='0.5.0'), 'type': FieldInfo(annotation=Literal['model'], required=False, default='model'), 'id': FieldInfo(annotation=Union[ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]], NoneType], required=False), 'documentation': FieldInfo(annotation=Union[Annotated[Path, PathType, Predicate], RelativeFilePath, HttpUrl], required=True, examples=['https://raw.githubusercontent.com/bioimage-io/spec-bioimage-io/main/example_descriptions/models/unet2d_nuclei_broad/README.md', 'README.md'], metadata=[AfterValidator(func=<function _validate_md_suffix>), PlainSerializer(func=<function _package>, return_type=PydanticUndefined, when_used='unless-none')]), 'inputs': FieldInfo(annotation=Sequence[InputTensorDescr], required=True, metadata=[MinLen(min_length=1)]), 'outputs': FieldInfo(annotation=Sequence[OutputTensorDescr], required=True, metadata=[MinLen(min_length=1)]), 'packaged_by': FieldInfo(annotation=List[Author], required=False, default_factory=list), 'parent': FieldInfo(annotation=Union[LinkedModel, NoneType], required=False), 'run_mode': FieldInfo(annotation=Union[RunMode, NoneType], required=False, metadata=[AfterWarner(func=<function as_warning.<locals>.wrapper>, severity=30, msg="Run mode '{value}' has limited support across consumer softwares.", context={'typ': None})]), 'timestamp': FieldInfo(annotation=Datetime, required=False, default=Datetime(root=datetime.datetime(2024, 3, 14, 14, 46, 42, 87090))), 'training_data': FieldInfo(annotation=Union[LinkedDataset, DatasetDescr, NoneType], required=False), 'weights': FieldInfo(annotation=WeightsDescr, required=True)}
 
         
     
    
@@ -12660,182 +12785,182 @@ 
    Inherited Members
    
 
     
    
     
-            
    2260def generate_covers(
-2261    inputs: Sequence[Tuple[InputTensorDescr, NDArray[Any]]],
-2262    outputs: Sequence[Tuple[OutputTensorDescr, NDArray[Any]]],
-2263) -> List[Path]:
-2264    def squeeze(
-2265        data: NDArray[Any], axes: Sequence[AnyAxis]
-2266    ) -> Tuple[NDArray[Any], List[AnyAxis]]:
-2267        """apply numpy.ndarray.squeeze while keeping track of the axis descriptions remaining"""
-2268        if data.ndim != len(axes):
-2269            raise ValueError(
-2270                f"tensor shape {data.shape} does not match described axes"
-2271                + f" {[a.id for a in axes]}"
-2272            )
-2273
-2274        axes = [deepcopy(a) for a, s in zip(axes, data.shape) if s != 1]
-2275        return data.squeeze(), axes
-2276
-2277    def normalize(
-2278        data: NDArray[Any], axis: Optional[Tuple[int, ...]], eps: float = 1e-7
-2279    ) -> NDArray[np.float32]:
-2280        data = data.astype("float32")
-2281        data -= data.min(axis=axis, keepdims=True)
-2282        data /= data.max(axis=axis, keepdims=True) + eps
-2283        return data
-2284
-2285    def to_2d_image(data: NDArray[Any], axes: Sequence[AnyAxis]):
-2286        original_shape = data.shape
-2287        data, axes = squeeze(data, axes)
-2288
-2289        # take slice fom any batch or index axis if needed
-2290        # and convert the first channel axis and take a slice from any additional channel axes
-2291        slices: Tuple[slice, ...] = ()
-2292        ndim = data.ndim
-2293        ndim_need = 3 if any(isinstance(a, ChannelAxis) for a in axes) else 2
-2294        has_c_axis = False
-2295        for i, a in enumerate(axes):
-2296            s = data.shape[i]
-2297            assert s > 1
-2298            if isinstance(a, (BatchAxis, IndexAxis)) and ndim > ndim_need:
-2299                data = data[slices + (slice(s // 2 - 1, s // 2),)]
-2300                ndim -= 1
-2301            elif isinstance(a, ChannelAxis):
-2302                if has_c_axis:
-2303                    # second channel axis
-2304                    data = data[slices + (slice(0, 1),)]
-2305                    ndim -= 1
-2306                else:
-2307                    has_c_axis = True
-2308                    if s == 2:
-2309                        # visualize two channels with cyan and magenta
-2310                        data = np.concatenate(
-2311                            [
-2312                                data[slices + (slice(1, 2),)],
-2313                                data[slices + (slice(0, 1),)],
-2314                                (
-2315                                    data[slices + (slice(0, 1),)]
-2316                                    + data[slices + (slice(1, 2),)]
-2317                                )
-2318                                / 2,  # TODO: take maximum instead?
-2319                            ],
-2320                            axis=i,
-2321                        )
-2322                    elif data.shape[i] == 3:
-2323                        pass  # visualize 3 channels as RGB
-2324                    else:
-2325                        # visualize first 3 channels as RGB
-2326                        data = data[slices + (slice(3),)]
-2327
-2328                    assert data.shape[i] == 3
-2329
-2330            slices += (slice(None),)  # type: ignore
-2331
-2332        data, axes = squeeze(data, axes)
-2333        assert len(axes) == ndim
-2334        # take slice from z axis if needed
-2335        slices = ()
-2336        if ndim > ndim_need:
-2337            for i, a in enumerate(axes):
-2338                s = data.shape[i]
-2339                if a.id.root == "z":
-2340                    data = data[slices + (slice(s // 2 - 1, s // 2),)]
-2341                    data, axes = squeeze(data, axes)
-2342                    ndim -= 1
-2343                    break
-2344
-2345            slices += (slice(None),)
-2346
-2347        # take slice from any space or time axis
-2348        slices = ()
-2349
-2350        for i, a in enumerate(axes):
-2351            if ndim <= ndim_need:
-2352                break
+            
    2284def generate_covers(
+2285    inputs: Sequence[Tuple[InputTensorDescr, NDArray[Any]]],
+2286    outputs: Sequence[Tuple[OutputTensorDescr, NDArray[Any]]],
+2287) -> List[Path]:
+2288    def squeeze(
+2289        data: NDArray[Any], axes: Sequence[AnyAxis]
+2290    ) -> Tuple[NDArray[Any], List[AnyAxis]]:
+2291        """apply numpy.ndarray.squeeze while keeping track of the axis descriptions remaining"""
+2292        if data.ndim != len(axes):
+2293            raise ValueError(
+2294                f"tensor shape {data.shape} does not match described axes"
+2295                + f" {[a.id for a in axes]}"
+2296            )
+2297
+2298        axes = [deepcopy(a) for a, s in zip(axes, data.shape) if s != 1]
+2299        return data.squeeze(), axes
+2300
+2301    def normalize(
+2302        data: NDArray[Any], axis: Optional[Tuple[int, ...]], eps: float = 1e-7
+2303    ) -> NDArray[np.float32]:
+2304        data = data.astype("float32")
+2305        data -= data.min(axis=axis, keepdims=True)
+2306        data /= data.max(axis=axis, keepdims=True) + eps
+2307        return data
+2308
+2309    def to_2d_image(data: NDArray[Any], axes: Sequence[AnyAxis]):
+2310        original_shape = data.shape
+2311        data, axes = squeeze(data, axes)
+2312
+2313        # take slice fom any batch or index axis if needed
+2314        # and convert the first channel axis and take a slice from any additional channel axes
+2315        slices: Tuple[slice, ...] = ()
+2316        ndim = data.ndim
+2317        ndim_need = 3 if any(isinstance(a, ChannelAxis) for a in axes) else 2
+2318        has_c_axis = False
+2319        for i, a in enumerate(axes):
+2320            s = data.shape[i]
+2321            assert s > 1
+2322            if isinstance(a, (BatchAxis, IndexAxis)) and ndim > ndim_need:
+2323                data = data[slices + (slice(s // 2 - 1, s // 2),)]
+2324                ndim -= 1
+2325            elif isinstance(a, ChannelAxis):
+2326                if has_c_axis:
+2327                    # second channel axis
+2328                    data = data[slices + (slice(0, 1),)]
+2329                    ndim -= 1
+2330                else:
+2331                    has_c_axis = True
+2332                    if s == 2:
+2333                        # visualize two channels with cyan and magenta
+2334                        data = np.concatenate(
+2335                            [
+2336                                data[slices + (slice(1, 2),)],
+2337                                data[slices + (slice(0, 1),)],
+2338                                (
+2339                                    data[slices + (slice(0, 1),)]
+2340                                    + data[slices + (slice(1, 2),)]
+2341                                )
+2342                                / 2,  # TODO: take maximum instead?
+2343                            ],
+2344                            axis=i,
+2345                        )
+2346                    elif data.shape[i] == 3:
+2347                        pass  # visualize 3 channels as RGB
+2348                    else:
+2349                        # visualize first 3 channels as RGB
+2350                        data = data[slices + (slice(3),)]
+2351
+2352                    assert data.shape[i] == 3
 2353
-2354            s = data.shape[i]
-2355            assert s > 1
-2356            if isinstance(
-2357                a, (SpaceInputAxis, SpaceOutputAxis, TimeInputAxis, TimeOutputAxis)
-2358            ):
-2359                data = data[slices + (slice(s // 2 - 1, s // 2),)]
-2360                ndim -= 1
-2361
-2362            slices += (slice(None),)  # type: ignore
-2363
-2364        del slices
-2365        data, axes = squeeze(data, axes)
-2366        assert len(axes) == ndim
-2367
-2368        if (has_c_axis and ndim != 3) or ndim != 2:
-2369            raise ValueError(
-2370                f"Failed to construct cover image from shape {original_shape}"
-2371            )
-2372
-2373        if not has_c_axis:
-2374            assert ndim == 2
-2375            data = np.repeat(data[:, :, None], 3, axis=2)
-2376            axes.append(ChannelAxis(channel_names=list(map(Identifier, "RGB"))))
-2377            ndim += 1
-2378
-2379        assert ndim == 3
-2380
-2381        # transpose axis order such that longest axis comes first...
-2382        axis_order = list(np.argsort(list(data.shape)))
-2383        axis_order.reverse()
-2384        # ... and channel axis is last
-2385        c = [i for i in range(3) if isinstance(axes[i], ChannelAxis)][0]
-2386        axis_order.append(axis_order.pop(c))
-2387        axes = [axes[ao] for ao in axis_order]
-2388        data = data.transpose(axis_order)
-2389
-2390        # h, w = data.shape[:2]
-2391        # if h / w  in (1.0 or 2.0):
-2392        #     pass
-2393        # elif h / w < 2:
-2394        # TODO: enforce 2:1 or 1:1 aspect ratio for generated cover images
-2395
-2396        norm_along = (
-2397            tuple(i for i, a in enumerate(axes) if a.type in ("space", "time")) or None
-2398        )
-2399        # normalize the data and map to 8 bit
-2400        data = normalize(data, norm_along)
-2401        data = (data * 255).astype("uint8")
+2354            slices += (slice(None),)  # type: ignore
+2355
+2356        data, axes = squeeze(data, axes)
+2357        assert len(axes) == ndim
+2358        # take slice from z axis if needed
+2359        slices = ()
+2360        if ndim > ndim_need:
+2361            for i, a in enumerate(axes):
+2362                s = data.shape[i]
+2363                if a.id == AxisId("z"):
+2364                    data = data[slices + (slice(s // 2 - 1, s // 2),)]
+2365                    data, axes = squeeze(data, axes)
+2366                    ndim -= 1
+2367                    break
+2368
+2369            slices += (slice(None),)
+2370
+2371        # take slice from any space or time axis
+2372        slices = ()
+2373
+2374        for i, a in enumerate(axes):
+2375            if ndim <= ndim_need:
+2376                break
+2377
+2378            s = data.shape[i]
+2379            assert s > 1
+2380            if isinstance(
+2381                a, (SpaceInputAxis, SpaceOutputAxis, TimeInputAxis, TimeOutputAxis)
+2382            ):
+2383                data = data[slices + (slice(s // 2 - 1, s // 2),)]
+2384                ndim -= 1
+2385
+2386            slices += (slice(None),)  # type: ignore
+2387
+2388        del slices
+2389        data, axes = squeeze(data, axes)
+2390        assert len(axes) == ndim
+2391
+2392        if (has_c_axis and ndim != 3) or ndim != 2:
+2393            raise ValueError(
+2394                f"Failed to construct cover image from shape {original_shape}"
+2395            )
+2396
+2397        if not has_c_axis:
+2398            assert ndim == 2
+2399            data = np.repeat(data[:, :, None], 3, axis=2)
+2400            axes.append(ChannelAxis(channel_names=list(map(Identifier, "RGB"))))
+2401            ndim += 1
 2402
-2403        return data
+2403        assert ndim == 3
 2404
-2405    def create_diagonal_split_image(im0: NDArray[Any], im1: NDArray[Any]):
-2406        assert im0.dtype == im1.dtype == np.uint8
-2407        assert im0.shape == im1.shape
-2408        assert im0.ndim == 3
-2409        N, M, C = im0.shape
-2410        assert C == 3
-2411        out = np.ones((N, M, C), dtype="uint8")
-2412        for c in range(C):
-2413            outc = np.tril(im0[..., c])
-2414            mask = outc == 0
-2415            outc[mask] = np.triu(im1[..., c])[mask]
-2416            out[..., c] = outc
-2417
-2418        return out
+2405        # transpose axis order such that longest axis comes first...
+2406        axis_order = list(np.argsort(list(data.shape)))
+2407        axis_order.reverse()
+2408        # ... and channel axis is last
+2409        c = [i for i in range(3) if isinstance(axes[i], ChannelAxis)][0]
+2410        axis_order.append(axis_order.pop(c))
+2411        axes = [axes[ao] for ao in axis_order]
+2412        data = data.transpose(axis_order)
+2413
+2414        # h, w = data.shape[:2]
+2415        # if h / w  in (1.0 or 2.0):
+2416        #     pass
+2417        # elif h / w < 2:
+2418        # TODO: enforce 2:1 or 1:1 aspect ratio for generated cover images
 2419
-2420    ipt_descr, ipt = inputs[0]
-2421    out_descr, out = outputs[0]
-2422
-2423    ipt_img = to_2d_image(ipt, ipt_descr.axes)
-2424    out_img = to_2d_image(out, out_descr.axes)
-2425
-2426    cover_folder = Path(mkdtemp())
-2427    if ipt_img.shape == out_img.shape:
-2428        covers = [cover_folder / "cover.png"]
-2429        imageio.imwrite(covers[0], create_diagonal_split_image(ipt_img, out_img))
-2430    else:
-2431        covers = [cover_folder / "input.png", cover_folder / "output.png"]
-2432        imageio.imwrite(covers[0], ipt_img)
-2433        imageio.imwrite(covers[1], out_img)
-2434
-2435    return covers
+2420        norm_along = (
+2421            tuple(i for i, a in enumerate(axes) if a.type in ("space", "time")) or None
+2422        )
+2423        # normalize the data and map to 8 bit
+2424        data = normalize(data, norm_along)
+2425        data = (data * 255).astype("uint8")
+2426
+2427        return data
+2428
+2429    def create_diagonal_split_image(im0: NDArray[Any], im1: NDArray[Any]):
+2430        assert im0.dtype == im1.dtype == np.uint8
+2431        assert im0.shape == im1.shape
+2432        assert im0.ndim == 3
+2433        N, M, C = im0.shape
+2434        assert C == 3
+2435        out = np.ones((N, M, C), dtype="uint8")
+2436        for c in range(C):
+2437            outc = np.tril(im0[..., c])
+2438            mask = outc == 0
+2439            outc[mask] = np.triu(im1[..., c])[mask]
+2440            out[..., c] = outc
+2441
+2442        return out
+2443
+2444    ipt_descr, ipt = inputs[0]
+2445    out_descr, out = outputs[0]
+2446
+2447    ipt_img = to_2d_image(ipt, ipt_descr.axes)
+2448    out_img = to_2d_image(out, out_descr.axes)
+2449
+2450    cover_folder = Path(mkdtemp())
+2451    if ipt_img.shape == out_img.shape:
+2452        covers = [cover_folder / "cover.png"]
+2453        imageio.imwrite(covers[0], create_diagonal_split_image(ipt_img, out_img))
+2454    else:
+2455        covers = [cover_folder / "input.png", cover_folder / "output.png"]
+2456        imageio.imwrite(covers[0], ipt_img)
+2457        imageio.imwrite(covers[1], out_img)
+2458
+2459    return covers
 
    
 
 
diff --git a/bioimageio/spec/notebook/v0_2.html b/bioimageio/spec/notebook/v0_2.html
index d47007748..0eca26f51 100644
--- a/bioimageio/spec/notebook/v0_2.html
+++ b/bioimageio/spec/notebook/v0_2.html
@@ -227,7 +227,7 @@ 
    
                             
    
                             
    
                                 
    
-            source: Union[Annotated[bioimageio.spec._internal.url.HttpUrl, WithSuffix(suffix='.ipynb', case_sensitive=True)], Annotated[pathlib.Path, PathType(path_type='file'), Predicate(func=<function PurePath.is_absolute at 0x7f1c25245940>), WithSuffix(suffix='.ipynb', case_sensitive=True)], Annotated[bioimageio.spec._internal.io.RelativeFilePath, WithSuffix(suffix='.ipynb', case_sensitive=True)]]
+            source: Union[Annotated[bioimageio.spec._internal.url.HttpUrl, WithSuffix(suffix='.ipynb', case_sensitive=True)], Annotated[pathlib.Path, PathType(path_type='file'), Predicate(func=<function PurePath.is_absolute at 0x7afca4145940>), WithSuffix(suffix='.ipynb', case_sensitive=True)], Annotated[bioimageio.spec._internal.io.RelativeFilePath, WithSuffix(suffix='.ipynb', case_sensitive=True)]]
 
         
     
    
diff --git a/bioimageio/spec/notebook/v0_3.html b/bioimageio/spec/notebook/v0_3.html
index 19936cb49..b518dd3e9 100644
--- a/bioimageio/spec/notebook/v0_3.html
+++ b/bioimageio/spec/notebook/v0_3.html
@@ -225,7 +225,7 @@ 
    
                             
    
                             
    
                                 
    
-            source: Union[Annotated[bioimageio.spec._internal.url.HttpUrl, WithSuffix(suffix='.ipynb', case_sensitive=True)], Annotated[pathlib.Path, PathType(path_type='file'), Predicate(func=<function PurePath.is_absolute at 0x7f1c25245940>), WithSuffix(suffix='.ipynb', case_sensitive=True)], Annotated[bioimageio.spec._internal.io.RelativeFilePath, WithSuffix(suffix='.ipynb', case_sensitive=True)]]
+            source: Union[Annotated[bioimageio.spec._internal.url.HttpUrl, WithSuffix(suffix='.ipynb', case_sensitive=True)], Annotated[pathlib.Path, PathType(path_type='file'), Predicate(func=<function PurePath.is_absolute at 0x7afca4145940>), WithSuffix(suffix='.ipynb', case_sensitive=True)], Annotated[bioimageio.spec._internal.io.RelativeFilePath, WithSuffix(suffix='.ipynb', case_sensitive=True)]]
 
         
     
    
diff --git a/bioimageio_schema_latest.json b/bioimageio_schema_latest.json
index 4ffa1bce0..94cfa921a 100644
--- a/bioimageio_schema_latest.json
+++ b/bioimageio_schema_latest.json
@@ -231,12 +231,9 @@
             "additionalProperties": false,
             "properties": {
                 "id": {
-                    "allOf": [
-                        {
-                            "$ref": "#/$defs/ValidatedString_Annotated_str__MinLen__AfterValidator__AfterValidator__Annotated_TypeVar__Predicate___MaxLen___Predicate_func__function__lambda__at_0x7fe608a7ba60__"
-                        }
-                    ],
-                    "default": "batch"
+                    "default": "batch",
+                    "title": "Id",
+                    "type": "string"
                 },
                 "description": {
                     "default": "",
@@ -283,12 +280,9 @@
             "additionalProperties": false,
             "properties": {
                 "id": {
-                    "allOf": [
-                        {
-                            "$ref": "#/$defs/ValidatedString_Annotated_str__MinLen__AfterValidator__AfterValidator__Annotated_TypeVar__Predicate___MaxLen___Predicate_func__function__lambda__at_0x7fe608d8ba60__"
-                        }
-                    ],
-                    "default": "channel"
+                    "default": "channel",
+                    "title": "Id",
+                    "type": "string"
                 },
                 "description": {
                     "default": "",
@@ -570,7 +564,7 @@
                 "axis": {
                     "anyOf": [
                         {
-                            "$ref": "#/$defs/ValidatedString_Annotated_str__MinLen__AfterValidator__AfterValidator__Annotated_TypeVar__Predicate___MaxLen___Predicate_func__function__lambda__at_0x7fe608d8ba60__"
+                            "type": "string"
                         },
                         {
                             "type": "null"
@@ -580,7 +574,8 @@
                     "examples": [
                         "channel",
                         "index"
-                    ]
+                    ],
+                    "title": "Axis"
                 }
             },
             "required": [
@@ -645,12 +640,9 @@
             "additionalProperties": false,
             "properties": {
                 "id": {
-                    "allOf": [
-                        {
-                            "$ref": "#/$defs/ValidatedString_Annotated_str__MinLen__AfterValidator__AfterValidator__Annotated_TypeVar__Predicate___MaxLen___Predicate_func__function__lambda__at_0x7fe608d8ba60__"
-                        }
-                    ],
-                    "default": "index"
+                    "default": "index",
+                    "title": "Id",
+                    "type": "string"
                 },
                 "description": {
                     "default": "",
@@ -1560,10 +1552,11 @@
             "description": "A tensor axis size (extent in pixels/frames) defined in relation to a reference axis.\n\n`axis.size = reference.size * reference.scale / axis.scale + offset`\n\nnote:\n1. The axis and the referenced axis need to have the same unit (or no unit).\n2. Batch axes may not be referenced.\n3. Fractions are rounded down.\n\nexample:\nAn unisotropic input image of w*h=100*49 pixels depicts a phsical space of 200*196mm\u00b2.\nLet's assume that we want to express the image height h in relation to its width w\ninstead of only accepting input images of exactly 100*49 pixels\n(for example to express a range of valid image shapes by parametrizing w, see `ParameterizedSize`).\n\n>>> w = SpaceInputAxis(id=AxisId(\"w\"), size=100, unit=\"millimeter\", scale=2)\n>>> h = SpaceInputAxis(\n...     id=AxisId(\"h\"),\n...     size=SizeReference(tensor_id=TensorId(\"input\"), axis_id=AxisId(\"w\"), offset=-1),\n...     unit=\"millimeter\",\n...     scale=4,\n... )\n>>> print(h.size.compute(h, w))\n49\n\n-> h = w * w.scale / h.scale + offset = 100 * 2mm / 4mm - 1 = 49",
             "properties": {
                 "tensor_id": {
-                    "$ref": "#/$defs/bioimageio__spec___internal__validated_string__ValidatedString_Annotated_str__MinLen__AfterValidator__AfterValidator__Annotated_TypeVar__Predicate___MaxLen____1"
+                    "$ref": "#/$defs/ValidatedString_Annotated_str__MinLen__AfterValidator__AfterValidator__Annotated_TypeVar__Predicate___MaxLen__"
                 },
                 "axis_id": {
-                    "$ref": "#/$defs/bioimageio__spec___internal__validated_string__ValidatedString_Annotated_str__MinLen__AfterValidator__AfterValidator__Annotated_TypeVar__Predicate___MaxLen____2"
+                    "title": "Axis Id",
+                    "type": "string"
                 },
                 "offset": {
                     "default": 0,
@@ -1582,17 +1575,14 @@
             "additionalProperties": false,
             "properties": {
                 "id": {
-                    "allOf": [
-                        {
-                            "$ref": "#/$defs/ValidatedString_Annotated_str__MinLen__AfterValidator__AfterValidator__Annotated_TypeVar__Predicate___MaxLen___Predicate_func__function__lambda__at_0x7fe608d8ba60__"
-                        }
-                    ],
                     "default": "x",
                     "examples": [
                         "x",
                         "y",
                         "z"
-                    ]
+                    ],
+                    "title": "Id",
+                    "type": "string"
                 },
                 "description": {
                     "default": "",
@@ -1695,17 +1685,14 @@
                     "type": "integer"
                 },
                 "id": {
-                    "allOf": [
-                        {
-                            "$ref": "#/$defs/ValidatedString_Annotated_str__MinLen__AfterValidator__AfterValidator__Annotated_TypeVar__Predicate___MaxLen___Predicate_func__function__lambda__at_0x7fe608d8ba60__"
-                        }
-                    ],
                     "default": "x",
                     "examples": [
                         "x",
                         "y",
                         "z"
-                    ]
+                    ],
+                    "title": "Id",
+                    "type": "string"
                 },
                 "description": {
                     "default": "",
@@ -1802,12 +1789,9 @@
             "additionalProperties": false,
             "properties": {
                 "id": {
-                    "allOf": [
-                        {
-                            "$ref": "#/$defs/ValidatedString_Annotated_str__MinLen__AfterValidator__AfterValidator__Annotated_TypeVar__Predicate___MaxLen___Predicate_func__function__lambda__at_0x7fe608d8ba60__"
-                        }
-                    ],
-                    "default": "time"
+                    "default": "time",
+                    "title": "Id",
+                    "type": "string"
                 },
                 "description": {
                     "default": "",
@@ -1907,12 +1891,9 @@
                     "type": "integer"
                 },
                 "id": {
-                    "allOf": [
-                        {
-                            "$ref": "#/$defs/ValidatedString_Annotated_str__MinLen__AfterValidator__AfterValidator__Annotated_TypeVar__Predicate___MaxLen___Predicate_func__function__lambda__at_0x7fe608d8ba60__"
-                        }
-                    ],
-                    "default": "time"
+                    "default": "time",
+                    "title": "Id",
+                    "type": "string"
                 },
                 "description": {
                     "default": "",
@@ -2043,14 +2024,8 @@
             "title": "ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate]]]",
             "type": "string"
         },
-        "ValidatedString_Annotated_str__MinLen__AfterValidator__AfterValidator__Annotated_TypeVar__Predicate___MaxLen___Predicate_func__function__lambda__at_0x7fe608a7ba60__": {
-            "maxLength": 16,
-            "minLength": 1,
-            "title": "ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]",
-            "type": "string"
-        },
-        "ValidatedString_Annotated_str__MinLen__AfterValidator__AfterValidator__Annotated_TypeVar__Predicate___MaxLen___Predicate_func__function__lambda__at_0x7fe608d8ba60__": {
-            "maxLength": 16,
+        "ValidatedString_Annotated_str__MinLen__AfterValidator__AfterValidator__Annotated_TypeVar__Predicate___MaxLen__": {
+            "maxLength": 32,
             "minLength": 1,
             "title": "ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]",
             "type": "string"
@@ -2125,18 +2100,6 @@
                 }
             ]
         },
-        "bioimageio__spec___internal__validated_string__ValidatedString_Annotated_str__MinLen__AfterValidator__AfterValidator__Annotated_TypeVar__Predicate___MaxLen____1": {
-            "maxLength": 32,
-            "minLength": 1,
-            "title": "ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]",
-            "type": "string"
-        },
-        "bioimageio__spec___internal__validated_string__ValidatedString_Annotated_str__MinLen__AfterValidator__AfterValidator__Annotated_TypeVar__Predicate___MaxLen____2": {
-            "maxLength": 16,
-            "minLength": 1,
-            "title": "ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]",
-            "type": "string"
-        },
         "bioimageio__spec__application__v0_2__ApplicationDescr": {
             "additionalProperties": false,
             "description": "Bioimage.io description of an application.",
@@ -6355,7 +6318,7 @@
                 "id": {
                     "allOf": [
                         {
-                            "$ref": "#/$defs/bioimageio__spec___internal__validated_string__ValidatedString_Annotated_str__MinLen__AfterValidator__AfterValidator__Annotated_TypeVar__Predicate___MaxLen____1"
+                            "$ref": "#/$defs/ValidatedString_Annotated_str__MinLen__AfterValidator__AfterValidator__Annotated_TypeVar__Predicate___MaxLen__"
                         }
                     ],
                     "default": "input"
@@ -6918,7 +6881,7 @@
                             "$ref": "#/$defs/Datetime"
                         }
                     ],
-                    "default": "2024-03-13T14:32:41.745321"
+                    "default": "2024-03-14T14:46:39.928277"
                 },
                 "training_data": {
                     "anyOf": [
@@ -7045,7 +7008,7 @@
                 "id": {
                     "allOf": [
                         {
-                            "$ref": "#/$defs/bioimageio__spec___internal__validated_string__ValidatedString_Annotated_str__MinLen__AfterValidator__AfterValidator__Annotated_TypeVar__Predicate___MaxLen____1"
+                            "$ref": "#/$defs/ValidatedString_Annotated_str__MinLen__AfterValidator__AfterValidator__Annotated_TypeVar__Predicate___MaxLen__"
                         }
                     ],
                     "default": "output"
@@ -7328,7 +7291,7 @@
                 "axis": {
                     "anyOf": [
                         {
-                            "$ref": "#/$defs/ValidatedString_Annotated_str__MinLen__AfterValidator__AfterValidator__Annotated_TypeVar__Predicate___MaxLen___Predicate_func__function__lambda__at_0x7fe608d8ba60__"
+                            "type": "string"
                         },
                         {
                             "type": "null"
@@ -7337,7 +7300,8 @@
                     "default": null,
                     "examples": [
                         "channel"
-                    ]
+                    ],
+                    "title": "Axis"
                 },
                 "gain": {
                     "anyOf": [
@@ -7399,13 +7363,13 @@
             "description": "Scale a tensor's data distribution to match another tensor's mean/std.\n`out  = (tensor - mean) / (std + eps) * (ref_std + eps) + ref_mean.`",
             "properties": {
                 "reference_tensor": {
-                    "$ref": "#/$defs/bioimageio__spec___internal__validated_string__ValidatedString_Annotated_str__MinLen__AfterValidator__AfterValidator__Annotated_TypeVar__Predicate___MaxLen____1"
+                    "$ref": "#/$defs/ValidatedString_Annotated_str__MinLen__AfterValidator__AfterValidator__Annotated_TypeVar__Predicate___MaxLen__"
                 },
                 "axes": {
                     "anyOf": [
                         {
                             "items": {
-                                "$ref": "#/$defs/bioimageio__spec___internal__validated_string__ValidatedString_Annotated_str__MinLen__AfterValidator__AfterValidator__Annotated_TypeVar__Predicate___MaxLen____2"
+                                "type": "string"
                             },
                             "type": "array"
                         },
@@ -7463,7 +7427,7 @@
                     "anyOf": [
                         {
                             "items": {
-                                "$ref": "#/$defs/bioimageio__spec___internal__validated_string__ValidatedString_Annotated_str__MinLen__AfterValidator__AfterValidator__Annotated_TypeVar__Predicate___MaxLen____2"
+                                "type": "string"
                             },
                             "type": "array"
                         },
@@ -7505,7 +7469,7 @@
                 "reference_tensor": {
                     "anyOf": [
                         {
-                            "$ref": "#/$defs/bioimageio__spec___internal__validated_string__ValidatedString_Annotated_str__MinLen__AfterValidator__AfterValidator__Annotated_TypeVar__Predicate___MaxLen____1"
+                            "$ref": "#/$defs/ValidatedString_Annotated_str__MinLen__AfterValidator__AfterValidator__Annotated_TypeVar__Predicate___MaxLen__"
                         },
                         {
                             "type": "null"
@@ -7892,7 +7856,7 @@
                     "anyOf": [
                         {
                             "items": {
-                                "$ref": "#/$defs/bioimageio__spec___internal__validated_string__ValidatedString_Annotated_str__MinLen__AfterValidator__AfterValidator__Annotated_TypeVar__Predicate___MaxLen____2"
+                                "type": "string"
                             },
                             "type": "array"
                         },
diff --git a/bioimageio_schema_v0-5-0post2.json b/bioimageio_schema_v0-5-0post2.json
index 4ffa1bce0..94cfa921a 100644
--- a/bioimageio_schema_v0-5-0post2.json
+++ b/bioimageio_schema_v0-5-0post2.json
@@ -231,12 +231,9 @@
             "additionalProperties": false,
             "properties": {
                 "id": {
-                    "allOf": [
-                        {
-                            "$ref": "#/$defs/ValidatedString_Annotated_str__MinLen__AfterValidator__AfterValidator__Annotated_TypeVar__Predicate___MaxLen___Predicate_func__function__lambda__at_0x7fe608a7ba60__"
-                        }
-                    ],
-                    "default": "batch"
+                    "default": "batch",
+                    "title": "Id",
+                    "type": "string"
                 },
                 "description": {
                     "default": "",
@@ -283,12 +280,9 @@
             "additionalProperties": false,
             "properties": {
                 "id": {
-                    "allOf": [
-                        {
-                            "$ref": "#/$defs/ValidatedString_Annotated_str__MinLen__AfterValidator__AfterValidator__Annotated_TypeVar__Predicate___MaxLen___Predicate_func__function__lambda__at_0x7fe608d8ba60__"
-                        }
-                    ],
-                    "default": "channel"
+                    "default": "channel",
+                    "title": "Id",
+                    "type": "string"
                 },
                 "description": {
                     "default": "",
@@ -570,7 +564,7 @@
                 "axis": {
                     "anyOf": [
                         {
-                            "$ref": "#/$defs/ValidatedString_Annotated_str__MinLen__AfterValidator__AfterValidator__Annotated_TypeVar__Predicate___MaxLen___Predicate_func__function__lambda__at_0x7fe608d8ba60__"
+                            "type": "string"
                         },
                         {
                             "type": "null"
@@ -580,7 +574,8 @@
                     "examples": [
                         "channel",
                         "index"
-                    ]
+                    ],
+                    "title": "Axis"
                 }
             },
             "required": [
@@ -645,12 +640,9 @@
             "additionalProperties": false,
             "properties": {
                 "id": {
-                    "allOf": [
-                        {
-                            "$ref": "#/$defs/ValidatedString_Annotated_str__MinLen__AfterValidator__AfterValidator__Annotated_TypeVar__Predicate___MaxLen___Predicate_func__function__lambda__at_0x7fe608d8ba60__"
-                        }
-                    ],
-                    "default": "index"
+                    "default": "index",
+                    "title": "Id",
+                    "type": "string"
                 },
                 "description": {
                     "default": "",
@@ -1560,10 +1552,11 @@
             "description": "A tensor axis size (extent in pixels/frames) defined in relation to a reference axis.\n\n`axis.size = reference.size * reference.scale / axis.scale + offset`\n\nnote:\n1. The axis and the referenced axis need to have the same unit (or no unit).\n2. Batch axes may not be referenced.\n3. Fractions are rounded down.\n\nexample:\nAn unisotropic input image of w*h=100*49 pixels depicts a phsical space of 200*196mm\u00b2.\nLet's assume that we want to express the image height h in relation to its width w\ninstead of only accepting input images of exactly 100*49 pixels\n(for example to express a range of valid image shapes by parametrizing w, see `ParameterizedSize`).\n\n>>> w = SpaceInputAxis(id=AxisId(\"w\"), size=100, unit=\"millimeter\", scale=2)\n>>> h = SpaceInputAxis(\n...     id=AxisId(\"h\"),\n...     size=SizeReference(tensor_id=TensorId(\"input\"), axis_id=AxisId(\"w\"), offset=-1),\n...     unit=\"millimeter\",\n...     scale=4,\n... )\n>>> print(h.size.compute(h, w))\n49\n\n-> h = w * w.scale / h.scale + offset = 100 * 2mm / 4mm - 1 = 49",
             "properties": {
                 "tensor_id": {
-                    "$ref": "#/$defs/bioimageio__spec___internal__validated_string__ValidatedString_Annotated_str__MinLen__AfterValidator__AfterValidator__Annotated_TypeVar__Predicate___MaxLen____1"
+                    "$ref": "#/$defs/ValidatedString_Annotated_str__MinLen__AfterValidator__AfterValidator__Annotated_TypeVar__Predicate___MaxLen__"
                 },
                 "axis_id": {
-                    "$ref": "#/$defs/bioimageio__spec___internal__validated_string__ValidatedString_Annotated_str__MinLen__AfterValidator__AfterValidator__Annotated_TypeVar__Predicate___MaxLen____2"
+                    "title": "Axis Id",
+                    "type": "string"
                 },
                 "offset": {
                     "default": 0,
@@ -1582,17 +1575,14 @@
             "additionalProperties": false,
             "properties": {
                 "id": {
-                    "allOf": [
-                        {
-                            "$ref": "#/$defs/ValidatedString_Annotated_str__MinLen__AfterValidator__AfterValidator__Annotated_TypeVar__Predicate___MaxLen___Predicate_func__function__lambda__at_0x7fe608d8ba60__"
-                        }
-                    ],
                     "default": "x",
                     "examples": [
                         "x",
                         "y",
                         "z"
-                    ]
+                    ],
+                    "title": "Id",
+                    "type": "string"
                 },
                 "description": {
                     "default": "",
@@ -1695,17 +1685,14 @@
                     "type": "integer"
                 },
                 "id": {
-                    "allOf": [
-                        {
-                            "$ref": "#/$defs/ValidatedString_Annotated_str__MinLen__AfterValidator__AfterValidator__Annotated_TypeVar__Predicate___MaxLen___Predicate_func__function__lambda__at_0x7fe608d8ba60__"
-                        }
-                    ],
                     "default": "x",
                     "examples": [
                         "x",
                         "y",
                         "z"
-                    ]
+                    ],
+                    "title": "Id",
+                    "type": "string"
                 },
                 "description": {
                     "default": "",
@@ -1802,12 +1789,9 @@
             "additionalProperties": false,
             "properties": {
                 "id": {
-                    "allOf": [
-                        {
-                            "$ref": "#/$defs/ValidatedString_Annotated_str__MinLen__AfterValidator__AfterValidator__Annotated_TypeVar__Predicate___MaxLen___Predicate_func__function__lambda__at_0x7fe608d8ba60__"
-                        }
-                    ],
-                    "default": "time"
+                    "default": "time",
+                    "title": "Id",
+                    "type": "string"
                 },
                 "description": {
                     "default": "",
@@ -1907,12 +1891,9 @@
                     "type": "integer"
                 },
                 "id": {
-                    "allOf": [
-                        {
-                            "$ref": "#/$defs/ValidatedString_Annotated_str__MinLen__AfterValidator__AfterValidator__Annotated_TypeVar__Predicate___MaxLen___Predicate_func__function__lambda__at_0x7fe608d8ba60__"
-                        }
-                    ],
-                    "default": "time"
+                    "default": "time",
+                    "title": "Id",
+                    "type": "string"
                 },
                 "description": {
                     "default": "",
@@ -2043,14 +2024,8 @@
             "title": "ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate]]]",
             "type": "string"
         },
-        "ValidatedString_Annotated_str__MinLen__AfterValidator__AfterValidator__Annotated_TypeVar__Predicate___MaxLen___Predicate_func__function__lambda__at_0x7fe608a7ba60__": {
-            "maxLength": 16,
-            "minLength": 1,
-            "title": "ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]",
-            "type": "string"
-        },
-        "ValidatedString_Annotated_str__MinLen__AfterValidator__AfterValidator__Annotated_TypeVar__Predicate___MaxLen___Predicate_func__function__lambda__at_0x7fe608d8ba60__": {
-            "maxLength": 16,
+        "ValidatedString_Annotated_str__MinLen__AfterValidator__AfterValidator__Annotated_TypeVar__Predicate___MaxLen__": {
+            "maxLength": 32,
             "minLength": 1,
             "title": "ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]",
             "type": "string"
@@ -2125,18 +2100,6 @@
                 }
             ]
         },
-        "bioimageio__spec___internal__validated_string__ValidatedString_Annotated_str__MinLen__AfterValidator__AfterValidator__Annotated_TypeVar__Predicate___MaxLen____1": {
-            "maxLength": 32,
-            "minLength": 1,
-            "title": "ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]",
-            "type": "string"
-        },
-        "bioimageio__spec___internal__validated_string__ValidatedString_Annotated_str__MinLen__AfterValidator__AfterValidator__Annotated_TypeVar__Predicate___MaxLen____2": {
-            "maxLength": 16,
-            "minLength": 1,
-            "title": "ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]",
-            "type": "string"
-        },
         "bioimageio__spec__application__v0_2__ApplicationDescr": {
             "additionalProperties": false,
             "description": "Bioimage.io description of an application.",
@@ -6355,7 +6318,7 @@
                 "id": {
                     "allOf": [
                         {
-                            "$ref": "#/$defs/bioimageio__spec___internal__validated_string__ValidatedString_Annotated_str__MinLen__AfterValidator__AfterValidator__Annotated_TypeVar__Predicate___MaxLen____1"
+                            "$ref": "#/$defs/ValidatedString_Annotated_str__MinLen__AfterValidator__AfterValidator__Annotated_TypeVar__Predicate___MaxLen__"
                         }
                     ],
                     "default": "input"
@@ -6918,7 +6881,7 @@
                             "$ref": "#/$defs/Datetime"
                         }
                     ],
-                    "default": "2024-03-13T14:32:41.745321"
+                    "default": "2024-03-14T14:46:39.928277"
                 },
                 "training_data": {
                     "anyOf": [
@@ -7045,7 +7008,7 @@
                 "id": {
                     "allOf": [
                         {
-                            "$ref": "#/$defs/bioimageio__spec___internal__validated_string__ValidatedString_Annotated_str__MinLen__AfterValidator__AfterValidator__Annotated_TypeVar__Predicate___MaxLen____1"
+                            "$ref": "#/$defs/ValidatedString_Annotated_str__MinLen__AfterValidator__AfterValidator__Annotated_TypeVar__Predicate___MaxLen__"
                         }
                     ],
                     "default": "output"
@@ -7328,7 +7291,7 @@
                 "axis": {
                     "anyOf": [
                         {
-                            "$ref": "#/$defs/ValidatedString_Annotated_str__MinLen__AfterValidator__AfterValidator__Annotated_TypeVar__Predicate___MaxLen___Predicate_func__function__lambda__at_0x7fe608d8ba60__"
+                            "type": "string"
                         },
                         {
                             "type": "null"
@@ -7337,7 +7300,8 @@
                     "default": null,
                     "examples": [
                         "channel"
-                    ]
+                    ],
+                    "title": "Axis"
                 },
                 "gain": {
                     "anyOf": [
@@ -7399,13 +7363,13 @@
             "description": "Scale a tensor's data distribution to match another tensor's mean/std.\n`out  = (tensor - mean) / (std + eps) * (ref_std + eps) + ref_mean.`",
             "properties": {
                 "reference_tensor": {
-                    "$ref": "#/$defs/bioimageio__spec___internal__validated_string__ValidatedString_Annotated_str__MinLen__AfterValidator__AfterValidator__Annotated_TypeVar__Predicate___MaxLen____1"
+                    "$ref": "#/$defs/ValidatedString_Annotated_str__MinLen__AfterValidator__AfterValidator__Annotated_TypeVar__Predicate___MaxLen__"
                 },
                 "axes": {
                     "anyOf": [
                         {
                             "items": {
-                                "$ref": "#/$defs/bioimageio__spec___internal__validated_string__ValidatedString_Annotated_str__MinLen__AfterValidator__AfterValidator__Annotated_TypeVar__Predicate___MaxLen____2"
+                                "type": "string"
                             },
                             "type": "array"
                         },
@@ -7463,7 +7427,7 @@
                     "anyOf": [
                         {
                             "items": {
-                                "$ref": "#/$defs/bioimageio__spec___internal__validated_string__ValidatedString_Annotated_str__MinLen__AfterValidator__AfterValidator__Annotated_TypeVar__Predicate___MaxLen____2"
+                                "type": "string"
                             },
                             "type": "array"
                         },
@@ -7505,7 +7469,7 @@
                 "reference_tensor": {
                     "anyOf": [
                         {
-                            "$ref": "#/$defs/bioimageio__spec___internal__validated_string__ValidatedString_Annotated_str__MinLen__AfterValidator__AfterValidator__Annotated_TypeVar__Predicate___MaxLen____1"
+                            "$ref": "#/$defs/ValidatedString_Annotated_str__MinLen__AfterValidator__AfterValidator__Annotated_TypeVar__Predicate___MaxLen__"
                         },
                         {
                             "type": "null"
@@ -7892,7 +7856,7 @@
                     "anyOf": [
                         {
                             "items": {
-                                "$ref": "#/$defs/bioimageio__spec___internal__validated_string__ValidatedString_Annotated_str__MinLen__AfterValidator__AfterValidator__Annotated_TypeVar__Predicate___MaxLen____2"
+                                "type": "string"
                             },
                             "type": "array"
                         },
diff --git a/search.js b/search.js
index c18152425..c2bc6a864 100644
--- a/search.js
+++ b/search.js
@@ -1,6 +1,6 @@
 window.pdocSearch = (function(){
 /** elasticlunr - http://weixsong.github.io * Copyright (C) 2017 Oliver Nightingale * Copyright (C) 2017 Wei Song * MIT Licensed */!function(){function e(e){if(null===e||"object"!=typeof e)return e;var t=e.constructor();for(var n in e)e.hasOwnProperty(n)&&(t[n]=e[n]);return t}var t=function(e){var n=new t.Index;return n.pipeline.add(t.trimmer,t.stopWordFilter,t.stemmer),e&&e.call(n,n),n};t.version="0.9.5",lunr=t,t.utils={},t.utils.warn=function(e){return function(t){e.console&&console.warn&&console.warn(t)}}(this),t.utils.toString=function(e){return void 0===e||null===e?"":e.toString()},t.EventEmitter=function(){this.events={}},t.EventEmitter.prototype.addListener=function(){var e=Array.prototype.slice.call(arguments),t=e.pop(),n=e;if("function"!=typeof t)throw new TypeError("last argument must be a function");n.forEach(function(e){this.hasHandler(e)||(this.events[e]=[]),this.events[e].push(t)},this)},t.EventEmitter.prototype.removeListener=function(e,t){if(this.hasHandler(e)){var n=this.events[e].indexOf(t);-1!==n&&(this.events[e].splice(n,1),0==this.events[e].length&&delete this.events[e])}},t.EventEmitter.prototype.emit=function(e){if(this.hasHandler(e)){var t=Array.prototype.slice.call(arguments,1);this.events[e].forEach(function(e){e.apply(void 0,t)},this)}},t.EventEmitter.prototype.hasHandler=function(e){return e in this.events},t.tokenizer=function(e){if(!arguments.length||null===e||void 0===e)return[];if(Array.isArray(e)){var n=e.filter(function(e){return null===e||void 0===e?!1:!0});n=n.map(function(e){return t.utils.toString(e).toLowerCase()});var i=[];return n.forEach(function(e){var n=e.split(t.tokenizer.seperator);i=i.concat(n)},this),i}return e.toString().trim().toLowerCase().split(t.tokenizer.seperator)},t.tokenizer.defaultSeperator=/[\s\-]+/,t.tokenizer.seperator=t.tokenizer.defaultSeperator,t.tokenizer.setSeperator=function(e){null!==e&&void 0!==e&&"object"==typeof e&&(t.tokenizer.seperator=e)},t.tokenizer.resetSeperator=function(){t.tokenizer.seperator=t.tokenizer.defaultSeperator},t.tokenizer.getSeperator=function(){return t.tokenizer.seperator},t.Pipeline=function(){this._queue=[]},t.Pipeline.registeredFunctions={},t.Pipeline.registerFunction=function(e,n){n in t.Pipeline.registeredFunctions&&t.utils.warn("Overwriting existing registered function: "+n),e.label=n,t.Pipeline.registeredFunctions[n]=e},t.Pipeline.getRegisteredFunction=function(e){return e in t.Pipeline.registeredFunctions!=!0?null:t.Pipeline.registeredFunctions[e]},t.Pipeline.warnIfFunctionNotRegistered=function(e){var n=e.label&&e.label in this.registeredFunctions;n||t.utils.warn("Function is not registered with pipeline. This may cause problems when serialising the index.\n",e)},t.Pipeline.load=function(e){var n=new t.Pipeline;return e.forEach(function(e){var i=t.Pipeline.getRegisteredFunction(e);if(!i)throw new Error("Cannot load un-registered function: "+e);n.add(i)}),n},t.Pipeline.prototype.add=function(){var e=Array.prototype.slice.call(arguments);e.forEach(function(e){t.Pipeline.warnIfFunctionNotRegistered(e),this._queue.push(e)},this)},t.Pipeline.prototype.after=function(e,n){t.Pipeline.warnIfFunctionNotRegistered(n);var i=this._queue.indexOf(e);if(-1===i)throw new Error("Cannot find existingFn");this._queue.splice(i+1,0,n)},t.Pipeline.prototype.before=function(e,n){t.Pipeline.warnIfFunctionNotRegistered(n);var i=this._queue.indexOf(e);if(-1===i)throw new Error("Cannot find existingFn");this._queue.splice(i,0,n)},t.Pipeline.prototype.remove=function(e){var t=this._queue.indexOf(e);-1!==t&&this._queue.splice(t,1)},t.Pipeline.prototype.run=function(e){for(var t=[],n=e.length,i=this._queue.length,o=0;n>o;o++){for(var r=e[o],s=0;i>s&&(r=this._queue[s](r,o,e),void 0!==r&&null!==r);s++);void 0!==r&&null!==r&&t.push(r)}return t},t.Pipeline.prototype.reset=function(){this._queue=[]},t.Pipeline.prototype.get=function(){return this._queue},t.Pipeline.prototype.toJSON=function(){return this._queue.map(function(e){return t.Pipeline.warnIfFunctionNotRegistered(e),e.label})},t.Index=function(){this._fields=[],this._ref="id",this.pipeline=new t.Pipeline,this.documentStore=new t.DocumentStore,this.index={},this.eventEmitter=new t.EventEmitter,this._idfCache={},this.on("add","remove","update",function(){this._idfCache={}}.bind(this))},t.Index.prototype.on=function(){var e=Array.prototype.slice.call(arguments);return this.eventEmitter.addListener.apply(this.eventEmitter,e)},t.Index.prototype.off=function(e,t){return this.eventEmitter.removeListener(e,t)},t.Index.load=function(e){e.version!==t.version&&t.utils.warn("version mismatch: current "+t.version+" importing "+e.version);var n=new this;n._fields=e.fields,n._ref=e.ref,n.documentStore=t.DocumentStore.load(e.documentStore),n.pipeline=t.Pipeline.load(e.pipeline),n.index={};for(var i in e.index)n.index[i]=t.InvertedIndex.load(e.index[i]);return n},t.Index.prototype.addField=function(e){return this._fields.push(e),this.index[e]=new t.InvertedIndex,this},t.Index.prototype.setRef=function(e){return this._ref=e,this},t.Index.prototype.saveDocument=function(e){return this.documentStore=new t.DocumentStore(e),this},t.Index.prototype.addDoc=function(e,n){if(e){var n=void 0===n?!0:n,i=e[this._ref];this.documentStore.addDoc(i,e),this._fields.forEach(function(n){var o=this.pipeline.run(t.tokenizer(e[n]));this.documentStore.addFieldLength(i,n,o.length);var r={};o.forEach(function(e){e in r?r[e]+=1:r[e]=1},this);for(var s in r){var u=r[s];u=Math.sqrt(u),this.index[n].addToken(s,{ref:i,tf:u})}},this),n&&this.eventEmitter.emit("add",e,this)}},t.Index.prototype.removeDocByRef=function(e){if(e&&this.documentStore.isDocStored()!==!1&&this.documentStore.hasDoc(e)){var t=this.documentStore.getDoc(e);this.removeDoc(t,!1)}},t.Index.prototype.removeDoc=function(e,n){if(e){var n=void 0===n?!0:n,i=e[this._ref];this.documentStore.hasDoc(i)&&(this.documentStore.removeDoc(i),this._fields.forEach(function(n){var o=this.pipeline.run(t.tokenizer(e[n]));o.forEach(function(e){this.index[n].removeToken(e,i)},this)},this),n&&this.eventEmitter.emit("remove",e,this))}},t.Index.prototype.updateDoc=function(e,t){var t=void 0===t?!0:t;this.removeDocByRef(e[this._ref],!1),this.addDoc(e,!1),t&&this.eventEmitter.emit("update",e,this)},t.Index.prototype.idf=function(e,t){var n="@"+t+"/"+e;if(Object.prototype.hasOwnProperty.call(this._idfCache,n))return this._idfCache[n];var i=this.index[t].getDocFreq(e),o=1+Math.log(this.documentStore.length/(i+1));return this._idfCache[n]=o,o},t.Index.prototype.getFields=function(){return this._fields.slice()},t.Index.prototype.search=function(e,n){if(!e)return[];e="string"==typeof e?{any:e}:JSON.parse(JSON.stringify(e));var i=null;null!=n&&(i=JSON.stringify(n));for(var o=new t.Configuration(i,this.getFields()).get(),r={},s=Object.keys(e),u=0;u0&&t.push(e);for(var i in n)"docs"!==i&&"df"!==i&&this.expandToken(e+i,t,n[i]);return t},t.InvertedIndex.prototype.toJSON=function(){return{root:this.root}},t.Configuration=function(e,n){var e=e||"";if(void 0==n||null==n)throw new Error("fields should not be null");this.config={};var i;try{i=JSON.parse(e),this.buildUserConfig(i,n)}catch(o){t.utils.warn("user configuration parse failed, will use default configuration"),this.buildDefaultConfig(n)}},t.Configuration.prototype.buildDefaultConfig=function(e){this.reset(),e.forEach(function(e){this.config[e]={boost:1,bool:"OR",expand:!1}},this)},t.Configuration.prototype.buildUserConfig=function(e,n){var i="OR",o=!1;if(this.reset(),"bool"in e&&(i=e.bool||i),"expand"in e&&(o=e.expand||o),"fields"in e)for(var r in e.fields)if(n.indexOf(r)>-1){var s=e.fields[r],u=o;void 0!=s.expand&&(u=s.expand),this.config[r]={boost:s.boost||0===s.boost?s.boost:1,bool:s.bool||i,expand:u}}else t.utils.warn("field name in user configuration not found in index instance fields");else this.addAllFields2UserConfig(i,o,n)},t.Configuration.prototype.addAllFields2UserConfig=function(e,t,n){n.forEach(function(n){this.config[n]={boost:1,bool:e,expand:t}},this)},t.Configuration.prototype.get=function(){return this.config},t.Configuration.prototype.reset=function(){this.config={}},lunr.SortedSet=function(){this.length=0,this.elements=[]},lunr.SortedSet.load=function(e){var t=new this;return t.elements=e,t.length=e.length,t},lunr.SortedSet.prototype.add=function(){var e,t;for(e=0;e1;){if(r===e)return o;e>r&&(t=o),r>e&&(n=o),i=n-t,o=t+Math.floor(i/2),r=this.elements[o]}return r===e?o:-1},lunr.SortedSet.prototype.locationFor=function(e){for(var t=0,n=this.elements.length,i=n-t,o=t+Math.floor(i/2),r=this.elements[o];i>1;)e>r&&(t=o),r>e&&(n=o),i=n-t,o=t+Math.floor(i/2),r=this.elements[o];return r>e?o:e>r?o+1:void 0},lunr.SortedSet.prototype.intersect=function(e){for(var t=new lunr.SortedSet,n=0,i=0,o=this.length,r=e.length,s=this.elements,u=e.elements;;){if(n>o-1||i>r-1)break;s[n]!==u[i]?s[n]u[i]&&i++:(t.add(s[n]),n++,i++)}return t},lunr.SortedSet.prototype.clone=function(){var e=new lunr.SortedSet;return e.elements=this.toArray(),e.length=e.elements.length,e},lunr.SortedSet.prototype.union=function(e){var t,n,i;this.length>=e.length?(t=this,n=e):(t=e,n=this),i=t.clone();for(var o=0,r=n.toArray();o
    \n"}, "bioimageio.spec._internal.common_nodes": {"fullname": "bioimageio.spec._internal.common_nodes", "modulename": "bioimageio.spec._internal.common_nodes", "kind": "module", "doc": "
    \n"}, "bioimageio.spec._internal.common_nodes.StringNode": {"fullname": "bioimageio.spec._internal.common_nodes.StringNode", "modulename": "bioimageio.spec._internal.common_nodes", "qualname": "StringNode", "kind": "class", "doc": "
    deprecated! don't use for new spec fields!
    \n", "bases": "collections.UserString, abc.ABC"}, "bioimageio.spec._internal.common_nodes.StringNode.__init__": {"fullname": "bioimageio.spec._internal.common_nodes.StringNode.__init__", "modulename": "bioimageio.spec._internal.common_nodes", "qualname": "StringNode.__init__", "kind": "function", "doc": "
    \n", "signature": "(seq: object)"}, "bioimageio.spec._internal.common_nodes.StringNode.model_fields": {"fullname": "bioimageio.spec._internal.common_nodes.StringNode.model_fields", "modulename": "bioimageio.spec._internal.common_nodes", "qualname": "StringNode.model_fields", "kind": "variable", "doc": "
    \n"}, "bioimageio.spec._internal.common_nodes.CArgs": {"fullname": "bioimageio.spec._internal.common_nodes.CArgs", "modulename": "bioimageio.spec._internal.common_nodes", "qualname": "CArgs", "kind": "variable", "doc": "
    \n", "default_value": "CArgs"}, "bioimageio.spec._internal.common_nodes.Converter": {"fullname": "bioimageio.spec._internal.common_nodes.Converter", "modulename": "bioimageio.spec._internal.common_nodes", "qualname": "Converter", "kind": "class", "doc": "
    Abstract base class for generic types.
    \n\n
    On Python 3.12 and newer, generic classes implicitly inherit from\nGeneric when they declare a parameter list after the class's name::
    \n\n
    class Mapping[KT, VT]:\n    def __getitem__(self, key: KT) -> VT:\n        ...\n    # Etc.\n
    \n\n
    On older versions of Python, however, generic classes have to\nexplicitly inherit from Generic.
    \n\n
    After a class has been declared to be generic, it can then be used as\nfollows::
    \n\n
    def lookup_name[KT, VT](mapping: Mapping[KT, VT], key: KT, default: VT) -> VT:\n    try:\n        return mapping[key]\n    except KeyError:\n        return default\n
    \n", "bases": "typing.Generic[~SRC, ~TGT, typing.Unpack[CArgs]], abc.ABC"}, "bioimageio.spec._internal.common_nodes.Converter.src": {"fullname": "bioimageio.spec._internal.common_nodes.Converter.src", "modulename": "bioimageio.spec._internal.common_nodes", "qualname": "Converter.src", "kind": "variable", "doc": "
    \n", "annotation": ": Final[Type[~SRC]]"}, "bioimageio.spec._internal.common_nodes.Converter.tgt": {"fullname": "bioimageio.spec._internal.common_nodes.Converter.tgt", "modulename": "bioimageio.spec._internal.common_nodes", "qualname": "Converter.tgt", "kind": "variable", "doc": "
    \n", "annotation": ": Final[Type[~TGT]]"}, "bioimageio.spec._internal.common_nodes.Converter.convert": {"fullname": "bioimageio.spec._internal.common_nodes.Converter.convert", "modulename": "bioimageio.spec._internal.common_nodes", "qualname": "Converter.convert", "kind": "function", "doc": "
    convert source node
    \n\n
    Args:\n    source: A bioimageio description node
    \n\n
    Raises:\n    ValidationError: conversion failed
    \n", "signature": "(self, source: ~SRC, /, *args: Unpack[CArgs]) -> ~TGT:", "funcdef": "def"}, "bioimageio.spec._internal.common_nodes.Converter.convert_as_dict": {"fullname": "bioimageio.spec._internal.common_nodes.Converter.convert_as_dict", "modulename": "bioimageio.spec._internal.common_nodes", "qualname": "Converter.convert_as_dict", "kind": "function", "doc": "
    \n", "signature": "(self, source: ~SRC, /, *args: Unpack[CArgs]) -> Dict[str, Any]:", "funcdef": "def"}, "bioimageio.spec._internal.common_nodes.NodeWithExplicitlySetFields": {"fullname": "bioimageio.spec._internal.common_nodes.NodeWithExplicitlySetFields", "modulename": "bioimageio.spec._internal.common_nodes", "qualname": "NodeWithExplicitlySetFields", "kind": "class", "doc": "
    Subpart of a resource description
    \n", "bases": "bioimageio.spec._internal.node.Node"}, "bioimageio.spec._internal.common_nodes.NodeWithExplicitlySetFields.fields_to_set_explicitly": {"fullname": "bioimageio.spec._internal.common_nodes.NodeWithExplicitlySetFields.fields_to_set_explicitly", "modulename": "bioimageio.spec._internal.common_nodes", "qualname": "NodeWithExplicitlySetFields.fields_to_set_explicitly", "kind": "variable", "doc": "
    set set these fields explicitly with their default value if they are not set,\nsuch that they are always included even when dumping with 'exlude_unset'
    \n", "annotation": ": ClassVar[FrozenSet[LiteralString]]", "default_value": "frozenset()"}, "bioimageio.spec._internal.common_nodes.NodeWithExplicitlySetFields.set_fields_explicitly": {"fullname": "bioimageio.spec._internal.common_nodes.NodeWithExplicitlySetFields.set_fields_explicitly", "modulename": "bioimageio.spec._internal.common_nodes", "qualname": "NodeWithExplicitlySetFields.set_fields_explicitly", "kind": "function", "doc": "
    \n", "signature": "(cls, data: Union[Any, Dict[str, Any]]) -> Union[Any, Dict[str, Any]]:", "funcdef": "def"}, "bioimageio.spec._internal.common_nodes.NodeWithExplicitlySetFields.model_config": {"fullname": "bioimageio.spec._internal.common_nodes.NodeWithExplicitlySetFields.model_config", "modulename": "bioimageio.spec._internal.common_nodes", "qualname": "NodeWithExplicitlySetFields.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec._internal.common_nodes.NodeWithExplicitlySetFields.model_fields": {"fullname": "bioimageio.spec._internal.common_nodes.NodeWithExplicitlySetFields.model_fields", "modulename": "bioimageio.spec._internal.common_nodes", "qualname": "NodeWithExplicitlySetFields.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec._internal.common_nodes.NodeWithExplicitlySetFields.model_computed_fields": {"fullname": "bioimageio.spec._internal.common_nodes.NodeWithExplicitlySetFields.model_computed_fields", "modulename": "bioimageio.spec._internal.common_nodes", "qualname": "NodeWithExplicitlySetFields.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec._internal.common_nodes.ResourceDescrBase": {"fullname": "bioimageio.spec._internal.common_nodes.ResourceDescrBase", "modulename": "bioimageio.spec._internal.common_nodes", "qualname": "ResourceDescrBase", "kind": "class", "doc": "
    base class for all resource descriptions
    \n", "bases": "NodeWithExplicitlySetFields, abc.ABC, _ResourceDescrBaseAbstractFieldsProtocol"}, "bioimageio.spec._internal.common_nodes.ResourceDescrBase.fields_to_set_explicitly": {"fullname": "bioimageio.spec._internal.common_nodes.ResourceDescrBase.fields_to_set_explicitly", "modulename": "bioimageio.spec._internal.common_nodes", "qualname": "ResourceDescrBase.fields_to_set_explicitly", "kind": "variable", "doc": "
    set set these fields explicitly with their default value if they are not set,\nsuch that they are always included even when dumping with 'exlude_unset'
    \n", "annotation": ": ClassVar[FrozenSet[LiteralString]]", "default_value": "frozenset({'type', 'format_version'})"}, "bioimageio.spec._internal.common_nodes.ResourceDescrBase.implemented_format_version": {"fullname": "bioimageio.spec._internal.common_nodes.ResourceDescrBase.implemented_format_version", "modulename": "bioimageio.spec._internal.common_nodes", "qualname": "ResourceDescrBase.implemented_format_version", "kind": "variable", "doc": "
    \n", "annotation": ": ClassVar[str]"}, "bioimageio.spec._internal.common_nodes.ResourceDescrBase.implemented_format_version_tuple": {"fullname": "bioimageio.spec._internal.common_nodes.ResourceDescrBase.implemented_format_version_tuple", "modulename": "bioimageio.spec._internal.common_nodes", "qualname": "ResourceDescrBase.implemented_format_version_tuple", "kind": "variable", "doc": "
    \n", "annotation": ": ClassVar[Tuple[int, int, int]]"}, "bioimageio.spec._internal.common_nodes.ResourceDescrBase.validation_summary": {"fullname": "bioimageio.spec._internal.common_nodes.ResourceDescrBase.validation_summary", "modulename": "bioimageio.spec._internal.common_nodes", "qualname": "ResourceDescrBase.validation_summary", "kind": "variable", "doc": "
    \n", "annotation": ": bioimageio.spec.summary.ValidationSummary"}, "bioimageio.spec._internal.common_nodes.ResourceDescrBase.root": {"fullname": "bioimageio.spec._internal.common_nodes.ResourceDescrBase.root", "modulename": "bioimageio.spec._internal.common_nodes", "qualname": "ResourceDescrBase.root", "kind": "variable", "doc": "
    \n", "annotation": ": Union[bioimageio.spec._internal.url.HttpUrl, Annotated[pathlib.Path, PathType(path_type='dir')]]"}, "bioimageio.spec._internal.common_nodes.ResourceDescrBase.load": {"fullname": "bioimageio.spec._internal.common_nodes.ResourceDescrBase.load", "modulename": "bioimageio.spec._internal.common_nodes", "qualname": "ResourceDescrBase.load", "kind": "function", "doc": "
    \n", "signature": "(\tcls,\tdata: Dict[str, YamlValue],\tcontext: Optional[bioimageio.spec._internal.validation_context.ValidationContext] = None) -> Union[Self, bioimageio.spec._internal.common_nodes.InvalidDescr]:", "funcdef": "def"}, "bioimageio.spec._internal.common_nodes.ResourceDescrBase.model_config": {"fullname": "bioimageio.spec._internal.common_nodes.ResourceDescrBase.model_config", "modulename": "bioimageio.spec._internal.common_nodes", "qualname": "ResourceDescrBase.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec._internal.common_nodes.ResourceDescrBase.model_post_init": {"fullname": "bioimageio.spec._internal.common_nodes.ResourceDescrBase.model_post_init", "modulename": "bioimageio.spec._internal.common_nodes", "qualname": "ResourceDescrBase.model_post_init", "kind": "function", "doc": "
    This function is meant to behave like a BaseModel method to initialise private attributes.
    \n\n
    It takes context as an argument since that's what pydantic-core passes when calling it.
    \n\n
    Args:\n    self: The BaseModel instance.\n    __context: The context.
    \n", "signature": "(self: pydantic.main.BaseModel, __context: Any) -> None:", "funcdef": "def"}, "bioimageio.spec._internal.common_nodes.ResourceDescrBase.model_fields": {"fullname": "bioimageio.spec._internal.common_nodes.ResourceDescrBase.model_fields", "modulename": "bioimageio.spec._internal.common_nodes", "qualname": "ResourceDescrBase.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec._internal.common_nodes.ResourceDescrBase.model_computed_fields": {"fullname": "bioimageio.spec._internal.common_nodes.ResourceDescrBase.model_computed_fields", "modulename": "bioimageio.spec._internal.common_nodes", "qualname": "ResourceDescrBase.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec._internal.common_nodes.InvalidDescr": {"fullname": "bioimageio.spec._internal.common_nodes.InvalidDescr", "modulename": "bioimageio.spec._internal.common_nodes", "qualname": "InvalidDescr", "kind": "class", "doc": "
    base class for all resource descriptions
    \n", "bases": "ResourceDescrBase"}, "bioimageio.spec._internal.common_nodes.InvalidDescr.type": {"fullname": "bioimageio.spec._internal.common_nodes.InvalidDescr.type", "modulename": "bioimageio.spec._internal.common_nodes", "qualname": "InvalidDescr.type", "kind": "variable", "doc": "
    \n", "annotation": ": Any"}, "bioimageio.spec._internal.common_nodes.InvalidDescr.format_version": {"fullname": "bioimageio.spec._internal.common_nodes.InvalidDescr.format_version", "modulename": "bioimageio.spec._internal.common_nodes", "qualname": "InvalidDescr.format_version", "kind": "variable", "doc": "
    \n", "annotation": ": Any"}, "bioimageio.spec._internal.common_nodes.InvalidDescr.fields_to_set_explicitly": {"fullname": "bioimageio.spec._internal.common_nodes.InvalidDescr.fields_to_set_explicitly", "modulename": "bioimageio.spec._internal.common_nodes", "qualname": "InvalidDescr.fields_to_set_explicitly", "kind": "variable", "doc": "
    set set these fields explicitly with their default value if they are not set,\nsuch that they are always included even when dumping with 'exlude_unset'
    \n", "annotation": ": ClassVar[FrozenSet[LiteralString]]", "default_value": "frozenset()"}, "bioimageio.spec._internal.common_nodes.InvalidDescr.implemented_format_version": {"fullname": "bioimageio.spec._internal.common_nodes.InvalidDescr.implemented_format_version", "modulename": "bioimageio.spec._internal.common_nodes", "qualname": "InvalidDescr.implemented_format_version", "kind": "variable", "doc": "
    \n", "annotation": ": ClassVar[str]", "default_value": "'unknown'"}, "bioimageio.spec._internal.common_nodes.InvalidDescr.implemented_format_version_tuple": {"fullname": "bioimageio.spec._internal.common_nodes.InvalidDescr.implemented_format_version_tuple", "modulename": "bioimageio.spec._internal.common_nodes", "qualname": "InvalidDescr.implemented_format_version_tuple", "kind": "variable", "doc": "
    \n", "annotation": ": ClassVar[Tuple[int, int, int]]", "default_value": "(0, 0, 0)"}, "bioimageio.spec._internal.common_nodes.InvalidDescr.model_config": {"fullname": "bioimageio.spec._internal.common_nodes.InvalidDescr.model_config", "modulename": "bioimageio.spec._internal.common_nodes", "qualname": "InvalidDescr.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'allow', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True, 'title': 'An invalid resource description'}"}, "bioimageio.spec._internal.common_nodes.InvalidDescr.model_fields": {"fullname": "bioimageio.spec._internal.common_nodes.InvalidDescr.model_fields", "modulename": "bioimageio.spec._internal.common_nodes", "qualname": "InvalidDescr.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'type': FieldInfo(annotation=Any, required=False, default='unknown'), 'format_version': FieldInfo(annotation=Any, required=False, default='unknown')}"}, "bioimageio.spec._internal.common_nodes.InvalidDescr.model_computed_fields": {"fullname": "bioimageio.spec._internal.common_nodes.InvalidDescr.model_computed_fields", "modulename": "bioimageio.spec._internal.common_nodes", "qualname": "InvalidDescr.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec._internal.common_nodes.KwargsNode": {"fullname": "bioimageio.spec._internal.common_nodes.KwargsNode", "modulename": "bioimageio.spec._internal.common_nodes", "qualname": "KwargsNode", "kind": "class", "doc": "
    Subpart of a resource description
    \n", "bases": "bioimageio.spec._internal.node.Node"}, "bioimageio.spec._internal.common_nodes.KwargsNode.get": {"fullname": "bioimageio.spec._internal.common_nodes.KwargsNode.get", "modulename": "bioimageio.spec._internal.common_nodes", "qualname": "KwargsNode.get", "kind": "function", "doc": "
    \n", "signature": "(self, item: str, default: Any = None) -> Any:", "funcdef": "def"}, "bioimageio.spec._internal.common_nodes.KwargsNode.model_config": {"fullname": "bioimageio.spec._internal.common_nodes.KwargsNode.model_config", "modulename": "bioimageio.spec._internal.common_nodes", "qualname": "KwargsNode.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec._internal.common_nodes.KwargsNode.model_fields": {"fullname": "bioimageio.spec._internal.common_nodes.KwargsNode.model_fields", "modulename": "bioimageio.spec._internal.common_nodes", "qualname": "KwargsNode.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec._internal.common_nodes.KwargsNode.model_computed_fields": {"fullname": "bioimageio.spec._internal.common_nodes.KwargsNode.model_computed_fields", "modulename": "bioimageio.spec._internal.common_nodes", "qualname": "KwargsNode.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec._internal.constants": {"fullname": "bioimageio.spec._internal.constants", "modulename": "bioimageio.spec._internal.constants", "kind": "module", "doc": "
    \n"}, "bioimageio.spec._internal.constants.DOI_REGEX": {"fullname": "bioimageio.spec._internal.constants.DOI_REGEX", "modulename": "bioimageio.spec._internal.constants", "qualname": "DOI_REGEX", "kind": "variable", "doc": "
    \n", "default_value": "'^10\\\\.[0-9]{4}.+$'"}, "bioimageio.spec._internal.constants.IN_PACKAGE_MESSAGE": {"fullname": "bioimageio.spec._internal.constants.IN_PACKAGE_MESSAGE", "modulename": "bioimageio.spec._internal.constants", "qualname": "IN_PACKAGE_MESSAGE", "kind": "variable", "doc": "
    DEPRECATED, use ImportantFileSource to indicate that a file source should be included in a package
    \n", "default_value": "'\u2208\ud83d\udce6 '"}, "bioimageio.spec._internal.constants.SHA256_HINT": {"fullname": "bioimageio.spec._internal.constants.SHA256_HINT", "modulename": "bioimageio.spec._internal.constants", "qualname": "SHA256_HINT", "kind": "variable", "doc": "
    \n", "default_value": ""You can drag and drop your file to this\\n[online tool](http://emn178.github.io/online-tools/sha256_checksum.html) to generate a SHA256 in your browser.\\nOr you can generate a SHA256 checksum with Python's `hashlib`,\\n[here is a codesnippet](https://gist.github.com/FynnBe/e64460463df89439cff218bbf59c1100).""}, "bioimageio.spec._internal.constants.SI_UNIT_REGEX": {"fullname": "bioimageio.spec._internal.constants.SI_UNIT_REGEX", "modulename": "bioimageio.spec._internal.constants", "qualname": "SI_UNIT_REGEX", "kind": "variable", "doc": "
    \n", "default_value": "'^(Q|R|Y|Z|E|P|T|G|M|k|h|da|d|c|m|\u00b5|n|p|f|a|z|y|r|q)?(m|g|s|A|K|mol|cd|Hz|N|Pa|J|W|C|V|F|\u03a9|S|Wb|T|H|lm|lx|Bq|Gy|Sv|kat|l|L)(\\\\^[+-]?[1-9]\\\\d*)?((\u00b7(Q|R|Y|Z|E|P|T|G|M|k|h|da|d|c|m|\u00b5|n|p|f|a|z|y|r|q)?(m|g|s|A|K|mol|cd|Hz|N|Pa|J|W|C|V|F|\u03a9|S|Wb|T|H|lm|lx|Bq|Gy|Sv|kat|l|L)(\\\\^[+-]?[1-9]\\\\d*)?)|(/(Q|R|Y|Z|E|P|T|G|M|k|h|da|d|c|m|\u00b5|n|p|f|a|z|y|r|q)?(m|g|s|A|K|mol|cd|Hz|N|Pa|J|W|C|V|F|\u03a9|S|Wb|T|H|lm|lx|Bq|Gy|Sv|kat|l|L)(\\\\^+?[1-9]\\\\d*)?))*$'"}, "bioimageio.spec._internal.constants.MinMax": {"fullname": "bioimageio.spec._internal.constants.MinMax", "modulename": "bioimageio.spec._internal.constants", "qualname": "MinMax", "kind": "class", "doc": "
    MinMax(min, max)
    \n", "bases": "typing.NamedTuple"}, "bioimageio.spec._internal.constants.MinMax.__init__": {"fullname": "bioimageio.spec._internal.constants.MinMax.__init__", "modulename": "bioimageio.spec._internal.constants", "qualname": "MinMax.__init__", "kind": "function", "doc": "
    Create new instance of MinMax(min, max)
    \n", "signature": "(\tmin: ForwardRef('Union[int, float]'),\tmax: ForwardRef('Union[int, float]'))"}, "bioimageio.spec._internal.constants.MinMax.min": {"fullname": "bioimageio.spec._internal.constants.MinMax.min", "modulename": "bioimageio.spec._internal.constants", "qualname": "MinMax.min", "kind": "variable", "doc": "
    Alias for field number 0
    \n", "annotation": ": Union[int, float]"}, "bioimageio.spec._internal.constants.MinMax.max": {"fullname": "bioimageio.spec._internal.constants.MinMax.max", "modulename": "bioimageio.spec._internal.constants", "qualname": "MinMax.max", "kind": "variable", "doc": "
    Alias for field number 1
    \n", "annotation": ": Union[int, float]"}, "bioimageio.spec._internal.constants.DTYPE_LIMITS": {"fullname": "bioimageio.spec._internal.constants.DTYPE_LIMITS", "modulename": "bioimageio.spec._internal.constants", "qualname": "DTYPE_LIMITS", "kind": "variable", "doc": "
    \n", "default_value": "mappingproxy({'float32': MinMax(min=-3.4028235e+38, max=3.4028235e+38), 'float64': MinMax(min=-1.7976931348623157e+308, max=1.7976931348623157e+308), 'uint8': MinMax(min=0, max=255), 'int8': MinMax(min=-128, max=127), 'uint16': MinMax(min=0, max=65535), 'int16': MinMax(min=-32768, max=32767), 'uint32': MinMax(min=0, max=4294967295), 'int32': MinMax(min=-2147483648, max=2147483647), 'uint64': MinMax(min=0, max=18446744073709551615), 'int64': MinMax(min=-9223372036854775808, max=9223372036854775807)})"}, "bioimageio.spec._internal.constants.KNOWN_GH_USERS": {"fullname": "bioimageio.spec._internal.constants.KNOWN_GH_USERS", "modulename": "bioimageio.spec._internal.constants", "qualname": "KNOWN_GH_USERS", "kind": "variable", "doc": "
    \n", "annotation": ": Set[str]", "default_value": "{'danifranco', 'jansanrom', 'lenkaback', 'ctr26', 'k-dominik', 'iarganda', 'fynnbe', 'pedgomgal1', 'githubuser2', 'ivanhcenalmor', 'carlosuc3m', 'esgomezm', 'aaitorg', 'bioimageiobot', 'clementcaporal', 'cfusterbarcelo', 'constantinpape', 'oeway', 'donglaiw'}"}, "bioimageio.spec._internal.constants.N_KNOWN_GH_USERS": {"fullname": "bioimageio.spec._internal.constants.N_KNOWN_GH_USERS", "modulename": "bioimageio.spec._internal.constants", "qualname": "N_KNOWN_GH_USERS", "kind": "variable", "doc": "
    \n", "default_value": "19"}, "bioimageio.spec._internal.constants.KNOWN_INVALID_GH_USERS": {"fullname": "bioimageio.spec._internal.constants.KNOWN_INVALID_GH_USERS", "modulename": "bioimageio.spec._internal.constants", "qualname": "KNOWN_INVALID_GH_USERS", "kind": "variable", "doc": "
    \n", "annotation": ": Set[str]", "default_value": "{'arratemunoz', 'lmescu'}"}, "bioimageio.spec._internal.constants.N_KNOWN_INVALID_GH_USERS": {"fullname": "bioimageio.spec._internal.constants.N_KNOWN_INVALID_GH_USERS", "modulename": "bioimageio.spec._internal.constants", "qualname": "N_KNOWN_INVALID_GH_USERS", "kind": "variable", "doc": "
    \n", "default_value": "2"}, "bioimageio.spec._internal.constants.VERSION": {"fullname": "bioimageio.spec._internal.constants.VERSION", "modulename": "bioimageio.spec._internal.constants", "qualname": "VERSION", "kind": "variable", "doc": "
    \n", "annotation": ": str", "default_value": "'0.5.0post2'"}, "bioimageio.spec._internal.constants.TAG_CATEGORIES": {"fullname": "bioimageio.spec._internal.constants.TAG_CATEGORIES", "modulename": "bioimageio.spec._internal.constants", "qualname": "TAG_CATEGORIES", "kind": "variable", "doc": "
    \n", "annotation": ": Mapping[str, Mapping[str, Sequence[str]]]", "default_value": "{'model': {'modality': ['electron-microscopy', 'cryo-electron-microscopy', 'fluorescence-light-microscopy', 'transmission-light-microscopy', 'super-resolution-microscopy', 'x-ray-microscopy', 'force-microscopy', 'high-content-imaging', 'whole-slide-imaging', 'other'], 'dims': ['2d', '3d', '2d-t', '3d-t'], 'content': ['cells', 'nuclei', 'extracellular-vesicles', 'tissue', 'plant', 'mitochondria', 'vasculature', 'cell-membrane', 'brain', 'whole-organism'], 'framework': ['tensorflow', 'pytorch', 'tensorflow.js'], 'software': ['ilastik', 'imagej', 'fiji', 'imjoy', 'deepimagej', 'n2v'], 'network': ['unet', 'densenet', 'resnet', 'inception', 'shufflenet'], 'task': ['semantic-segmentation', 'instance-segmentation', 'object-detection', 'image-classification', 'denoising', 'image-restoration', 'image-reconstruction', 'in-silico-labeling']}}"}, "bioimageio.spec._internal.docs_utils": {"fullname": "bioimageio.spec._internal.docs_utils", "modulename": "bioimageio.spec._internal.docs_utils", "kind": "module", "doc": "
    \n"}, "bioimageio.spec._internal.docs_utils.get_ref_url": {"fullname": "bioimageio.spec._internal.docs_utils.get_ref_url", "modulename": "bioimageio.spec._internal.docs_utils", "qualname": "get_ref_url", "kind": "function", "doc": "
    get github url with line range fragment to reference implementation from non-raw github file url
    \n\n
    example:
    \n\n
    \n
    >>> get_ref_url(\n...     "class",\n...     "Binarize",\n...     "https://github.com/bioimage-io/core-bioimage-io-python/blob/main/bioimageio/core/prediction_pipeline/_processing.py"\n... )\n'https://github.com/bioimage-io/core-bioimage-io-python/blob/main/bioimageio/core/prediction_pipeline/_processing.py#L120-L127'\n
    \n
    \n", "signature": "(\ttype_: Literal['class', 'function'],\tname: str,\tgithub_file_url: str) -> str:", "funcdef": "def"}, "bioimageio.spec._internal.field_validation": {"fullname": "bioimageio.spec._internal.field_validation", "modulename": "bioimageio.spec._internal.field_validation", "kind": "module", "doc": "
    \n"}, "bioimageio.spec._internal.field_validation.RestrictCharacters": {"fullname": "bioimageio.spec._internal.field_validation.RestrictCharacters", "modulename": "bioimageio.spec._internal.field_validation", "qualname": "RestrictCharacters", "kind": "class", "doc": "
    \n"}, "bioimageio.spec._internal.field_validation.RestrictCharacters.__init__": {"fullname": "bioimageio.spec._internal.field_validation.RestrictCharacters.__init__", "modulename": "bioimageio.spec._internal.field_validation", "qualname": "RestrictCharacters.__init__", "kind": "function", "doc": "
    \n", "signature": "(alphabet: str)"}, "bioimageio.spec._internal.field_validation.RestrictCharacters.alphabet": {"fullname": "bioimageio.spec._internal.field_validation.RestrictCharacters.alphabet", "modulename": "bioimageio.spec._internal.field_validation", "qualname": "RestrictCharacters.alphabet", "kind": "variable", "doc": "
    \n", "annotation": ": str"}, "bioimageio.spec._internal.field_validation.RestrictCharacters.validate": {"fullname": "bioimageio.spec._internal.field_validation.RestrictCharacters.validate", "modulename": "bioimageio.spec._internal.field_validation", "qualname": "RestrictCharacters.validate", "kind": "function", "doc": "
    \n", "signature": "(self, value: str) -> str:", "funcdef": "def"}, "bioimageio.spec._internal.field_validation.is_valid_yaml_leaf_value": {"fullname": "bioimageio.spec._internal.field_validation.is_valid_yaml_leaf_value", "modulename": "bioimageio.spec._internal.field_validation", "qualname": "is_valid_yaml_leaf_value", "kind": "function", "doc": "
    \n", "signature": "(value: Any) -> bool:", "funcdef": "def"}, "bioimageio.spec._internal.field_validation.is_valid_yaml_key": {"fullname": "bioimageio.spec._internal.field_validation.is_valid_yaml_key", "modulename": "bioimageio.spec._internal.field_validation", "qualname": "is_valid_yaml_key", "kind": "function", "doc": "
    \n", "signature": "(value: Union[Any, Sequence[Any]]) -> bool:", "funcdef": "def"}, "bioimageio.spec._internal.field_validation.is_valid_yaml_mapping": {"fullname": "bioimageio.spec._internal.field_validation.is_valid_yaml_mapping", "modulename": "bioimageio.spec._internal.field_validation", "qualname": "is_valid_yaml_mapping", "kind": "function", "doc": "
    \n", "signature": "(value: Union[Any, Mapping[Any, Any]]) -> bool:", "funcdef": "def"}, "bioimageio.spec._internal.field_validation.is_valid_yaml_sequence": {"fullname": "bioimageio.spec._internal.field_validation.is_valid_yaml_sequence", "modulename": "bioimageio.spec._internal.field_validation", "qualname": "is_valid_yaml_sequence", "kind": "function", "doc": "
    \n", "signature": "(value: Union[Any, Sequence[Any]]) -> bool:", "funcdef": "def"}, "bioimageio.spec._internal.field_validation.is_valid_yaml_value": {"fullname": "bioimageio.spec._internal.field_validation.is_valid_yaml_value", "modulename": "bioimageio.spec._internal.field_validation", "qualname": "is_valid_yaml_value", "kind": "function", "doc": "
    \n", "signature": "(value: Any) -> bool:", "funcdef": "def"}, "bioimageio.spec._internal.field_validation.validate_unique_entries": {"fullname": "bioimageio.spec._internal.field_validation.validate_unique_entries", "modulename": "bioimageio.spec._internal.field_validation", "qualname": "validate_unique_entries", "kind": "function", "doc": "
    \n", "signature": "(seq: Sequence[Hashable]):", "funcdef": "def"}, "bioimageio.spec._internal.field_validation.AfterValidator": {"fullname": "bioimageio.spec._internal.field_validation.AfterValidator", "modulename": "bioimageio.spec._internal.field_validation", "qualname": "AfterValidator", "kind": "class", "doc": "
    \n", "bases": "pydantic.functional_validators.AfterValidator"}, "bioimageio.spec._internal.field_validation.AfterValidator.__init__": {"fullname": "bioimageio.spec._internal.field_validation.AfterValidator.__init__", "modulename": "bioimageio.spec._internal.field_validation", "qualname": "AfterValidator.__init__", "kind": "function", "doc": "
    \n", "signature": "(\tfunc: 'core_schema.NoInfoValidatorFunction | core_schema.WithInfoValidatorFunction')"}, "bioimageio.spec._internal.field_validation.BeforeValidator": {"fullname": "bioimageio.spec._internal.field_validation.BeforeValidator", "modulename": "bioimageio.spec._internal.field_validation", "qualname": "BeforeValidator", "kind": "class", "doc": "
    \n", "bases": "pydantic.functional_validators.BeforeValidator"}, "bioimageio.spec._internal.field_validation.BeforeValidator.__init__": {"fullname": "bioimageio.spec._internal.field_validation.BeforeValidator.__init__", "modulename": "bioimageio.spec._internal.field_validation", "qualname": "BeforeValidator.__init__", "kind": "function", "doc": "
    \n", "signature": "(\tfunc: 'core_schema.NoInfoValidatorFunction | core_schema.WithInfoValidatorFunction')"}, "bioimageio.spec._internal.field_validation.Predicate": {"fullname": "bioimageio.spec._internal.field_validation.Predicate", "modulename": "bioimageio.spec._internal.field_validation", "qualname": "Predicate", "kind": "class", "doc": "
    \n", "bases": "annotated_types.Predicate"}, "bioimageio.spec._internal.field_validation.Predicate.__init__": {"fullname": "bioimageio.spec._internal.field_validation.Predicate.__init__", "modulename": "bioimageio.spec._internal.field_validation", "qualname": "Predicate.__init__", "kind": "function", "doc": "
    \n", "signature": "(func: Callable[[Any], bool])"}, "bioimageio.spec._internal.field_validation.validate_gh_user": {"fullname": "bioimageio.spec._internal.field_validation.validate_gh_user", "modulename": "bioimageio.spec._internal.field_validation", "qualname": "validate_gh_user", "kind": "function", "doc": "
    \n", "signature": "(username: str, hotfix_known_errorenous_names: bool = True) -> str:", "funcdef": "def"}, "bioimageio.spec._internal.field_warning": {"fullname": "bioimageio.spec._internal.field_warning", "modulename": "bioimageio.spec._internal.field_warning", "kind": "module", "doc": "
    \n"}, "bioimageio.spec._internal.field_warning.ValidatorFunction": {"fullname": "bioimageio.spec._internal.field_warning.ValidatorFunction", "modulename": "bioimageio.spec._internal.field_warning", "qualname": "ValidatorFunction", "kind": "variable", "doc": "
    \n", "default_value": "typing.Union[typing.Callable[[typing.Any], typing.Any], typing.Callable[[typing.Any, pydantic_core.core_schema.ValidationInfo], typing.Any]]"}, "bioimageio.spec._internal.field_warning.AnnotationMetaData": {"fullname": "bioimageio.spec._internal.field_warning.AnnotationMetaData", "modulename": "bioimageio.spec._internal.field_warning", "qualname": "AnnotationMetaData", "kind": "variable", "doc": "
    \n", "default_value": "typing.Union[annotated_types.BaseMetadata, annotated_types.GroupedMetadata]"}, "bioimageio.spec._internal.field_warning.warn": {"fullname": "bioimageio.spec._internal.field_warning.warn", "modulename": "bioimageio.spec._internal.field_warning", "qualname": "warn", "kind": "function", "doc": "
    treat a type or its annotation metadata as a warning condition
    \n", "signature": "(\ttyp: Union[annotated_types.BaseMetadata, annotated_types.GroupedMetadata, Any],\tmsg: LiteralString,\tseverity: Literal[20, 30, 35] = 30):", "funcdef": "def"}, "bioimageio.spec._internal.field_warning.call_validator_func": {"fullname": "bioimageio.spec._internal.field_warning.call_validator_func", "modulename": "bioimageio.spec._internal.field_warning", "qualname": "call_validator_func", "kind": "function", "doc": "
    \n", "signature": "(\tfunc: Union[pydantic.functional_validators._V2ValidatorClsMethod, Callable[[Any, pydantic_core.core_schema.ValidationInfo], Any], pydantic.functional_validators._OnlyValueValidatorClsMethod, Callable[[Any], Any]],\tmode: Literal['after', 'before', 'plain', 'wrap'],\tvalue: Any,\tinfo: pydantic_core.core_schema.ValidationInfo) -> Any:", "funcdef": "def"}, "bioimageio.spec._internal.field_warning.as_warning": {"fullname": "bioimageio.spec._internal.field_warning.as_warning", "modulename": "bioimageio.spec._internal.field_warning", "qualname": "as_warning", "kind": "function", "doc": "
    turn validation function into a no-op, based on warning level
    \n", "signature": "(\tfunc: Union[pydantic.functional_validators._V2ValidatorClsMethod, Callable[[Any, pydantic_core.core_schema.ValidationInfo], Any], pydantic.functional_validators._OnlyValueValidatorClsMethod, Callable[[Any], Any]],\t*,\tmode: Literal['after', 'before', 'plain', 'wrap'] = 'after',\tseverity: Literal[20, 30, 35] = 30,\tmsg: Optional[LiteralString] = None,\tmsg_context: Optional[Dict[str, Any]] = None) -> Union[Callable[[Any], Any], Callable[[Any, pydantic_core.core_schema.ValidationInfo], Any]]:", "funcdef": "def"}, "bioimageio.spec._internal.field_warning.AfterWarner": {"fullname": "bioimageio.spec._internal.field_warning.AfterWarner", "modulename": "bioimageio.spec._internal.field_warning", "qualname": "AfterWarner", "kind": "class", "doc": "
    Like AfterValidator, but wraps validation func as_warning
    \n", "bases": "pydantic.functional_validators.AfterValidator"}, "bioimageio.spec._internal.field_warning.AfterWarner.__init__": {"fullname": "bioimageio.spec._internal.field_warning.AfterWarner.__init__", "modulename": "bioimageio.spec._internal.field_warning", "qualname": "AfterWarner.__init__", "kind": "function", "doc": "
    \n", "signature": "(\tfunc: 'core_schema.NoInfoValidatorFunction | core_schema.WithInfoValidatorFunction',\tseverity: Literal[20, 30, 35] = 30,\tmsg: Optional[LiteralString] = None,\tcontext: Optional[Dict[str, Any]] = None)"}, "bioimageio.spec._internal.field_warning.AfterWarner.severity": {"fullname": "bioimageio.spec._internal.field_warning.AfterWarner.severity", "modulename": "bioimageio.spec._internal.field_warning", "qualname": "AfterWarner.severity", "kind": "variable", "doc": "
    \n", "annotation": ": Literal[20, 30, 35]"}, "bioimageio.spec._internal.field_warning.AfterWarner.msg": {"fullname": "bioimageio.spec._internal.field_warning.AfterWarner.msg", "modulename": "bioimageio.spec._internal.field_warning", "qualname": "AfterWarner.msg", "kind": "variable", "doc": "
    \n", "annotation": ": Optional[LiteralString]"}, "bioimageio.spec._internal.field_warning.AfterWarner.context": {"fullname": "bioimageio.spec._internal.field_warning.AfterWarner.context", "modulename": "bioimageio.spec._internal.field_warning", "qualname": "AfterWarner.context", "kind": "variable", "doc": "
    \n", "annotation": ": Optional[Dict[str, Any]]"}, "bioimageio.spec._internal.field_warning.BeforeWarner": {"fullname": "bioimageio.spec._internal.field_warning.BeforeWarner", "modulename": "bioimageio.spec._internal.field_warning", "qualname": "BeforeWarner", "kind": "class", "doc": "
    Like BeforeValidator, but wraps validation func as_warning
    \n", "bases": "pydantic.functional_validators.BeforeValidator"}, "bioimageio.spec._internal.field_warning.BeforeWarner.__init__": {"fullname": "bioimageio.spec._internal.field_warning.BeforeWarner.__init__", "modulename": "bioimageio.spec._internal.field_warning", "qualname": "BeforeWarner.__init__", "kind": "function", "doc": "
    \n", "signature": "(\tfunc: 'core_schema.NoInfoValidatorFunction | core_schema.WithInfoValidatorFunction',\tseverity: Literal[20, 30, 35] = 30,\tmsg: Optional[LiteralString] = None,\tcontext: Optional[Dict[str, Any]] = None)"}, "bioimageio.spec._internal.field_warning.BeforeWarner.severity": {"fullname": "bioimageio.spec._internal.field_warning.BeforeWarner.severity", "modulename": "bioimageio.spec._internal.field_warning", "qualname": "BeforeWarner.severity", "kind": "variable", "doc": "
    \n", "annotation": ": Literal[20, 30, 35]"}, "bioimageio.spec._internal.field_warning.BeforeWarner.msg": {"fullname": "bioimageio.spec._internal.field_warning.BeforeWarner.msg", "modulename": "bioimageio.spec._internal.field_warning", "qualname": "BeforeWarner.msg", "kind": "variable", "doc": "
    \n", "annotation": ": Optional[LiteralString]"}, "bioimageio.spec._internal.field_warning.BeforeWarner.context": {"fullname": "bioimageio.spec._internal.field_warning.BeforeWarner.context", "modulename": "bioimageio.spec._internal.field_warning", "qualname": "BeforeWarner.context", "kind": "variable", "doc": "
    \n", "annotation": ": Optional[Dict[str, Any]]"}, "bioimageio.spec._internal.field_warning.issue_warning": {"fullname": "bioimageio.spec._internal.field_warning.issue_warning", "modulename": "bioimageio.spec._internal.field_warning", "qualname": "issue_warning", "kind": "function", "doc": "
    \n", "signature": "(\tmsg: LiteralString,\t*,\tvalue: Any,\tseverity: Literal[20, 30, 35] = 30,\tmsg_context: Optional[Dict[str, Any]] = None):", "funcdef": "def"}, "bioimageio.spec._internal.io": {"fullname": "bioimageio.spec._internal.io", "modulename": "bioimageio.spec._internal.io", "kind": "module", "doc": "
    \n"}, "bioimageio.spec._internal.io.Sha256": {"fullname": "bioimageio.spec._internal.io.Sha256", "modulename": "bioimageio.spec._internal.io", "qualname": "Sha256", "kind": "class", "doc": "
    SHA-256 hash value
    \n", "bases": "pydantic.main.BaseModel, typing.Generic[~RootModelRootType]"}, "bioimageio.spec._internal.io.RelativePathBase": {"fullname": "bioimageio.spec._internal.io.RelativePathBase", "modulename": "bioimageio.spec._internal.io", "qualname": "RelativePathBase", "kind": "class", "doc": "
    Usage docs: https://docs.pydantic.dev/2.6/concepts/models/#rootmodel-and-custom-root-types
    \n\n
    A Pydantic BaseModel for the root object of the model.
    \n\n
    Attributes:\n    root: The root object of the model.\n    __pydantic_root_model__: Whether the model is a RootModel.\n    __pydantic_private__: Private fields in the model.\n    __pydantic_extra__: Extra fields in the model.
    \n", "bases": "pydantic.root_model.RootModel[PurePath], typing.Generic[~AbsolutePathT]"}, "bioimageio.spec._internal.io.RelativePathBase.path": {"fullname": "bioimageio.spec._internal.io.RelativePathBase.path", "modulename": "bioimageio.spec._internal.io", "qualname": "RelativePathBase.path", "kind": "variable", "doc": "
    \n", "annotation": ": pathlib.PurePath"}, "bioimageio.spec._internal.io.RelativePathBase.absolute": {"fullname": "bioimageio.spec._internal.io.RelativePathBase.absolute", "modulename": "bioimageio.spec._internal.io", "qualname": "RelativePathBase.absolute", "kind": "variable", "doc": "
    the absolute path/url (resolved at time of initialization with the root of the ValidationContext)
    \n", "annotation": ": ~AbsolutePathT"}, "bioimageio.spec._internal.io.RelativePathBase.model_post_init": {"fullname": "bioimageio.spec._internal.io.RelativePathBase.model_post_init", "modulename": "bioimageio.spec._internal.io", "qualname": "RelativePathBase.model_post_init", "kind": "function", "doc": "
    We need to both initialize private attributes and call the user-defined model_post_init\nmethod.
    \n", "signature": "(self: pydantic.main.BaseModel, _ModelMetaclass__context: Any) -> None:", "funcdef": "def"}, "bioimageio.spec._internal.io.RelativePathBase.get_absolute": {"fullname": "bioimageio.spec._internal.io.RelativePathBase.get_absolute", "modulename": "bioimageio.spec._internal.io", "qualname": "RelativePathBase.get_absolute", "kind": "function", "doc": "
    \n", "signature": "(\tself,\troot: Union[bioimageio.spec._internal.root_url.RootHttpUrl, Annotated[pathlib.Path, PathType(path_type='dir'), Predicate(func=<function PurePath.is_absolute>)], pydantic_core._pydantic_core.Url]) -> ~AbsolutePathT:", "funcdef": "def"}, "bioimageio.spec._internal.io.RelativePath": {"fullname": "bioimageio.spec._internal.io.RelativePath", "modulename": "bioimageio.spec._internal.io", "qualname": "RelativePath", "kind": "class", "doc": "
    Usage docs: https://docs.pydantic.dev/2.6/concepts/models/#rootmodel-and-custom-root-types
    \n\n
    A Pydantic BaseModel for the root object of the model.
    \n\n
    Attributes:\n    root: The root object of the model.\n    __pydantic_root_model__: Whether the model is a RootModel.\n    __pydantic_private__: Private fields in the model.\n    __pydantic_extra__: Extra fields in the model.
    \n", "bases": "pydantic.root_model.RootModel[PurePath], typing.Generic[~AbsolutePathT]"}, "bioimageio.spec._internal.io.RelativePath.get_absolute": {"fullname": "bioimageio.spec._internal.io.RelativePath.get_absolute", "modulename": "bioimageio.spec._internal.io", "qualname": "RelativePath.get_absolute", "kind": "function", "doc": "
    \n", "signature": "(\tself,\troot: bioimageio.spec._internal.root_url.RootHttpUrl | pathlib.Path | pydantic_core._pydantic_core.Url) -> Union[Annotated[pathlib.Path, PathType(path_type='file'), Predicate(func=<function PurePath.is_absolute at 0x7f1c25245940>)], Annotated[pathlib.Path, PathType(path_type='dir'), Predicate(func=<function PurePath.is_absolute at 0x7f1c25245940>)], bioimageio.spec._internal.url.HttpUrl]:", "funcdef": "def"}, "bioimageio.spec._internal.io.RelativeFilePath": {"fullname": "bioimageio.spec._internal.io.RelativeFilePath", "modulename": "bioimageio.spec._internal.io", "qualname": "RelativeFilePath", "kind": "class", "doc": "
    Usage docs: https://docs.pydantic.dev/2.6/concepts/models/#rootmodel-and-custom-root-types
    \n\n
    A Pydantic BaseModel for the root object of the model.
    \n\n
    Attributes:\n    root: The root object of the model.\n    __pydantic_root_model__: Whether the model is a RootModel.\n    __pydantic_private__: Private fields in the model.\n    __pydantic_extra__: Extra fields in the model.
    \n", "bases": "pydantic.root_model.RootModel[PurePath], typing.Generic[~AbsolutePathT]"}, "bioimageio.spec._internal.io.RelativeFilePath.get_absolute": {"fullname": "bioimageio.spec._internal.io.RelativeFilePath.get_absolute", "modulename": "bioimageio.spec._internal.io", "qualname": "RelativeFilePath.get_absolute", "kind": "function", "doc": "
    \n", "signature": "(\tself,\troot: bioimageio.spec._internal.root_url.RootHttpUrl | pathlib.Path | pydantic_core._pydantic_core.Url) -> Union[Annotated[pathlib.Path, PathType(path_type='file'), Predicate(func=<function PurePath.is_absolute at 0x7f1c25245940>)], bioimageio.spec._internal.url.HttpUrl]:", "funcdef": "def"}, "bioimageio.spec._internal.io.RelativeDirectory": {"fullname": "bioimageio.spec._internal.io.RelativeDirectory", "modulename": "bioimageio.spec._internal.io", "qualname": "RelativeDirectory", "kind": "class", "doc": "
    Usage docs: https://docs.pydantic.dev/2.6/concepts/models/#rootmodel-and-custom-root-types
    \n\n
    A Pydantic BaseModel for the root object of the model.
    \n\n
    Attributes:\n    root: The root object of the model.\n    __pydantic_root_model__: Whether the model is a RootModel.\n    __pydantic_private__: Private fields in the model.\n    __pydantic_extra__: Extra fields in the model.
    \n", "bases": "pydantic.root_model.RootModel[PurePath], typing.Generic[~AbsolutePathT]"}, "bioimageio.spec._internal.io.RelativeDirectory.get_absolute": {"fullname": "bioimageio.spec._internal.io.RelativeDirectory.get_absolute", "modulename": "bioimageio.spec._internal.io", "qualname": "RelativeDirectory.get_absolute", "kind": "function", "doc": "
    \n", "signature": "(\tself,\troot: bioimageio.spec._internal.root_url.RootHttpUrl | pathlib.Path | pydantic_core._pydantic_core.Url) -> Union[Annotated[pathlib.Path, PathType(path_type='dir'), Predicate(func=<function PurePath.is_absolute at 0x7f1c25245940>)], bioimageio.spec._internal.url.HttpUrl]:", "funcdef": "def"}, "bioimageio.spec._internal.io.FileSource": {"fullname": "bioimageio.spec._internal.io.FileSource", "modulename": "bioimageio.spec._internal.io", "qualname": "FileSource", "kind": "variable", "doc": "
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    \n", "annotation": ": Union[LiteralString, Tuple[LiteralString, ...]]"}, "bioimageio.spec._internal.io.WithSuffix.case_sensitive": {"fullname": "bioimageio.spec._internal.io.WithSuffix.case_sensitive", "modulename": "bioimageio.spec._internal.io", "qualname": "WithSuffix.case_sensitive", "kind": "variable", "doc": "
    \n", "annotation": ": bool"}, "bioimageio.spec._internal.io.WithSuffix.validate": {"fullname": "bioimageio.spec._internal.io.WithSuffix.validate", "modulename": "bioimageio.spec._internal.io", "qualname": "WithSuffix.validate", "kind": "function", "doc": "
    \n", "signature": "(\tself,\tvalue: Union[Annotated[pathlib.Path, PathType(path_type='file')], bioimageio.spec._internal.io.RelativeFilePath, bioimageio.spec._internal.url.HttpUrl, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]]) -> Union[Annotated[pathlib.Path, PathType(path_type='file')], bioimageio.spec._internal.io.RelativeFilePath, bioimageio.spec._internal.url.HttpUrl, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]]:", "funcdef": "def"}, "bioimageio.spec._internal.io.wo_special_file_name": {"fullname": "bioimageio.spec._internal.io.wo_special_file_name", "modulename": "bioimageio.spec._internal.io", "qualname": "wo_special_file_name", "kind": "function", "doc": "
    \n", "signature": "(\tsrc: Union[Annotated[pathlib.Path, PathType(path_type='file')], bioimageio.spec._internal.io.RelativeFilePath, bioimageio.spec._internal.url.HttpUrl, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]]) -> Union[Annotated[pathlib.Path, PathType(path_type='file')], bioimageio.spec._internal.io.RelativeFilePath, bioimageio.spec._internal.url.HttpUrl, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]]:", "funcdef": "def"}, "bioimageio.spec._internal.io.include_in_package_serializer": {"fullname": "bioimageio.spec._internal.io.include_in_package_serializer", "modulename": "bioimageio.spec._internal.io", "qualname": "include_in_package_serializer", "kind": "variable", "doc": "
    \n", "default_value": "PlainSerializer(func=<function _package>, return_type=PydanticUndefined, when_used='unless-none')"}, "bioimageio.spec._internal.io.ImportantFileSource": {"fullname": "bioimageio.spec._internal.io.ImportantFileSource", "modulename": "bioimageio.spec._internal.io", "qualname": "ImportantFileSource", "kind": "variable", "doc": "
    \n", "default_value": "typing.Annotated[typing.Union[typing.Annotated[pathlib.Path, PathType(path_type='file')], bioimageio.spec._internal.io.RelativeFilePath, bioimageio.spec._internal.url.HttpUrl, typing.Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator(func=<function wo_special_file_name>), PlainSerializer(func=<function _package>, return_type=PydanticUndefined, when_used='unless-none')]"}, "bioimageio.spec._internal.io.has_valid_rdf_name": {"fullname": "bioimageio.spec._internal.io.has_valid_rdf_name", "modulename": "bioimageio.spec._internal.io", "qualname": "has_valid_rdf_name", "kind": "function", "doc": "
    \n", "signature": "(\tsrc: Union[Annotated[pathlib.Path, PathType(path_type='file')], bioimageio.spec._internal.io.RelativeFilePath, bioimageio.spec._internal.url.HttpUrl, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]]) -> bool:", "funcdef": "def"}, "bioimageio.spec._internal.io.is_valid_rdf_name": {"fullname": "bioimageio.spec._internal.io.is_valid_rdf_name", "modulename": "bioimageio.spec._internal.io", "qualname": "is_valid_rdf_name", "kind": "function", "doc": "
    \n", "signature": "(file_name: str) -> bool:", "funcdef": "def"}, "bioimageio.spec._internal.io.ensure_has_valid_rdf_name": {"fullname": "bioimageio.spec._internal.io.ensure_has_valid_rdf_name", "modulename": "bioimageio.spec._internal.io", "qualname": "ensure_has_valid_rdf_name", "kind": "function", "doc": "
    \n", "signature": "(\tsrc: Union[Annotated[pathlib.Path, PathType(path_type='file')], bioimageio.spec._internal.io.RelativeFilePath, bioimageio.spec._internal.url.HttpUrl, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]]) -> Union[Annotated[pathlib.Path, PathType(path_type='file')], bioimageio.spec._internal.io.RelativeFilePath, bioimageio.spec._internal.url.HttpUrl, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]]:", "funcdef": "def"}, "bioimageio.spec._internal.io.ensure_is_valid_rdf_name": {"fullname": "bioimageio.spec._internal.io.ensure_is_valid_rdf_name", "modulename": "bioimageio.spec._internal.io", "qualname": "ensure_is_valid_rdf_name", "kind": "function", "doc": "
    \n", "signature": "(file_name: str) -> str:", "funcdef": "def"}, "bioimageio.spec._internal.io.YamlLeafValue": {"fullname": "bioimageio.spec._internal.io.YamlLeafValue", "modulename": "bioimageio.spec._internal.io", "qualname": "YamlLeafValue", "kind": "variable", "doc": "
    \n", "default_value": "typing.Union[bool, datetime.date, datetime.datetime, int, float, str, NoneType]"}, "bioimageio.spec._internal.io.YamlKey": {"fullname": "bioimageio.spec._internal.io.YamlKey", "modulename": "bioimageio.spec._internal.io", "qualname": "YamlKey", "kind": "variable", "doc": "
    \n", "default_value": "typing.Union[bool, datetime.date, datetime.datetime, int, float, str, NoneType, typing.Tuple[typing.Union[bool, datetime.date, datetime.datetime, int, float, str, NoneType], ...]]"}, "bioimageio.spec._internal.io.YamlValue": {"fullname": "bioimageio.spec._internal.io.YamlValue", "modulename": "bioimageio.spec._internal.io", "qualname": "YamlValue", "kind": "variable", "doc": "
    \n", "default_value": "Union[bool, datetime.date, datetime.datetime, int, float, str, NoneType, List[ForwardRef('YamlValue')], Dict[Union[bool, datetime.date, datetime.datetime, int, float, str, NoneType, Tuple[Union[bool, datetime.date, datetime.datetime, int, float, str, NoneType], ...]], ForwardRef('YamlValue')]]"}, "bioimageio.spec._internal.io.BioimageioYamlContent": {"fullname": "bioimageio.spec._internal.io.BioimageioYamlContent", "modulename": "bioimageio.spec._internal.io", "qualname": "BioimageioYamlContent", "kind": "variable", "doc": "
    \n", "default_value": "typing.Dict[str, YamlValue]"}, "bioimageio.spec._internal.io.BioimageioYamlSource": {"fullname": "bioimageio.spec._internal.io.BioimageioYamlSource", "modulename": "bioimageio.spec._internal.io", "qualname": "BioimageioYamlSource", "kind": "variable", "doc": "
    \n", "default_value": "typing.Union[typing.Annotated[pathlib.Path, PathType(path_type='file')], bioimageio.spec._internal.io.RelativeFilePath, bioimageio.spec._internal.url.HttpUrl, typing.Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)], str, typing.Dict[str, YamlValue]]"}, "bioimageio.spec._internal.io.OpenedBioimageioYaml": {"fullname": "bioimageio.spec._internal.io.OpenedBioimageioYaml", "modulename": "bioimageio.spec._internal.io", "qualname": "OpenedBioimageioYaml", "kind": "class", "doc": "
    \n"}, "bioimageio.spec._internal.io.OpenedBioimageioYaml.__init__": {"fullname": "bioimageio.spec._internal.io.OpenedBioimageioYaml.__init__", "modulename": "bioimageio.spec._internal.io", "qualname": "OpenedBioimageioYaml.__init__", "kind": "function", "doc": "
    \n", "signature": "(\tcontent: Dict[str, YamlValue],\toriginal_root: Union[Annotated[pathlib.Path, PathType(path_type='dir'), Predicate(func=<function PurePath.is_absolute>)], bioimageio.spec._internal.root_url.RootHttpUrl],\toriginal_file_name: str)"}, "bioimageio.spec._internal.io.OpenedBioimageioYaml.content": {"fullname": "bioimageio.spec._internal.io.OpenedBioimageioYaml.content", "modulename": "bioimageio.spec._internal.io", "qualname": "OpenedBioimageioYaml.content", "kind": "variable", "doc": "
    \n", "annotation": ": Dict[str, YamlValue]"}, "bioimageio.spec._internal.io.OpenedBioimageioYaml.original_root": {"fullname": "bioimageio.spec._internal.io.OpenedBioimageioYaml.original_root", "modulename": "bioimageio.spec._internal.io", "qualname": "OpenedBioimageioYaml.original_root", "kind": "variable", "doc": "
    \n", "annotation": ": Union[Annotated[pathlib.Path, PathType(path_type='dir'), Predicate(func=<function PurePath.is_absolute at 0x7f1c25245940>)], bioimageio.spec._internal.root_url.RootHttpUrl]"}, "bioimageio.spec._internal.io.OpenedBioimageioYaml.original_file_name": {"fullname": "bioimageio.spec._internal.io.OpenedBioimageioYaml.original_file_name", "modulename": "bioimageio.spec._internal.io", "qualname": "OpenedBioimageioYaml.original_file_name", "kind": "variable", "doc": "
    \n", "annotation": ": str"}, "bioimageio.spec._internal.io.DownloadedFile": {"fullname": "bioimageio.spec._internal.io.DownloadedFile", "modulename": "bioimageio.spec._internal.io", "qualname": "DownloadedFile", "kind": "class", "doc": "
    \n"}, "bioimageio.spec._internal.io.DownloadedFile.__init__": {"fullname": "bioimageio.spec._internal.io.DownloadedFile.__init__", "modulename": "bioimageio.spec._internal.io", "qualname": "DownloadedFile.__init__", "kind": "function", "doc": "
    \n", "signature": "(\tpath: Annotated[pathlib.Path, PathType(path_type='file')],\toriginal_root: Union[Annotated[pathlib.Path, PathType(path_type='dir'), Predicate(func=<function PurePath.is_absolute>)], bioimageio.spec._internal.root_url.RootHttpUrl],\toriginal_file_name: str)"}, "bioimageio.spec._internal.io.DownloadedFile.path": {"fullname": "bioimageio.spec._internal.io.DownloadedFile.path", "modulename": "bioimageio.spec._internal.io", "qualname": "DownloadedFile.path", "kind": "variable", "doc": "
    \n", "annotation": ": Annotated[pathlib.Path, PathType(path_type='file')]"}, "bioimageio.spec._internal.io.DownloadedFile.original_root": {"fullname": "bioimageio.spec._internal.io.DownloadedFile.original_root", "modulename": "bioimageio.spec._internal.io", "qualname": "DownloadedFile.original_root", "kind": "variable", "doc": "
    \n", "annotation": ": Union[Annotated[pathlib.Path, PathType(path_type='dir'), Predicate(func=<function PurePath.is_absolute at 0x7f1c25245940>)], bioimageio.spec._internal.root_url.RootHttpUrl]"}, "bioimageio.spec._internal.io.DownloadedFile.original_file_name": {"fullname": "bioimageio.spec._internal.io.DownloadedFile.original_file_name", "modulename": "bioimageio.spec._internal.io", "qualname": "DownloadedFile.original_file_name", "kind": "variable", "doc": "
    \n", "annotation": ": str"}, "bioimageio.spec._internal.io.HashKwargs": {"fullname": "bioimageio.spec._internal.io.HashKwargs", "modulename": "bioimageio.spec._internal.io", "qualname": "HashKwargs", "kind": "class", "doc": "
    \n", "bases": "typing.TypedDict"}, "bioimageio.spec._internal.io.HashKwargs.sha256": {"fullname": "bioimageio.spec._internal.io.HashKwargs.sha256", "modulename": "bioimageio.spec._internal.io", "qualname": "HashKwargs.sha256", "kind": "variable", "doc": "
    \n", "annotation": ": NotRequired[Optional[bioimageio.spec._internal.io.Sha256]]"}, "bioimageio.spec._internal.io.StrictFileSource": {"fullname": "bioimageio.spec._internal.io.StrictFileSource", "modulename": "bioimageio.spec._internal.io", "qualname": "StrictFileSource", "kind": "variable", "doc": "
    \n", "default_value": "typing.Union[bioimageio.spec._internal.url.HttpUrl, typing.Annotated[pathlib.Path, PathType(path_type='file')], bioimageio.spec._internal.io.RelativeFilePath]"}, "bioimageio.spec._internal.io.interprete_file_source": {"fullname": "bioimageio.spec._internal.io.interprete_file_source", "modulename": "bioimageio.spec._internal.io", "qualname": "interprete_file_source", "kind": "function", "doc": "
    \n", "signature": "(\tfile_source: Union[Annotated[pathlib.Path, PathType(path_type='file')], bioimageio.spec._internal.io.RelativeFilePath, bioimageio.spec._internal.url.HttpUrl, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)], str]) -> Union[bioimageio.spec._internal.url.HttpUrl, Annotated[pathlib.Path, PathType(path_type='file')], bioimageio.spec._internal.io.RelativeFilePath]:", "funcdef": "def"}, "bioimageio.spec._internal.io.download": {"fullname": "bioimageio.spec._internal.io.download", "modulename": "bioimageio.spec._internal.io", "qualname": "download", "kind": "function", "doc": "
    \n", "signature": "(\tsource: Union[Annotated[pathlib.Path, PathType(path_type='file')], bioimageio.spec._internal.io.RelativeFilePath, bioimageio.spec._internal.url.HttpUrl, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)], str, bioimageio.spec._internal.io.FileDescr],\t/,\t**kwargs: Unpack[bioimageio.spec._internal.io.HashKwargs]) -> bioimageio.spec._internal.io.DownloadedFile:", "funcdef": "def"}, "bioimageio.spec._internal.io.FileDescr": {"fullname": "bioimageio.spec._internal.io.FileDescr", "modulename": "bioimageio.spec._internal.io", "qualname": "FileDescr", "kind": "class", "doc": "
    Subpart of a resource description
    \n", "bases": "bioimageio.spec._internal.node.Node"}, "bioimageio.spec._internal.io.FileDescr.source": {"fullname": "bioimageio.spec._internal.io.FileDescr.source", "modulename": "bioimageio.spec._internal.io", "qualname": "FileDescr.source", "kind": "variable", "doc": "
    \u2208\ud83d\udce6 file source
    \n", "annotation": ": Annotated[Union[Annotated[pathlib.Path, PathType(path_type='file')], bioimageio.spec._internal.io.RelativeFilePath, bioimageio.spec._internal.url.HttpUrl, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator(func=<function wo_special_file_name at 0x7f1c21c3ef20>), PlainSerializer(func=<function _package at 0x7f1c21c782c0>, return_type=PydanticUndefined, when_used='unless-none')]"}, "bioimageio.spec._internal.io.FileDescr.sha256": {"fullname": "bioimageio.spec._internal.io.FileDescr.sha256", "modulename": "bioimageio.spec._internal.io", "qualname": "FileDescr.sha256", "kind": "variable", "doc": "
    SHA256 checksum of the source file
    \n", "annotation": ": Optional[bioimageio.spec._internal.io.Sha256]"}, "bioimageio.spec._internal.io.FileDescr.validate_sha256": {"fullname": "bioimageio.spec._internal.io.FileDescr.validate_sha256", "modulename": "bioimageio.spec._internal.io", "qualname": "FileDescr.validate_sha256", "kind": "function", "doc": "
    \n", "signature": "(self) -> Self:", "funcdef": "def"}, "bioimageio.spec._internal.io.FileDescr.download": {"fullname": "bioimageio.spec._internal.io.FileDescr.download", "modulename": "bioimageio.spec._internal.io", "qualname": "FileDescr.download", "kind": "function", "doc": "
    \n", "signature": "(self):", "funcdef": "def"}, "bioimageio.spec._internal.io.FileDescr.model_config": {"fullname": "bioimageio.spec._internal.io.FileDescr.model_config", "modulename": "bioimageio.spec._internal.io", "qualname": "FileDescr.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec._internal.io.FileDescr.model_fields": {"fullname": "bioimageio.spec._internal.io.FileDescr.model_fields", "modulename": "bioimageio.spec._internal.io", "qualname": "FileDescr.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'source': FieldInfo(annotation=Union[Annotated[Path, PathType], RelativeFilePath, HttpUrl, Annotated[Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], required=True, metadata=[AfterValidator(func=<function wo_special_file_name>), PlainSerializer(func=<function _package>, return_type=PydanticUndefined, when_used='unless-none')]), 'sha256': FieldInfo(annotation=Union[Sha256, NoneType], required=False)}"}, "bioimageio.spec._internal.io.FileDescr.model_computed_fields": {"fullname": "bioimageio.spec._internal.io.FileDescr.model_computed_fields", "modulename": "bioimageio.spec._internal.io", "qualname": "FileDescr.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec._internal.io.extract_file_name": {"fullname": "bioimageio.spec._internal.io.extract_file_name", "modulename": "bioimageio.spec._internal.io", "qualname": "extract_file_name", "kind": "function", "doc": "
    \n", "signature": "(\tsrc: Union[Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)], bioimageio.spec._internal.url.HttpUrl, pathlib.PurePath, bioimageio.spec._internal.io.RelativeFilePath]) -> str:", "funcdef": "def"}, "bioimageio.spec._internal.io.get_sha256": {"fullname": "bioimageio.spec._internal.io.get_sha256", "modulename": "bioimageio.spec._internal.io", "qualname": "get_sha256", "kind": "function", "doc": "
    from https://stackoverflow.com/a/44873382
    \n", "signature": "(path: pathlib.Path) -> bioimageio.spec._internal.io.Sha256:", "funcdef": "def"}, "bioimageio.spec._internal.io.RelativePathBase[Union[Annotated[Path, PathType, Predicate], Annotated[Path, PathType, Predicate], HttpUrl]]": {"fullname": "bioimageio.spec._internal.io.RelativePathBase[Union[Annotated[Path, PathType, Predicate], Annotated[Path, PathType, Predicate], HttpUrl]]", "modulename": "bioimageio.spec._internal.io", "qualname": "RelativePathBase[Union[Annotated[Path, PathType, Predicate], Annotated[Path, PathType, Predicate], HttpUrl]]", "kind": "class", "doc": "
    Usage docs: https://docs.pydantic.dev/2.6/concepts/models/#rootmodel-and-custom-root-types
    \n\n
    A Pydantic BaseModel for the root object of the model.
    \n\n
    Attributes:\n    root: The root object of the model.\n    __pydantic_root_model__: Whether the model is a RootModel.\n    __pydantic_private__: Private fields in the model.\n    __pydantic_extra__: Extra fields in the model.
    \n", "bases": "pydantic.root_model.RootModel[PurePath], typing.Generic[~AbsolutePathT]"}, "bioimageio.spec._internal.io.RelativePathBase[Union[Annotated[Path, PathType, Predicate], HttpUrl]]": {"fullname": "bioimageio.spec._internal.io.RelativePathBase[Union[Annotated[Path, PathType, Predicate], HttpUrl]]", "modulename": "bioimageio.spec._internal.io", "qualname": "RelativePathBase[Union[Annotated[Path, PathType, Predicate], HttpUrl]]", "kind": "class", "doc": "
    Usage docs: https://docs.pydantic.dev/2.6/concepts/models/#rootmodel-and-custom-root-types
    \n\n
    A Pydantic BaseModel for the root object of the model.
    \n\n
    Attributes:\n    root: The root object of the model.\n    __pydantic_root_model__: Whether the model is a RootModel.\n    __pydantic_private__: Private fields in the model.\n    __pydantic_extra__: Extra fields in the model.
    \n", "bases": "pydantic.root_model.RootModel[PurePath], typing.Generic[~AbsolutePathT]"}, "bioimageio.spec._internal.io.RelativePathBase[Union[Annotated[Path, PathType, Predicate], HttpUrl]]_": {"fullname": "bioimageio.spec._internal.io.RelativePathBase[Union[Annotated[Path, PathType, Predicate], HttpUrl]]_", "modulename": "bioimageio.spec._internal.io", "qualname": "RelativePathBase[Union[Annotated[Path, PathType, Predicate], HttpUrl]]_", "kind": "variable", "doc": "
    \n", "default_value": "<class 'bioimageio.spec._internal.io.RelativePathBase[Union[Annotated[Path, PathType, Predicate], HttpUrl]]'>"}, "bioimageio.spec._internal.io_basics": {"fullname": "bioimageio.spec._internal.io_basics", "modulename": "bioimageio.spec._internal.io_basics", "kind": "module", "doc": "
    \n"}, "bioimageio.spec._internal.io_basics.FileName": {"fullname": "bioimageio.spec._internal.io_basics.FileName", "modulename": "bioimageio.spec._internal.io_basics", "qualname": "FileName", "kind": "variable", "doc": "
    \n", "default_value": "<class 'str'>"}, "bioimageio.spec._internal.io_basics.AbsoluteDirectory": {"fullname": "bioimageio.spec._internal.io_basics.AbsoluteDirectory", "modulename": "bioimageio.spec._internal.io_basics", "qualname": "AbsoluteDirectory", "kind": "variable", "doc": "
    \n", "default_value": "typing.Annotated[pathlib.Path, PathType(path_type='dir'), Predicate(func=<function PurePath.is_absolute>)]"}, "bioimageio.spec._internal.io_basics.AbsoluteFilePath": {"fullname": "bioimageio.spec._internal.io_basics.AbsoluteFilePath", "modulename": "bioimageio.spec._internal.io_basics", "qualname": "AbsoluteFilePath", "kind": "variable", "doc": "
    \n", "default_value": "typing.Annotated[pathlib.Path, PathType(path_type='file'), Predicate(func=<function PurePath.is_absolute>)]"}, "bioimageio.spec._internal.io_basics.BIOIMAGEIO_YAML": {"fullname": "bioimageio.spec._internal.io_basics.BIOIMAGEIO_YAML", "modulename": "bioimageio.spec._internal.io_basics", "qualname": "BIOIMAGEIO_YAML", "kind": "variable", "doc": "
    \n", "default_value": "'rdf.yaml'"}, "bioimageio.spec._internal.io_basics.ALTERNATIVE_BIOIMAGEIO_YAML_NAMES": {"fullname": "bioimageio.spec._internal.io_basics.ALTERNATIVE_BIOIMAGEIO_YAML_NAMES", "modulename": "bioimageio.spec._internal.io_basics", "qualname": "ALTERNATIVE_BIOIMAGEIO_YAML_NAMES", "kind": "variable", "doc": "
    \n", "default_value": "('bioimageio.yaml', 'model.yaml')"}, "bioimageio.spec._internal.io_basics.ALL_BIOIMAGEIO_YAML_NAMES": {"fullname": "bioimageio.spec._internal.io_basics.ALL_BIOIMAGEIO_YAML_NAMES", "modulename": "bioimageio.spec._internal.io_basics", "qualname": "ALL_BIOIMAGEIO_YAML_NAMES", "kind": "variable", "doc": "
    \n", "default_value": "('rdf.yaml', 'bioimageio.yaml', 'model.yaml')"}, "bioimageio.spec._internal.io_utils": {"fullname": "bioimageio.spec._internal.io_utils", "modulename": "bioimageio.spec._internal.io_utils", "kind": "module", "doc": "
    \n"}, "bioimageio.spec._internal.io_utils.yaml": {"fullname": "bioimageio.spec._internal.io_utils.yaml", "modulename": "bioimageio.spec._internal.io_utils", "qualname": "yaml", "kind": "variable", "doc": "
    \n", "default_value": "<ruyaml.main.YAML object>"}, "bioimageio.spec._internal.io_utils.read_yaml": {"fullname": "bioimageio.spec._internal.io_utils.read_yaml", "modulename": "bioimageio.spec._internal.io_utils", "qualname": "read_yaml", "kind": "function", "doc": "
    \n", "signature": "(\tfile: Union[Annotated[pathlib.Path, PathType(path_type='file')], TextIO]) -> YamlValue:", "funcdef": "def"}, "bioimageio.spec._internal.io_utils.write_yaml": {"fullname": "bioimageio.spec._internal.io_utils.write_yaml", "modulename": "bioimageio.spec._internal.io_utils", "qualname": "write_yaml", "kind": "function", "doc": "
    \n", "signature": "(\tcontent: YamlValue,\t/,\tfile: Union[Annotated[pathlib.Path, PathType(path_type='new')], Annotated[pathlib.Path, PathType(path_type='file')], TextIO]):", "funcdef": "def"}, "bioimageio.spec._internal.io_utils.open_bioimageio_yaml": {"fullname": "bioimageio.spec._internal.io_utils.open_bioimageio_yaml", "modulename": "bioimageio.spec._internal.io_utils", "qualname": "open_bioimageio_yaml", "kind": "function", "doc": "
    \n", "signature": "(\tsource: Union[Annotated[pathlib.Path, PathType(path_type='file')], bioimageio.spec._internal.io.RelativeFilePath, bioimageio.spec._internal.url.HttpUrl, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)], str],\t/,\t**kwargs: Unpack[bioimageio.spec._internal.io.HashKwargs]) -> bioimageio.spec._internal.io.OpenedBioimageioYaml:", "funcdef": "def"}, "bioimageio.spec._internal.io_utils.identify_bioimageio_yaml_file": {"fullname": "bioimageio.spec._internal.io_utils.identify_bioimageio_yaml_file", "modulename": "bioimageio.spec._internal.io_utils", "qualname": "identify_bioimageio_yaml_file", "kind": "function", "doc": "
    \n", "signature": "(file_names: Iterable[str]) -> str:", "funcdef": "def"}, "bioimageio.spec._internal.io_utils.find_description_file_name": {"fullname": "bioimageio.spec._internal.io_utils.find_description_file_name", "modulename": "bioimageio.spec._internal.io_utils", "qualname": "find_description_file_name", "kind": "function", "doc": "
    \n", "signature": "(path: pathlib.Path) -> str:", "funcdef": "def"}, "bioimageio.spec._internal.io_utils.unzip": {"fullname": "bioimageio.spec._internal.io_utils.unzip", "modulename": "bioimageio.spec._internal.io_utils", "qualname": "unzip", "kind": "function", "doc": "
    \n", "signature": "(\tzip_file: Union[Annotated[pathlib.Path, PathType(path_type='file')], zipfile.ZipFile],\tout_path: Optional[Annotated[pathlib.Path, PathType(path_type='dir')]] = None,\toverwrite: bool = False) -> Annotated[pathlib.Path, PathType(path_type='dir')]:", "funcdef": "def"}, "bioimageio.spec._internal.io_utils.write_zip": {"fullname": "bioimageio.spec._internal.io_utils.write_zip", "modulename": "bioimageio.spec._internal.io_utils", "qualname": "write_zip", "kind": "function", "doc": "
    Write a zip archive.
    \n\n
    Args:\n    path: output path to write to.\n    content: dict mapping archive names to local file paths, strings (for text files), or dict (for yaml files).\n    compression: The numeric constant of compression method.\n    compression_level: Compression level to use when writing files to the archive.\n                       See https://docs.python.org/3/library/zipfile.html#zipfile.ZipFile
    \n", "signature": "(\tpath: Annotated[pathlib.Path, PathType(path_type='file')],\tcontent: Mapping[str, Union[str, Annotated[pathlib.Path, PathType(path_type='file')], Dict[Any, Any]]],\t*,\tcompression: int,\tcompression_level: int) -> None:", "funcdef": "def"}, "bioimageio.spec._internal.io_utils.load_array": {"fullname": "bioimageio.spec._internal.io_utils.load_array", "modulename": "bioimageio.spec._internal.io_utils", "qualname": "load_array", "kind": "function", "doc": "
    \n", "signature": "(\tsource: Union[Annotated[pathlib.Path, PathType(path_type='file')], bioimageio.spec._internal.io.RelativeFilePath, bioimageio.spec._internal.url.HttpUrl, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)], bioimageio.spec._internal.io.FileDescr]) -> numpy.ndarray[typing.Any, numpy.dtype[typing.Any]]:", "funcdef": "def"}, "bioimageio.spec._internal.io_utils.save_array": {"fullname": "bioimageio.spec._internal.io_utils.save_array", "modulename": "bioimageio.spec._internal.io_utils", "qualname": "save_array", "kind": "function", "doc": "
    \n", "signature": "(\tpath: pathlib.Path,\tarray: numpy.ndarray[typing.Any, numpy.dtype[typing.Any]]) -> None:", "funcdef": "def"}, "bioimageio.spec._internal.license_id": {"fullname": "bioimageio.spec._internal.license_id", "modulename": "bioimageio.spec._internal.license_id", "kind": "module", "doc": "
    \n"}, "bioimageio.spec._internal.license_id.DeprecatedLicenseId": {"fullname": "bioimageio.spec._internal.license_id.DeprecatedLicenseId", "modulename": "bioimageio.spec._internal.license_id", "qualname": "DeprecatedLicenseId", "kind": "class", "doc": "
    Usage docs: https://docs.pydantic.dev/2.6/concepts/models/#rootmodel-and-custom-root-types
    \n\n
    A Pydantic BaseModel for the root object of the model.
    \n\n
    Attributes:\n    root: The root object of the model.\n    __pydantic_root_model__: Whether the model is a RootModel.\n    __pydantic_private__: Private fields in the model.\n    __pydantic_extra__: Extra fields in the model.
    \n", "bases": "pydantic.main.BaseModel, typing.Generic[~RootModelRootType]"}, "bioimageio.spec._internal.license_id.LicenseId": {"fullname": "bioimageio.spec._internal.license_id.LicenseId", "modulename": "bioimageio.spec._internal.license_id", "qualname": "LicenseId", "kind": "class", "doc": "
    Usage docs: https://docs.pydantic.dev/2.6/concepts/models/#rootmodel-and-custom-root-types
    \n\n
    A Pydantic BaseModel for the root object of the model.
    \n\n
    Attributes:\n    root: The root object of the model.\n    __pydantic_root_model__: Whether the model is a RootModel.\n    __pydantic_private__: Private fields in the model.\n    __pydantic_extra__: Extra fields in the model.
    \n", "bases": "pydantic.main.BaseModel, typing.Generic[~RootModelRootType]"}, "bioimageio.spec._internal.license_id._LicenseId[Literal['AGPL-1.0', 'AGPL-3.0', 'BSD-2-Clause-FreeBSD', 'BSD-2-Clause-NetBSD', 'bzip2-1.0.5', 'eCos-2.0', 'GFDL-1.1', 'GFDL-1.2', 'GFDL-1.3', 'GPL-1.0', 'GPL-1.0+', 'GPL-2.0', 'GPL-2.0+', 'GPL-2.0-with-autoconf-exception', 'GPL-2.0-with-bison-exception', 'GPL-2.0-with-classpath-exception', 'GPL-2.0-with-font-exception', 'GPL-2.0-with-GCC-exception', 'GPL-3.0', 'GPL-3.0+', 'GPL-3.0-with-autoconf-exception', 'GPL-3.0-with-GCC-exception', 'LGPL-2.0', 'LGPL-2.0+', 'LGPL-2.1', 'LGPL-2.1+', 'LGPL-3.0', 'LGPL-3.0+', 'Nunit', 'StandardML-NJ', 'wxWindows']]": {"fullname": "bioimageio.spec._internal.license_id._LicenseId[Literal['AGPL-1.0', 'AGPL-3.0', 'BSD-2-Clause-FreeBSD', 'BSD-2-Clause-NetBSD', 'bzip2-1.0.5', 'eCos-2.0', 'GFDL-1.1', 'GFDL-1.2', 'GFDL-1.3', 'GPL-1.0', 'GPL-1.0+', 'GPL-2.0', 'GPL-2.0+', 'GPL-2.0-with-autoconf-exception', 'GPL-2.0-with-bison-exception', 'GPL-2.0-with-classpath-exception', 'GPL-2.0-with-font-exception', 'GPL-2.0-with-GCC-exception', 'GPL-3.0', 'GPL-3.0+', 'GPL-3.0-with-autoconf-exception', 'GPL-3.0-with-GCC-exception', 'LGPL-2.0', 'LGPL-2.0+', 'LGPL-2.1', 'LGPL-2.1+', 'LGPL-3.0', 'LGPL-3.0+', 'Nunit', 'StandardML-NJ', 'wxWindows']]", "modulename": "bioimageio.spec._internal.license_id", "qualname": "_LicenseId[Literal['AGPL-1.0', 'AGPL-3.0', 'BSD-2-Clause-FreeBSD', 'BSD-2-Clause-NetBSD', 'bzip2-1.0.5', 'eCos-2.0', 'GFDL-1.1', 'GFDL-1.2', 'GFDL-1.3', 'GPL-1.0', 'GPL-1.0+', 'GPL-2.0', 'GPL-2.0+', 'GPL-2.0-with-autoconf-exception', 'GPL-2.0-with-bison-exception', 'GPL-2.0-with-classpath-exception', 'GPL-2.0-with-font-exception', 'GPL-2.0-with-GCC-exception', 'GPL-3.0', 'GPL-3.0+', 'GPL-3.0-with-autoconf-exception', 'GPL-3.0-with-GCC-exception', 'LGPL-2.0', 'LGPL-2.0+', 'LGPL-2.1', 'LGPL-2.1+', 'LGPL-3.0', 'LGPL-3.0+', 'Nunit', 'StandardML-NJ', 'wxWindows']]", "kind": "class", "doc": "
    Usage docs: https://docs.pydantic.dev/2.6/concepts/models/#rootmodel-and-custom-root-types
    \n\n
    A Pydantic BaseModel for the root object of the model.
    \n\n
    Attributes:\n    root: The root object of the model.\n    __pydantic_root_model__: Whether the model is a RootModel.\n    __pydantic_private__: Private fields in the model.\n    __pydantic_extra__: Extra fields in the model.
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'DRL-1.0', 'DSDP', 'dtoa', 'dvipdfm', 'ECL-1.0', 'ECL-2.0', 'EFL-1.0', 'EFL-2.0', 'eGenix', 'Elastic-2.0', 'Entessa', 'EPICS', 'EPL-1.0', 'EPL-2.0', 'ErlPL-1.1', 'etalab-2.0', 'EUDatagrid', 'EUPL-1.0', 'EUPL-1.1', 'EUPL-1.2', 'Eurosym', 'Fair', 'FDK-AAC', 'Frameworx-1.0', 'FreeBSD-DOC', 'FreeImage', 'FSFAP', 'FSFUL', 'FSFULLR', 'FSFULLRWD', 'FTL', 'GD', 'GFDL-1.1-invariants-only', 'GFDL-1.1-invariants-or-later', 'GFDL-1.1-no-invariants-only', 'GFDL-1.1-no-invariants-or-later', 'GFDL-1.1-only', 'GFDL-1.1-or-later', 'GFDL-1.2-invariants-only', 'GFDL-1.2-invariants-or-later', 'GFDL-1.2-no-invariants-only', 'GFDL-1.2-no-invariants-or-later', 'GFDL-1.2-only', 'GFDL-1.2-or-later', 'GFDL-1.3-invariants-only', 'GFDL-1.3-invariants-or-later', 'GFDL-1.3-no-invariants-only', 'GFDL-1.3-no-invariants-or-later', 'GFDL-1.3-only', 'GFDL-1.3-or-later', 'Giftware', 'GL2PS', 'Glide', 'Glulxe', 'GLWTPL', 'gnuplot', 'GPL-1.0-only', 'GPL-1.0-or-later', 'GPL-2.0-only', 'GPL-2.0-or-later', 'GPL-3.0-only', 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'Spencer-86', 'Spencer-94', 'Spencer-99', 'SPL-1.0', 'SSH-OpenSSH', 'SSH-short', 'SSPL-1.0', 'SugarCRM-1.1.3', 'SunPro', 'SWL', 'Symlinks', 'TAPR-OHL-1.0', 'TCL', 'TCP-wrappers', 'TermReadKey', 'TMate', 'TORQUE-1.1', 'TOSL', 'TPDL', 'TPL-1.0', 'TTWL', 'TU-Berlin-1.0', 'TU-Berlin-2.0', 'UCAR', 'UCL-1.0', 'Unicode-DFS-2015', 'Unicode-DFS-2016', 'Unicode-TOU', 'UnixCrypt', 'Unlicense', 'UPL-1.0', 'Vim', 'VOSTROM', 'VSL-1.0', 'W3C', 'W3C-19980720', 'W3C-20150513', 'w3m', 'Watcom-1.0', 'Widget-Workshop', 'Wsuipa', 'WTFPL', 'X11', 'X11-distribute-modifications-variant', 'Xdebug-1.03', 'Xerox', 'Xfig', 'XFree86-1.1', 'xinetd', 'xlock', 'Xnet', 'xpp', 'XSkat', 'YPL-1.0', 'YPL-1.1', 'Zed', 'Zend-2.0', 'Zimbra-1.3', 'Zimbra-1.4', 'Zlib', 'zlib-acknowledgement', 'ZPL-1.1', 'ZPL-2.0', 'ZPL-2.1']]", "kind": "class", "doc": "
    Usage docs: https://docs.pydantic.dev/2.6/concepts/models/#rootmodel-and-custom-root-types
    \n\n
    A Pydantic BaseModel for the root object of the model.
    \n\n
    Attributes:\n    root: The root object of the model.\n    __pydantic_root_model__: Whether the model is a RootModel.\n    __pydantic_private__: Private fields in the model.\n    __pydantic_extra__: Extra fields in the model.
    \n", "bases": "pydantic.main.BaseModel, typing.Generic[~RootModelRootType]"}, "bioimageio.spec._internal.node": {"fullname": "bioimageio.spec._internal.node", "modulename": "bioimageio.spec._internal.node", "kind": "module", "doc": "
    \n"}, "bioimageio.spec._internal.node.Node": {"fullname": "bioimageio.spec._internal.node.Node", "modulename": "bioimageio.spec._internal.node", "qualname": "Node", "kind": "class", "doc": "
    Subpart of a resource description
    \n", "bases": "pydantic.main.BaseModel"}, "bioimageio.spec._internal.node.Node.model_validate": {"fullname": "bioimageio.spec._internal.node.Node.model_validate", "modulename": "bioimageio.spec._internal.node", "qualname": "Node.model_validate", "kind": "function", "doc": "
    Validate a pydantic model instance.
    \n\n
    Args:\n    obj: The object to validate.\n    strict: Whether to raise an exception on invalid fields.\n    from_attributes: Whether to extract data from object attributes.\n    context: Additional context to pass to the validator.
    \n\n
    Raises:\n    ValidationError: If the object failed validation.
    \n\n
    Returns:\n    The validated description instance.
    \n", "signature": "(\tcls,\tobj: Union[Any, Dict[str, Any]],\t*,\tstrict: Optional[bool] = None,\tfrom_attributes: Optional[bool] = None,\tcontext: Union[bioimageio.spec._internal.validation_context.ValidationContext, Dict[str, Any], NoneType] = None) -> Self:", "funcdef": "def"}, "bioimageio.spec._internal.node.Node.model_config": {"fullname": "bioimageio.spec._internal.node.Node.model_config", "modulename": "bioimageio.spec._internal.node", "qualname": "Node.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec._internal.node.Node.model_fields": {"fullname": "bioimageio.spec._internal.node.Node.model_fields", "modulename": "bioimageio.spec._internal.node", "qualname": "Node.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec._internal.node.Node.model_computed_fields": {"fullname": "bioimageio.spec._internal.node.Node.model_computed_fields", "modulename": "bioimageio.spec._internal.node", "qualname": "Node.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec._internal.packaging_context": {"fullname": "bioimageio.spec._internal.packaging_context", "modulename": "bioimageio.spec._internal.packaging_context", "kind": "module", "doc": "
    \n"}, "bioimageio.spec._internal.packaging_context.PackagingContext": {"fullname": "bioimageio.spec._internal.packaging_context.PackagingContext", "modulename": "bioimageio.spec._internal.packaging_context", "qualname": "PackagingContext", "kind": "class", "doc": "
    \n"}, "bioimageio.spec._internal.packaging_context.PackagingContext.__init__": {"fullname": "bioimageio.spec._internal.packaging_context.PackagingContext.__init__", "modulename": "bioimageio.spec._internal.packaging_context", "qualname": "PackagingContext.__init__", "kind": "function", "doc": "
    \n", "signature": "(\tbioimageio_yaml_file_name: str,\tfile_sources: Dict[str, Union[Annotated[pathlib.Path, PathType(path_type='file'), Predicate(func=<function PurePath.is_absolute>)], bioimageio.spec._internal.url.HttpUrl]] = <factory>)"}, "bioimageio.spec._internal.packaging_context.PackagingContext.bioimageio_yaml_file_name": {"fullname": "bioimageio.spec._internal.packaging_context.PackagingContext.bioimageio_yaml_file_name", "modulename": "bioimageio.spec._internal.packaging_context", "qualname": "PackagingContext.bioimageio_yaml_file_name", "kind": "variable", "doc": "
    \n", "annotation": ": str"}, "bioimageio.spec._internal.packaging_context.PackagingContext.file_sources": {"fullname": "bioimageio.spec._internal.packaging_context.PackagingContext.file_sources", "modulename": "bioimageio.spec._internal.packaging_context", "qualname": "PackagingContext.file_sources", "kind": "variable", "doc": "
    File sources to include in the packaged resource
    \n", "annotation": ": Dict[str, Union[Annotated[pathlib.Path, PathType(path_type='file'), Predicate(func=<function PurePath.is_absolute at 0x7f1c25245940>)], bioimageio.spec._internal.url.HttpUrl]]"}, "bioimageio.spec._internal.packaging_context.PackagingContext.replace": {"fullname": "bioimageio.spec._internal.packaging_context.PackagingContext.replace", "modulename": "bioimageio.spec._internal.packaging_context", "qualname": "PackagingContext.replace", "kind": "function", "doc": "
    return a modiefied copy
    \n", "signature": "(\tself,\t*,\tbioimageio_yaml_file_name: Optional[str] = None,\tfile_sources: Optional[Dict[str, Union[Annotated[pathlib.Path, PathType(path_type='file'), Predicate(func=<function PurePath.is_absolute>)], bioimageio.spec._internal.url.HttpUrl]]] = None) -> bioimageio.spec._internal.packaging_context.PackagingContext:", "funcdef": "def"}, "bioimageio.spec._internal.packaging_context.packaging_context_var": {"fullname": "bioimageio.spec._internal.packaging_context.packaging_context_var", "modulename": "bioimageio.spec._internal.packaging_context", "qualname": "packaging_context_var", "kind": "variable", "doc": "
    \n", "annotation": ": _contextvars.ContextVar[typing.Optional[bioimageio.spec._internal.packaging_context.PackagingContext]]", "default_value": "<ContextVar name='packaging_context_var' default=None>"}, "bioimageio.spec._internal.root_url": {"fullname": "bioimageio.spec._internal.root_url", "modulename": "bioimageio.spec._internal.root_url", "kind": "module", "doc": "
    \n"}, "bioimageio.spec._internal.root_url.RootHttpUrl": {"fullname": "bioimageio.spec._internal.root_url.RootHttpUrl", "modulename": "bioimageio.spec._internal.root_url", "qualname": "RootHttpUrl", "kind": "class", "doc": "
    A 'URL folder', possibly an invalid http URL
    \n", "bases": "pydantic.main.BaseModel, typing.Generic[~RootModelRootType]"}, "bioimageio.spec._internal.root_url.RootHttpUrl.scheme": {"fullname": "bioimageio.spec._internal.root_url.RootHttpUrl.scheme", "modulename": "bioimageio.spec._internal.root_url", "qualname": "RootHttpUrl.scheme", "kind": "variable", "doc": "
    \n", "annotation": ": str"}, "bioimageio.spec._internal.root_url.RootHttpUrl.host": {"fullname": "bioimageio.spec._internal.root_url.RootHttpUrl.host", "modulename": "bioimageio.spec._internal.root_url", "qualname": "RootHttpUrl.host", "kind": "variable", "doc": "
    \n", "annotation": ": Optional[str]"}, "bioimageio.spec._internal.root_url.RootHttpUrl.path": {"fullname": "bioimageio.spec._internal.root_url.RootHttpUrl.path", "modulename": "bioimageio.spec._internal.root_url", "qualname": "RootHttpUrl.path", "kind": "variable", "doc": "
    \n", "annotation": ": Optional[str]"}, "bioimageio.spec._internal.root_url.RootHttpUrl.parent": {"fullname": "bioimageio.spec._internal.root_url.RootHttpUrl.parent", "modulename": "bioimageio.spec._internal.root_url", "qualname": "RootHttpUrl.parent", "kind": "variable", "doc": "
    \n", "annotation": ": bioimageio.spec._internal.root_url.RootHttpUrl"}, "bioimageio.spec._internal.types": {"fullname": "bioimageio.spec._internal.types", "modulename": "bioimageio.spec._internal.types", "kind": "module", "doc": "
    \n"}, "bioimageio.spec._internal.types.NotEmpty": {"fullname": "bioimageio.spec._internal.types.NotEmpty", "modulename": "bioimageio.spec._internal.types", "qualname": "NotEmpty", "kind": "variable", "doc": "
    \n", "default_value": "typing.Annotated[~S, MinLen(min_length=1)]"}, "bioimageio.spec._internal.types.Datetime": {"fullname": "bioimageio.spec._internal.types.Datetime", "modulename": "bioimageio.spec._internal.types", "qualname": "Datetime", "kind": "class", "doc": "
    Timestamp in ISO 8601 format\nwith a few restrictions listed here.
    \n", "bases": "pydantic.main.BaseModel, typing.Generic[~RootModelRootType]"}, "bioimageio.spec._internal.types.Doi": {"fullname": "bioimageio.spec._internal.types.Doi", "modulename": "bioimageio.spec._internal.types", "qualname": "Doi", "kind": "variable", "doc": "
    \n", "default_value": "<class 'bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, StringConstraints]]'>"}, "bioimageio.spec._internal.types.FormatVersionPlaceholder": {"fullname": "bioimageio.spec._internal.types.FormatVersionPlaceholder", "modulename": "bioimageio.spec._internal.types", "qualname": "FormatVersionPlaceholder", "kind": "variable", "doc": "
    \n", "default_value": "typing.Literal['latest', 'discover']"}, "bioimageio.spec._internal.types.IdentifierAnno": {"fullname": "bioimageio.spec._internal.types.IdentifierAnno", "modulename": "bioimageio.spec._internal.types", "qualname": "IdentifierAnno", "kind": "variable", "doc": "
    \n", "default_value": "typing.Annotated[str, MinLen(min_length=1), AfterValidator(func=<function _validate_identifier>), AfterValidator(func=<function _validate_is_not_keyword>)]"}, "bioimageio.spec._internal.types.Identifier": {"fullname": "bioimageio.spec._internal.types.Identifier", "modulename": "bioimageio.spec._internal.types", "qualname": "Identifier", "kind": "variable", "doc": "
    \n", "default_value": "<class 'bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator]]'>"}, "bioimageio.spec._internal.types.LowerCaseIdentifierAnno": {"fullname": "bioimageio.spec._internal.types.LowerCaseIdentifierAnno", "modulename": "bioimageio.spec._internal.types", "qualname": "LowerCaseIdentifierAnno", "kind": "variable", "doc": "
    \n", "default_value": "typing.Annotated[str, MinLen(min_length=1), AfterValidator(func=<function _validate_identifier>), AfterValidator(func=<function _validate_is_not_keyword>), typing.Annotated[~_StrType, Predicate(func=<method 'islower' of 'str' objects>)]]"}, "bioimageio.spec._internal.types.LowerCaseIdentifier": {"fullname": "bioimageio.spec._internal.types.LowerCaseIdentifier", "modulename": "bioimageio.spec._internal.types", "qualname": "LowerCaseIdentifier", "kind": "variable", "doc": "
    \n", "default_value": "<class 'bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate]]]'>"}, "bioimageio.spec._internal.types.OrcidId": {"fullname": "bioimageio.spec._internal.types.OrcidId", "modulename": "bioimageio.spec._internal.types", "qualname": "OrcidId", "kind": "variable", "doc": "
    \n", "default_value": "<class 'bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, AfterValidator]]'>"}, "bioimageio.spec._internal.types.SiUnit": {"fullname": "bioimageio.spec._internal.types.SiUnit", "modulename": "bioimageio.spec._internal.types", "qualname": "SiUnit", "kind": "variable", "doc": "
    \n", "default_value": "<class 'bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, StringConstraints, BeforeValidator]]'>"}, "bioimageio.spec._internal.types.ResourceId": {"fullname": "bioimageio.spec._internal.types.ResourceId", "modulename": "bioimageio.spec._internal.types", "qualname": "ResourceId", "kind": "variable", "doc": "
    \n", "default_value": "<class 'bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]]'>"}, "bioimageio.spec._internal.types.ApplicationId": {"fullname": "bioimageio.spec._internal.types.ApplicationId", "modulename": "bioimageio.spec._internal.types", "qualname": "ApplicationId", "kind": "variable", "doc": "
    \n", "default_value": "<class 'bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]]'>"}, "bioimageio.spec._internal.types.CollectionId": {"fullname": "bioimageio.spec._internal.types.CollectionId", "modulename": "bioimageio.spec._internal.types", "qualname": "CollectionId", "kind": "variable", "doc": "
    \n", "default_value": "<class 'bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]]'>"}, "bioimageio.spec._internal.types.DatasetId": {"fullname": "bioimageio.spec._internal.types.DatasetId", "modulename": "bioimageio.spec._internal.types", "qualname": "DatasetId", "kind": "variable", "doc": "
    \n", "default_value": "<class 'bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]]'>"}, "bioimageio.spec._internal.types.ModelId": {"fullname": "bioimageio.spec._internal.types.ModelId", "modulename": "bioimageio.spec._internal.types", "qualname": "ModelId", "kind": "variable", "doc": "
    \n", "default_value": "<class 'bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]]'>"}, "bioimageio.spec._internal.types.NotebookId": {"fullname": "bioimageio.spec._internal.types.NotebookId", "modulename": "bioimageio.spec._internal.types", "qualname": "NotebookId", "kind": "variable", "doc": "
    \n", "default_value": "<class 'bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]]'>"}, "bioimageio.spec._internal.url": {"fullname": "bioimageio.spec._internal.url", "modulename": "bioimageio.spec._internal.url", "kind": "module", "doc": "
    \n"}, "bioimageio.spec._internal.url.check_url": {"fullname": "bioimageio.spec._internal.url.check_url", "modulename": "bioimageio.spec._internal.url", "qualname": "check_url", "kind": "function", "doc": "
    \n", "signature": "(url: str) -> None:", "funcdef": "def"}, "bioimageio.spec._internal.url.HttpUrl": {"fullname": "bioimageio.spec._internal.url.HttpUrl", "modulename": "bioimageio.spec._internal.url", "qualname": "HttpUrl", "kind": "class", "doc": "
    A 'URL folder', possibly an invalid http URL
    \n", "bases": "pydantic.main.BaseModel, typing.Generic[~RootModelRootType]"}, "bioimageio.spec._internal.utils": {"fullname": "bioimageio.spec._internal.utils", "modulename": "bioimageio.spec._internal.utils", "kind": "module", "doc": "
    \n"}, "bioimageio.spec._internal.utils.NestedDict": {"fullname": "bioimageio.spec._internal.utils.NestedDict", "modulename": "bioimageio.spec._internal.utils", "qualname": "NestedDict", "kind": "variable", "doc": "
    \n", "default_value": "typing.Dict[~K, ForwardRef('NestedDict[K, V] | V')]"}, "bioimageio.spec._internal.utils.nest_dict": {"fullname": "bioimageio.spec._internal.utils.nest_dict", "modulename": "bioimageio.spec._internal.utils", "qualname": "nest_dict", "kind": "function", "doc": "
    \n", "signature": "(flat_dict: Dict[Tuple[~K, ...], ~V]) -> 'NestedDict[K, V]':", "funcdef": "def"}, "bioimageio.spec._internal.utils.nest_dict_with_narrow_first_key": {"fullname": "bioimageio.spec._internal.utils.nest_dict_with_narrow_first_key", "modulename": "bioimageio.spec._internal.utils", "qualname": "nest_dict_with_narrow_first_key", "kind": "function", "doc": "
    convenience function to annotate a special version of a NestedDict.\nRoot level keys are of a narrower type than the nested keys. If not a ValueError is raisd.
    \n", "signature": "(\tflat_dict: Dict[Tuple[~K, ...], ~V],\tfirst_k: Type[~FirstK]) -> "Dict[FirstK, 'NestedDict[K, V] | V']":", "funcdef": "def"}, "bioimageio.spec._internal.utils.unindent": {"fullname": "bioimageio.spec._internal.utils.unindent", "modulename": "bioimageio.spec._internal.utils", "qualname": "unindent", "kind": "function", "doc": "
    remove minimum count of spaces at beginning of each line.
    \n\n
    Args:\n    text: indented text\n    ignore_first_line: allows to correctly unindent doc strings
    \n", "signature": "(text: str, ignore_first_line: bool = False):", "funcdef": "def"}, "bioimageio.spec._internal.utils.P": {"fullname": "bioimageio.spec._internal.utils.P", "modulename": "bioimageio.spec._internal.utils", "qualname": "P", "kind": "variable", "doc": "
    \n", "default_value": "~P"}, "bioimageio.spec._internal.utils.assert_all_params_set_explicitly": {"fullname": "bioimageio.spec._internal.utils.assert_all_params_set_explicitly", "modulename": "bioimageio.spec._internal.utils", "qualname": "assert_all_params_set_explicitly", "kind": "function", "doc": "
    \n", "signature": "(fn: Callable[~P, ~T]) -> Callable[~P, ~T]:", "funcdef": "def"}, "bioimageio.spec._internal.validated_string": {"fullname": "bioimageio.spec._internal.validated_string", "modulename": "bioimageio.spec._internal.validated_string", "kind": "module", "doc": "
    \n"}, "bioimageio.spec._internal.validated_string.ValidatedString": {"fullname": "bioimageio.spec._internal.validated_string.ValidatedString", "modulename": "bioimageio.spec._internal.validated_string", "qualname": "ValidatedString", "kind": "class", "doc": "
    Usage docs: https://docs.pydantic.dev/2.6/concepts/models/#rootmodel-and-custom-root-types
    \n\n
    A Pydantic BaseModel for the root object of the model.
    \n\n
    Attributes:\n    root: The root object of the model.\n    __pydantic_root_model__: Whether the model is a RootModel.\n    __pydantic_private__: Private fields in the model.\n    __pydantic_extra__: Extra fields in the model.
    \n", "bases": "pydantic.main.BaseModel, typing.Generic[~RootModelRootType]"}, "bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, AfterValidator]]": {"fullname": "bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, AfterValidator]]", "modulename": "bioimageio.spec._internal.validated_string", "qualname": "ValidatedString[Annotated[str, AfterValidator]]", "kind": "class", "doc": "
    Usage docs: https://docs.pydantic.dev/2.6/concepts/models/#rootmodel-and-custom-root-types
    \n\n
    A Pydantic BaseModel for the root object of the model.
    \n\n
    Attributes:\n    root: The root object of the model.\n    __pydantic_root_model__: Whether the model is a RootModel.\n    __pydantic_private__: Private fields in the model.\n    __pydantic_extra__: Extra fields in the model.
    \n", "bases": "pydantic.main.BaseModel, typing.Generic[~RootModelRootType]"}, "bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, StringConstraints]]": {"fullname": "bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, StringConstraints]]", "modulename": "bioimageio.spec._internal.validated_string", "qualname": "ValidatedString[Annotated[str, StringConstraints]]", "kind": "class", "doc": "
    Usage docs: https://docs.pydantic.dev/2.6/concepts/models/#rootmodel-and-custom-root-types
    \n\n
    A Pydantic BaseModel for the root object of the model.
    \n\n
    Attributes:\n    root: The root object of the model.\n    __pydantic_root_model__: Whether the model is a RootModel.\n    __pydantic_private__: Private fields in the model.\n    __pydantic_extra__: Extra fields in the model.
    \n", "bases": "pydantic.main.BaseModel, typing.Generic[~RootModelRootType]"}, "bioimageio.spec._internal.validated_string.ValidatedString[TypeVar]": {"fullname": "bioimageio.spec._internal.validated_string.ValidatedString[TypeVar]", "modulename": "bioimageio.spec._internal.validated_string", "qualname": "ValidatedString[TypeVar]", "kind": "class", "doc": "
    Usage docs: https://docs.pydantic.dev/2.6/concepts/models/#rootmodel-and-custom-root-types
    \n\n
    A Pydantic BaseModel for the root object of the model.
    \n\n
    Attributes:\n    root: The root object of the model.\n    __pydantic_root_model__: Whether the model is a RootModel.\n    __pydantic_private__: Private fields in the model.\n    __pydantic_extra__: Extra fields in the model.
    \n", "bases": "pydantic.main.BaseModel, typing.Generic[~RootModelRootType]"}, "bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, StringConstraints]]_": {"fullname": "bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, StringConstraints]]_", "modulename": "bioimageio.spec._internal.validated_string", "qualname": "ValidatedString[Annotated[str, StringConstraints]]_", "kind": "variable", "doc": "
    \n", "default_value": "<class 'bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, StringConstraints]]'>"}, "bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator]]": {"fullname": "bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator]]", "modulename": "bioimageio.spec._internal.validated_string", "qualname": "ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator]]", "kind": "class", "doc": "
    Usage docs: https://docs.pydantic.dev/2.6/concepts/models/#rootmodel-and-custom-root-types
    \n\n
    A Pydantic BaseModel for the root object of the model.
    \n\n
    Attributes:\n    root: The root object of the model.\n    __pydantic_root_model__: Whether the model is a RootModel.\n    __pydantic_private__: Private fields in the model.\n    __pydantic_extra__: Extra fields in the model.
    \n", "bases": "pydantic.main.BaseModel, typing.Generic[~RootModelRootType]"}, "bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate]]]": {"fullname": "bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate]]]", "modulename": "bioimageio.spec._internal.validated_string", "qualname": "ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate]]]", "kind": "class", "doc": "
    Usage docs: https://docs.pydantic.dev/2.6/concepts/models/#rootmodel-and-custom-root-types
    \n\n
    A Pydantic BaseModel for the root object of the model.
    \n\n
    Attributes:\n    root: The root object of the model.\n    __pydantic_root_model__: Whether the model is a RootModel.\n    __pydantic_private__: Private fields in the model.\n    __pydantic_extra__: Extra fields in the model.
    \n", "bases": "pydantic.main.BaseModel, typing.Generic[~RootModelRootType]"}, "bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, AfterValidator]]_": {"fullname": "bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, AfterValidator]]_", "modulename": "bioimageio.spec._internal.validated_string", "qualname": "ValidatedString[Annotated[str, AfterValidator]]_", "kind": "variable", "doc": "
    \n", "default_value": "<class 'bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, AfterValidator]]'>"}, "bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, StringConstraints, BeforeValidator]]": {"fullname": "bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, StringConstraints, BeforeValidator]]", "modulename": "bioimageio.spec._internal.validated_string", "qualname": "ValidatedString[Annotated[str, StringConstraints, BeforeValidator]]", "kind": "class", "doc": "
    Usage docs: https://docs.pydantic.dev/2.6/concepts/models/#rootmodel-and-custom-root-types
    \n\n
    A Pydantic BaseModel for the root object of the model.
    \n\n
    Attributes:\n    root: The root object of the model.\n    __pydantic_root_model__: Whether the model is a RootModel.\n    __pydantic_private__: Private fields in the model.\n    __pydantic_extra__: Extra fields in the model.
    \n", "bases": "pydantic.main.BaseModel, typing.Generic[~RootModelRootType]"}, "bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]]": {"fullname": "bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]]", "modulename": "bioimageio.spec._internal.validated_string", "qualname": "ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]]", "kind": "class", "doc": "
    Usage docs: https://docs.pydantic.dev/2.6/concepts/models/#rootmodel-and-custom-root-types
    \n\n
    A Pydantic BaseModel for the root object of the model.
    \n\n
    Attributes:\n    root: The root object of the model.\n    __pydantic_root_model__: Whether the model is a RootModel.\n    __pydantic_private__: Private fields in the model.\n    __pydantic_extra__: Extra fields in the model.
    \n", "bases": "pydantic.main.BaseModel, typing.Generic[~RootModelRootType]"}, "bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]": {"fullname": "bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]", "modulename": "bioimageio.spec._internal.validated_string", "qualname": "ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]", "kind": "class", "doc": "
    Usage docs: https://docs.pydantic.dev/2.6/concepts/models/#rootmodel-and-custom-root-types
    \n\n
    A Pydantic BaseModel for the root object of the model.
    \n\n
    Attributes:\n    root: The root object of the model.\n    __pydantic_root_model__: Whether the model is a RootModel.\n    __pydantic_private__: Private fields in the model.\n    __pydantic_extra__: Extra fields in the model.
    \n", "bases": "pydantic.main.BaseModel, typing.Generic[~RootModelRootType]"}, "bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]_": {"fullname": "bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]_", "modulename": "bioimageio.spec._internal.validated_string", "qualname": "ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]_", "kind": "variable", "doc": "
    \n", "default_value": "<class 'bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]'>"}, "bioimageio.spec._internal.validation_context": {"fullname": "bioimageio.spec._internal.validation_context", "modulename": "bioimageio.spec._internal.validation_context", "kind": "module", "doc": "
    \n"}, "bioimageio.spec._internal.validation_context.ValidationContext": {"fullname": "bioimageio.spec._internal.validation_context.ValidationContext", "modulename": "bioimageio.spec._internal.validation_context", "qualname": "ValidationContext", "kind": "class", "doc": "
    \n"}, "bioimageio.spec._internal.validation_context.ValidationContext.__init__": {"fullname": "bioimageio.spec._internal.validation_context.ValidationContext.__init__", "modulename": "bioimageio.spec._internal.validation_context", "qualname": "ValidationContext.__init__", "kind": "function", "doc": "
    \n", "signature": "(\troot: Union[bioimageio.spec._internal.root_url.RootHttpUrl, Annotated[pathlib.Path, PathType(path_type='dir'), Predicate(func=<function PurePath.is_absolute>)]] = PosixPath('.'),\twarning_level: Literal[20, 30, 35, 50] = 50,\tlog_warnings: bool = True,\tfile_name: Optional[str] = None,\tperform_io_checks: bool = True)"}, "bioimageio.spec._internal.validation_context.ValidationContext.root": {"fullname": "bioimageio.spec._internal.validation_context.ValidationContext.root", "modulename": "bioimageio.spec._internal.validation_context", "qualname": "ValidationContext.root", "kind": "variable", "doc": "
    url/directory serving as base to resolve any relative file paths
    \n", "annotation": ": Union[bioimageio.spec._internal.root_url.RootHttpUrl, Annotated[pathlib.Path, PathType(path_type='dir'), Predicate(func=<function PurePath.is_absolute at 0x7f1c25245940>)]]", "default_value": "PosixPath('.')"}, "bioimageio.spec._internal.validation_context.ValidationContext.warning_level": {"fullname": "bioimageio.spec._internal.validation_context.ValidationContext.warning_level", "modulename": "bioimageio.spec._internal.validation_context", "qualname": "ValidationContext.warning_level", "kind": "variable", "doc": "
    raise warnings of severity s as validation errors if s >= warning_level
    \n", "annotation": ": Literal[20, 30, 35, 50]", "default_value": "50"}, "bioimageio.spec._internal.validation_context.ValidationContext.log_warnings": {"fullname": "bioimageio.spec._internal.validation_context.ValidationContext.log_warnings", "modulename": "bioimageio.spec._internal.validation_context", "qualname": "ValidationContext.log_warnings", "kind": "variable", "doc": "
    if True log warnings that are not raised to the console
    \n", "annotation": ": bool", "default_value": "True"}, "bioimageio.spec._internal.validation_context.ValidationContext.file_name": {"fullname": "bioimageio.spec._internal.validation_context.ValidationContext.file_name", "modulename": "bioimageio.spec._internal.validation_context", "qualname": "ValidationContext.file_name", "kind": "variable", "doc": "
    file name of the bioimageio Yaml file
    \n", "annotation": ": Optional[str]", "default_value": "None"}, "bioimageio.spec._internal.validation_context.ValidationContext.perform_io_checks": {"fullname": "bioimageio.spec._internal.validation_context.ValidationContext.perform_io_checks", "modulename": "bioimageio.spec._internal.validation_context", "qualname": "ValidationContext.perform_io_checks", "kind": "variable", "doc": "
    wether or not to perform validation that requires file io,\ne.g. downloading a remote files.
    \n\n
    Existence of local absolute file paths is still being checked.
    \n", "annotation": ": bool", "default_value": "True"}, "bioimageio.spec._internal.validation_context.ValidationContext.replace": {"fullname": "bioimageio.spec._internal.validation_context.ValidationContext.replace", "modulename": "bioimageio.spec._internal.validation_context", "qualname": "ValidationContext.replace", "kind": "function", "doc": "
    \n", "signature": "(\tself,\troot: Union[bioimageio.spec._internal.root_url.RootHttpUrl, Annotated[pathlib.Path, PathType(path_type='dir')], NoneType] = None,\twarning_level: Optional[Literal[20, 30, 35, 50]] = None,\tlog_warnings: Optional[bool] = None,\tfile_name: Optional[str] = None,\tperform_io_checks: Optional[bool] = None) -> bioimageio.spec._internal.validation_context.ValidationContext:", "funcdef": "def"}, "bioimageio.spec._internal.validation_context.ValidationContext.source_name": {"fullname": "bioimageio.spec._internal.validation_context.ValidationContext.source_name", "modulename": "bioimageio.spec._internal.validation_context", "qualname": "ValidationContext.source_name", "kind": "variable", "doc": "
    \n", "annotation": ": str"}, "bioimageio.spec._internal.validation_context.validation_context_var": {"fullname": "bioimageio.spec._internal.validation_context.validation_context_var", "modulename": "bioimageio.spec._internal.validation_context", "qualname": "validation_context_var", "kind": "variable", "doc": "
    \n", "annotation": ": _contextvars.ContextVar[bioimageio.spec._internal.validation_context.ValidationContext]", "default_value": "<ContextVar name='validation_context_var' default=ValidationContext(_context_tokens=[], root=PosixPath('.'), warning_level=50, log_warnings=True, file_name=None, perform_io_checks=True)>"}, "bioimageio.spec._internal.version_type": {"fullname": "bioimageio.spec._internal.version_type", "modulename": "bioimageio.spec._internal.version_type", "kind": "module", "doc": "
    \n"}, "bioimageio.spec._internal.version_type.Version": {"fullname": "bioimageio.spec._internal.version_type.Version", "modulename": "bioimageio.spec._internal.version_type", "qualname": "Version", "kind": "class", "doc": "
    wraps a packaging.version.Version instance for validation in pydantic models
    \n", "bases": "pydantic.main.BaseModel, typing.Generic[~RootModelRootType]"}, "bioimageio.spec._internal.version_type.Version.epoch": {"fullname": "bioimageio.spec._internal.version_type.Version.epoch", "modulename": "bioimageio.spec._internal.version_type", "qualname": "Version.epoch", "kind": "variable", "doc": "
    The epoch of the version.
    \n\n
    \n
    >>> Version("2.0.0").epoch\n0\n>>> Version("1!2.0.0").epoch\n1\n
    \n
    \n", "annotation": ": int"}, "bioimageio.spec._internal.version_type.Version.release": {"fullname": "bioimageio.spec._internal.version_type.Version.release", "modulename": "bioimageio.spec._internal.version_type", "qualname": "Version.release", "kind": "variable", "doc": "
    The components of the \"release\" segment of the version.
    \n\n
    \n
    >>> Version("1.2.3").release\n(1, 2, 3)\n>>> Version("2.0.0").release\n(2, 0, 0)\n>>> Version("1!2.0.0.post0").release\n(2, 0, 0)\n
    \n
    \n\n
    Includes trailing zeroes but not the epoch or any pre-release / development /\npost-release suffixes.
    \n", "annotation": ": Tuple[int, ...]"}, "bioimageio.spec._internal.version_type.Version.pre": {"fullname": "bioimageio.spec._internal.version_type.Version.pre", "modulename": "bioimageio.spec._internal.version_type", "qualname": "Version.pre", "kind": "variable", "doc": "
    The pre-release segment of the version.
    \n\n
    \n
    >>> print(Version("1.2.3").pre)\nNone\n>>> Version("1.2.3a1").pre\n('a', 1)\n>>> Version("1.2.3b1").pre\n('b', 1)\n>>> Version("1.2.3rc1").pre\n('rc', 1)\n
    \n
    \n", "annotation": ": Optional[Tuple[str, int]]"}, "bioimageio.spec._internal.version_type.Version.post": {"fullname": "bioimageio.spec._internal.version_type.Version.post", "modulename": "bioimageio.spec._internal.version_type", "qualname": "Version.post", "kind": "variable", "doc": "
    The post-release number of the version.
    \n\n
    \n
    >>> print(Version("1.2.3").post)\nNone\n>>> Version("1.2.3.post1").post\n1\n
    \n
    \n", "annotation": ": Optional[int]"}, "bioimageio.spec._internal.version_type.Version.dev": {"fullname": "bioimageio.spec._internal.version_type.Version.dev", "modulename": "bioimageio.spec._internal.version_type", "qualname": "Version.dev", "kind": "variable", "doc": "
    The development number of the version.
    \n\n
    \n
    >>> print(Version("1.2.3").dev)\nNone\n>>> Version("1.2.3.dev1").dev\n1\n
    \n
    \n", "annotation": ": Optional[int]"}, "bioimageio.spec._internal.version_type.Version.local": {"fullname": "bioimageio.spec._internal.version_type.Version.local", "modulename": "bioimageio.spec._internal.version_type", "qualname": "Version.local", "kind": "variable", "doc": "
    The local version segment of the version.
    \n\n
    \n
    >>> print(Version("1.2.3").local)\nNone\n>>> Version("1.2.3+abc").local\n'abc'\n
    \n
    \n", "annotation": ": Optional[str]"}, "bioimageio.spec._internal.version_type.Version.public": {"fullname": "bioimageio.spec._internal.version_type.Version.public", "modulename": "bioimageio.spec._internal.version_type", "qualname": "Version.public", "kind": "variable", "doc": "
    The public portion of the version.
    \n\n
    \n
    >>> Version("1.2.3").public\n'1.2.3'\n>>> Version("1.2.3+abc").public\n'1.2.3'\n>>> Version("1.2.3+abc.dev1").public\n'1.2.3'\n
    \n
    \n", "annotation": ": str"}, "bioimageio.spec._internal.version_type.Version.base_version": {"fullname": "bioimageio.spec._internal.version_type.Version.base_version", "modulename": "bioimageio.spec._internal.version_type", "qualname": "Version.base_version", "kind": "variable", "doc": "
    The \"base version\" of the version.
    \n\n
    \n
    >>> Version("1.2.3").base_version\n'1.2.3'\n>>> Version("1.2.3+abc").base_version\n'1.2.3'\n>>> Version("1!1.2.3+abc.dev1").base_version\n'1!1.2.3'\n
    \n
    \n\n
    The \"base version\" is the public version of the project without any pre or post\nrelease markers.
    \n", "annotation": ": str"}, "bioimageio.spec._internal.version_type.Version.is_prerelease": {"fullname": "bioimageio.spec._internal.version_type.Version.is_prerelease", "modulename": "bioimageio.spec._internal.version_type", "qualname": "Version.is_prerelease", "kind": "variable", "doc": "
    Whether this version is a pre-release.
    \n\n
    \n
    >>> Version("1.2.3").is_prerelease\nFalse\n>>> Version("1.2.3a1").is_prerelease\nTrue\n>>> Version("1.2.3b1").is_prerelease\nTrue\n>>> Version("1.2.3rc1").is_prerelease\nTrue\n>>> Version("1.2.3dev1").is_prerelease\nTrue\n
    \n
    \n", "annotation": ": bool"}, "bioimageio.spec._internal.version_type.Version.is_postrelease": {"fullname": "bioimageio.spec._internal.version_type.Version.is_postrelease", "modulename": "bioimageio.spec._internal.version_type", "qualname": "Version.is_postrelease", "kind": "variable", "doc": "
    Whether this version is a post-release.
    \n\n
    \n
    >>> Version("1.2.3").is_postrelease\nFalse\n>>> Version("1.2.3.post1").is_postrelease\nTrue\n
    \n
    \n", "annotation": ": bool"}, "bioimageio.spec._internal.version_type.Version.is_devrelease": {"fullname": "bioimageio.spec._internal.version_type.Version.is_devrelease", "modulename": "bioimageio.spec._internal.version_type", "qualname": "Version.is_devrelease", "kind": "variable", "doc": "
    Whether this version is a development release.
    \n\n
    \n
    >>> Version("1.2.3").is_devrelease\nFalse\n>>> Version("1.2.3.dev1").is_devrelease\nTrue\n
    \n
    \n", "annotation": ": bool"}, "bioimageio.spec._internal.version_type.Version.major": {"fullname": "bioimageio.spec._internal.version_type.Version.major", "modulename": "bioimageio.spec._internal.version_type", "qualname": "Version.major", "kind": "variable", "doc": "
    The first item of release or 0 if unavailable.
    \n\n
    \n
    >>> Version("1.2.3").major\n1\n
    \n
    \n", "annotation": ": int"}, "bioimageio.spec._internal.version_type.Version.minor": {"fullname": "bioimageio.spec._internal.version_type.Version.minor", "modulename": "bioimageio.spec._internal.version_type", "qualname": "Version.minor", "kind": "variable", "doc": "
    The second item of release or 0 if unavailable.
    \n\n
    \n
    >>> Version("1.2.3").minor\n2\n>>> Version("1").minor\n0\n
    \n
    \n", "annotation": ": int"}, "bioimageio.spec._internal.version_type.Version.micro": {"fullname": "bioimageio.spec._internal.version_type.Version.micro", "modulename": "bioimageio.spec._internal.version_type", "qualname": "Version.micro", "kind": "variable", "doc": "
    The third item of release or 0 if unavailable.
    \n\n
    \n
    >>> Version("1.2.3").micro\n3\n>>> Version("1").micro\n0\n
    \n
    \n", "annotation": ": int"}, "bioimageio.spec._internal.warning_levels": {"fullname": "bioimageio.spec._internal.warning_levels", "modulename": "bioimageio.spec._internal.warning_levels", "kind": "module", "doc": "
    \n"}, "bioimageio.spec._internal.warning_levels.WarningSeverity": {"fullname": "bioimageio.spec._internal.warning_levels.WarningSeverity", "modulename": "bioimageio.spec._internal.warning_levels", "qualname": "WarningSeverity", "kind": "variable", "doc": "
    \n", "default_value": "typing.Literal[20, 30, 35]"}, "bioimageio.spec._internal.warning_levels.WarningLevel": {"fullname": "bioimageio.spec._internal.warning_levels.WarningLevel", "modulename": "bioimageio.spec._internal.warning_levels", "qualname": "WarningLevel", "kind": "variable", "doc": "
    With warning level x validation warnings of severity >=x are raised.\nHighest warning level 50/error does not raise any validaiton warnings (only validation errors).
    \n", "default_value": "typing.Literal[20, 30, 35, 50]"}, "bioimageio.spec.application": {"fullname": "bioimageio.spec.application", "modulename": "bioimageio.spec.application", "kind": "module", "doc": "
    implementaions of all released minor versions are available in submodules:
    \n\n\n"}, "bioimageio.spec.application.AnyApplicationDescr": {"fullname": "bioimageio.spec.application.AnyApplicationDescr", "modulename": "bioimageio.spec.application", "qualname": "AnyApplicationDescr", "kind": "variable", "doc": "
    Union of any released application desription
    \n", "default_value": "typing.Annotated[typing.Union[bioimageio.spec.application.v0_2.ApplicationDescr, bioimageio.spec.application.v0_3.ApplicationDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)]"}, "bioimageio.spec.application.v0_2": {"fullname": "bioimageio.spec.application.v0_2", "modulename": "bioimageio.spec.application.v0_2", "kind": "module", "doc": "
    \n"}, "bioimageio.spec.application.v0_2.ApplicationDescr": {"fullname": "bioimageio.spec.application.v0_2.ApplicationDescr", "modulename": "bioimageio.spec.application.v0_2", "qualname": "ApplicationDescr", "kind": "class", "doc": "
    Bioimage.io description of an application.
    \n", "bases": "bioimageio.spec.generic.v0_2.GenericDescrBase"}, "bioimageio.spec.application.v0_2.ApplicationDescr.type": {"fullname": "bioimageio.spec.application.v0_2.ApplicationDescr.type", "modulename": "bioimageio.spec.application.v0_2", "qualname": "ApplicationDescr.type", "kind": "variable", "doc": "
    \n", "annotation": ": Literal['application']"}, "bioimageio.spec.application.v0_2.ApplicationDescr.id": {"fullname": "bioimageio.spec.application.v0_2.ApplicationDescr.id", "modulename": "bioimageio.spec.application.v0_2", "qualname": "ApplicationDescr.id", "kind": "variable", "doc": "
    Model zoo (bioimage.io) wide, unique identifier (assigned by bioimage.io)
    \n", "annotation": ": Optional[bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]]]"}, "bioimageio.spec.application.v0_2.ApplicationDescr.source": {"fullname": "bioimageio.spec.application.v0_2.ApplicationDescr.source", "modulename": "bioimageio.spec.application.v0_2", "qualname": "ApplicationDescr.source", "kind": "variable", "doc": "
    The primary source of the application
    \n", "annotation": ": Annotated[Optional[Annotated[Union[Annotated[pathlib.Path, PathType(path_type='file')], bioimageio.spec._internal.io.RelativeFilePath, bioimageio.spec._internal.url.HttpUrl, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator(func=<function wo_special_file_name at 0x7f1c21c3ef20>), PlainSerializer(func=<function _package at 0x7f1c21c782c0>, return_type=PydanticUndefined, when_used='unless-none')]], FieldInfo(annotation=NoneType, required=True, description='URL or path to the source of the application')]"}, "bioimageio.spec.application.v0_2.ApplicationDescr.implemented_format_version": {"fullname": "bioimageio.spec.application.v0_2.ApplicationDescr.implemented_format_version", "modulename": "bioimageio.spec.application.v0_2", "qualname": "ApplicationDescr.implemented_format_version", "kind": "variable", "doc": "
    \n", "annotation": ": ClassVar[str]", "default_value": "'0.2.4'"}, "bioimageio.spec.application.v0_2.ApplicationDescr.implemented_format_version_tuple": {"fullname": "bioimageio.spec.application.v0_2.ApplicationDescr.implemented_format_version_tuple", "modulename": "bioimageio.spec.application.v0_2", "qualname": "ApplicationDescr.implemented_format_version_tuple", "kind": "variable", "doc": "
    \n", "annotation": ": ClassVar[Tuple[int, int, int]]", "default_value": "(0, 2, 4)"}, "bioimageio.spec.application.v0_2.ApplicationDescr.model_config": {"fullname": "bioimageio.spec.application.v0_2.ApplicationDescr.model_config", "modulename": "bioimageio.spec.application.v0_2", "qualname": "ApplicationDescr.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True, 'title': 'bioimage.io application specification'}"}, "bioimageio.spec.application.v0_2.ApplicationDescr.model_fields": {"fullname": "bioimageio.spec.application.v0_2.ApplicationDescr.model_fields", "modulename": "bioimageio.spec.application.v0_2", "qualname": "ApplicationDescr.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'name': FieldInfo(annotation=str, required=True, metadata=[MinLen(min_length=1), AfterWarner(func=<function as_warning.<locals>.wrapper>, severity=30, msg='Longer than 128 characters.', context={'typ': typing.Annotated[typing.Any, MaxLen(max_length=128)]})]), 'description': FieldInfo(annotation=str, required=True), 'covers': FieldInfo(annotation=List[Annotated[Union[HttpUrl, Annotated[Path, PathType, Predicate], RelativeFilePath], WithSuffix, PlainSerializer]], required=False, default_factory=list, description="Cover images. Please use an image smaller than 500KB and an aspect ratio width to height of 2:1.\\nThe supported image formats are: ('.gif', '.jpeg', '.jpg', '.png', '.svg')", examples=['cover.png']), 'id_emoji': FieldInfo(annotation=Union[Annotated[str, Len], NoneType], required=False), 'authors': FieldInfo(annotation=List[Author], required=False, default_factory=list), 'attachments': FieldInfo(annotation=Union[AttachmentsDescr, NoneType], required=False), 'cite': FieldInfo(annotation=List[CiteEntry], required=False, default_factory=list), 'config': FieldInfo(annotation=Dict[str, YamlValue], required=False, default_factory=dict, examples=[{'bioimageio': {'my_custom_key': 3837283, 'another_key': {'nested': 'value'}}, 'imagej': {'macro_dir': 'path/to/macro/file'}}]), 'download_url': FieldInfo(annotation=Union[HttpUrl, NoneType], required=False), 'git_repo': FieldInfo(annotation=Union[str, NoneType], required=False, examples=['https://github.com/bioimage-io/spec-bioimage-io/tree/main/example_descriptions/models/unet2d_nuclei_broad']), 'icon': FieldInfo(annotation=Union[Annotated[Union[Annotated[Path, PathType], RelativeFilePath, HttpUrl, Annotated[Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator, PlainSerializer], Annotated[str, Len], NoneType], required=False), 'links': FieldInfo(annotation=List[str], required=False, default_factory=list, examples=[('ilastik/ilastik', 'deepimagej/deepimagej', 'zero/notebook_u-net_3d_zerocostdl4mic')]), 'uploader': FieldInfo(annotation=Union[Uploader, NoneType], required=False), 'maintainers': FieldInfo(annotation=List[Maintainer], required=False, default_factory=list), 'rdf_source': FieldInfo(annotation=Union[Annotated[Path, PathType], RelativeFilePath, HttpUrl, Annotated[Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)], NoneType], required=False), 'tags': FieldInfo(annotation=List[str], required=False, default_factory=list, examples=[('unet2d', 'pytorch', 'nucleus', 'segmentation', 'dsb2018')]), 'version': FieldInfo(annotation=Union[Version, NoneType], required=False), 'version_number': FieldInfo(annotation=Union[int, NoneType], required=False), 'format_version': FieldInfo(annotation=Literal['0.2.4'], required=False, default='0.2.4'), 'badges': FieldInfo(annotation=List[BadgeDescr], required=False, default_factory=list), 'documentation': FieldInfo(annotation=Union[Annotated[Union[Annotated[Path, PathType], RelativeFilePath, HttpUrl, Annotated[Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator, PlainSerializer], NoneType], required=False, examples=['https://raw.githubusercontent.com/bioimage-io/spec-bioimage-io/main/example_descriptions/models/unet2d_nuclei_broad/README.md', 'README.md']), 'license': FieldInfo(annotation=Union[LicenseId, DeprecatedLicenseId, str, NoneType], required=False, examples=['CC-BY-4.0', 'MIT', 'BSD-2-Clause']), 'type': FieldInfo(annotation=Literal['application'], required=False, default='application'), 'id': FieldInfo(annotation=Union[ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]], NoneType], required=False), 'source': FieldInfo(annotation=Union[Annotated[Union[Annotated[Path, PathType], RelativeFilePath, HttpUrl, Annotated[Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator, PlainSerializer], NoneType], required=False, description='URL or path to the source of the application')}"}, "bioimageio.spec.application.v0_2.ApplicationDescr.model_computed_fields": {"fullname": "bioimageio.spec.application.v0_2.ApplicationDescr.model_computed_fields", "modulename": "bioimageio.spec.application.v0_2", "qualname": "ApplicationDescr.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.application.v0_2.LinkedApplication": {"fullname": "bioimageio.spec.application.v0_2.LinkedApplication", "modulename": "bioimageio.spec.application.v0_2", "qualname": "LinkedApplication", "kind": "class", "doc": "
    Reference to a bioimage.io application.
    \n", "bases": "bioimageio.spec._internal.node.Node"}, "bioimageio.spec.application.v0_2.LinkedApplication.id": {"fullname": "bioimageio.spec.application.v0_2.LinkedApplication.id", "modulename": "bioimageio.spec.application.v0_2", "qualname": "LinkedApplication.id", "kind": "variable", "doc": "
    A valid application id from the bioimage.io collection.
    \n", "annotation": ": bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]]"}, "bioimageio.spec.application.v0_2.LinkedApplication.version_number": {"fullname": "bioimageio.spec.application.v0_2.LinkedApplication.version_number", "modulename": "bioimageio.spec.application.v0_2", "qualname": "LinkedApplication.version_number", "kind": "variable", "doc": "
    version number (n-th published version, not the semantic version) of linked application
    \n", "annotation": ": Optional[int]"}, "bioimageio.spec.application.v0_2.LinkedApplication.model_config": {"fullname": "bioimageio.spec.application.v0_2.LinkedApplication.model_config", "modulename": "bioimageio.spec.application.v0_2", "qualname": "LinkedApplication.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.application.v0_2.LinkedApplication.model_fields": {"fullname": "bioimageio.spec.application.v0_2.LinkedApplication.model_fields", "modulename": "bioimageio.spec.application.v0_2", "qualname": "LinkedApplication.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'id': FieldInfo(annotation=ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]], required=True), 'version_number': FieldInfo(annotation=Union[int, NoneType], required=False)}"}, "bioimageio.spec.application.v0_2.LinkedApplication.model_computed_fields": {"fullname": "bioimageio.spec.application.v0_2.LinkedApplication.model_computed_fields", "modulename": "bioimageio.spec.application.v0_2", "qualname": "LinkedApplication.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.application.v0_3": {"fullname": "bioimageio.spec.application.v0_3", "modulename": "bioimageio.spec.application.v0_3", "kind": "module", "doc": "
    \n"}, "bioimageio.spec.application.v0_3.ApplicationDescr": {"fullname": "bioimageio.spec.application.v0_3.ApplicationDescr", "modulename": "bioimageio.spec.application.v0_3", "qualname": "ApplicationDescr", "kind": "class", "doc": "
    Bioimage.io description of an application.
    \n", "bases": "bioimageio.spec.generic.v0_3.GenericDescrBase"}, "bioimageio.spec.application.v0_3.ApplicationDescr.type": {"fullname": "bioimageio.spec.application.v0_3.ApplicationDescr.type", "modulename": "bioimageio.spec.application.v0_3", "qualname": "ApplicationDescr.type", "kind": "variable", "doc": "
    \n", "annotation": ": Literal['application']"}, "bioimageio.spec.application.v0_3.ApplicationDescr.id": {"fullname": "bioimageio.spec.application.v0_3.ApplicationDescr.id", "modulename": "bioimageio.spec.application.v0_3", "qualname": "ApplicationDescr.id", "kind": "variable", "doc": "
    Model zoo (bioimage.io) wide, unique identifier (assigned by bioimage.io)
    \n", "annotation": ": Optional[bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]]]"}, "bioimageio.spec.application.v0_3.ApplicationDescr.parent": {"fullname": "bioimageio.spec.application.v0_3.ApplicationDescr.parent", "modulename": "bioimageio.spec.application.v0_3", "qualname": "ApplicationDescr.parent", "kind": "variable", "doc": "
    The description from which this one is derived
    \n", "annotation": ": Optional[bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]]]"}, "bioimageio.spec.application.v0_3.ApplicationDescr.source": {"fullname": "bioimageio.spec.application.v0_3.ApplicationDescr.source", "modulename": "bioimageio.spec.application.v0_3", "qualname": "ApplicationDescr.source", "kind": "variable", "doc": "
    The primary source of the application
    \n", "annotation": ": Annotated[Optional[Annotated[Union[Annotated[pathlib.Path, PathType(path_type='file')], bioimageio.spec._internal.io.RelativeFilePath, bioimageio.spec._internal.url.HttpUrl, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator(func=<function wo_special_file_name at 0x7f1c21c3ef20>), PlainSerializer(func=<function _package at 0x7f1c21c782c0>, return_type=PydanticUndefined, when_used='unless-none')]], FieldInfo(annotation=NoneType, required=True, description='URL or path to the source of the application')]"}, "bioimageio.spec.application.v0_3.ApplicationDescr.implemented_format_version": {"fullname": "bioimageio.spec.application.v0_3.ApplicationDescr.implemented_format_version", "modulename": "bioimageio.spec.application.v0_3", "qualname": "ApplicationDescr.implemented_format_version", "kind": "variable", "doc": "
    \n", "annotation": ": ClassVar[str]", "default_value": "'0.3.0'"}, "bioimageio.spec.application.v0_3.ApplicationDescr.implemented_format_version_tuple": {"fullname": "bioimageio.spec.application.v0_3.ApplicationDescr.implemented_format_version_tuple", "modulename": "bioimageio.spec.application.v0_3", "qualname": "ApplicationDescr.implemented_format_version_tuple", "kind": "variable", "doc": "
    \n", "annotation": ": ClassVar[Tuple[int, int, int]]", "default_value": "(0, 3, 0)"}, "bioimageio.spec.application.v0_3.ApplicationDescr.model_config": {"fullname": "bioimageio.spec.application.v0_3.ApplicationDescr.model_config", "modulename": "bioimageio.spec.application.v0_3", "qualname": "ApplicationDescr.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True, 'title': 'bioimage.io application specification'}"}, "bioimageio.spec.application.v0_3.ApplicationDescr.model_fields": {"fullname": "bioimageio.spec.application.v0_3.ApplicationDescr.model_fields", "modulename": "bioimageio.spec.application.v0_3", "qualname": "ApplicationDescr.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'name': FieldInfo(annotation=str, required=True, metadata=[MinLen(min_length=1), MaxLen(max_length=128)]), 'description': FieldInfo(annotation=str, required=True, metadata=[MaxLen(max_length=1024), AfterWarner(func=<function as_warning.<locals>.wrapper>, severity=30, msg='Description longer than 512 characters.', context={'typ': typing.Annotated[typing.Any, MaxLen(max_length=512)]})]), 'covers': FieldInfo(annotation=List[Annotated[Union[HttpUrl, Annotated[Path, PathType, Predicate], RelativeFilePath], WithSuffix, PlainSerializer]], required=False, default_factory=list, description="Cover images. Please use an image smaller than 500KB and an aspect ratio width to height of 2:1 or 1:1.\\nThe supported image formats are: ('.gif', '.jpeg', '.jpg', '.png', '.svg')", examples=[]), 'id_emoji': FieldInfo(annotation=Union[Annotated[str, Len], NoneType], required=False), 'authors': FieldInfo(annotation=List[Author], required=True, metadata=[MinLen(min_length=1)]), 'attachments': FieldInfo(annotation=List[FileDescr], required=False, default_factory=list), 'cite': FieldInfo(annotation=List[CiteEntry], required=True, metadata=[MinLen(min_length=1)]), 'license': FieldInfo(annotation=Union[LicenseId, DeprecatedLicenseId], required=True, examples=['CC-BY-4.0', 'MIT', 'BSD-2-Clause'], metadata=[AfterWarner(func=<function as_warning.<locals>.wrapper>, severity=30, msg='{value} is deprecated, see https://spdx.org/licenses/{value}.html', context={'typ': <class 'bioimageio.spec._internal.license_id.LicenseId'>})]), 'config': FieldInfo(annotation=Dict[str, YamlValue], required=False, default_factory=dict, examples=[{'bioimageio': {'my_custom_key': 3837283, 'another_key': {'nested': 'value'}}, 'imagej': {'macro_dir': 'path/to/macro/file'}}]), 'git_repo': FieldInfo(annotation=Union[HttpUrl, NoneType], required=False, examples=['https://github.com/bioimage-io/spec-bioimage-io/tree/main/example_descriptions/models/unet2d_nuclei_broad']), 'icon': FieldInfo(annotation=Union[Annotated[Union[Annotated[Path, PathType], RelativeFilePath, HttpUrl, Annotated[Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator, PlainSerializer], Annotated[str, Len], NoneType], required=False), 'links': FieldInfo(annotation=List[str], required=False, default_factory=list, examples=[('ilastik/ilastik', 'deepimagej/deepimagej', 'zero/notebook_u-net_3d_zerocostdl4mic')]), 'uploader': FieldInfo(annotation=Union[Uploader, NoneType], required=False), 'maintainers': FieldInfo(annotation=List[Maintainer], required=False, default_factory=list), 'tags': FieldInfo(annotation=List[str], required=False, default_factory=list, examples=[('unet2d', 'pytorch', 'nucleus', 'segmentation', 'dsb2018')]), 'version': FieldInfo(annotation=Union[Version, NoneType], required=False), 'version_number': FieldInfo(annotation=Union[int, NoneType], required=False), 'format_version': FieldInfo(annotation=Literal['0.3.0'], required=False, default='0.3.0'), 'documentation': FieldInfo(annotation=Union[Annotated[Union[Annotated[Path, PathType, Predicate], RelativeFilePath, HttpUrl], AfterValidator, PlainSerializer], NoneType], required=False, examples=['https://raw.githubusercontent.com/bioimage-io/spec-bioimage-io/main/example_descriptions/models/unet2d_nuclei_broad/README.md', 'README.md']), 'badges': FieldInfo(annotation=List[BadgeDescr], required=False, default_factory=list), 'type': FieldInfo(annotation=Literal['application'], required=False, default='application'), 'id': FieldInfo(annotation=Union[ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]], NoneType], required=False), 'parent': FieldInfo(annotation=Union[ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]], NoneType], required=False), 'source': FieldInfo(annotation=Union[Annotated[Union[Annotated[Path, PathType], RelativeFilePath, HttpUrl, Annotated[Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator, PlainSerializer], NoneType], required=False, description='URL or path to the source of the application')}"}, "bioimageio.spec.application.v0_3.ApplicationDescr.model_computed_fields": {"fullname": "bioimageio.spec.application.v0_3.ApplicationDescr.model_computed_fields", "modulename": "bioimageio.spec.application.v0_3", "qualname": "ApplicationDescr.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.application.v0_3.LinkedApplication": {"fullname": "bioimageio.spec.application.v0_3.LinkedApplication", "modulename": "bioimageio.spec.application.v0_3", "qualname": "LinkedApplication", "kind": "class", "doc": "
    Reference to a bioimage.io application.
    \n", "bases": "bioimageio.spec._internal.node.Node"}, "bioimageio.spec.application.v0_3.LinkedApplication.id": {"fullname": "bioimageio.spec.application.v0_3.LinkedApplication.id", "modulename": "bioimageio.spec.application.v0_3", "qualname": "LinkedApplication.id", "kind": "variable", "doc": "
    A valid application id from the bioimage.io collection.
    \n", "annotation": ": bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]]"}, "bioimageio.spec.application.v0_3.LinkedApplication.version_number": {"fullname": "bioimageio.spec.application.v0_3.LinkedApplication.version_number", "modulename": "bioimageio.spec.application.v0_3", "qualname": "LinkedApplication.version_number", "kind": "variable", "doc": "
    version number (n-th published version, not the semantic version) of linked application
    \n", "annotation": ": int"}, "bioimageio.spec.application.v0_3.LinkedApplication.model_config": {"fullname": "bioimageio.spec.application.v0_3.LinkedApplication.model_config", "modulename": "bioimageio.spec.application.v0_3", "qualname": "LinkedApplication.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.application.v0_3.LinkedApplication.model_fields": {"fullname": "bioimageio.spec.application.v0_3.LinkedApplication.model_fields", "modulename": "bioimageio.spec.application.v0_3", "qualname": "LinkedApplication.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'id': FieldInfo(annotation=ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]], required=True), 'version_number': FieldInfo(annotation=int, required=True)}"}, "bioimageio.spec.application.v0_3.LinkedApplication.model_computed_fields": {"fullname": "bioimageio.spec.application.v0_3.LinkedApplication.model_computed_fields", "modulename": "bioimageio.spec.application.v0_3", "qualname": "LinkedApplication.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.collection": {"fullname": "bioimageio.spec.collection", "modulename": "bioimageio.spec.collection", "kind": "module", "doc": "
    implementaions of all released minor versions are available in submodules:
    \n\n\n"}, "bioimageio.spec.collection.AnyCollectionDescr": {"fullname": "bioimageio.spec.collection.AnyCollectionDescr", "modulename": "bioimageio.spec.collection", "qualname": "AnyCollectionDescr", "kind": "variable", "doc": "
    Union of any released collection desription
    \n", "default_value": "typing.Annotated[typing.Union[bioimageio.spec.collection.v0_2.CollectionDescr, bioimageio.spec.collection.v0_3.CollectionDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)]"}, "bioimageio.spec.collection.v0_2": {"fullname": "bioimageio.spec.collection.v0_2", "modulename": "bioimageio.spec.collection.v0_2", "kind": "module", "doc": "
    \n"}, "bioimageio.spec.collection.v0_2.EntryDescr": {"fullname": "bioimageio.spec.collection.v0_2.EntryDescr", "modulename": "bioimageio.spec.collection.v0_2", "qualname": "EntryDescr", "kind": "variable", "doc": "
    \n", "default_value": "typing.Union[bioimageio.spec.application.v0_2.ApplicationDescr, bioimageio.spec.dataset.v0_2.DatasetDescr, bioimageio.spec.generic.v0_2.GenericDescr, bioimageio.spec.model.v0_4.ModelDescr, bioimageio.spec.notebook.v0_2.NotebookDescr]"}, "bioimageio.spec.collection.v0_2.CollectionEntry": {"fullname": "bioimageio.spec.collection.v0_2.CollectionEntry", "modulename": "bioimageio.spec.collection.v0_2", "qualname": "CollectionEntry", "kind": "class", "doc": "
    A valid resource description (RD).\nThe entry RD is based on the collection description itself.\nFields are added/overwritten by the content of rdf_source if rdf_source is specified,\nand finally added/overwritten by any fields specified directly in the entry.\nExcept for the id field, fields are overwritten entirely, their content is not merged!\nThe final id for each collection entry is composed of the collection's id\nand the entry's 'sub-'id, specified remotely as part of rdf_source or superseeded in-place,\nsuch that the final_entry_id = <collection_id>/<entry_id>
    \n", "bases": "bioimageio.spec._internal.node.Node"}, "bioimageio.spec.collection.v0_2.CollectionEntry.rdf_source": {"fullname": "bioimageio.spec.collection.v0_2.CollectionEntry.rdf_source", "modulename": "bioimageio.spec.collection.v0_2", "qualname": "CollectionEntry.rdf_source", "kind": "variable", "doc": "
    resource description file (RDF) source to load entry from
    \n", "annotation": ": Union[Annotated[pathlib.Path, PathType(path_type='file')], bioimageio.spec._internal.io.RelativeFilePath, bioimageio.spec._internal.url.HttpUrl, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)], NoneType]"}, "bioimageio.spec.collection.v0_2.CollectionEntry.id": {"fullname": "bioimageio.spec.collection.v0_2.CollectionEntry.id", "modulename": "bioimageio.spec.collection.v0_2", "qualname": "CollectionEntry.id", "kind": "variable", "doc": "
    Collection entry sub id overwriting rdf_source.id.\nThe full collection entry's id is the collection's base id, followed by this sub id and separated by a slash '/'.
    \n", "annotation": ": Optional[bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]]]"}, "bioimageio.spec.collection.v0_2.CollectionEntry.rdf_update": {"fullname": "bioimageio.spec.collection.v0_2.CollectionEntry.rdf_update", "modulename": "bioimageio.spec.collection.v0_2", "qualname": "CollectionEntry.rdf_update", "kind": "variable", "doc": "
    \n", "annotation": ": Dict[str, YamlValue]"}, "bioimageio.spec.collection.v0_2.CollectionEntry.descr": {"fullname": "bioimageio.spec.collection.v0_2.CollectionEntry.descr", "modulename": "bioimageio.spec.collection.v0_2", "qualname": "CollectionEntry.descr", "kind": "variable", "doc": "
    \n", "annotation": ": Union[bioimageio.spec.application.v0_2.ApplicationDescr, bioimageio.spec.dataset.v0_2.DatasetDescr, bioimageio.spec.generic.v0_2.GenericDescr, bioimageio.spec.model.v0_4.ModelDescr, bioimageio.spec.notebook.v0_2.NotebookDescr, NoneType]"}, "bioimageio.spec.collection.v0_2.CollectionEntry.model_config": {"fullname": "bioimageio.spec.collection.v0_2.CollectionEntry.model_config", "modulename": "bioimageio.spec.collection.v0_2", "qualname": "CollectionEntry.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'allow', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.collection.v0_2.CollectionEntry.model_post_init": {"fullname": "bioimageio.spec.collection.v0_2.CollectionEntry.model_post_init", "modulename": "bioimageio.spec.collection.v0_2", "qualname": "CollectionEntry.model_post_init", "kind": "function", "doc": "
    This function is meant to behave like a BaseModel method to initialise private attributes.
    \n\n
    It takes context as an argument since that's what pydantic-core passes when calling it.
    \n\n
    Args:\n    self: The BaseModel instance.\n    __context: The context.
    \n", "signature": "(self: pydantic.main.BaseModel, __context: Any) -> None:", "funcdef": "def"}, "bioimageio.spec.collection.v0_2.CollectionEntry.model_fields": {"fullname": "bioimageio.spec.collection.v0_2.CollectionEntry.model_fields", "modulename": "bioimageio.spec.collection.v0_2", "qualname": "CollectionEntry.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'rdf_source': FieldInfo(annotation=Union[Annotated[Path, PathType], RelativeFilePath, HttpUrl, Annotated[Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)], NoneType], required=False), 'id': FieldInfo(annotation=Union[ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]], NoneType], required=False)}"}, "bioimageio.spec.collection.v0_2.CollectionEntry.model_computed_fields": {"fullname": "bioimageio.spec.collection.v0_2.CollectionEntry.model_computed_fields", "modulename": "bioimageio.spec.collection.v0_2", "qualname": "CollectionEntry.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.collection.v0_2.CollectionDescr": {"fullname": "bioimageio.spec.collection.v0_2.CollectionDescr", "modulename": "bioimageio.spec.collection.v0_2", "qualname": "CollectionDescr", "kind": "class", "doc": "
    A bioimage.io collection describes several other bioimage.io resources.\nNote that collections cannot be nested; resources listed under collection may not be collections themselves.
    \n", "bases": "bioimageio.spec.generic.v0_2.GenericDescrBase"}, "bioimageio.spec.collection.v0_2.CollectionDescr.type": {"fullname": "bioimageio.spec.collection.v0_2.CollectionDescr.type", "modulename": "bioimageio.spec.collection.v0_2", "qualname": "CollectionDescr.type", "kind": "variable", "doc": "
    \n", "annotation": ": Literal['collection']"}, "bioimageio.spec.collection.v0_2.CollectionDescr.id": {"fullname": "bioimageio.spec.collection.v0_2.CollectionDescr.id", "modulename": "bioimageio.spec.collection.v0_2", "qualname": "CollectionDescr.id", "kind": "variable", "doc": "
    Model zoo (bioimage.io) wide, unique identifier (assigned by bioimage.io)
    \n", "annotation": ": Optional[bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]]]"}, "bioimageio.spec.collection.v0_2.CollectionDescr.collection": {"fullname": "bioimageio.spec.collection.v0_2.CollectionDescr.collection", "modulename": "bioimageio.spec.collection.v0_2", "qualname": "CollectionDescr.collection", "kind": "variable", "doc": "
    Collection entries
    \n", "annotation": ": Annotated[List[bioimageio.spec.collection.v0_2.CollectionEntry], MinLen(min_length=1)]"}, "bioimageio.spec.collection.v0_2.CollectionDescr.finalize_entries": {"fullname": "bioimageio.spec.collection.v0_2.CollectionDescr.finalize_entries", "modulename": "bioimageio.spec.collection.v0_2", "qualname": "CollectionDescr.finalize_entries", "kind": "function", "doc": "
    \n", "signature": "(self) -> Self:", "funcdef": "def"}, "bioimageio.spec.collection.v0_2.CollectionDescr.move_groups_to_collection_field": {"fullname": "bioimageio.spec.collection.v0_2.CollectionDescr.move_groups_to_collection_field", "modulename": "bioimageio.spec.collection.v0_2", "qualname": "CollectionDescr.move_groups_to_collection_field", "kind": "function", "doc": "
    \n", "signature": "(cls, data: Dict[str, YamlValue]) -> Dict[str, YamlValue]:", "funcdef": "def"}, "bioimageio.spec.collection.v0_2.CollectionDescr.implemented_format_version": {"fullname": "bioimageio.spec.collection.v0_2.CollectionDescr.implemented_format_version", "modulename": "bioimageio.spec.collection.v0_2", "qualname": "CollectionDescr.implemented_format_version", "kind": "variable", "doc": "
    \n", "annotation": ": ClassVar[str]", "default_value": "'0.2.4'"}, "bioimageio.spec.collection.v0_2.CollectionDescr.implemented_format_version_tuple": {"fullname": "bioimageio.spec.collection.v0_2.CollectionDescr.implemented_format_version_tuple", "modulename": "bioimageio.spec.collection.v0_2", "qualname": "CollectionDescr.implemented_format_version_tuple", "kind": "variable", "doc": "
    \n", "annotation": ": ClassVar[Tuple[int, int, int]]", "default_value": "(0, 2, 4)"}, "bioimageio.spec.collection.v0_2.CollectionDescr.model_config": {"fullname": "bioimageio.spec.collection.v0_2.CollectionDescr.model_config", "modulename": "bioimageio.spec.collection.v0_2", "qualname": "CollectionDescr.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'allow', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True, 'title': 'bioimage.io collection specification'}"}, "bioimageio.spec.collection.v0_2.CollectionDescr.model_fields": {"fullname": "bioimageio.spec.collection.v0_2.CollectionDescr.model_fields", "modulename": "bioimageio.spec.collection.v0_2", "qualname": "CollectionDescr.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'name': FieldInfo(annotation=str, required=True, metadata=[MinLen(min_length=1), AfterWarner(func=<function as_warning.<locals>.wrapper>, severity=30, msg='Longer than 128 characters.', context={'typ': typing.Annotated[typing.Any, MaxLen(max_length=128)]})]), 'description': FieldInfo(annotation=str, required=True), 'covers': FieldInfo(annotation=List[Annotated[Union[HttpUrl, Annotated[Path, PathType, Predicate], RelativeFilePath], WithSuffix, PlainSerializer]], required=False, default_factory=list, description="Cover images. Please use an image smaller than 500KB and an aspect ratio width to height of 2:1.\\nThe supported image formats are: ('.gif', '.jpeg', '.jpg', '.png', '.svg')", examples=['cover.png']), 'id_emoji': FieldInfo(annotation=Union[Annotated[str, Len], NoneType], required=False), 'authors': FieldInfo(annotation=List[Author], required=False, default_factory=list), 'attachments': FieldInfo(annotation=Union[AttachmentsDescr, NoneType], required=False), 'cite': FieldInfo(annotation=List[CiteEntry], required=False, default_factory=list), 'config': FieldInfo(annotation=Dict[str, YamlValue], required=False, default_factory=dict, examples=[{'bioimageio': {'my_custom_key': 3837283, 'another_key': {'nested': 'value'}}, 'imagej': {'macro_dir': 'path/to/macro/file'}}]), 'download_url': FieldInfo(annotation=Union[HttpUrl, NoneType], required=False), 'git_repo': FieldInfo(annotation=Union[str, NoneType], required=False, examples=['https://github.com/bioimage-io/spec-bioimage-io/tree/main/example_descriptions/models/unet2d_nuclei_broad']), 'icon': FieldInfo(annotation=Union[Annotated[Union[Annotated[Path, PathType], RelativeFilePath, HttpUrl, Annotated[Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator, PlainSerializer], Annotated[str, Len], NoneType], required=False), 'links': FieldInfo(annotation=List[str], required=False, default_factory=list, examples=[('ilastik/ilastik', 'deepimagej/deepimagej', 'zero/notebook_u-net_3d_zerocostdl4mic')]), 'uploader': FieldInfo(annotation=Union[Uploader, NoneType], required=False), 'maintainers': FieldInfo(annotation=List[Maintainer], required=False, default_factory=list), 'rdf_source': FieldInfo(annotation=Union[Annotated[Path, PathType], RelativeFilePath, HttpUrl, Annotated[Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)], NoneType], required=False), 'tags': FieldInfo(annotation=List[str], required=False, default_factory=list, examples=[('unet2d', 'pytorch', 'nucleus', 'segmentation', 'dsb2018')]), 'version': FieldInfo(annotation=Union[Version, NoneType], required=False), 'version_number': FieldInfo(annotation=Union[int, NoneType], required=False), 'format_version': FieldInfo(annotation=Literal['0.2.4'], required=False, default='0.2.4'), 'badges': FieldInfo(annotation=List[BadgeDescr], required=False, default_factory=list), 'documentation': FieldInfo(annotation=Union[Annotated[Union[Annotated[Path, PathType], RelativeFilePath, HttpUrl, Annotated[Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator, PlainSerializer], NoneType], required=False, examples=['https://raw.githubusercontent.com/bioimage-io/spec-bioimage-io/main/example_descriptions/models/unet2d_nuclei_broad/README.md', 'README.md']), 'license': FieldInfo(annotation=Union[LicenseId, DeprecatedLicenseId, str, NoneType], required=False, examples=['CC-BY-4.0', 'MIT', 'BSD-2-Clause']), 'type': FieldInfo(annotation=Literal['collection'], required=False, default='collection'), 'id': FieldInfo(annotation=Union[ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]], NoneType], required=False), 'collection': FieldInfo(annotation=List[CollectionEntry], required=True, metadata=[MinLen(min_length=1)])}"}, "bioimageio.spec.collection.v0_2.CollectionDescr.model_computed_fields": {"fullname": "bioimageio.spec.collection.v0_2.CollectionDescr.model_computed_fields", "modulename": "bioimageio.spec.collection.v0_2", "qualname": "CollectionDescr.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.collection.v0_2.LinkedCollection": {"fullname": "bioimageio.spec.collection.v0_2.LinkedCollection", "modulename": "bioimageio.spec.collection.v0_2", "qualname": "LinkedCollection", "kind": "class", "doc": "
    Reference to a bioimage.io collection.
    \n", "bases": "bioimageio.spec._internal.node.Node"}, "bioimageio.spec.collection.v0_2.LinkedCollection.id": {"fullname": "bioimageio.spec.collection.v0_2.LinkedCollection.id", "modulename": "bioimageio.spec.collection.v0_2", "qualname": "LinkedCollection.id", "kind": "variable", "doc": "
    A valid collection id from the bioimage.io collection.
    \n", "annotation": ": bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]]"}, "bioimageio.spec.collection.v0_2.LinkedCollection.version_number": {"fullname": "bioimageio.spec.collection.v0_2.LinkedCollection.version_number", "modulename": "bioimageio.spec.collection.v0_2", "qualname": "LinkedCollection.version_number", "kind": "variable", "doc": "
    version number (n-th published version, not the semantic version) of linked collection
    \n", "annotation": ": Optional[int]"}, "bioimageio.spec.collection.v0_2.LinkedCollection.model_config": {"fullname": "bioimageio.spec.collection.v0_2.LinkedCollection.model_config", "modulename": "bioimageio.spec.collection.v0_2", "qualname": "LinkedCollection.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.collection.v0_2.LinkedCollection.model_fields": {"fullname": "bioimageio.spec.collection.v0_2.LinkedCollection.model_fields", "modulename": "bioimageio.spec.collection.v0_2", "qualname": "LinkedCollection.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'id': FieldInfo(annotation=ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]], required=True), 'version_number': FieldInfo(annotation=Union[int, NoneType], required=False)}"}, "bioimageio.spec.collection.v0_2.LinkedCollection.model_computed_fields": {"fullname": "bioimageio.spec.collection.v0_2.LinkedCollection.model_computed_fields", "modulename": "bioimageio.spec.collection.v0_2", "qualname": "LinkedCollection.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.collection.v0_3": {"fullname": "bioimageio.spec.collection.v0_3", "modulename": "bioimageio.spec.collection.v0_3", "kind": "module", "doc": "
    \n"}, "bioimageio.spec.collection.v0_3.EntryDescr": {"fullname": "bioimageio.spec.collection.v0_3.EntryDescr", "modulename": "bioimageio.spec.collection.v0_3", "qualname": "EntryDescr", "kind": "variable", "doc": "
    \n", "default_value": "typing.Union[bioimageio.spec.application.v0_2.ApplicationDescr, bioimageio.spec.application.v0_3.ApplicationDescr, bioimageio.spec.dataset.v0_2.DatasetDescr, bioimageio.spec.dataset.v0_3.DatasetDescr, bioimageio.spec.model.v0_4.ModelDescr, bioimageio.spec.model.v0_5.ModelDescr, bioimageio.spec.notebook.v0_2.NotebookDescr, bioimageio.spec.notebook.v0_3.NotebookDescr, bioimageio.spec.generic.v0_2.GenericDescr, bioimageio.spec.generic.v0_3.GenericDescr]"}, "bioimageio.spec.collection.v0_3.CollectionEntry": {"fullname": "bioimageio.spec.collection.v0_3.CollectionEntry", "modulename": "bioimageio.spec.collection.v0_3", "qualname": "CollectionEntry", "kind": "class", "doc": "
    A collection entry description is based on the collection description itself.\nFields are added/overwritten by the content of descr_source if descr_source is set,\nand finally added/overwritten by any fields specified directly in the entry.\nExcept for the id field, fields are overwritten entirely, their content is not merged!\nThe final id for each collection entry is composed of the collection's id\nand the entry's 'sub-'id, specified externally in descr_source or superseeded in-place,\nsuch that the final_entry_id = <collection_id>/<entry_id>
    \n", "bases": "bioimageio.spec._internal.node.Node"}, "bioimageio.spec.collection.v0_3.CollectionEntry.entry_source": {"fullname": "bioimageio.spec.collection.v0_3.CollectionEntry.entry_source", "modulename": "bioimageio.spec.collection.v0_3", "qualname": "CollectionEntry.entry_source", "kind": "variable", "doc": "
    an external source this entry description is based on
    \n", "annotation": ": Union[Annotated[pathlib.Path, PathType(path_type='file')], bioimageio.spec._internal.io.RelativeFilePath, bioimageio.spec._internal.url.HttpUrl, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)], NoneType]"}, "bioimageio.spec.collection.v0_3.CollectionEntry.id": {"fullname": "bioimageio.spec.collection.v0_3.CollectionEntry.id", "modulename": "bioimageio.spec.collection.v0_3", "qualname": "CollectionEntry.id", "kind": "variable", "doc": "
    Collection entry sub id overwriting rdf_source.id.\nThe full collection entry's id is the collection's base id, followed by this sub id and separated by a slash '/'.
    \n", "annotation": ": Optional[bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]]]"}, "bioimageio.spec.collection.v0_3.CollectionEntry.entry_update": {"fullname": "bioimageio.spec.collection.v0_3.CollectionEntry.entry_update", "modulename": "bioimageio.spec.collection.v0_3", "qualname": "CollectionEntry.entry_update", "kind": "variable", "doc": "
    \n", "annotation": ": Dict[str, YamlValue]"}, "bioimageio.spec.collection.v0_3.CollectionEntry.descr": {"fullname": "bioimageio.spec.collection.v0_3.CollectionEntry.descr", "modulename": "bioimageio.spec.collection.v0_3", "qualname": "CollectionEntry.descr", "kind": "variable", "doc": "
    \n", "annotation": ": Union[bioimageio.spec.application.v0_2.ApplicationDescr, bioimageio.spec.application.v0_3.ApplicationDescr, bioimageio.spec.dataset.v0_2.DatasetDescr, bioimageio.spec.dataset.v0_3.DatasetDescr, bioimageio.spec.model.v0_4.ModelDescr, bioimageio.spec.model.v0_5.ModelDescr, bioimageio.spec.notebook.v0_2.NotebookDescr, bioimageio.spec.notebook.v0_3.NotebookDescr, bioimageio.spec.generic.v0_2.GenericDescr, bioimageio.spec.generic.v0_3.GenericDescr, NoneType]"}, "bioimageio.spec.collection.v0_3.CollectionEntry.model_config": {"fullname": "bioimageio.spec.collection.v0_3.CollectionEntry.model_config", "modulename": "bioimageio.spec.collection.v0_3", "qualname": "CollectionEntry.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'allow', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.collection.v0_3.CollectionEntry.model_post_init": {"fullname": "bioimageio.spec.collection.v0_3.CollectionEntry.model_post_init", "modulename": "bioimageio.spec.collection.v0_3", "qualname": "CollectionEntry.model_post_init", "kind": "function", "doc": "
    This function is meant to behave like a BaseModel method to initialise private attributes.
    \n\n
    It takes context as an argument since that's what pydantic-core passes when calling it.
    \n\n
    Args:\n    self: The BaseModel instance.\n    __context: The context.
    \n", "signature": "(self: pydantic.main.BaseModel, __context: Any) -> None:", "funcdef": "def"}, "bioimageio.spec.collection.v0_3.CollectionEntry.model_fields": {"fullname": "bioimageio.spec.collection.v0_3.CollectionEntry.model_fields", "modulename": "bioimageio.spec.collection.v0_3", "qualname": "CollectionEntry.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'entry_source': FieldInfo(annotation=Union[Annotated[Path, PathType], RelativeFilePath, HttpUrl, Annotated[Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)], NoneType], required=False), 'id': FieldInfo(annotation=Union[ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]], NoneType], required=False)}"}, "bioimageio.spec.collection.v0_3.CollectionEntry.model_computed_fields": {"fullname": "bioimageio.spec.collection.v0_3.CollectionEntry.model_computed_fields", "modulename": "bioimageio.spec.collection.v0_3", "qualname": "CollectionEntry.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.collection.v0_3.CollectionDescr": {"fullname": "bioimageio.spec.collection.v0_3.CollectionDescr", "modulename": "bioimageio.spec.collection.v0_3", "qualname": "CollectionDescr", "kind": "class", "doc": "
    A bioimage.io collection resource description file (collection RDF) describes a collection of bioimage.io\nresources.\nThe resources listed in a collection RDF have types other than 'collection'; collections cannot be nested.
    \n", "bases": "bioimageio.spec.generic.v0_3.GenericDescrBase"}, "bioimageio.spec.collection.v0_3.CollectionDescr.type": {"fullname": "bioimageio.spec.collection.v0_3.CollectionDescr.type", "modulename": "bioimageio.spec.collection.v0_3", "qualname": "CollectionDescr.type", "kind": "variable", "doc": "
    \n", "annotation": ": Literal['collection']"}, "bioimageio.spec.collection.v0_3.CollectionDescr.id": {"fullname": "bioimageio.spec.collection.v0_3.CollectionDescr.id", "modulename": "bioimageio.spec.collection.v0_3", "qualname": "CollectionDescr.id", "kind": "variable", "doc": "
    Model zoo (bioimage.io) wide, unique identifier (assigned by bioimage.io)
    \n", "annotation": ": Optional[bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]]]"}, "bioimageio.spec.collection.v0_3.CollectionDescr.parent": {"fullname": "bioimageio.spec.collection.v0_3.CollectionDescr.parent", "modulename": "bioimageio.spec.collection.v0_3", "qualname": "CollectionDescr.parent", "kind": "variable", "doc": "
    The description from which this one is derived
    \n", "annotation": ": Optional[bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]]]"}, "bioimageio.spec.collection.v0_3.CollectionDescr.collection": {"fullname": "bioimageio.spec.collection.v0_3.CollectionDescr.collection", "modulename": "bioimageio.spec.collection.v0_3", "qualname": "CollectionDescr.collection", "kind": "variable", "doc": "
    Collection entries
    \n", "annotation": ": Annotated[List[bioimageio.spec.collection.v0_3.CollectionEntry], MinLen(min_length=1)]"}, "bioimageio.spec.collection.v0_3.CollectionDescr.finalize_entries": {"fullname": "bioimageio.spec.collection.v0_3.CollectionDescr.finalize_entries", "modulename": "bioimageio.spec.collection.v0_3", "qualname": "CollectionDescr.finalize_entries", "kind": "function", "doc": "
    \n", "signature": "(self) -> Self:", "funcdef": "def"}, "bioimageio.spec.collection.v0_3.CollectionDescr.implemented_format_version": {"fullname": "bioimageio.spec.collection.v0_3.CollectionDescr.implemented_format_version", "modulename": "bioimageio.spec.collection.v0_3", "qualname": "CollectionDescr.implemented_format_version", "kind": "variable", "doc": "
    \n", "annotation": ": ClassVar[str]", "default_value": "'0.3.0'"}, "bioimageio.spec.collection.v0_3.CollectionDescr.implemented_format_version_tuple": {"fullname": "bioimageio.spec.collection.v0_3.CollectionDescr.implemented_format_version_tuple", "modulename": "bioimageio.spec.collection.v0_3", "qualname": "CollectionDescr.implemented_format_version_tuple", "kind": "variable", "doc": "
    \n", "annotation": ": ClassVar[Tuple[int, int, int]]", "default_value": "(0, 3, 0)"}, "bioimageio.spec.collection.v0_3.CollectionDescr.model_config": {"fullname": "bioimageio.spec.collection.v0_3.CollectionDescr.model_config", "modulename": "bioimageio.spec.collection.v0_3", "qualname": "CollectionDescr.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'allow', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True, 'title': 'bioimage.io collection specification'}"}, "bioimageio.spec.collection.v0_3.CollectionDescr.model_fields": {"fullname": "bioimageio.spec.collection.v0_3.CollectionDescr.model_fields", "modulename": "bioimageio.spec.collection.v0_3", "qualname": "CollectionDescr.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'name': FieldInfo(annotation=str, required=True, metadata=[MinLen(min_length=1), MaxLen(max_length=128)]), 'description': FieldInfo(annotation=str, required=True, metadata=[MaxLen(max_length=1024), AfterWarner(func=<function as_warning.<locals>.wrapper>, severity=30, msg='Description longer than 512 characters.', context={'typ': typing.Annotated[typing.Any, MaxLen(max_length=512)]})]), 'covers': FieldInfo(annotation=List[Annotated[Union[HttpUrl, Annotated[Path, PathType, Predicate], RelativeFilePath], WithSuffix, PlainSerializer]], required=False, default_factory=list, description="Cover images. Please use an image smaller than 500KB and an aspect ratio width to height of 2:1 or 1:1.\\nThe supported image formats are: ('.gif', '.jpeg', '.jpg', '.png', '.svg')", examples=[]), 'id_emoji': FieldInfo(annotation=Union[Annotated[str, Len], NoneType], required=False), 'authors': FieldInfo(annotation=List[Author], required=True, metadata=[MinLen(min_length=1)]), 'attachments': FieldInfo(annotation=List[FileDescr], required=False, default_factory=list), 'cite': FieldInfo(annotation=List[CiteEntry], required=True, metadata=[MinLen(min_length=1)]), 'license': FieldInfo(annotation=Union[LicenseId, DeprecatedLicenseId], required=True, examples=['CC-BY-4.0', 'MIT', 'BSD-2-Clause'], metadata=[AfterWarner(func=<function as_warning.<locals>.wrapper>, severity=30, msg='{value} is deprecated, see https://spdx.org/licenses/{value}.html', context={'typ': <class 'bioimageio.spec._internal.license_id.LicenseId'>})]), 'config': FieldInfo(annotation=Dict[str, YamlValue], required=False, default_factory=dict, examples=[{'bioimageio': {'my_custom_key': 3837283, 'another_key': {'nested': 'value'}}, 'imagej': {'macro_dir': 'path/to/macro/file'}}]), 'git_repo': FieldInfo(annotation=Union[HttpUrl, NoneType], required=False, examples=['https://github.com/bioimage-io/spec-bioimage-io/tree/main/example_descriptions/models/unet2d_nuclei_broad']), 'icon': FieldInfo(annotation=Union[Annotated[Union[Annotated[Path, PathType], RelativeFilePath, HttpUrl, Annotated[Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator, PlainSerializer], Annotated[str, Len], NoneType], required=False), 'links': FieldInfo(annotation=List[str], required=False, default_factory=list, examples=[('ilastik/ilastik', 'deepimagej/deepimagej', 'zero/notebook_u-net_3d_zerocostdl4mic')]), 'uploader': FieldInfo(annotation=Union[Uploader, NoneType], required=False), 'maintainers': FieldInfo(annotation=List[Maintainer], required=False, default_factory=list), 'tags': FieldInfo(annotation=List[str], required=False, default_factory=list, examples=[('unet2d', 'pytorch', 'nucleus', 'segmentation', 'dsb2018')]), 'version': FieldInfo(annotation=Union[Version, NoneType], required=False), 'version_number': FieldInfo(annotation=Union[int, NoneType], required=False), 'format_version': FieldInfo(annotation=Literal['0.3.0'], required=False, default='0.3.0'), 'documentation': FieldInfo(annotation=Union[Annotated[Union[Annotated[Path, PathType, Predicate], RelativeFilePath, HttpUrl], AfterValidator, PlainSerializer], NoneType], required=False, examples=['https://raw.githubusercontent.com/bioimage-io/spec-bioimage-io/main/example_descriptions/models/unet2d_nuclei_broad/README.md', 'README.md']), 'badges': FieldInfo(annotation=List[BadgeDescr], required=False, default_factory=list), 'type': FieldInfo(annotation=Literal['collection'], required=False, default='collection'), 'id': FieldInfo(annotation=Union[ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]], NoneType], required=False), 'parent': FieldInfo(annotation=Union[ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]], NoneType], required=False), 'collection': FieldInfo(annotation=List[CollectionEntry], required=True, metadata=[MinLen(min_length=1)])}"}, "bioimageio.spec.collection.v0_3.CollectionDescr.model_computed_fields": {"fullname": "bioimageio.spec.collection.v0_3.CollectionDescr.model_computed_fields", "modulename": "bioimageio.spec.collection.v0_3", "qualname": "CollectionDescr.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.collection.v0_3.LinkedCollection": {"fullname": "bioimageio.spec.collection.v0_3.LinkedCollection", "modulename": "bioimageio.spec.collection.v0_3", "qualname": "LinkedCollection", "kind": "class", "doc": "
    Reference to a bioimage.io collection.
    \n", "bases": "bioimageio.spec._internal.node.Node"}, "bioimageio.spec.collection.v0_3.LinkedCollection.id": {"fullname": "bioimageio.spec.collection.v0_3.LinkedCollection.id", "modulename": "bioimageio.spec.collection.v0_3", "qualname": "LinkedCollection.id", "kind": "variable", "doc": "
    A valid collection id from the bioimage.io collection.
    \n", "annotation": ": bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]]"}, "bioimageio.spec.collection.v0_3.LinkedCollection.version_number": {"fullname": "bioimageio.spec.collection.v0_3.LinkedCollection.version_number", "modulename": "bioimageio.spec.collection.v0_3", "qualname": "LinkedCollection.version_number", "kind": "variable", "doc": "
    version number (n-th published version, not the semantic version) of linked collection
    \n", "annotation": ": int"}, "bioimageio.spec.collection.v0_3.LinkedCollection.model_config": {"fullname": "bioimageio.spec.collection.v0_3.LinkedCollection.model_config", "modulename": "bioimageio.spec.collection.v0_3", "qualname": "LinkedCollection.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.collection.v0_3.LinkedCollection.model_fields": {"fullname": "bioimageio.spec.collection.v0_3.LinkedCollection.model_fields", "modulename": "bioimageio.spec.collection.v0_3", "qualname": "LinkedCollection.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'id': FieldInfo(annotation=ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]], required=True), 'version_number': FieldInfo(annotation=int, required=True)}"}, "bioimageio.spec.collection.v0_3.LinkedCollection.model_computed_fields": {"fullname": "bioimageio.spec.collection.v0_3.LinkedCollection.model_computed_fields", "modulename": "bioimageio.spec.collection.v0_3", "qualname": "LinkedCollection.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.common": {"fullname": "bioimageio.spec.common", "modulename": "bioimageio.spec.common", "kind": "module", "doc": "
    \n"}, "bioimageio.spec.dataset": {"fullname": "bioimageio.spec.dataset", "modulename": "bioimageio.spec.dataset", "kind": "module", "doc": "
    implementaions of all released minor versions are available in submodules:
    \n\n\n"}, "bioimageio.spec.dataset.AnyDatasetDescr": {"fullname": "bioimageio.spec.dataset.AnyDatasetDescr", "modulename": "bioimageio.spec.dataset", "qualname": "AnyDatasetDescr", "kind": "variable", "doc": "
    Union of any released dataset desription
    \n", "default_value": "typing.Annotated[typing.Union[bioimageio.spec.dataset.v0_2.DatasetDescr, bioimageio.spec.dataset.v0_3.DatasetDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)]"}, "bioimageio.spec.dataset.v0_2": {"fullname": "bioimageio.spec.dataset.v0_2", "modulename": "bioimageio.spec.dataset.v0_2", "kind": "module", "doc": "
    \n"}, "bioimageio.spec.dataset.v0_2.DatasetDescr": {"fullname": "bioimageio.spec.dataset.v0_2.DatasetDescr", "modulename": "bioimageio.spec.dataset.v0_2", "qualname": "DatasetDescr", "kind": "class", "doc": "
    A bioimage.io dataset resource description file (dataset RDF) describes a dataset relevant to bioimage\nprocessing.
    \n", "bases": "bioimageio.spec.generic.v0_2.GenericDescrBase"}, "bioimageio.spec.dataset.v0_2.DatasetDescr.type": {"fullname": "bioimageio.spec.dataset.v0_2.DatasetDescr.type", "modulename": "bioimageio.spec.dataset.v0_2", "qualname": "DatasetDescr.type", "kind": "variable", "doc": "
    \n", "annotation": ": Literal['dataset']"}, "bioimageio.spec.dataset.v0_2.DatasetDescr.id": {"fullname": "bioimageio.spec.dataset.v0_2.DatasetDescr.id", "modulename": "bioimageio.spec.dataset.v0_2", "qualname": "DatasetDescr.id", "kind": "variable", "doc": "
    Model zoo (bioimage.io) wide, unique identifier (assigned by bioimage.io)
    \n", "annotation": ": Optional[bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]]]"}, "bioimageio.spec.dataset.v0_2.DatasetDescr.source": {"fullname": "bioimageio.spec.dataset.v0_2.DatasetDescr.source", "modulename": "bioimageio.spec.dataset.v0_2", "qualname": "DatasetDescr.source", "kind": "variable", "doc": "
    \"URL to the source of the dataset.
    \n", "annotation": ": Optional[bioimageio.spec._internal.url.HttpUrl]"}, "bioimageio.spec.dataset.v0_2.DatasetDescr.implemented_format_version": {"fullname": "bioimageio.spec.dataset.v0_2.DatasetDescr.implemented_format_version", "modulename": "bioimageio.spec.dataset.v0_2", "qualname": "DatasetDescr.implemented_format_version", "kind": "variable", "doc": "
    \n", "annotation": ": ClassVar[str]", "default_value": "'0.2.4'"}, "bioimageio.spec.dataset.v0_2.DatasetDescr.implemented_format_version_tuple": {"fullname": "bioimageio.spec.dataset.v0_2.DatasetDescr.implemented_format_version_tuple", "modulename": "bioimageio.spec.dataset.v0_2", "qualname": "DatasetDescr.implemented_format_version_tuple", "kind": "variable", "doc": "
    \n", "annotation": ": ClassVar[Tuple[int, int, int]]", "default_value": "(0, 2, 4)"}, "bioimageio.spec.dataset.v0_2.DatasetDescr.model_config": {"fullname": "bioimageio.spec.dataset.v0_2.DatasetDescr.model_config", "modulename": "bioimageio.spec.dataset.v0_2", "qualname": "DatasetDescr.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True, 'title': 'bioimage.io dataset specification'}"}, "bioimageio.spec.dataset.v0_2.DatasetDescr.model_fields": {"fullname": "bioimageio.spec.dataset.v0_2.DatasetDescr.model_fields", "modulename": "bioimageio.spec.dataset.v0_2", "qualname": "DatasetDescr.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'name': FieldInfo(annotation=str, required=True, metadata=[MinLen(min_length=1), AfterWarner(func=<function as_warning.<locals>.wrapper>, severity=30, msg='Longer than 128 characters.', context={'typ': typing.Annotated[typing.Any, MaxLen(max_length=128)]})]), 'description': FieldInfo(annotation=str, required=True), 'covers': FieldInfo(annotation=List[Annotated[Union[HttpUrl, Annotated[Path, PathType, Predicate], RelativeFilePath], WithSuffix, PlainSerializer]], required=False, default_factory=list, description="Cover images. Please use an image smaller than 500KB and an aspect ratio width to height of 2:1.\\nThe supported image formats are: ('.gif', '.jpeg', '.jpg', '.png', '.svg')", examples=['cover.png']), 'id_emoji': FieldInfo(annotation=Union[Annotated[str, Len], NoneType], required=False), 'authors': FieldInfo(annotation=List[Author], required=False, default_factory=list), 'attachments': FieldInfo(annotation=Union[AttachmentsDescr, NoneType], required=False), 'cite': FieldInfo(annotation=List[CiteEntry], required=False, default_factory=list), 'config': FieldInfo(annotation=Dict[str, YamlValue], required=False, default_factory=dict, examples=[{'bioimageio': {'my_custom_key': 3837283, 'another_key': {'nested': 'value'}}, 'imagej': {'macro_dir': 'path/to/macro/file'}}]), 'download_url': FieldInfo(annotation=Union[HttpUrl, NoneType], required=False), 'git_repo': FieldInfo(annotation=Union[str, NoneType], required=False, examples=['https://github.com/bioimage-io/spec-bioimage-io/tree/main/example_descriptions/models/unet2d_nuclei_broad']), 'icon': FieldInfo(annotation=Union[Annotated[Union[Annotated[Path, PathType], RelativeFilePath, HttpUrl, Annotated[Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator, PlainSerializer], Annotated[str, Len], NoneType], required=False), 'links': FieldInfo(annotation=List[str], required=False, default_factory=list, examples=[('ilastik/ilastik', 'deepimagej/deepimagej', 'zero/notebook_u-net_3d_zerocostdl4mic')]), 'uploader': FieldInfo(annotation=Union[Uploader, NoneType], required=False), 'maintainers': FieldInfo(annotation=List[Maintainer], required=False, default_factory=list), 'rdf_source': FieldInfo(annotation=Union[Annotated[Path, PathType], RelativeFilePath, HttpUrl, Annotated[Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)], NoneType], required=False), 'tags': FieldInfo(annotation=List[str], required=False, default_factory=list, examples=[('unet2d', 'pytorch', 'nucleus', 'segmentation', 'dsb2018')]), 'version': FieldInfo(annotation=Union[Version, NoneType], required=False), 'version_number': FieldInfo(annotation=Union[int, NoneType], required=False), 'format_version': FieldInfo(annotation=Literal['0.2.4'], required=False, default='0.2.4'), 'badges': FieldInfo(annotation=List[BadgeDescr], required=False, default_factory=list), 'documentation': FieldInfo(annotation=Union[Annotated[Union[Annotated[Path, PathType], RelativeFilePath, HttpUrl, Annotated[Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator, PlainSerializer], NoneType], required=False, examples=['https://raw.githubusercontent.com/bioimage-io/spec-bioimage-io/main/example_descriptions/models/unet2d_nuclei_broad/README.md', 'README.md']), 'license': FieldInfo(annotation=Union[LicenseId, DeprecatedLicenseId, str, NoneType], required=False, examples=['CC-BY-4.0', 'MIT', 'BSD-2-Clause']), 'type': FieldInfo(annotation=Literal['dataset'], required=False, default='dataset'), 'id': FieldInfo(annotation=Union[ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]], NoneType], required=False), 'source': FieldInfo(annotation=Union[HttpUrl, NoneType], required=False)}"}, "bioimageio.spec.dataset.v0_2.DatasetDescr.model_computed_fields": {"fullname": "bioimageio.spec.dataset.v0_2.DatasetDescr.model_computed_fields", "modulename": "bioimageio.spec.dataset.v0_2", "qualname": "DatasetDescr.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.dataset.v0_2.LinkedDataset": {"fullname": "bioimageio.spec.dataset.v0_2.LinkedDataset", "modulename": "bioimageio.spec.dataset.v0_2", "qualname": "LinkedDataset", "kind": "class", "doc": "
    Reference to a bioimage.io dataset.
    \n", "bases": "bioimageio.spec._internal.node.Node"}, "bioimageio.spec.dataset.v0_2.LinkedDataset.id": {"fullname": "bioimageio.spec.dataset.v0_2.LinkedDataset.id", "modulename": "bioimageio.spec.dataset.v0_2", "qualname": "LinkedDataset.id", "kind": "variable", "doc": "
    A valid dataset id from the bioimage.io collection.
    \n", "annotation": ": bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]]"}, "bioimageio.spec.dataset.v0_2.LinkedDataset.version_number": {"fullname": "bioimageio.spec.dataset.v0_2.LinkedDataset.version_number", "modulename": "bioimageio.spec.dataset.v0_2", "qualname": "LinkedDataset.version_number", "kind": "variable", "doc": "
    version number (n-th published version, not the semantic version) of linked dataset
    \n", "annotation": ": Optional[int]"}, "bioimageio.spec.dataset.v0_2.LinkedDataset.model_config": {"fullname": "bioimageio.spec.dataset.v0_2.LinkedDataset.model_config", "modulename": "bioimageio.spec.dataset.v0_2", "qualname": "LinkedDataset.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.dataset.v0_2.LinkedDataset.model_fields": {"fullname": "bioimageio.spec.dataset.v0_2.LinkedDataset.model_fields", "modulename": "bioimageio.spec.dataset.v0_2", "qualname": "LinkedDataset.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'id': FieldInfo(annotation=ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]], required=True), 'version_number': FieldInfo(annotation=Union[int, NoneType], required=False)}"}, "bioimageio.spec.dataset.v0_2.LinkedDataset.model_computed_fields": {"fullname": "bioimageio.spec.dataset.v0_2.LinkedDataset.model_computed_fields", "modulename": "bioimageio.spec.dataset.v0_2", "qualname": "LinkedDataset.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.dataset.v0_3": {"fullname": "bioimageio.spec.dataset.v0_3", "modulename": "bioimageio.spec.dataset.v0_3", "kind": "module", "doc": "
    \n"}, "bioimageio.spec.dataset.v0_3.DatasetDescr": {"fullname": "bioimageio.spec.dataset.v0_3.DatasetDescr", "modulename": "bioimageio.spec.dataset.v0_3", "qualname": "DatasetDescr", "kind": "class", "doc": "
    A bioimage.io dataset resource description file (dataset RDF) describes a dataset relevant to bioimage\nprocessing.
    \n", "bases": "bioimageio.spec.generic.v0_3.GenericDescrBase"}, "bioimageio.spec.dataset.v0_3.DatasetDescr.type": {"fullname": "bioimageio.spec.dataset.v0_3.DatasetDescr.type", "modulename": "bioimageio.spec.dataset.v0_3", "qualname": "DatasetDescr.type", "kind": "variable", "doc": "
    \n", "annotation": ": Literal['dataset']"}, "bioimageio.spec.dataset.v0_3.DatasetDescr.id": {"fullname": "bioimageio.spec.dataset.v0_3.DatasetDescr.id", "modulename": "bioimageio.spec.dataset.v0_3", "qualname": "DatasetDescr.id", "kind": "variable", "doc": "
    Model zoo (bioimage.io) wide, unique identifier (assigned by bioimage.io)
    \n", "annotation": ": Optional[bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]]]"}, "bioimageio.spec.dataset.v0_3.DatasetDescr.parent": {"fullname": "bioimageio.spec.dataset.v0_3.DatasetDescr.parent", "modulename": "bioimageio.spec.dataset.v0_3", "qualname": "DatasetDescr.parent", "kind": "variable", "doc": "
    The description from which this one is derived
    \n", "annotation": ": Optional[bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]]]"}, "bioimageio.spec.dataset.v0_3.DatasetDescr.source": {"fullname": "bioimageio.spec.dataset.v0_3.DatasetDescr.source", "modulename": "bioimageio.spec.dataset.v0_3", "qualname": "DatasetDescr.source", "kind": "variable", "doc": "
    \"URL to the source of the dataset.
    \n", "annotation": ": Optional[bioimageio.spec._internal.url.HttpUrl]"}, "bioimageio.spec.dataset.v0_3.DatasetDescr.implemented_format_version": {"fullname": "bioimageio.spec.dataset.v0_3.DatasetDescr.implemented_format_version", "modulename": "bioimageio.spec.dataset.v0_3", "qualname": "DatasetDescr.implemented_format_version", "kind": "variable", "doc": "
    \n", "annotation": ": ClassVar[str]", "default_value": "'0.3.0'"}, "bioimageio.spec.dataset.v0_3.DatasetDescr.implemented_format_version_tuple": {"fullname": "bioimageio.spec.dataset.v0_3.DatasetDescr.implemented_format_version_tuple", "modulename": "bioimageio.spec.dataset.v0_3", "qualname": "DatasetDescr.implemented_format_version_tuple", "kind": "variable", "doc": "
    \n", "annotation": ": ClassVar[Tuple[int, int, int]]", "default_value": "(0, 3, 0)"}, "bioimageio.spec.dataset.v0_3.DatasetDescr.model_config": {"fullname": "bioimageio.spec.dataset.v0_3.DatasetDescr.model_config", "modulename": "bioimageio.spec.dataset.v0_3", "qualname": "DatasetDescr.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True, 'title': 'bioimage.io dataset specification'}"}, "bioimageio.spec.dataset.v0_3.DatasetDescr.model_fields": {"fullname": "bioimageio.spec.dataset.v0_3.DatasetDescr.model_fields", "modulename": "bioimageio.spec.dataset.v0_3", "qualname": "DatasetDescr.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'name': FieldInfo(annotation=str, required=True, metadata=[MinLen(min_length=1), MaxLen(max_length=128)]), 'description': FieldInfo(annotation=str, required=True, metadata=[MaxLen(max_length=1024), AfterWarner(func=<function as_warning.<locals>.wrapper>, severity=30, msg='Description longer than 512 characters.', context={'typ': typing.Annotated[typing.Any, MaxLen(max_length=512)]})]), 'covers': FieldInfo(annotation=List[Annotated[Union[HttpUrl, Annotated[Path, PathType, Predicate], RelativeFilePath], WithSuffix, PlainSerializer]], required=False, default_factory=list, description="Cover images. Please use an image smaller than 500KB and an aspect ratio width to height of 2:1 or 1:1.\\nThe supported image formats are: ('.gif', '.jpeg', '.jpg', '.png', '.svg')", examples=[]), 'id_emoji': FieldInfo(annotation=Union[Annotated[str, Len], NoneType], required=False), 'authors': FieldInfo(annotation=List[Author], required=True, metadata=[MinLen(min_length=1)]), 'attachments': FieldInfo(annotation=List[FileDescr], required=False, default_factory=list), 'cite': FieldInfo(annotation=List[CiteEntry], required=True, metadata=[MinLen(min_length=1)]), 'license': FieldInfo(annotation=Union[LicenseId, DeprecatedLicenseId], required=True, examples=['CC-BY-4.0', 'MIT', 'BSD-2-Clause'], metadata=[AfterWarner(func=<function as_warning.<locals>.wrapper>, severity=30, msg='{value} is deprecated, see https://spdx.org/licenses/{value}.html', context={'typ': <class 'bioimageio.spec._internal.license_id.LicenseId'>})]), 'config': FieldInfo(annotation=Dict[str, YamlValue], required=False, default_factory=dict, examples=[{'bioimageio': {'my_custom_key': 3837283, 'another_key': {'nested': 'value'}}, 'imagej': {'macro_dir': 'path/to/macro/file'}}]), 'git_repo': FieldInfo(annotation=Union[HttpUrl, NoneType], required=False, examples=['https://github.com/bioimage-io/spec-bioimage-io/tree/main/example_descriptions/models/unet2d_nuclei_broad']), 'icon': FieldInfo(annotation=Union[Annotated[Union[Annotated[Path, PathType], RelativeFilePath, HttpUrl, Annotated[Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator, PlainSerializer], Annotated[str, Len], NoneType], required=False), 'links': FieldInfo(annotation=List[str], required=False, default_factory=list, examples=[('ilastik/ilastik', 'deepimagej/deepimagej', 'zero/notebook_u-net_3d_zerocostdl4mic')]), 'uploader': FieldInfo(annotation=Union[Uploader, NoneType], required=False), 'maintainers': FieldInfo(annotation=List[Maintainer], required=False, default_factory=list), 'tags': FieldInfo(annotation=List[str], required=False, default_factory=list, examples=[('unet2d', 'pytorch', 'nucleus', 'segmentation', 'dsb2018')]), 'version': FieldInfo(annotation=Union[Version, NoneType], required=False), 'version_number': FieldInfo(annotation=Union[int, NoneType], required=False), 'format_version': FieldInfo(annotation=Literal['0.3.0'], required=False, default='0.3.0'), 'documentation': FieldInfo(annotation=Union[Annotated[Union[Annotated[Path, PathType, Predicate], RelativeFilePath, HttpUrl], AfterValidator, PlainSerializer], NoneType], required=False, examples=['https://raw.githubusercontent.com/bioimage-io/spec-bioimage-io/main/example_descriptions/models/unet2d_nuclei_broad/README.md', 'README.md']), 'badges': FieldInfo(annotation=List[BadgeDescr], required=False, default_factory=list), 'type': FieldInfo(annotation=Literal['dataset'], required=False, default='dataset'), 'id': FieldInfo(annotation=Union[ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]], NoneType], required=False), 'parent': FieldInfo(annotation=Union[ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]], NoneType], required=False), 'source': FieldInfo(annotation=Union[HttpUrl, NoneType], required=False)}"}, "bioimageio.spec.dataset.v0_3.DatasetDescr.model_computed_fields": {"fullname": "bioimageio.spec.dataset.v0_3.DatasetDescr.model_computed_fields", "modulename": "bioimageio.spec.dataset.v0_3", "qualname": "DatasetDescr.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.dataset.v0_3.LinkedDataset": {"fullname": "bioimageio.spec.dataset.v0_3.LinkedDataset", "modulename": "bioimageio.spec.dataset.v0_3", "qualname": "LinkedDataset", "kind": "class", "doc": "
    Reference to a bioimage.io dataset.
    \n", "bases": "bioimageio.spec._internal.node.Node"}, "bioimageio.spec.dataset.v0_3.LinkedDataset.id": {"fullname": "bioimageio.spec.dataset.v0_3.LinkedDataset.id", "modulename": "bioimageio.spec.dataset.v0_3", "qualname": "LinkedDataset.id", "kind": "variable", "doc": "
    A valid dataset id from the bioimage.io collection.
    \n", "annotation": ": bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]]"}, "bioimageio.spec.dataset.v0_3.LinkedDataset.version_number": {"fullname": "bioimageio.spec.dataset.v0_3.LinkedDataset.version_number", "modulename": "bioimageio.spec.dataset.v0_3", "qualname": "LinkedDataset.version_number", "kind": "variable", "doc": "
    version number (n-th published version, not the semantic version) of linked dataset
    \n", "annotation": ": int"}, "bioimageio.spec.dataset.v0_3.LinkedDataset.model_config": {"fullname": "bioimageio.spec.dataset.v0_3.LinkedDataset.model_config", "modulename": "bioimageio.spec.dataset.v0_3", "qualname": "LinkedDataset.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.dataset.v0_3.LinkedDataset.model_fields": {"fullname": "bioimageio.spec.dataset.v0_3.LinkedDataset.model_fields", "modulename": "bioimageio.spec.dataset.v0_3", "qualname": "LinkedDataset.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'id': FieldInfo(annotation=ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]], required=True), 'version_number': FieldInfo(annotation=int, required=True)}"}, "bioimageio.spec.dataset.v0_3.LinkedDataset.model_computed_fields": {"fullname": "bioimageio.spec.dataset.v0_3.LinkedDataset.model_computed_fields", "modulename": "bioimageio.spec.dataset.v0_3", "qualname": "LinkedDataset.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.generic": {"fullname": "bioimageio.spec.generic", "modulename": "bioimageio.spec.generic", "kind": "module", "doc": "
    implementaions of all released minor versions are available in submodules:
    \n\n\n"}, "bioimageio.spec.generic.AnyGenericDescr": {"fullname": "bioimageio.spec.generic.AnyGenericDescr", "modulename": "bioimageio.spec.generic", "qualname": "AnyGenericDescr", "kind": "variable", "doc": "
    Union of any released generic desription
    \n", "default_value": "typing.Annotated[typing.Union[bioimageio.spec.generic.v0_2.GenericDescr, bioimageio.spec.generic.v0_3.GenericDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)]"}, "bioimageio.spec.generic.v0_2": {"fullname": "bioimageio.spec.generic.v0_2", "modulename": "bioimageio.spec.generic.v0_2", "kind": "module", "doc": "
    \n"}, "bioimageio.spec.generic.v0_2.KNOWN_SPECIFIC_RESOURCE_TYPES": {"fullname": "bioimageio.spec.generic.v0_2.KNOWN_SPECIFIC_RESOURCE_TYPES", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "KNOWN_SPECIFIC_RESOURCE_TYPES", "kind": "variable", "doc": "
    \n", "default_value": "('application', 'collection', 'dataset', 'model', 'notebook')"}, "bioimageio.spec.generic.v0_2.VALID_COVER_IMAGE_EXTENSIONS": {"fullname": "bioimageio.spec.generic.v0_2.VALID_COVER_IMAGE_EXTENSIONS", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "VALID_COVER_IMAGE_EXTENSIONS", "kind": "variable", "doc": "
    \n", "default_value": "('.gif', '.jpeg', '.jpg', '.png', '.svg')"}, "bioimageio.spec.generic.v0_2.CoverImageSource": {"fullname": "bioimageio.spec.generic.v0_2.CoverImageSource", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "CoverImageSource", "kind": "variable", "doc": "
    \n", "default_value": "typing.Annotated[typing.Union[bioimageio.spec._internal.url.HttpUrl, typing.Annotated[pathlib.Path, PathType(path_type='file'), Predicate(func=<function PurePath.is_absolute>)], bioimageio.spec._internal.io.RelativeFilePath], WithSuffix(suffix=('.gif', '.jpeg', '.jpg', '.png', '.svg'), case_sensitive=False), PlainSerializer(func=<function _package>, return_type=PydanticUndefined, when_used='unless-none')]"}, "bioimageio.spec.generic.v0_2.AttachmentsDescr": {"fullname": "bioimageio.spec.generic.v0_2.AttachmentsDescr", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "AttachmentsDescr", "kind": "class", "doc": "
    Subpart of a resource description
    \n", "bases": "bioimageio.spec._internal.node.Node"}, "bioimageio.spec.generic.v0_2.AttachmentsDescr.model_config": {"fullname": "bioimageio.spec.generic.v0_2.AttachmentsDescr.model_config", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "AttachmentsDescr.model_config", "kind": "variable", "doc": "
    update pydantic model config to allow additional unknown keys
    \n", "default_value": "{'extra': 'allow', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.generic.v0_2.AttachmentsDescr.files": {"fullname": "bioimageio.spec.generic.v0_2.AttachmentsDescr.files", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "AttachmentsDescr.files", "kind": "variable", "doc": "
    \u2208\ud83d\udce6 File attachments
    \n", "annotation": ": List[Annotated[Union[Annotated[pathlib.Path, PathType(path_type='file')], bioimageio.spec._internal.io.RelativeFilePath, bioimageio.spec._internal.url.HttpUrl, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator(func=<function wo_special_file_name at 0x7f1c21c3ef20>), PlainSerializer(func=<function _package at 0x7f1c21c782c0>, return_type=PydanticUndefined, when_used='unless-none')]]"}, "bioimageio.spec.generic.v0_2.AttachmentsDescr.model_fields": {"fullname": "bioimageio.spec.generic.v0_2.AttachmentsDescr.model_fields", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "AttachmentsDescr.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'files': FieldInfo(annotation=List[Annotated[Union[Annotated[Path, PathType], RelativeFilePath, HttpUrl, Annotated[Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator, PlainSerializer]], required=False, default_factory=list)}"}, "bioimageio.spec.generic.v0_2.AttachmentsDescr.model_computed_fields": {"fullname": "bioimageio.spec.generic.v0_2.AttachmentsDescr.model_computed_fields", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "AttachmentsDescr.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.generic.v0_2.Uploader": {"fullname": "bioimageio.spec.generic.v0_2.Uploader", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "Uploader", "kind": "class", "doc": "
    Subpart of a resource description
    \n", "bases": "bioimageio.spec._internal.node.Node"}, "bioimageio.spec.generic.v0_2.Uploader.email": {"fullname": "bioimageio.spec.generic.v0_2.Uploader.email", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "Uploader.email", "kind": "variable", "doc": "
    Email
    \n", "annotation": ": pydantic.networks.EmailStr"}, "bioimageio.spec.generic.v0_2.Uploader.name": {"fullname": "bioimageio.spec.generic.v0_2.Uploader.name", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "Uploader.name", "kind": "variable", "doc": "
    name
    \n", "annotation": ": Optional[Annotated[str, AfterValidator(func=<function _remove_slashes at 0x7f1c21cbe700>)]]"}, "bioimageio.spec.generic.v0_2.Uploader.model_config": {"fullname": "bioimageio.spec.generic.v0_2.Uploader.model_config", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "Uploader.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.generic.v0_2.Uploader.model_fields": {"fullname": "bioimageio.spec.generic.v0_2.Uploader.model_fields", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "Uploader.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'email': FieldInfo(annotation=EmailStr, required=True), 'name': FieldInfo(annotation=Union[Annotated[str, AfterValidator], NoneType], required=False)}"}, "bioimageio.spec.generic.v0_2.Uploader.model_computed_fields": {"fullname": "bioimageio.spec.generic.v0_2.Uploader.model_computed_fields", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "Uploader.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.generic.v0_2.Author": {"fullname": "bioimageio.spec.generic.v0_2.Author", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "Author", "kind": "class", "doc": "
    Subpart of a resource description
    \n", "bases": "_Person"}, "bioimageio.spec.generic.v0_2.Author.name": {"fullname": "bioimageio.spec.generic.v0_2.Author.name", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "Author.name", "kind": "variable", "doc": "
    \n", "annotation": ": Annotated[str, AfterValidator(func=<function _remove_slashes at 0x7f1c21cbe700>)]"}, "bioimageio.spec.generic.v0_2.Author.github_user": {"fullname": "bioimageio.spec.generic.v0_2.Author.github_user", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "Author.github_user", "kind": "variable", "doc": "
    \n", "annotation": ": Optional[str]"}, "bioimageio.spec.generic.v0_2.Author.model_config": {"fullname": "bioimageio.spec.generic.v0_2.Author.model_config", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "Author.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.generic.v0_2.Author.model_fields": {"fullname": "bioimageio.spec.generic.v0_2.Author.model_fields", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "Author.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'affiliation': FieldInfo(annotation=Union[str, NoneType], required=False), 'email': FieldInfo(annotation=Union[EmailStr, NoneType], required=False), 'orcid': FieldInfo(annotation=Union[ValidatedString[Annotated[str, AfterValidator]], NoneType], required=False, examples=['0000-0001-2345-6789']), 'name': FieldInfo(annotation=str, required=True, metadata=[AfterValidator(func=<function _remove_slashes>)]), 'github_user': FieldInfo(annotation=Union[str, NoneType], required=False)}"}, "bioimageio.spec.generic.v0_2.Author.model_computed_fields": {"fullname": "bioimageio.spec.generic.v0_2.Author.model_computed_fields", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "Author.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.generic.v0_2.Maintainer": {"fullname": "bioimageio.spec.generic.v0_2.Maintainer", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "Maintainer", "kind": "class", "doc": "
    Subpart of a resource description
    \n", "bases": "_Person"}, "bioimageio.spec.generic.v0_2.Maintainer.name": {"fullname": "bioimageio.spec.generic.v0_2.Maintainer.name", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "Maintainer.name", "kind": "variable", "doc": "
    \n", "annotation": ": Optional[Annotated[str, AfterValidator(func=<function _remove_slashes at 0x7f1c21cbe700>)]]"}, "bioimageio.spec.generic.v0_2.Maintainer.github_user": {"fullname": "bioimageio.spec.generic.v0_2.Maintainer.github_user", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "Maintainer.github_user", "kind": "variable", "doc": "
    \n", "annotation": ": str"}, "bioimageio.spec.generic.v0_2.Maintainer.model_config": {"fullname": "bioimageio.spec.generic.v0_2.Maintainer.model_config", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "Maintainer.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.generic.v0_2.Maintainer.model_fields": {"fullname": "bioimageio.spec.generic.v0_2.Maintainer.model_fields", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "Maintainer.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'affiliation': FieldInfo(annotation=Union[str, NoneType], required=False), 'email': FieldInfo(annotation=Union[EmailStr, NoneType], required=False), 'orcid': FieldInfo(annotation=Union[ValidatedString[Annotated[str, AfterValidator]], NoneType], required=False, examples=['0000-0001-2345-6789']), 'name': FieldInfo(annotation=Union[Annotated[str, AfterValidator], NoneType], required=False), 'github_user': FieldInfo(annotation=str, required=True)}"}, "bioimageio.spec.generic.v0_2.Maintainer.model_computed_fields": {"fullname": "bioimageio.spec.generic.v0_2.Maintainer.model_computed_fields", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "Maintainer.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.generic.v0_2.BadgeDescr": {"fullname": "bioimageio.spec.generic.v0_2.BadgeDescr", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "BadgeDescr", "kind": "class", "doc": "
    A custom badge
    \n", "bases": "bioimageio.spec._internal.node.Node"}, "bioimageio.spec.generic.v0_2.BadgeDescr.label": {"fullname": "bioimageio.spec.generic.v0_2.BadgeDescr.label", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "BadgeDescr.label", "kind": "variable", "doc": "
    badge label to display on hover
    \n", "annotation": ": Annotated[str, FieldInfo(annotation=NoneType, required=True, examples=['Open in Colab'])]"}, "bioimageio.spec.generic.v0_2.BadgeDescr.icon": {"fullname": "bioimageio.spec.generic.v0_2.BadgeDescr.icon", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "BadgeDescr.icon", "kind": "variable", "doc": "
    badge icon
    \n", "annotation": ": Annotated[Optional[bioimageio.spec._internal.url.HttpUrl], FieldInfo(annotation=NoneType, required=True, examples=['https://colab.research.google.com/assets/colab-badge.svg'])]"}, "bioimageio.spec.generic.v0_2.BadgeDescr.url": {"fullname": "bioimageio.spec.generic.v0_2.BadgeDescr.url", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "BadgeDescr.url", "kind": "variable", "doc": "
    target URL
    \n", "annotation": ": Annotated[bioimageio.spec._internal.url.HttpUrl, FieldInfo(annotation=NoneType, required=True, examples=['https://colab.research.google.com/github/HenriquesLab/ZeroCostDL4Mic/blob/master/Colab_notebooks/U-net_2D_ZeroCostDL4Mic.ipynb'])]"}, "bioimageio.spec.generic.v0_2.BadgeDescr.model_config": {"fullname": "bioimageio.spec.generic.v0_2.BadgeDescr.model_config", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "BadgeDescr.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True, 'title': 'Custom badge'}"}, "bioimageio.spec.generic.v0_2.BadgeDescr.model_fields": {"fullname": "bioimageio.spec.generic.v0_2.BadgeDescr.model_fields", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "BadgeDescr.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'label': FieldInfo(annotation=str, required=True, examples=['Open in Colab']), 'icon': FieldInfo(annotation=Union[HttpUrl, NoneType], required=False, examples=['https://colab.research.google.com/assets/colab-badge.svg']), 'url': FieldInfo(annotation=HttpUrl, required=True, examples=['https://colab.research.google.com/github/HenriquesLab/ZeroCostDL4Mic/blob/master/Colab_notebooks/U-net_2D_ZeroCostDL4Mic.ipynb'])}"}, "bioimageio.spec.generic.v0_2.BadgeDescr.model_computed_fields": {"fullname": "bioimageio.spec.generic.v0_2.BadgeDescr.model_computed_fields", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "BadgeDescr.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.generic.v0_2.CiteEntry": {"fullname": "bioimageio.spec.generic.v0_2.CiteEntry", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "CiteEntry", "kind": "class", "doc": "
    Subpart of a resource description
    \n", "bases": "bioimageio.spec._internal.node.Node"}, "bioimageio.spec.generic.v0_2.CiteEntry.text": {"fullname": "bioimageio.spec.generic.v0_2.CiteEntry.text", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "CiteEntry.text", "kind": "variable", "doc": "
    free text description
    \n", "annotation": ": str"}, "bioimageio.spec.generic.v0_2.CiteEntry.doi": {"fullname": "bioimageio.spec.generic.v0_2.CiteEntry.doi", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "CiteEntry.doi", "kind": "variable", "doc": "
    A digital object identifier (DOI) is the prefered citation reference.\nSee https://www.doi.org/ for details. (alternatively specify url)
    \n", "annotation": ": Optional[bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, StringConstraints]]]"}, "bioimageio.spec.generic.v0_2.CiteEntry.accept_prefixed_doi": {"fullname": "bioimageio.spec.generic.v0_2.CiteEntry.accept_prefixed_doi", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "CiteEntry.accept_prefixed_doi", "kind": "function", "doc": "
    \n", "signature": "(cls, doi: Any) -> Any:", "funcdef": "def"}, "bioimageio.spec.generic.v0_2.CiteEntry.url": {"fullname": "bioimageio.spec.generic.v0_2.CiteEntry.url", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "CiteEntry.url", "kind": "variable", "doc": "
    URL to cite (preferably specify a doi instead)
    \n", "annotation": ": Optional[str]"}, "bioimageio.spec.generic.v0_2.CiteEntry.model_config": {"fullname": "bioimageio.spec.generic.v0_2.CiteEntry.model_config", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "CiteEntry.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.generic.v0_2.CiteEntry.model_fields": {"fullname": "bioimageio.spec.generic.v0_2.CiteEntry.model_fields", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "CiteEntry.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'text': FieldInfo(annotation=str, required=True), 'doi': FieldInfo(annotation=Union[ValidatedString[Annotated[str, StringConstraints]], NoneType], required=False), 'url': FieldInfo(annotation=Union[str, NoneType], required=False)}"}, "bioimageio.spec.generic.v0_2.CiteEntry.model_computed_fields": {"fullname": "bioimageio.spec.generic.v0_2.CiteEntry.model_computed_fields", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "CiteEntry.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.generic.v0_2.LinkedResource": {"fullname": "bioimageio.spec.generic.v0_2.LinkedResource", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "LinkedResource", "kind": "class", "doc": "
    Reference to a bioimage.io resource
    \n", "bases": "bioimageio.spec._internal.node.Node"}, "bioimageio.spec.generic.v0_2.LinkedResource.id": {"fullname": "bioimageio.spec.generic.v0_2.LinkedResource.id", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "LinkedResource.id", "kind": "variable", "doc": "
    A valid resource id from the bioimage.io collection.
    \n", "annotation": ": bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]]"}, "bioimageio.spec.generic.v0_2.LinkedResource.version_number": {"fullname": "bioimageio.spec.generic.v0_2.LinkedResource.version_number", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "LinkedResource.version_number", "kind": "variable", "doc": "
    version number (n-th published version, not the semantic version) of linked resource
    \n", "annotation": ": Optional[int]"}, "bioimageio.spec.generic.v0_2.LinkedResource.model_config": {"fullname": "bioimageio.spec.generic.v0_2.LinkedResource.model_config", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "LinkedResource.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.generic.v0_2.LinkedResource.model_fields": {"fullname": "bioimageio.spec.generic.v0_2.LinkedResource.model_fields", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "LinkedResource.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'id': FieldInfo(annotation=ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]], required=True), 'version_number': FieldInfo(annotation=Union[int, NoneType], required=False)}"}, "bioimageio.spec.generic.v0_2.LinkedResource.model_computed_fields": {"fullname": "bioimageio.spec.generic.v0_2.LinkedResource.model_computed_fields", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "LinkedResource.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.generic.v0_2.GenericModelDescrBase": {"fullname": "bioimageio.spec.generic.v0_2.GenericModelDescrBase", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "GenericModelDescrBase", "kind": "class", "doc": "
    Base for all resource descriptions including of model descriptions
    \n", "bases": "bioimageio.spec._internal.common_nodes.ResourceDescrBase"}, "bioimageio.spec.generic.v0_2.GenericModelDescrBase.name": {"fullname": "bioimageio.spec.generic.v0_2.GenericModelDescrBase.name", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "GenericModelDescrBase.name", "kind": "variable", "doc": "
    A human-friendly name of the resource description
    \n", "annotation": ": Annotated[str, MinLen(min_length=1), AfterWarner(func=<function as_warning.<locals>.wrapper at 0x7f1c21d18fe0>, severity=30, msg='Longer than 128 characters.', context={'typ': Annotated[Any, MaxLen(max_length=128)]})]"}, "bioimageio.spec.generic.v0_2.GenericModelDescrBase.description": {"fullname": "bioimageio.spec.generic.v0_2.GenericModelDescrBase.description", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "GenericModelDescrBase.description", "kind": "variable", "doc": "
    \n", "annotation": ": str"}, "bioimageio.spec.generic.v0_2.GenericModelDescrBase.covers": {"fullname": "bioimageio.spec.generic.v0_2.GenericModelDescrBase.covers", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "GenericModelDescrBase.covers", "kind": "variable", "doc": "
    \u2208\ud83d\udce6 Cover images. Please use an image smaller than 500KB and an aspect ratio width to height of 2:1.
    \n", "annotation": ": Annotated[List[Annotated[Union[bioimageio.spec._internal.url.HttpUrl, Annotated[pathlib.Path, PathType(path_type='file'), Predicate(func=<function PurePath.is_absolute at 0x7f1c25245940>)], bioimageio.spec._internal.io.RelativeFilePath], WithSuffix(suffix=('.gif', '.jpeg', '.jpg', '.png', '.svg'), case_sensitive=False), PlainSerializer(func=<function _package at 0x7f1c21c782c0>, return_type=PydanticUndefined, when_used='unless-none')]], FieldInfo(annotation=NoneType, required=True, description="Cover images. Please use an image smaller than 500KB and an aspect ratio width to height of 2:1.\\nThe supported image formats are: ('.gif', '.jpeg', '.jpg', '.png', '.svg')", examples=['cover.png'])]"}, "bioimageio.spec.generic.v0_2.GenericModelDescrBase.id_emoji": {"fullname": "bioimageio.spec.generic.v0_2.GenericModelDescrBase.id_emoji", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "GenericModelDescrBase.id_emoji", "kind": "variable", "doc": "
    UTF-8 emoji for display alongside the id.
    \n", "annotation": ": Optional[Annotated[str, Len(min_length=1, max_length=1)]]"}, "bioimageio.spec.generic.v0_2.GenericModelDescrBase.authors": {"fullname": "bioimageio.spec.generic.v0_2.GenericModelDescrBase.authors", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "GenericModelDescrBase.authors", "kind": "variable", "doc": "
    The authors are the creators of the RDF and the primary points of contact.
    \n", "annotation": ": List[bioimageio.spec.generic.v0_2.Author]"}, "bioimageio.spec.generic.v0_2.GenericModelDescrBase.accept_author_strings": {"fullname": "bioimageio.spec.generic.v0_2.GenericModelDescrBase.accept_author_strings", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "GenericModelDescrBase.accept_author_strings", "kind": "function", "doc": "
    we unofficially accept strings as author entries
    \n", "signature": "(cls, authors: Union[Any, Sequence[Any]]) -> Any:", "funcdef": "def"}, "bioimageio.spec.generic.v0_2.GenericModelDescrBase.attachments": {"fullname": "bioimageio.spec.generic.v0_2.GenericModelDescrBase.attachments", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "GenericModelDescrBase.attachments", "kind": "variable", "doc": "
    file and other attachments
    \n", "annotation": ": Optional[bioimageio.spec.generic.v0_2.AttachmentsDescr]"}, "bioimageio.spec.generic.v0_2.GenericModelDescrBase.cite": {"fullname": "bioimageio.spec.generic.v0_2.GenericModelDescrBase.cite", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "GenericModelDescrBase.cite", "kind": "variable", "doc": "
    citations
    \n", "annotation": ": List[bioimageio.spec.generic.v0_2.CiteEntry]"}, "bioimageio.spec.generic.v0_2.GenericModelDescrBase.config": {"fullname": "bioimageio.spec.generic.v0_2.GenericModelDescrBase.config", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "GenericModelDescrBase.config", "kind": "variable", "doc": "
    A field for custom configuration that can contain any keys not present in the RDF spec.\nThis means you should not store, for example, a github repo URL in config since we already have the\ngit_repo field defined in the spec.\nKeys in config may be very specific to a tool or consumer software. To avoid conflicting definitions,\nit is recommended to wrap added configuration into a sub-field named with the specific domain or tool name,\nfor example:
    \n\n
    \n
    config:\n    bioimageio:  # here is the domain name\n        my_custom_key: 3837283\n        another_key:\n            nested: value\n    imagej:       # config specific to ImageJ\n        macro_dir: path/to/macro/file\n
    \n
    \n\n
    If possible, please use snake_case for keys in config.\nYou may want to list linked files additionally under attachments to include them when packaging a resource\n(packaging a resource means downloading/copying important linked files and creating a ZIP archive that contains\nan altered rdf.yaml file with local references to the downloaded files)
    \n", "annotation": ": Annotated[Dict[str, YamlValue], FieldInfo(annotation=NoneType, required=True, examples=[{'bioimageio': {'my_custom_key': 3837283, 'another_key': {'nested': 'value'}}, 'imagej': {'macro_dir': 'path/to/macro/file'}}])]"}, "bioimageio.spec.generic.v0_2.GenericModelDescrBase.download_url": {"fullname": "bioimageio.spec.generic.v0_2.GenericModelDescrBase.download_url", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "GenericModelDescrBase.download_url", "kind": "variable", "doc": "
    URL to download the resource from (deprecated)
    \n", "annotation": ": Optional[bioimageio.spec._internal.url.HttpUrl]"}, "bioimageio.spec.generic.v0_2.GenericModelDescrBase.git_repo": {"fullname": "bioimageio.spec.generic.v0_2.GenericModelDescrBase.git_repo", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "GenericModelDescrBase.git_repo", "kind": "variable", "doc": "
    A URL to the Git repository where the resource is being developed.
    \n", "annotation": ": Annotated[Optional[str], FieldInfo(annotation=NoneType, required=True, examples=['https://github.com/bioimage-io/spec-bioimage-io/tree/main/example_descriptions/models/unet2d_nuclei_broad'])]"}, "bioimageio.spec.generic.v0_2.GenericModelDescrBase.icon": {"fullname": "bioimageio.spec.generic.v0_2.GenericModelDescrBase.icon", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "GenericModelDescrBase.icon", "kind": "variable", "doc": "
    An icon for illustration
    \n", "annotation": ": Union[Annotated[Union[Annotated[pathlib.Path, PathType(path_type='file')], bioimageio.spec._internal.io.RelativeFilePath, bioimageio.spec._internal.url.HttpUrl, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator(func=<function wo_special_file_name at 0x7f1c21c3ef20>), PlainSerializer(func=<function _package at 0x7f1c21c782c0>, return_type=PydanticUndefined, when_used='unless-none')], Annotated[str, Len(min_length=1, max_length=2)], NoneType]"}, "bioimageio.spec.generic.v0_2.GenericModelDescrBase.links": {"fullname": "bioimageio.spec.generic.v0_2.GenericModelDescrBase.links", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "GenericModelDescrBase.links", "kind": "variable", "doc": "
    IDs of other bioimage.io resources
    \n", "annotation": ": Annotated[List[str], FieldInfo(annotation=NoneType, required=True, examples=[('ilastik/ilastik', 'deepimagej/deepimagej', 'zero/notebook_u-net_3d_zerocostdl4mic')])]"}, "bioimageio.spec.generic.v0_2.GenericModelDescrBase.uploader": {"fullname": "bioimageio.spec.generic.v0_2.GenericModelDescrBase.uploader", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "GenericModelDescrBase.uploader", "kind": "variable", "doc": "
    The person who uploaded the model (e.g. to bioimage.io)
    \n", "annotation": ": Optional[bioimageio.spec.generic.v0_2.Uploader]"}, "bioimageio.spec.generic.v0_2.GenericModelDescrBase.maintainers": {"fullname": "bioimageio.spec.generic.v0_2.GenericModelDescrBase.maintainers", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "GenericModelDescrBase.maintainers", "kind": "variable", "doc": "
    Maintainers of this resource.\nIf not specified authors are maintainers and at least some of them should specify their github_user name
    \n", "annotation": ": List[bioimageio.spec.generic.v0_2.Maintainer]"}, "bioimageio.spec.generic.v0_2.GenericModelDescrBase.rdf_source": {"fullname": "bioimageio.spec.generic.v0_2.GenericModelDescrBase.rdf_source", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "GenericModelDescrBase.rdf_source", "kind": "variable", "doc": "
    Resource description file (RDF) source; used to keep track of where an rdf.yaml was loaded from.\nDo not set this field in a YAML file.
    \n", "annotation": ": Union[Annotated[pathlib.Path, PathType(path_type='file')], bioimageio.spec._internal.io.RelativeFilePath, bioimageio.spec._internal.url.HttpUrl, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)], NoneType]"}, "bioimageio.spec.generic.v0_2.GenericModelDescrBase.tags": {"fullname": "bioimageio.spec.generic.v0_2.GenericModelDescrBase.tags", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "GenericModelDescrBase.tags", "kind": "variable", "doc": "
    Associated tags
    \n", "annotation": ": Annotated[List[str], FieldInfo(annotation=NoneType, required=True, examples=[('unet2d', 'pytorch', 'nucleus', 'segmentation', 'dsb2018')])]"}, "bioimageio.spec.generic.v0_2.GenericModelDescrBase.warn_about_tag_categories": {"fullname": "bioimageio.spec.generic.v0_2.GenericModelDescrBase.warn_about_tag_categories", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "GenericModelDescrBase.warn_about_tag_categories", "kind": "function", "doc": "
    \n", "signature": "(value: Any, info: pydantic_core.core_schema.ValidationInfo) -> Any:", "funcdef": "def"}, "bioimageio.spec.generic.v0_2.GenericModelDescrBase.version": {"fullname": "bioimageio.spec.generic.v0_2.GenericModelDescrBase.version", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "GenericModelDescrBase.version", "kind": "variable", "doc": "
    The version of the resource following SemVer 2.0.
    \n", "annotation": ": Optional[bioimageio.spec._internal.version_type.Version]"}, "bioimageio.spec.generic.v0_2.GenericModelDescrBase.version_number": {"fullname": "bioimageio.spec.generic.v0_2.GenericModelDescrBase.version_number", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "GenericModelDescrBase.version_number", "kind": "variable", "doc": "
    version number (n-th published version, not the semantic version)
    \n", "annotation": ": Optional[int]"}, "bioimageio.spec.generic.v0_2.GenericModelDescrBase.model_config": {"fullname": "bioimageio.spec.generic.v0_2.GenericModelDescrBase.model_config", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "GenericModelDescrBase.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.generic.v0_2.GenericModelDescrBase.model_fields": {"fullname": "bioimageio.spec.generic.v0_2.GenericModelDescrBase.model_fields", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "GenericModelDescrBase.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'name': FieldInfo(annotation=str, required=True, metadata=[MinLen(min_length=1), AfterWarner(func=<function as_warning.<locals>.wrapper>, severity=30, msg='Longer than 128 characters.', context={'typ': typing.Annotated[typing.Any, MaxLen(max_length=128)]})]), 'description': FieldInfo(annotation=str, required=True), 'covers': FieldInfo(annotation=List[Annotated[Union[HttpUrl, Annotated[Path, PathType, Predicate], RelativeFilePath], WithSuffix, PlainSerializer]], required=False, default_factory=list, description="Cover images. Please use an image smaller than 500KB and an aspect ratio width to height of 2:1.\\nThe supported image formats are: ('.gif', '.jpeg', '.jpg', '.png', '.svg')", examples=['cover.png']), 'id_emoji': FieldInfo(annotation=Union[Annotated[str, Len], NoneType], required=False), 'authors': FieldInfo(annotation=List[Author], required=False, default_factory=list), 'attachments': FieldInfo(annotation=Union[AttachmentsDescr, NoneType], required=False), 'cite': FieldInfo(annotation=List[CiteEntry], required=False, default_factory=list), 'config': FieldInfo(annotation=Dict[str, YamlValue], required=False, default_factory=dict, examples=[{'bioimageio': {'my_custom_key': 3837283, 'another_key': {'nested': 'value'}}, 'imagej': {'macro_dir': 'path/to/macro/file'}}]), 'download_url': FieldInfo(annotation=Union[HttpUrl, NoneType], required=False), 'git_repo': FieldInfo(annotation=Union[str, NoneType], required=False, examples=['https://github.com/bioimage-io/spec-bioimage-io/tree/main/example_descriptions/models/unet2d_nuclei_broad']), 'icon': FieldInfo(annotation=Union[Annotated[Union[Annotated[Path, PathType], RelativeFilePath, HttpUrl, Annotated[Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator, PlainSerializer], Annotated[str, Len], NoneType], required=False), 'links': FieldInfo(annotation=List[str], required=False, default_factory=list, examples=[('ilastik/ilastik', 'deepimagej/deepimagej', 'zero/notebook_u-net_3d_zerocostdl4mic')]), 'uploader': FieldInfo(annotation=Union[Uploader, NoneType], required=False), 'maintainers': FieldInfo(annotation=List[Maintainer], required=False, default_factory=list), 'rdf_source': FieldInfo(annotation=Union[Annotated[Path, PathType], RelativeFilePath, HttpUrl, Annotated[Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)], NoneType], required=False), 'tags': FieldInfo(annotation=List[str], required=False, default_factory=list, examples=[('unet2d', 'pytorch', 'nucleus', 'segmentation', 'dsb2018')]), 'version': FieldInfo(annotation=Union[Version, NoneType], required=False), 'version_number': FieldInfo(annotation=Union[int, NoneType], required=False)}"}, "bioimageio.spec.generic.v0_2.GenericModelDescrBase.model_computed_fields": {"fullname": "bioimageio.spec.generic.v0_2.GenericModelDescrBase.model_computed_fields", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "GenericModelDescrBase.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.generic.v0_2.GenericDescrBase": {"fullname": "bioimageio.spec.generic.v0_2.GenericDescrBase", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "GenericDescrBase", "kind": "class", "doc": "
    Base for all resource descriptions except for the model descriptions
    \n", "bases": "GenericModelDescrBase"}, "bioimageio.spec.generic.v0_2.GenericDescrBase.format_version": {"fullname": "bioimageio.spec.generic.v0_2.GenericDescrBase.format_version", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "GenericDescrBase.format_version", "kind": "variable", "doc": "
    The format version of this resource specification\n(not the version of the resource description)\nWhen creating a new resource always use the latest micro/patch version described here.\nThe format_version is important for any consumer software to understand how to parse the fields.
    \n", "annotation": ": Literal['0.2.4']"}, "bioimageio.spec.generic.v0_2.GenericDescrBase.badges": {"fullname": "bioimageio.spec.generic.v0_2.GenericDescrBase.badges", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "GenericDescrBase.badges", "kind": "variable", "doc": "
    badges associated with this resource
    \n", "annotation": ": List[bioimageio.spec.generic.v0_2.BadgeDescr]"}, "bioimageio.spec.generic.v0_2.GenericDescrBase.documentation": {"fullname": "bioimageio.spec.generic.v0_2.GenericDescrBase.documentation", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "GenericDescrBase.documentation", "kind": "variable", "doc": "
    \u2208\ud83d\udce6 URL or relative path to a markdown file with additional documentation.\nThe recommended documentation file name is README.md. An .md suffix is mandatory.
    \n", "annotation": ": Annotated[Optional[Annotated[Union[Annotated[pathlib.Path, PathType(path_type='file')], bioimageio.spec._internal.io.RelativeFilePath, bioimageio.spec._internal.url.HttpUrl, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator(func=<function wo_special_file_name at 0x7f1c21c3ef20>), PlainSerializer(func=<function _package at 0x7f1c21c782c0>, return_type=PydanticUndefined, when_used='unless-none')]], FieldInfo(annotation=NoneType, required=True, examples=['https://raw.githubusercontent.com/bioimage-io/spec-bioimage-io/main/example_descriptions/models/unet2d_nuclei_broad/README.md', 'README.md'])]"}, "bioimageio.spec.generic.v0_2.GenericDescrBase.license": {"fullname": "bioimageio.spec.generic.v0_2.GenericDescrBase.license", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "GenericDescrBase.license", "kind": "variable", "doc": "
    A SPDX license identifier.\nWe do not support custom license beyond the SPDX license list, if you need that please\nopen a GitHub issue to discuss your intentions with the community.
    \n", "annotation": ": Annotated[Union[bioimageio.spec._internal.license_id.LicenseId, bioimageio.spec._internal.license_id.DeprecatedLicenseId, str, NoneType], FieldInfo(annotation=NoneType, required=True, examples=['CC-BY-4.0', 'MIT', 'BSD-2-Clause'])]"}, "bioimageio.spec.generic.v0_2.GenericDescrBase.deprecated_spdx_license": {"fullname": "bioimageio.spec.generic.v0_2.GenericDescrBase.deprecated_spdx_license", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "GenericDescrBase.deprecated_spdx_license", "kind": "function", "doc": "
    \n", "signature": "(\tcls,\tvalue: Union[bioimageio.spec._internal.license_id.LicenseId, bioimageio.spec._internal.license_id.DeprecatedLicenseId, str, NoneType]):", "funcdef": "def"}, "bioimageio.spec.generic.v0_2.GenericDescrBase.implemented_format_version": {"fullname": "bioimageio.spec.generic.v0_2.GenericDescrBase.implemented_format_version", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "GenericDescrBase.implemented_format_version", "kind": "variable", "doc": "
    \n", "annotation": ": ClassVar[str]", "default_value": "'0.2.4'"}, "bioimageio.spec.generic.v0_2.GenericDescrBase.implemented_format_version_tuple": {"fullname": "bioimageio.spec.generic.v0_2.GenericDescrBase.implemented_format_version_tuple", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "GenericDescrBase.implemented_format_version_tuple", "kind": "variable", "doc": "
    \n", "annotation": ": ClassVar[Tuple[int, int, int]]", "default_value": "(0, 2, 4)"}, "bioimageio.spec.generic.v0_2.GenericDescrBase.model_config": {"fullname": "bioimageio.spec.generic.v0_2.GenericDescrBase.model_config", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "GenericDescrBase.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.generic.v0_2.GenericDescrBase.model_fields": {"fullname": "bioimageio.spec.generic.v0_2.GenericDescrBase.model_fields", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "GenericDescrBase.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'name': FieldInfo(annotation=str, required=True, metadata=[MinLen(min_length=1), AfterWarner(func=<function as_warning.<locals>.wrapper>, severity=30, msg='Longer than 128 characters.', context={'typ': typing.Annotated[typing.Any, MaxLen(max_length=128)]})]), 'description': FieldInfo(annotation=str, required=True), 'covers': FieldInfo(annotation=List[Annotated[Union[HttpUrl, Annotated[Path, PathType, Predicate], RelativeFilePath], WithSuffix, PlainSerializer]], required=False, default_factory=list, description="Cover images. Please use an image smaller than 500KB and an aspect ratio width to height of 2:1.\\nThe supported image formats are: ('.gif', '.jpeg', '.jpg', '.png', '.svg')", examples=['cover.png']), 'id_emoji': FieldInfo(annotation=Union[Annotated[str, Len], NoneType], required=False), 'authors': FieldInfo(annotation=List[Author], required=False, default_factory=list), 'attachments': FieldInfo(annotation=Union[AttachmentsDescr, NoneType], required=False), 'cite': FieldInfo(annotation=List[CiteEntry], required=False, default_factory=list), 'config': FieldInfo(annotation=Dict[str, YamlValue], required=False, default_factory=dict, examples=[{'bioimageio': {'my_custom_key': 3837283, 'another_key': {'nested': 'value'}}, 'imagej': {'macro_dir': 'path/to/macro/file'}}]), 'download_url': FieldInfo(annotation=Union[HttpUrl, NoneType], required=False), 'git_repo': FieldInfo(annotation=Union[str, NoneType], required=False, examples=['https://github.com/bioimage-io/spec-bioimage-io/tree/main/example_descriptions/models/unet2d_nuclei_broad']), 'icon': FieldInfo(annotation=Union[Annotated[Union[Annotated[Path, PathType], RelativeFilePath, HttpUrl, Annotated[Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator, PlainSerializer], Annotated[str, Len], NoneType], required=False), 'links': FieldInfo(annotation=List[str], required=False, default_factory=list, examples=[('ilastik/ilastik', 'deepimagej/deepimagej', 'zero/notebook_u-net_3d_zerocostdl4mic')]), 'uploader': FieldInfo(annotation=Union[Uploader, NoneType], required=False), 'maintainers': FieldInfo(annotation=List[Maintainer], required=False, default_factory=list), 'rdf_source': FieldInfo(annotation=Union[Annotated[Path, PathType], RelativeFilePath, HttpUrl, Annotated[Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)], NoneType], required=False), 'tags': FieldInfo(annotation=List[str], required=False, default_factory=list, examples=[('unet2d', 'pytorch', 'nucleus', 'segmentation', 'dsb2018')]), 'version': FieldInfo(annotation=Union[Version, NoneType], required=False), 'version_number': FieldInfo(annotation=Union[int, NoneType], required=False), 'format_version': FieldInfo(annotation=Literal['0.2.4'], required=False, default='0.2.4'), 'badges': FieldInfo(annotation=List[BadgeDescr], required=False, default_factory=list), 'documentation': FieldInfo(annotation=Union[Annotated[Union[Annotated[Path, PathType], RelativeFilePath, HttpUrl, Annotated[Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator, PlainSerializer], NoneType], required=False, examples=['https://raw.githubusercontent.com/bioimage-io/spec-bioimage-io/main/example_descriptions/models/unet2d_nuclei_broad/README.md', 'README.md']), 'license': FieldInfo(annotation=Union[LicenseId, DeprecatedLicenseId, str, NoneType], required=False, examples=['CC-BY-4.0', 'MIT', 'BSD-2-Clause'])}"}, "bioimageio.spec.generic.v0_2.GenericDescrBase.model_computed_fields": {"fullname": "bioimageio.spec.generic.v0_2.GenericDescrBase.model_computed_fields", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "GenericDescrBase.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.generic.v0_2.GenericDescr": {"fullname": "bioimageio.spec.generic.v0_2.GenericDescr", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "GenericDescr", "kind": "class", "doc": "
    Specification of the fields used in a generic bioimage.io-compliant resource description file (RDF).
    \n\n
    An RDF is a YAML file that describes a resource such as a model, a dataset, or a notebook.\nNote that those resources are described with a type-specific RDF.\nUse this generic resource description, if none of the known specific types matches your resource.
    \n", "bases": "GenericDescrBase"}, "bioimageio.spec.generic.v0_2.GenericDescr.type": {"fullname": "bioimageio.spec.generic.v0_2.GenericDescr.type", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "GenericDescr.type", "kind": "variable", "doc": "
    The resource type assigns a broad category to the resource.
    \n", "annotation": ": Annotated[str, Annotated[~_StrType, Predicate(func=<method 'islower' of 'str' objects>)], FieldInfo(annotation=NoneType, required=True, frozen=True)]"}, "bioimageio.spec.generic.v0_2.GenericDescr.id": {"fullname": "bioimageio.spec.generic.v0_2.GenericDescr.id", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "GenericDescr.id", "kind": "variable", "doc": "
    Model zoo (bioimage.io) wide, unique identifier (assigned by bioimage.io)
    \n", "annotation": ": Optional[bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]]]"}, "bioimageio.spec.generic.v0_2.GenericDescr.source": {"fullname": "bioimageio.spec.generic.v0_2.GenericDescr.source", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "GenericDescr.source", "kind": "variable", "doc": "
    The primary source of the resource
    \n", "annotation": ": Optional[bioimageio.spec._internal.url.HttpUrl]"}, "bioimageio.spec.generic.v0_2.GenericDescr.check_specific_types": {"fullname": "bioimageio.spec.generic.v0_2.GenericDescr.check_specific_types", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "GenericDescr.check_specific_types", "kind": "function", "doc": "
    \n", "signature": "(cls, value: str) -> str:", "funcdef": "def"}, "bioimageio.spec.generic.v0_2.GenericDescr.implemented_format_version": {"fullname": "bioimageio.spec.generic.v0_2.GenericDescr.implemented_format_version", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "GenericDescr.implemented_format_version", "kind": "variable", "doc": "
    \n", "annotation": ": ClassVar[str]", "default_value": "'0.2.4'"}, "bioimageio.spec.generic.v0_2.GenericDescr.implemented_format_version_tuple": {"fullname": "bioimageio.spec.generic.v0_2.GenericDescr.implemented_format_version_tuple", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "GenericDescr.implemented_format_version_tuple", "kind": "variable", "doc": "
    \n", "annotation": ": ClassVar[Tuple[int, int, int]]", "default_value": "(0, 2, 4)"}, "bioimageio.spec.generic.v0_2.GenericDescr.model_config": {"fullname": "bioimageio.spec.generic.v0_2.GenericDescr.model_config", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "GenericDescr.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'ignore', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True, 'title': 'bioimage.io generic specification'}"}, "bioimageio.spec.generic.v0_2.GenericDescr.model_fields": {"fullname": "bioimageio.spec.generic.v0_2.GenericDescr.model_fields", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "GenericDescr.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'name': FieldInfo(annotation=str, required=True, metadata=[MinLen(min_length=1), AfterWarner(func=<function as_warning.<locals>.wrapper>, severity=30, msg='Longer than 128 characters.', context={'typ': typing.Annotated[typing.Any, MaxLen(max_length=128)]})]), 'description': FieldInfo(annotation=str, required=True), 'covers': FieldInfo(annotation=List[Annotated[Union[HttpUrl, Annotated[Path, PathType, Predicate], RelativeFilePath], WithSuffix, PlainSerializer]], required=False, default_factory=list, description="Cover images. Please use an image smaller than 500KB and an aspect ratio width to height of 2:1.\\nThe supported image formats are: ('.gif', '.jpeg', '.jpg', '.png', '.svg')", examples=['cover.png']), 'id_emoji': FieldInfo(annotation=Union[Annotated[str, Len], NoneType], required=False), 'authors': FieldInfo(annotation=List[Author], required=False, default_factory=list), 'attachments': FieldInfo(annotation=Union[AttachmentsDescr, NoneType], required=False), 'cite': FieldInfo(annotation=List[CiteEntry], required=False, default_factory=list), 'config': FieldInfo(annotation=Dict[str, YamlValue], required=False, default_factory=dict, examples=[{'bioimageio': {'my_custom_key': 3837283, 'another_key': {'nested': 'value'}}, 'imagej': {'macro_dir': 'path/to/macro/file'}}]), 'download_url': FieldInfo(annotation=Union[HttpUrl, NoneType], required=False), 'git_repo': FieldInfo(annotation=Union[str, NoneType], required=False, examples=['https://github.com/bioimage-io/spec-bioimage-io/tree/main/example_descriptions/models/unet2d_nuclei_broad']), 'icon': FieldInfo(annotation=Union[Annotated[Union[Annotated[Path, PathType], RelativeFilePath, HttpUrl, Annotated[Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator, PlainSerializer], Annotated[str, Len], NoneType], required=False), 'links': FieldInfo(annotation=List[str], required=False, default_factory=list, examples=[('ilastik/ilastik', 'deepimagej/deepimagej', 'zero/notebook_u-net_3d_zerocostdl4mic')]), 'uploader': FieldInfo(annotation=Union[Uploader, NoneType], required=False), 'maintainers': FieldInfo(annotation=List[Maintainer], required=False, default_factory=list), 'rdf_source': FieldInfo(annotation=Union[Annotated[Path, PathType], RelativeFilePath, HttpUrl, Annotated[Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)], NoneType], required=False), 'tags': FieldInfo(annotation=List[str], required=False, default_factory=list, examples=[('unet2d', 'pytorch', 'nucleus', 'segmentation', 'dsb2018')]), 'version': FieldInfo(annotation=Union[Version, NoneType], required=False), 'version_number': FieldInfo(annotation=Union[int, NoneType], required=False), 'format_version': FieldInfo(annotation=Literal['0.2.4'], required=False, default='0.2.4'), 'badges': FieldInfo(annotation=List[BadgeDescr], required=False, default_factory=list), 'documentation': FieldInfo(annotation=Union[Annotated[Union[Annotated[Path, PathType], RelativeFilePath, HttpUrl, Annotated[Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator, PlainSerializer], NoneType], required=False, examples=['https://raw.githubusercontent.com/bioimage-io/spec-bioimage-io/main/example_descriptions/models/unet2d_nuclei_broad/README.md', 'README.md']), 'license': FieldInfo(annotation=Union[LicenseId, DeprecatedLicenseId, str, NoneType], required=False, examples=['CC-BY-4.0', 'MIT', 'BSD-2-Clause']), 'type': FieldInfo(annotation=str, required=False, default='generic', frozen=True, metadata=[typing.Annotated[~_StrType, Predicate(func=<method 'islower' of 'str' objects>)]]), 'id': FieldInfo(annotation=Union[ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]], NoneType], required=False), 'source': FieldInfo(annotation=Union[HttpUrl, NoneType], required=False)}"}, "bioimageio.spec.generic.v0_2.GenericDescr.model_computed_fields": {"fullname": "bioimageio.spec.generic.v0_2.GenericDescr.model_computed_fields", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "GenericDescr.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.generic.v0_3": {"fullname": "bioimageio.spec.generic.v0_3", "modulename": "bioimageio.spec.generic.v0_3", "kind": "module", "doc": "
    \n"}, "bioimageio.spec.generic.v0_3.KNOWN_SPECIFIC_RESOURCE_TYPES": {"fullname": "bioimageio.spec.generic.v0_3.KNOWN_SPECIFIC_RESOURCE_TYPES", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "KNOWN_SPECIFIC_RESOURCE_TYPES", "kind": "variable", "doc": "
    \n", "default_value": "('application', 'collection', 'dataset', 'model', 'notebook')"}, "bioimageio.spec.generic.v0_3.DocumentationSource": {"fullname": "bioimageio.spec.generic.v0_3.DocumentationSource", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "DocumentationSource", "kind": "variable", "doc": "
    \n", "default_value": "typing.Annotated[typing.Union[typing.Annotated[pathlib.Path, PathType(path_type='file'), Predicate(func=<function PurePath.is_absolute>)], bioimageio.spec._internal.io.RelativeFilePath, bioimageio.spec._internal.url.HttpUrl], AfterValidator(func=<function _validate_md_suffix>), PlainSerializer(func=<function _package>, return_type=PydanticUndefined, when_used='unless-none')]"}, "bioimageio.spec.generic.v0_3.Author": {"fullname": "bioimageio.spec.generic.v0_3.Author", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "Author", "kind": "class", "doc": "
    Subpart of a resource description
    \n", "bases": "bioimageio.spec.generic.v0_2.Author"}, "bioimageio.spec.generic.v0_3.Author.name": {"fullname": "bioimageio.spec.generic.v0_3.Author.name", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "Author.name", "kind": "variable", "doc": "
    \n", "annotation": ": Annotated[str, Predicate(func=<function _has_no_slash at 0x7f1c21bacb80>)]"}, "bioimageio.spec.generic.v0_3.Author.github_user": {"fullname": "bioimageio.spec.generic.v0_3.Author.github_user", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "Author.github_user", "kind": "variable", "doc": "
    \n", "annotation": ": Optional[str]"}, "bioimageio.spec.generic.v0_3.Author.model_config": {"fullname": "bioimageio.spec.generic.v0_3.Author.model_config", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "Author.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.generic.v0_3.Author.model_fields": {"fullname": "bioimageio.spec.generic.v0_3.Author.model_fields", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "Author.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'affiliation': FieldInfo(annotation=Union[str, NoneType], required=False), 'email': FieldInfo(annotation=Union[EmailStr, NoneType], required=False), 'orcid': FieldInfo(annotation=Union[ValidatedString[Annotated[str, AfterValidator]], NoneType], required=False, examples=['0000-0001-2345-6789']), 'name': FieldInfo(annotation=str, required=True, metadata=[Predicate(func=<function _has_no_slash>)]), 'github_user': FieldInfo(annotation=Union[str, NoneType], required=False)}"}, "bioimageio.spec.generic.v0_3.Author.model_computed_fields": {"fullname": "bioimageio.spec.generic.v0_3.Author.model_computed_fields", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "Author.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.generic.v0_3.Maintainer": {"fullname": "bioimageio.spec.generic.v0_3.Maintainer", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "Maintainer", "kind": "class", "doc": "
    Subpart of a resource description
    \n", "bases": "bioimageio.spec.generic.v0_2.Maintainer"}, "bioimageio.spec.generic.v0_3.Maintainer.name": {"fullname": "bioimageio.spec.generic.v0_3.Maintainer.name", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "Maintainer.name", "kind": "variable", "doc": "
    \n", "annotation": ": Optional[Annotated[str, Predicate(func=<function _has_no_slash at 0x7f1c21bacb80>)]]"}, "bioimageio.spec.generic.v0_3.Maintainer.github_user": {"fullname": "bioimageio.spec.generic.v0_3.Maintainer.github_user", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "Maintainer.github_user", "kind": "variable", "doc": "
    \n", "annotation": ": str"}, "bioimageio.spec.generic.v0_3.Maintainer.validate_gh_user": {"fullname": "bioimageio.spec.generic.v0_3.Maintainer.validate_gh_user", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "Maintainer.validate_gh_user", "kind": "function", "doc": "
    \n", "signature": "(cls, value: str):", "funcdef": "def"}, "bioimageio.spec.generic.v0_3.Maintainer.model_config": {"fullname": "bioimageio.spec.generic.v0_3.Maintainer.model_config", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "Maintainer.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.generic.v0_3.Maintainer.model_fields": {"fullname": "bioimageio.spec.generic.v0_3.Maintainer.model_fields", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "Maintainer.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'affiliation': FieldInfo(annotation=Union[str, NoneType], required=False), 'email': FieldInfo(annotation=Union[EmailStr, NoneType], required=False), 'orcid': FieldInfo(annotation=Union[ValidatedString[Annotated[str, AfterValidator]], NoneType], required=False, examples=['0000-0001-2345-6789']), 'name': FieldInfo(annotation=Union[Annotated[str, Predicate], NoneType], required=False), 'github_user': FieldInfo(annotation=str, required=True)}"}, "bioimageio.spec.generic.v0_3.Maintainer.model_computed_fields": {"fullname": "bioimageio.spec.generic.v0_3.Maintainer.model_computed_fields", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "Maintainer.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.generic.v0_3.CiteEntry": {"fullname": "bioimageio.spec.generic.v0_3.CiteEntry", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "CiteEntry", "kind": "class", "doc": "
    Subpart of a resource description
    \n", "bases": "bioimageio.spec._internal.node.Node"}, "bioimageio.spec.generic.v0_3.CiteEntry.text": {"fullname": "bioimageio.spec.generic.v0_3.CiteEntry.text", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "CiteEntry.text", "kind": "variable", "doc": "
    free text description
    \n", "annotation": ": str"}, "bioimageio.spec.generic.v0_3.CiteEntry.doi": {"fullname": "bioimageio.spec.generic.v0_3.CiteEntry.doi", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "CiteEntry.doi", "kind": "variable", "doc": "
    A digital object identifier (DOI) is the prefered citation reference.\nSee https://www.doi.org/ for details. (alternatively specify url)
    \n", "annotation": ": Optional[bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, StringConstraints]]]"}, "bioimageio.spec.generic.v0_3.CiteEntry.url": {"fullname": "bioimageio.spec.generic.v0_3.CiteEntry.url", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "CiteEntry.url", "kind": "variable", "doc": "
    URL to cite (preferably specify a doi instead)
    \n", "annotation": ": Optional[bioimageio.spec._internal.url.HttpUrl]"}, "bioimageio.spec.generic.v0_3.CiteEntry.model_config": {"fullname": "bioimageio.spec.generic.v0_3.CiteEntry.model_config", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "CiteEntry.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.generic.v0_3.CiteEntry.model_fields": {"fullname": "bioimageio.spec.generic.v0_3.CiteEntry.model_fields", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "CiteEntry.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'text': FieldInfo(annotation=str, required=True), 'doi': FieldInfo(annotation=Union[ValidatedString[Annotated[str, StringConstraints]], NoneType], required=False), 'url': FieldInfo(annotation=Union[HttpUrl, NoneType], required=False)}"}, "bioimageio.spec.generic.v0_3.CiteEntry.model_computed_fields": {"fullname": "bioimageio.spec.generic.v0_3.CiteEntry.model_computed_fields", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "CiteEntry.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.generic.v0_3.LinkedResource": {"fullname": "bioimageio.spec.generic.v0_3.LinkedResource", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "LinkedResource", "kind": "class", "doc": "
    Reference to a bioimage.io resource
    \n", "bases": "bioimageio.spec._internal.node.Node"}, "bioimageio.spec.generic.v0_3.LinkedResource.id": {"fullname": "bioimageio.spec.generic.v0_3.LinkedResource.id", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "LinkedResource.id", "kind": "variable", "doc": "
    A valid resource id from the official bioimage.io collection.
    \n", "annotation": ": bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]]"}, "bioimageio.spec.generic.v0_3.LinkedResource.version_number": {"fullname": "bioimageio.spec.generic.v0_3.LinkedResource.version_number", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "LinkedResource.version_number", "kind": "variable", "doc": "
    version number (n-th published version, not the semantic version) of linked resource
    \n", "annotation": ": int"}, "bioimageio.spec.generic.v0_3.LinkedResource.model_config": {"fullname": "bioimageio.spec.generic.v0_3.LinkedResource.model_config", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "LinkedResource.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.generic.v0_3.LinkedResource.model_fields": {"fullname": "bioimageio.spec.generic.v0_3.LinkedResource.model_fields", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "LinkedResource.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'id': FieldInfo(annotation=ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]], required=True), 'version_number': FieldInfo(annotation=int, required=True)}"}, "bioimageio.spec.generic.v0_3.LinkedResource.model_computed_fields": {"fullname": "bioimageio.spec.generic.v0_3.LinkedResource.model_computed_fields", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "LinkedResource.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.generic.v0_3.GenericModelDescrBase": {"fullname": "bioimageio.spec.generic.v0_3.GenericModelDescrBase", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "GenericModelDescrBase", "kind": "class", "doc": "
    Base for all resource descriptions including of model descriptions
    \n", "bases": "bioimageio.spec._internal.common_nodes.ResourceDescrBase"}, "bioimageio.spec.generic.v0_3.GenericModelDescrBase.name": {"fullname": "bioimageio.spec.generic.v0_3.GenericModelDescrBase.name", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "GenericModelDescrBase.name", "kind": "variable", "doc": "
    A human-friendly name of the resource description
    \n", "annotation": ": Annotated[str, MinLen(min_length=1), MaxLen(max_length=128)]"}, "bioimageio.spec.generic.v0_3.GenericModelDescrBase.description": {"fullname": "bioimageio.spec.generic.v0_3.GenericModelDescrBase.description", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "GenericModelDescrBase.description", "kind": "variable", "doc": "
    A string containing a brief description.
    \n", "annotation": ": Annotated[str, MaxLen(max_length=1024), AfterWarner(func=<function as_warning.<locals>.wrapper at 0x7f1c138bef20>, severity=30, msg='Description longer than 512 characters.', context={'typ': Annotated[Any, MaxLen(max_length=512)]})]"}, "bioimageio.spec.generic.v0_3.GenericModelDescrBase.covers": {"fullname": "bioimageio.spec.generic.v0_3.GenericModelDescrBase.covers", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "GenericModelDescrBase.covers", "kind": "variable", "doc": "
    \u2208\ud83d\udce6 Cover images.
    \n", "annotation": ": Annotated[List[Annotated[Union[bioimageio.spec._internal.url.HttpUrl, Annotated[pathlib.Path, PathType(path_type='file'), Predicate(func=<function PurePath.is_absolute at 0x7f1c25245940>)], bioimageio.spec._internal.io.RelativeFilePath], WithSuffix(suffix=('.gif', '.jpeg', '.jpg', '.png', '.svg'), case_sensitive=False), PlainSerializer(func=<function _package at 0x7f1c21c782c0>, return_type=PydanticUndefined, when_used='unless-none')]], FieldInfo(annotation=NoneType, required=True, description="Cover images. Please use an image smaller than 500KB and an aspect ratio width to height of 2:1 or 1:1.\\nThe supported image formats are: ('.gif', '.jpeg', '.jpg', '.png', '.svg')", examples=[])]"}, "bioimageio.spec.generic.v0_3.GenericModelDescrBase.id_emoji": {"fullname": "bioimageio.spec.generic.v0_3.GenericModelDescrBase.id_emoji", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "GenericModelDescrBase.id_emoji", "kind": "variable", "doc": "
    UTF-8 emoji for display alongside the id.
    \n", "annotation": ": Optional[Annotated[str, Len(min_length=1, max_length=1)]]"}, "bioimageio.spec.generic.v0_3.GenericModelDescrBase.authors": {"fullname": "bioimageio.spec.generic.v0_3.GenericModelDescrBase.authors", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "GenericModelDescrBase.authors", "kind": "variable", "doc": "
    The authors are the creators of this resource description and the primary points of contact.
    \n", "annotation": ": Annotated[List[bioimageio.spec.generic.v0_3.Author], MinLen(min_length=1)]"}, "bioimageio.spec.generic.v0_3.GenericModelDescrBase.attachments": {"fullname": "bioimageio.spec.generic.v0_3.GenericModelDescrBase.attachments", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "GenericModelDescrBase.attachments", "kind": "variable", "doc": "
    file attachments
    \n", "annotation": ": List[bioimageio.spec._internal.io.FileDescr]"}, "bioimageio.spec.generic.v0_3.GenericModelDescrBase.cite": {"fullname": "bioimageio.spec.generic.v0_3.GenericModelDescrBase.cite", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "GenericModelDescrBase.cite", "kind": "variable", "doc": "
    citations
    \n", "annotation": ": Annotated[List[bioimageio.spec.generic.v0_3.CiteEntry], MinLen(min_length=1)]"}, "bioimageio.spec.generic.v0_3.GenericModelDescrBase.license": {"fullname": "bioimageio.spec.generic.v0_3.GenericModelDescrBase.license", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "GenericModelDescrBase.license", "kind": "variable", "doc": "
    A SPDX license identifier.\nWe do not support custom license beyond the SPDX license list, if you need that please\nopen a GitHub issue\nto discuss your intentions with the community.
    \n", "annotation": ": Annotated[Union[bioimageio.spec._internal.license_id.LicenseId, bioimageio.spec._internal.license_id.DeprecatedLicenseId], AfterWarner(func=<function as_warning.<locals>.wrapper at 0x7f1c138bd620>, severity=30, msg='{value} is deprecated, see https://spdx.org/licenses/{value}.html', context={'typ': <class 'bioimageio.spec._internal.license_id.LicenseId'>}), FieldInfo(annotation=NoneType, required=True, examples=['CC-BY-4.0', 'MIT', 'BSD-2-Clause'])]"}, "bioimageio.spec.generic.v0_3.GenericModelDescrBase.config": {"fullname": "bioimageio.spec.generic.v0_3.GenericModelDescrBase.config", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "GenericModelDescrBase.config", "kind": "variable", "doc": "
    A field for custom configuration that can contain any keys not present in the RDF spec.\nThis means you should not store, for example, a GitHub repo URL in config since there is a git_repo field.\nKeys in config may be very specific to a tool or consumer software. To avoid conflicting definitions,\nit is recommended to wrap added configuration into a sub-field named with the specific domain or tool name,\nfor example:
    \n\n
    \n
    config:\n    bioimageio:  # here is the domain name\n        my_custom_key: 3837283\n        another_key:\n            nested: value\n    imagej:       # config specific to ImageJ\n        macro_dir: path/to/macro/file\n
    \n
    \n\n
    If possible, please use snake_case for keys in config.\nYou may want to list linked files additionally under attachments to include them when packaging a resource.\n(Packaging a resource means downloading/copying important linked files and creating a ZIP archive that contains\nan altered rdf.yaml file with local references to the downloaded files.)
    \n", "annotation": ": Annotated[Dict[str, YamlValue], FieldInfo(annotation=NoneType, required=True, examples=[{'bioimageio': {'my_custom_key': 3837283, 'another_key': {'nested': 'value'}}, 'imagej': {'macro_dir': 'path/to/macro/file'}}])]"}, "bioimageio.spec.generic.v0_3.GenericModelDescrBase.git_repo": {"fullname": "bioimageio.spec.generic.v0_3.GenericModelDescrBase.git_repo", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "GenericModelDescrBase.git_repo", "kind": "variable", "doc": "
    A URL to the Git repository where the resource is being developed.
    \n", "annotation": ": Annotated[Optional[bioimageio.spec._internal.url.HttpUrl], FieldInfo(annotation=NoneType, required=True, examples=['https://github.com/bioimage-io/spec-bioimage-io/tree/main/example_descriptions/models/unet2d_nuclei_broad'])]"}, "bioimageio.spec.generic.v0_3.GenericModelDescrBase.icon": {"fullname": "bioimageio.spec.generic.v0_3.GenericModelDescrBase.icon", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "GenericModelDescrBase.icon", "kind": "variable", "doc": "
    An icon for illustration, e.g. on bioimage.io
    \n", "annotation": ": Union[Annotated[Union[Annotated[pathlib.Path, PathType(path_type='file')], bioimageio.spec._internal.io.RelativeFilePath, bioimageio.spec._internal.url.HttpUrl, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator(func=<function wo_special_file_name at 0x7f1c21c3ef20>), PlainSerializer(func=<function _package at 0x7f1c21c782c0>, return_type=PydanticUndefined, when_used='unless-none')], Annotated[str, Len(min_length=1, max_length=2)], NoneType]"}, "bioimageio.spec.generic.v0_3.GenericModelDescrBase.links": {"fullname": "bioimageio.spec.generic.v0_3.GenericModelDescrBase.links", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "GenericModelDescrBase.links", "kind": "variable", "doc": "
    IDs of other bioimage.io resources
    \n", "annotation": ": Annotated[List[str], FieldInfo(annotation=NoneType, required=True, examples=[('ilastik/ilastik', 'deepimagej/deepimagej', 'zero/notebook_u-net_3d_zerocostdl4mic')])]"}, "bioimageio.spec.generic.v0_3.GenericModelDescrBase.uploader": {"fullname": "bioimageio.spec.generic.v0_3.GenericModelDescrBase.uploader", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "GenericModelDescrBase.uploader", "kind": "variable", "doc": "
    The person who uploaded the model (e.g. to bioimage.io)
    \n", "annotation": ": Optional[bioimageio.spec.generic.v0_2.Uploader]"}, "bioimageio.spec.generic.v0_3.GenericModelDescrBase.maintainers": {"fullname": "bioimageio.spec.generic.v0_3.GenericModelDescrBase.maintainers", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "GenericModelDescrBase.maintainers", "kind": "variable", "doc": "
    Maintainers of this resource.\nIf not specified, authors are maintainers and at least some of them has to specify their github_user name
    \n", "annotation": ": List[bioimageio.spec.generic.v0_3.Maintainer]"}, "bioimageio.spec.generic.v0_3.GenericModelDescrBase.check_maintainers_exist": {"fullname": "bioimageio.spec.generic.v0_3.GenericModelDescrBase.check_maintainers_exist", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "GenericModelDescrBase.check_maintainers_exist", "kind": "function", "doc": "
    \n", "signature": "(value: Any, info: pydantic_core.core_schema.ValidationInfo) -> Any:", "funcdef": "def"}, "bioimageio.spec.generic.v0_3.GenericModelDescrBase.tags": {"fullname": "bioimageio.spec.generic.v0_3.GenericModelDescrBase.tags", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "GenericModelDescrBase.tags", "kind": "variable", "doc": "
    Associated tags
    \n", "annotation": ": Annotated[List[str], FieldInfo(annotation=NoneType, required=True, examples=[('unet2d', 'pytorch', 'nucleus', 'segmentation', 'dsb2018')])]"}, "bioimageio.spec.generic.v0_3.GenericModelDescrBase.warn_about_tag_categories": {"fullname": "bioimageio.spec.generic.v0_3.GenericModelDescrBase.warn_about_tag_categories", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "GenericModelDescrBase.warn_about_tag_categories", "kind": "function", "doc": "
    \n", "signature": "(value: Any, info: pydantic_core.core_schema.ValidationInfo) -> Any:", "funcdef": "def"}, "bioimageio.spec.generic.v0_3.GenericModelDescrBase.version": {"fullname": "bioimageio.spec.generic.v0_3.GenericModelDescrBase.version", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "GenericModelDescrBase.version", "kind": "variable", "doc": "
    The version of the resource following SemVer 2.0.
    \n", "annotation": ": Optional[bioimageio.spec._internal.version_type.Version]"}, "bioimageio.spec.generic.v0_3.GenericModelDescrBase.version_number": {"fullname": "bioimageio.spec.generic.v0_3.GenericModelDescrBase.version_number", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "GenericModelDescrBase.version_number", "kind": "variable", "doc": "
    version number (n-th published version, not the semantic version)
    \n", "annotation": ": Optional[int]"}, "bioimageio.spec.generic.v0_3.GenericModelDescrBase.model_config": {"fullname": "bioimageio.spec.generic.v0_3.GenericModelDescrBase.model_config", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "GenericModelDescrBase.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.generic.v0_3.GenericModelDescrBase.model_fields": {"fullname": "bioimageio.spec.generic.v0_3.GenericModelDescrBase.model_fields", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "GenericModelDescrBase.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'name': FieldInfo(annotation=str, required=True, metadata=[MinLen(min_length=1), MaxLen(max_length=128)]), 'description': FieldInfo(annotation=str, required=True, metadata=[MaxLen(max_length=1024), AfterWarner(func=<function as_warning.<locals>.wrapper>, severity=30, msg='Description longer than 512 characters.', context={'typ': typing.Annotated[typing.Any, MaxLen(max_length=512)]})]), 'covers': FieldInfo(annotation=List[Annotated[Union[HttpUrl, Annotated[Path, PathType, Predicate], RelativeFilePath], WithSuffix, PlainSerializer]], required=False, default_factory=list, description="Cover images. Please use an image smaller than 500KB and an aspect ratio width to height of 2:1 or 1:1.\\nThe supported image formats are: ('.gif', '.jpeg', '.jpg', '.png', '.svg')", examples=[]), 'id_emoji': FieldInfo(annotation=Union[Annotated[str, Len], NoneType], required=False), 'authors': FieldInfo(annotation=List[Author], required=True, metadata=[MinLen(min_length=1)]), 'attachments': FieldInfo(annotation=List[FileDescr], required=False, default_factory=list), 'cite': FieldInfo(annotation=List[CiteEntry], required=True, metadata=[MinLen(min_length=1)]), 'license': FieldInfo(annotation=Union[LicenseId, DeprecatedLicenseId], required=True, examples=['CC-BY-4.0', 'MIT', 'BSD-2-Clause'], metadata=[AfterWarner(func=<function as_warning.<locals>.wrapper>, severity=30, msg='{value} is deprecated, see https://spdx.org/licenses/{value}.html', context={'typ': <class 'bioimageio.spec._internal.license_id.LicenseId'>})]), 'config': FieldInfo(annotation=Dict[str, YamlValue], required=False, default_factory=dict, examples=[{'bioimageio': {'my_custom_key': 3837283, 'another_key': {'nested': 'value'}}, 'imagej': {'macro_dir': 'path/to/macro/file'}}]), 'git_repo': FieldInfo(annotation=Union[HttpUrl, NoneType], required=False, examples=['https://github.com/bioimage-io/spec-bioimage-io/tree/main/example_descriptions/models/unet2d_nuclei_broad']), 'icon': FieldInfo(annotation=Union[Annotated[Union[Annotated[Path, PathType], RelativeFilePath, HttpUrl, Annotated[Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator, PlainSerializer], Annotated[str, Len], NoneType], required=False), 'links': FieldInfo(annotation=List[str], required=False, default_factory=list, examples=[('ilastik/ilastik', 'deepimagej/deepimagej', 'zero/notebook_u-net_3d_zerocostdl4mic')]), 'uploader': FieldInfo(annotation=Union[Uploader, NoneType], required=False), 'maintainers': FieldInfo(annotation=List[Maintainer], required=False, default_factory=list), 'tags': FieldInfo(annotation=List[str], required=False, default_factory=list, examples=[('unet2d', 'pytorch', 'nucleus', 'segmentation', 'dsb2018')]), 'version': FieldInfo(annotation=Union[Version, NoneType], required=False), 'version_number': FieldInfo(annotation=Union[int, NoneType], required=False)}"}, "bioimageio.spec.generic.v0_3.GenericModelDescrBase.model_computed_fields": {"fullname": "bioimageio.spec.generic.v0_3.GenericModelDescrBase.model_computed_fields", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "GenericModelDescrBase.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.generic.v0_3.GenericDescrBase": {"fullname": "bioimageio.spec.generic.v0_3.GenericDescrBase", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "GenericDescrBase", "kind": "class", "doc": "
    Base for all resource descriptions except for the model descriptions
    \n", "bases": "GenericModelDescrBase"}, "bioimageio.spec.generic.v0_3.GenericDescrBase.format_version": {"fullname": "bioimageio.spec.generic.v0_3.GenericDescrBase.format_version", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "GenericDescrBase.format_version", "kind": "variable", "doc": "
    The format version of this resource specification
    \n", "annotation": ": Literal['0.3.0']"}, "bioimageio.spec.generic.v0_3.GenericDescrBase.documentation": {"fullname": "bioimageio.spec.generic.v0_3.GenericDescrBase.documentation", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "GenericDescrBase.documentation", "kind": "variable", "doc": "
    \u2208\ud83d\udce6 URL or relative path to a markdown file with additional documentation.\nThe recommended documentation file name is README.md. An .md suffix is mandatory.
    \n", "annotation": ": Annotated[Optional[Annotated[Union[Annotated[pathlib.Path, PathType(path_type='file'), Predicate(func=<function PurePath.is_absolute at 0x7f1c25245940>)], bioimageio.spec._internal.io.RelativeFilePath, bioimageio.spec._internal.url.HttpUrl], AfterValidator(func=<function _validate_md_suffix at 0x7f1c21d1afc0>), PlainSerializer(func=<function _package at 0x7f1c21c782c0>, return_type=PydanticUndefined, when_used='unless-none')]], FieldInfo(annotation=NoneType, required=True, examples=['https://raw.githubusercontent.com/bioimage-io/spec-bioimage-io/main/example_descriptions/models/unet2d_nuclei_broad/README.md', 'README.md'])]"}, "bioimageio.spec.generic.v0_3.GenericDescrBase.badges": {"fullname": "bioimageio.spec.generic.v0_3.GenericDescrBase.badges", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "GenericDescrBase.badges", "kind": "variable", "doc": "
    badges associated with this resource
    \n", "annotation": ": List[bioimageio.spec.generic.v0_2.BadgeDescr]"}, "bioimageio.spec.generic.v0_3.GenericDescrBase.implemented_format_version": {"fullname": "bioimageio.spec.generic.v0_3.GenericDescrBase.implemented_format_version", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "GenericDescrBase.implemented_format_version", "kind": "variable", "doc": "
    \n", "annotation": ": ClassVar[str]", "default_value": "'0.3.0'"}, "bioimageio.spec.generic.v0_3.GenericDescrBase.implemented_format_version_tuple": {"fullname": "bioimageio.spec.generic.v0_3.GenericDescrBase.implemented_format_version_tuple", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "GenericDescrBase.implemented_format_version_tuple", "kind": "variable", "doc": "
    \n", "annotation": ": ClassVar[Tuple[int, int, int]]", "default_value": "(0, 3, 0)"}, "bioimageio.spec.generic.v0_3.GenericDescrBase.model_config": {"fullname": "bioimageio.spec.generic.v0_3.GenericDescrBase.model_config", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "GenericDescrBase.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.generic.v0_3.GenericDescrBase.model_fields": {"fullname": "bioimageio.spec.generic.v0_3.GenericDescrBase.model_fields", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "GenericDescrBase.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'name': FieldInfo(annotation=str, required=True, metadata=[MinLen(min_length=1), MaxLen(max_length=128)]), 'description': FieldInfo(annotation=str, required=True, metadata=[MaxLen(max_length=1024), AfterWarner(func=<function as_warning.<locals>.wrapper>, severity=30, msg='Description longer than 512 characters.', context={'typ': typing.Annotated[typing.Any, MaxLen(max_length=512)]})]), 'covers': FieldInfo(annotation=List[Annotated[Union[HttpUrl, Annotated[Path, PathType, Predicate], RelativeFilePath], WithSuffix, PlainSerializer]], required=False, default_factory=list, description="Cover images. Please use an image smaller than 500KB and an aspect ratio width to height of 2:1 or 1:1.\\nThe supported image formats are: ('.gif', '.jpeg', '.jpg', '.png', '.svg')", examples=[]), 'id_emoji': FieldInfo(annotation=Union[Annotated[str, Len], NoneType], required=False), 'authors': FieldInfo(annotation=List[Author], required=True, metadata=[MinLen(min_length=1)]), 'attachments': FieldInfo(annotation=List[FileDescr], required=False, default_factory=list), 'cite': FieldInfo(annotation=List[CiteEntry], required=True, metadata=[MinLen(min_length=1)]), 'license': FieldInfo(annotation=Union[LicenseId, DeprecatedLicenseId], required=True, examples=['CC-BY-4.0', 'MIT', 'BSD-2-Clause'], metadata=[AfterWarner(func=<function as_warning.<locals>.wrapper>, severity=30, msg='{value} is deprecated, see https://spdx.org/licenses/{value}.html', context={'typ': <class 'bioimageio.spec._internal.license_id.LicenseId'>})]), 'config': FieldInfo(annotation=Dict[str, YamlValue], required=False, default_factory=dict, examples=[{'bioimageio': {'my_custom_key': 3837283, 'another_key': {'nested': 'value'}}, 'imagej': {'macro_dir': 'path/to/macro/file'}}]), 'git_repo': FieldInfo(annotation=Union[HttpUrl, NoneType], required=False, examples=['https://github.com/bioimage-io/spec-bioimage-io/tree/main/example_descriptions/models/unet2d_nuclei_broad']), 'icon': FieldInfo(annotation=Union[Annotated[Union[Annotated[Path, PathType], RelativeFilePath, HttpUrl, Annotated[Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator, PlainSerializer], Annotated[str, Len], NoneType], required=False), 'links': FieldInfo(annotation=List[str], required=False, default_factory=list, examples=[('ilastik/ilastik', 'deepimagej/deepimagej', 'zero/notebook_u-net_3d_zerocostdl4mic')]), 'uploader': FieldInfo(annotation=Union[Uploader, NoneType], required=False), 'maintainers': FieldInfo(annotation=List[Maintainer], required=False, default_factory=list), 'tags': FieldInfo(annotation=List[str], required=False, default_factory=list, examples=[('unet2d', 'pytorch', 'nucleus', 'segmentation', 'dsb2018')]), 'version': FieldInfo(annotation=Union[Version, NoneType], required=False), 'version_number': FieldInfo(annotation=Union[int, NoneType], required=False), 'format_version': FieldInfo(annotation=Literal['0.3.0'], required=False, default='0.3.0'), 'documentation': FieldInfo(annotation=Union[Annotated[Union[Annotated[Path, PathType, Predicate], RelativeFilePath, HttpUrl], AfterValidator, PlainSerializer], NoneType], required=False, examples=['https://raw.githubusercontent.com/bioimage-io/spec-bioimage-io/main/example_descriptions/models/unet2d_nuclei_broad/README.md', 'README.md']), 'badges': FieldInfo(annotation=List[BadgeDescr], required=False, default_factory=list)}"}, "bioimageio.spec.generic.v0_3.GenericDescrBase.model_computed_fields": {"fullname": "bioimageio.spec.generic.v0_3.GenericDescrBase.model_computed_fields", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "GenericDescrBase.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.generic.v0_3.GenericDescr": {"fullname": "bioimageio.spec.generic.v0_3.GenericDescr", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "GenericDescr", "kind": "class", "doc": "
    Specification of the fields used in a generic bioimage.io-compliant resource description file (RDF).
    \n\n
    An RDF is a YAML file that describes a resource such as a model, a dataset, or a notebook.\nNote that those resources are described with a type-specific RDF.\nUse this generic resource description, if none of the known specific types matches your resource.
    \n", "bases": "GenericDescrBase"}, "bioimageio.spec.generic.v0_3.GenericDescr.type": {"fullname": "bioimageio.spec.generic.v0_3.GenericDescr.type", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "GenericDescr.type", "kind": "variable", "doc": "
    The resource type assigns a broad category to the resource.
    \n", "annotation": ": Annotated[str, Annotated[~_StrType, Predicate(func=<method 'islower' of 'str' objects>)]]"}, "bioimageio.spec.generic.v0_3.GenericDescr.id": {"fullname": "bioimageio.spec.generic.v0_3.GenericDescr.id", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "GenericDescr.id", "kind": "variable", "doc": "
    Model zoo (bioimage.io) wide, unique identifier (assigned by bioimage.io)
    \n", "annotation": ": Optional[bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]]]"}, "bioimageio.spec.generic.v0_3.GenericDescr.parent": {"fullname": "bioimageio.spec.generic.v0_3.GenericDescr.parent", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "GenericDescr.parent", "kind": "variable", "doc": "
    The description from which this one is derived
    \n", "annotation": ": Optional[bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]]]"}, "bioimageio.spec.generic.v0_3.GenericDescr.source": {"fullname": "bioimageio.spec.generic.v0_3.GenericDescr.source", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "GenericDescr.source", "kind": "variable", "doc": "
    The primary source of the resource
    \n", "annotation": ": Optional[bioimageio.spec._internal.url.HttpUrl]"}, "bioimageio.spec.generic.v0_3.GenericDescr.check_specific_types": {"fullname": "bioimageio.spec.generic.v0_3.GenericDescr.check_specific_types", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "GenericDescr.check_specific_types", "kind": "function", "doc": "
    \n", "signature": "(cls, value: str) -> str:", "funcdef": "def"}, "bioimageio.spec.generic.v0_3.GenericDescr.implemented_format_version": {"fullname": "bioimageio.spec.generic.v0_3.GenericDescr.implemented_format_version", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "GenericDescr.implemented_format_version", "kind": "variable", "doc": "
    \n", "annotation": ": ClassVar[str]", "default_value": "'0.3.0'"}, "bioimageio.spec.generic.v0_3.GenericDescr.implemented_format_version_tuple": {"fullname": "bioimageio.spec.generic.v0_3.GenericDescr.implemented_format_version_tuple", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "GenericDescr.implemented_format_version_tuple", "kind": "variable", "doc": "
    \n", "annotation": ": ClassVar[Tuple[int, int, int]]", "default_value": "(0, 3, 0)"}, "bioimageio.spec.generic.v0_3.GenericDescr.model_config": {"fullname": "bioimageio.spec.generic.v0_3.GenericDescr.model_config", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "GenericDescr.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'ignore', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True, 'title': 'bioimage.io generic specification'}"}, "bioimageio.spec.generic.v0_3.GenericDescr.model_fields": {"fullname": "bioimageio.spec.generic.v0_3.GenericDescr.model_fields", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "GenericDescr.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'name': FieldInfo(annotation=str, required=True, metadata=[MinLen(min_length=1), MaxLen(max_length=128)]), 'description': FieldInfo(annotation=str, required=True, metadata=[MaxLen(max_length=1024), AfterWarner(func=<function as_warning.<locals>.wrapper>, severity=30, msg='Description longer than 512 characters.', context={'typ': typing.Annotated[typing.Any, MaxLen(max_length=512)]})]), 'covers': FieldInfo(annotation=List[Annotated[Union[HttpUrl, Annotated[Path, PathType, Predicate], RelativeFilePath], WithSuffix, PlainSerializer]], required=False, default_factory=list, description="Cover images. Please use an image smaller than 500KB and an aspect ratio width to height of 2:1 or 1:1.\\nThe supported image formats are: ('.gif', '.jpeg', '.jpg', '.png', '.svg')", examples=[]), 'id_emoji': FieldInfo(annotation=Union[Annotated[str, Len], NoneType], required=False), 'authors': FieldInfo(annotation=List[Author], required=True, metadata=[MinLen(min_length=1)]), 'attachments': FieldInfo(annotation=List[FileDescr], required=False, default_factory=list), 'cite': FieldInfo(annotation=List[CiteEntry], required=True, metadata=[MinLen(min_length=1)]), 'license': FieldInfo(annotation=Union[LicenseId, DeprecatedLicenseId], required=True, examples=['CC-BY-4.0', 'MIT', 'BSD-2-Clause'], metadata=[AfterWarner(func=<function as_warning.<locals>.wrapper>, severity=30, msg='{value} is deprecated, see https://spdx.org/licenses/{value}.html', context={'typ': <class 'bioimageio.spec._internal.license_id.LicenseId'>})]), 'config': FieldInfo(annotation=Dict[str, YamlValue], required=False, default_factory=dict, examples=[{'bioimageio': {'my_custom_key': 3837283, 'another_key': {'nested': 'value'}}, 'imagej': {'macro_dir': 'path/to/macro/file'}}]), 'git_repo': FieldInfo(annotation=Union[HttpUrl, NoneType], required=False, examples=['https://github.com/bioimage-io/spec-bioimage-io/tree/main/example_descriptions/models/unet2d_nuclei_broad']), 'icon': FieldInfo(annotation=Union[Annotated[Union[Annotated[Path, PathType], RelativeFilePath, HttpUrl, Annotated[Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator, PlainSerializer], Annotated[str, Len], NoneType], required=False), 'links': FieldInfo(annotation=List[str], required=False, default_factory=list, examples=[('ilastik/ilastik', 'deepimagej/deepimagej', 'zero/notebook_u-net_3d_zerocostdl4mic')]), 'uploader': FieldInfo(annotation=Union[Uploader, NoneType], required=False), 'maintainers': FieldInfo(annotation=List[Maintainer], required=False, default_factory=list), 'tags': FieldInfo(annotation=List[str], required=False, default_factory=list, examples=[('unet2d', 'pytorch', 'nucleus', 'segmentation', 'dsb2018')]), 'version': FieldInfo(annotation=Union[Version, NoneType], required=False), 'version_number': FieldInfo(annotation=Union[int, NoneType], required=False), 'format_version': FieldInfo(annotation=Literal['0.3.0'], required=False, default='0.3.0'), 'documentation': FieldInfo(annotation=Union[Annotated[Union[Annotated[Path, PathType, Predicate], RelativeFilePath, HttpUrl], AfterValidator, PlainSerializer], NoneType], required=False, examples=['https://raw.githubusercontent.com/bioimage-io/spec-bioimage-io/main/example_descriptions/models/unet2d_nuclei_broad/README.md', 'README.md']), 'badges': FieldInfo(annotation=List[BadgeDescr], required=False, default_factory=list), 'type': FieldInfo(annotation=str, required=False, default='generic', frozen=True, metadata=[typing.Annotated[~_StrType, Predicate(func=<method 'islower' of 'str' objects>)]]), 'id': FieldInfo(annotation=Union[ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]], NoneType], required=False), 'parent': FieldInfo(annotation=Union[ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]], NoneType], required=False), 'source': FieldInfo(annotation=Union[HttpUrl, NoneType], required=False)}"}, "bioimageio.spec.generic.v0_3.GenericDescr.model_computed_fields": {"fullname": "bioimageio.spec.generic.v0_3.GenericDescr.model_computed_fields", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "GenericDescr.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model": {"fullname": "bioimageio.spec.model", "modulename": "bioimageio.spec.model", "kind": "module", "doc": "
    implementaions of all released minor versions are available in submodules:
    \n\n\n"}, "bioimageio.spec.model.AnyModelDescr": {"fullname": "bioimageio.spec.model.AnyModelDescr", "modulename": "bioimageio.spec.model", "qualname": "AnyModelDescr", "kind": "variable", "doc": "
    Union of any released model desription
    \n", "default_value": "typing.Annotated[typing.Union[bioimageio.spec.model.v0_4.ModelDescr, bioimageio.spec.model.v0_5.ModelDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)]"}, "bioimageio.spec.model.v0_4": {"fullname": "bioimageio.spec.model.v0_4", "modulename": "bioimageio.spec.model.v0_4", "kind": "module", "doc": "
    \n"}, "bioimageio.spec.model.v0_4.AxesStr": {"fullname": "bioimageio.spec.model.v0_4.AxesStr", "modulename": "bioimageio.spec.model.v0_4", "qualname": "AxesStr", "kind": "variable", "doc": "
    \n", "default_value": "typing.Annotated[str, RestrictCharacters(alphabet='bitczyx'), AfterValidator(func=<function validate_unique_entries>)]"}, "bioimageio.spec.model.v0_4.AxesInCZYX": {"fullname": "bioimageio.spec.model.v0_4.AxesInCZYX", "modulename": "bioimageio.spec.model.v0_4", "qualname": "AxesInCZYX", "kind": "variable", "doc": "
    \n", "default_value": "typing.Annotated[str, RestrictCharacters(alphabet='czyx'), AfterValidator(func=<function validate_unique_entries>)]"}, "bioimageio.spec.model.v0_4.PostprocessingName": {"fullname": "bioimageio.spec.model.v0_4.PostprocessingName", "modulename": "bioimageio.spec.model.v0_4", "qualname": "PostprocessingName", "kind": "variable", "doc": "
    \n", "default_value": "typing.Literal['binarize', 'clip', 'scale_linear', 'sigmoid', 'zero_mean_unit_variance', 'scale_range', 'scale_mean_variance']"}, "bioimageio.spec.model.v0_4.PreprocessingName": {"fullname": "bioimageio.spec.model.v0_4.PreprocessingName", "modulename": "bioimageio.spec.model.v0_4", "qualname": "PreprocessingName", "kind": "variable", "doc": "
    \n", "default_value": "typing.Literal['binarize', 'clip', 'scale_linear', 'sigmoid', 'zero_mean_unit_variance', 'scale_range']"}, "bioimageio.spec.model.v0_4.TensorName": {"fullname": "bioimageio.spec.model.v0_4.TensorName", "modulename": "bioimageio.spec.model.v0_4", "qualname": "TensorName", "kind": "variable", "doc": "
    \n", "default_value": "<class 'bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate]]]'>"}, "bioimageio.spec.model.v0_4.CallableFromDepencency": {"fullname": "bioimageio.spec.model.v0_4.CallableFromDepencency", "modulename": "bioimageio.spec.model.v0_4", "qualname": "CallableFromDepencency", "kind": "class", "doc": "
    deprecated! don't use for new spec fields!
    \n", "bases": "bioimageio.spec._internal.common_nodes.StringNode"}, "bioimageio.spec.model.v0_4.CallableFromDepencency.module_name": {"fullname": "bioimageio.spec.model.v0_4.CallableFromDepencency.module_name", "modulename": "bioimageio.spec.model.v0_4", "qualname": "CallableFromDepencency.module_name", "kind": "variable", "doc": "
    \n", "annotation": ": str"}, "bioimageio.spec.model.v0_4.CallableFromDepencency.check_submodules": {"fullname": "bioimageio.spec.model.v0_4.CallableFromDepencency.check_submodules", "modulename": "bioimageio.spec.model.v0_4", "qualname": "CallableFromDepencency.check_submodules", "kind": "function", "doc": "
    \n", "signature": "(cls, module_name: str) -> str:", "funcdef": "def"}, "bioimageio.spec.model.v0_4.CallableFromDepencency.callable_name": {"fullname": "bioimageio.spec.model.v0_4.CallableFromDepencency.callable_name", "modulename": "bioimageio.spec.model.v0_4", "qualname": "CallableFromDepencency.callable_name", "kind": "variable", "doc": "
    \n", "annotation": ": bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator]]"}, "bioimageio.spec.model.v0_4.CallableFromFile": {"fullname": "bioimageio.spec.model.v0_4.CallableFromFile", "modulename": "bioimageio.spec.model.v0_4", "qualname": "CallableFromFile", "kind": "class", "doc": "
    deprecated! don't use for new spec fields!
    \n", "bases": "bioimageio.spec._internal.common_nodes.StringNode"}, "bioimageio.spec.model.v0_4.CallableFromFile.source_file": {"fullname": "bioimageio.spec.model.v0_4.CallableFromFile.source_file", "modulename": "bioimageio.spec.model.v0_4", "qualname": "CallableFromFile.source_file", "kind": "variable", "doc": "
    \u2208\ud83d\udce6 Python module that implements callable_name
    \n", "annotation": ": Annotated[Union[bioimageio.spec._internal.url.HttpUrl, bioimageio.spec._internal.io.RelativeFilePath], PlainSerializer(func=<function _package at 0x7f1c21c782c0>, return_type=PydanticUndefined, when_used='unless-none')]"}, "bioimageio.spec.model.v0_4.CallableFromFile.callable_name": {"fullname": "bioimageio.spec.model.v0_4.CallableFromFile.callable_name", "modulename": "bioimageio.spec.model.v0_4", "qualname": "CallableFromFile.callable_name", "kind": "variable", "doc": "
    The Python identifier of
    \n", "annotation": ": bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator]]"}, "bioimageio.spec.model.v0_4.CustomCallable": {"fullname": "bioimageio.spec.model.v0_4.CustomCallable", "modulename": "bioimageio.spec.model.v0_4", "qualname": "CustomCallable", "kind": "variable", "doc": "
    \n", "default_value": "typing.Union[bioimageio.spec.model.v0_4.CallableFromFile, bioimageio.spec.model.v0_4.CallableFromDepencency]"}, "bioimageio.spec.model.v0_4.Dependencies": {"fullname": "bioimageio.spec.model.v0_4.Dependencies", "modulename": "bioimageio.spec.model.v0_4", "qualname": "Dependencies", "kind": "class", "doc": "
    deprecated! don't use for new spec fields!
    \n", "bases": "bioimageio.spec._internal.common_nodes.StringNode"}, "bioimageio.spec.model.v0_4.Dependencies.manager": {"fullname": "bioimageio.spec.model.v0_4.Dependencies.manager", "modulename": "bioimageio.spec.model.v0_4", "qualname": "Dependencies.manager", "kind": "variable", "doc": "
    Dependency manager
    \n", "annotation": ": Annotated[str, MinLen(min_length=1), FieldInfo(annotation=NoneType, required=True, examples=['conda', 'maven', 'pip'])]"}, "bioimageio.spec.model.v0_4.Dependencies.file": {"fullname": "bioimageio.spec.model.v0_4.Dependencies.file", "modulename": "bioimageio.spec.model.v0_4", "qualname": "Dependencies.file", "kind": "variable", "doc": "
    \u2208\ud83d\udce6 Dependency file
    \n", "annotation": ": Annotated[Union[Annotated[pathlib.Path, PathType(path_type='file')], bioimageio.spec._internal.io.RelativeFilePath, bioimageio.spec._internal.url.HttpUrl, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator(func=<function wo_special_file_name at 0x7f1c21c3ef20>), PlainSerializer(func=<function _package at 0x7f1c21c782c0>, return_type=PydanticUndefined, when_used='unless-none'), FieldInfo(annotation=NoneType, required=True, examples=['environment.yaml', 'pom.xml', 'requirements.txt'])]"}, "bioimageio.spec.model.v0_4.WeightsFormat": {"fullname": "bioimageio.spec.model.v0_4.WeightsFormat", "modulename": "bioimageio.spec.model.v0_4", "qualname": "WeightsFormat", "kind": "variable", "doc": "
    \n", "default_value": "typing.Literal['keras_hdf5', 'onnx', 'pytorch_state_dict', 'tensorflow_js', 'tensorflow_saved_model_bundle', 'torchscript']"}, "bioimageio.spec.model.v0_4.WeightsDescr": {"fullname": "bioimageio.spec.model.v0_4.WeightsDescr", "modulename": "bioimageio.spec.model.v0_4", "qualname": "WeightsDescr", "kind": "class", "doc": "
    Subpart of a resource description
    \n", "bases": "bioimageio.spec._internal.node.Node"}, "bioimageio.spec.model.v0_4.WeightsDescr.keras_hdf5": {"fullname": "bioimageio.spec.model.v0_4.WeightsDescr.keras_hdf5", "modulename": "bioimageio.spec.model.v0_4", "qualname": "WeightsDescr.keras_hdf5", "kind": "variable", "doc": "
    \n", "annotation": ": Optional[bioimageio.spec.model.v0_4.KerasHdf5WeightsDescr]"}, "bioimageio.spec.model.v0_4.WeightsDescr.onnx": {"fullname": "bioimageio.spec.model.v0_4.WeightsDescr.onnx", "modulename": "bioimageio.spec.model.v0_4", "qualname": "WeightsDescr.onnx", "kind": "variable", "doc": "
    \n", "annotation": ": Optional[bioimageio.spec.model.v0_4.OnnxWeightsDescr]"}, "bioimageio.spec.model.v0_4.WeightsDescr.pytorch_state_dict": {"fullname": "bioimageio.spec.model.v0_4.WeightsDescr.pytorch_state_dict", "modulename": "bioimageio.spec.model.v0_4", "qualname": "WeightsDescr.pytorch_state_dict", "kind": "variable", "doc": "
    \n", "annotation": ": Optional[bioimageio.spec.model.v0_4.PytorchStateDictWeightsDescr]"}, "bioimageio.spec.model.v0_4.WeightsDescr.tensorflow_js": {"fullname": "bioimageio.spec.model.v0_4.WeightsDescr.tensorflow_js", "modulename": "bioimageio.spec.model.v0_4", "qualname": "WeightsDescr.tensorflow_js", "kind": "variable", "doc": "
    \n", "annotation": ": Optional[bioimageio.spec.model.v0_4.TensorflowJsWeightsDescr]"}, "bioimageio.spec.model.v0_4.WeightsDescr.tensorflow_saved_model_bundle": {"fullname": "bioimageio.spec.model.v0_4.WeightsDescr.tensorflow_saved_model_bundle", "modulename": "bioimageio.spec.model.v0_4", "qualname": "WeightsDescr.tensorflow_saved_model_bundle", "kind": "variable", "doc": "
    \n", "annotation": ": Optional[bioimageio.spec.model.v0_4.TensorflowSavedModelBundleWeightsDescr]"}, "bioimageio.spec.model.v0_4.WeightsDescr.torchscript": {"fullname": "bioimageio.spec.model.v0_4.WeightsDescr.torchscript", "modulename": "bioimageio.spec.model.v0_4", "qualname": "WeightsDescr.torchscript", "kind": "variable", "doc": "
    \n", "annotation": ": Optional[bioimageio.spec.model.v0_4.TorchscriptWeightsDescr]"}, "bioimageio.spec.model.v0_4.WeightsDescr.check_one_entry": {"fullname": "bioimageio.spec.model.v0_4.WeightsDescr.check_one_entry", "modulename": "bioimageio.spec.model.v0_4", "qualname": "WeightsDescr.check_one_entry", "kind": "function", "doc": "
    \n", "signature": "(self) -> Self:", "funcdef": "def"}, "bioimageio.spec.model.v0_4.WeightsDescr.model_config": {"fullname": "bioimageio.spec.model.v0_4.WeightsDescr.model_config", "modulename": "bioimageio.spec.model.v0_4", "qualname": "WeightsDescr.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_4.WeightsDescr.model_fields": {"fullname": "bioimageio.spec.model.v0_4.WeightsDescr.model_fields", "modulename": "bioimageio.spec.model.v0_4", "qualname": "WeightsDescr.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'keras_hdf5': FieldInfo(annotation=Union[KerasHdf5WeightsDescr, NoneType], required=False), 'onnx': FieldInfo(annotation=Union[OnnxWeightsDescr, NoneType], required=False), 'pytorch_state_dict': FieldInfo(annotation=Union[PytorchStateDictWeightsDescr, NoneType], required=False), 'tensorflow_js': FieldInfo(annotation=Union[TensorflowJsWeightsDescr, NoneType], required=False), 'tensorflow_saved_model_bundle': FieldInfo(annotation=Union[TensorflowSavedModelBundleWeightsDescr, NoneType], required=False), 'torchscript': FieldInfo(annotation=Union[TorchscriptWeightsDescr, NoneType], required=False)}"}, "bioimageio.spec.model.v0_4.WeightsDescr.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_4.WeightsDescr.model_computed_fields", "modulename": "bioimageio.spec.model.v0_4", "qualname": "WeightsDescr.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_4.WeightsEntryDescrBase": {"fullname": "bioimageio.spec.model.v0_4.WeightsEntryDescrBase", "modulename": "bioimageio.spec.model.v0_4", "qualname": "WeightsEntryDescrBase", "kind": "class", "doc": "
    Subpart of a resource description
    \n", "bases": "bioimageio.spec._internal.io.FileDescr"}, "bioimageio.spec.model.v0_4.WeightsEntryDescrBase.type": {"fullname": "bioimageio.spec.model.v0_4.WeightsEntryDescrBase.type", "modulename": "bioimageio.spec.model.v0_4", "qualname": "WeightsEntryDescrBase.type", "kind": "variable", "doc": "
    \n", "annotation": ": ClassVar[Literal['keras_hdf5', 'onnx', 'pytorch_state_dict', 'tensorflow_js', 'tensorflow_saved_model_bundle', 'torchscript']]"}, "bioimageio.spec.model.v0_4.WeightsEntryDescrBase.weights_format_name": {"fullname": "bioimageio.spec.model.v0_4.WeightsEntryDescrBase.weights_format_name", "modulename": "bioimageio.spec.model.v0_4", "qualname": "WeightsEntryDescrBase.weights_format_name", "kind": "variable", "doc": "
    \n", "annotation": ": ClassVar[str]"}, "bioimageio.spec.model.v0_4.WeightsEntryDescrBase.source": {"fullname": "bioimageio.spec.model.v0_4.WeightsEntryDescrBase.source", "modulename": "bioimageio.spec.model.v0_4", "qualname": "WeightsEntryDescrBase.source", "kind": "variable", "doc": "
    \u2208\ud83d\udce6 The weights file.
    \n", "annotation": ": Annotated[Union[Annotated[pathlib.Path, PathType(path_type='file')], bioimageio.spec._internal.io.RelativeFilePath, bioimageio.spec._internal.url.HttpUrl, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator(func=<function wo_special_file_name at 0x7f1c21c3ef20>), PlainSerializer(func=<function _package at 0x7f1c21c782c0>, return_type=PydanticUndefined, when_used='unless-none')]"}, "bioimageio.spec.model.v0_4.WeightsEntryDescrBase.attachments": {"fullname": "bioimageio.spec.model.v0_4.WeightsEntryDescrBase.attachments", "modulename": "bioimageio.spec.model.v0_4", "qualname": "WeightsEntryDescrBase.attachments", "kind": "variable", "doc": "
    Attachments that are specific to this weights entry.
    \n", "annotation": ": Annotated[Optional[bioimageio.spec.generic.v0_2.AttachmentsDescr], AfterWarner(func=<function as_warning.<locals>.wrapper at 0x7f1c1306dbc0>, severity=35, msg='Weights entry depends on additional attachments.', context={'typ': None})]"}, "bioimageio.spec.model.v0_4.WeightsEntryDescrBase.authors": {"fullname": "bioimageio.spec.model.v0_4.WeightsEntryDescrBase.authors", "modulename": "bioimageio.spec.model.v0_4", "qualname": "WeightsEntryDescrBase.authors", "kind": "variable", "doc": "
    Authors\nEither the person(s) that have trained this model resulting in the original weights file.\n    (If this is the initial weights entry, i.e. it does not have a parent)\nOr the person(s) who have converted the weights to this weights format.\n    (If this is a child weight, i.e. it has a parent field)
    \n", "annotation": ": Optional[List[bioimageio.spec.generic.v0_2.Author]]"}, "bioimageio.spec.model.v0_4.WeightsEntryDescrBase.dependencies": {"fullname": "bioimageio.spec.model.v0_4.WeightsEntryDescrBase.dependencies", "modulename": "bioimageio.spec.model.v0_4", "qualname": "WeightsEntryDescrBase.dependencies", "kind": "variable", "doc": "
    Dependency manager and dependency file, specified as <dependency manager>:<relative file path>.
    \n", "annotation": ": Annotated[Optional[bioimageio.spec.model.v0_4.Dependencies], AfterWarner(func=<function as_warning.<locals>.wrapper at 0x7f1c1306fce0>, severity=30, msg='Custom dependencies ({value}) specified. Avoid this whenever possible to allow execution in a wider range of software environments.', context={'typ': None}), FieldInfo(annotation=NoneType, required=True, examples=['conda:environment.yaml', 'maven:./pom.xml', 'pip:./requirements.txt'])]"}, "bioimageio.spec.model.v0_4.WeightsEntryDescrBase.parent": {"fullname": "bioimageio.spec.model.v0_4.WeightsEntryDescrBase.parent", "modulename": "bioimageio.spec.model.v0_4", "qualname": "WeightsEntryDescrBase.parent", "kind": "variable", "doc": "
    The source weights these weights were converted from.\nFor example, if a model's weights were converted from the pytorch_state_dict format to torchscript,\nThe pytorch_state_dict weights entry has no parent and is the parent of the torchscript weights.\nAll weight entries except one (the initial set of weights resulting from training the model),\nneed to have this field.
    \n", "annotation": ": Annotated[Optional[Literal['keras_hdf5', 'onnx', 'pytorch_state_dict', 'tensorflow_js', 'tensorflow_saved_model_bundle', 'torchscript']], FieldInfo(annotation=NoneType, required=True, examples=['pytorch_state_dict'])]"}, "bioimageio.spec.model.v0_4.WeightsEntryDescrBase.check_parent_is_not_self": {"fullname": "bioimageio.spec.model.v0_4.WeightsEntryDescrBase.check_parent_is_not_self", "modulename": "bioimageio.spec.model.v0_4", "qualname": "WeightsEntryDescrBase.check_parent_is_not_self", "kind": "function", "doc": "
    \n", "signature": "(self) -> Self:", "funcdef": "def"}, "bioimageio.spec.model.v0_4.WeightsEntryDescrBase.model_config": {"fullname": "bioimageio.spec.model.v0_4.WeightsEntryDescrBase.model_config", "modulename": "bioimageio.spec.model.v0_4", "qualname": "WeightsEntryDescrBase.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_4.WeightsEntryDescrBase.model_fields": {"fullname": "bioimageio.spec.model.v0_4.WeightsEntryDescrBase.model_fields", "modulename": "bioimageio.spec.model.v0_4", "qualname": "WeightsEntryDescrBase.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'source': FieldInfo(annotation=Union[Annotated[Path, PathType], RelativeFilePath, HttpUrl, Annotated[Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], required=True, metadata=[AfterValidator(func=<function wo_special_file_name>), PlainSerializer(func=<function _package>, return_type=PydanticUndefined, when_used='unless-none')]), 'sha256': FieldInfo(annotation=Union[Sha256, NoneType], required=False), 'attachments': FieldInfo(annotation=Union[AttachmentsDescr, NoneType], required=False, metadata=[AfterWarner(func=<function as_warning.<locals>.wrapper>, severity=35, msg='Weights entry depends on additional attachments.', context={'typ': None})]), 'authors': FieldInfo(annotation=Union[List[Author], NoneType], required=False), 'dependencies': FieldInfo(annotation=Union[Dependencies, NoneType], required=False, examples=['conda:environment.yaml', 'maven:./pom.xml', 'pip:./requirements.txt'], metadata=[AfterWarner(func=<function as_warning.<locals>.wrapper>, severity=30, msg='Custom dependencies ({value}) specified. Avoid this whenever possible to allow execution in a wider range of software environments.', context={'typ': None})]), 'parent': FieldInfo(annotation=Union[Literal['keras_hdf5', 'onnx', 'pytorch_state_dict', 'tensorflow_js', 'tensorflow_saved_model_bundle', 'torchscript'], NoneType], required=False, examples=['pytorch_state_dict'])}"}, "bioimageio.spec.model.v0_4.WeightsEntryDescrBase.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_4.WeightsEntryDescrBase.model_computed_fields", "modulename": "bioimageio.spec.model.v0_4", "qualname": "WeightsEntryDescrBase.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_4.KerasHdf5WeightsDescr": {"fullname": "bioimageio.spec.model.v0_4.KerasHdf5WeightsDescr", "modulename": "bioimageio.spec.model.v0_4", "qualname": "KerasHdf5WeightsDescr", "kind": "class", "doc": "
    Subpart of a resource description
    \n", "bases": "WeightsEntryDescrBase"}, "bioimageio.spec.model.v0_4.KerasHdf5WeightsDescr.type": {"fullname": "bioimageio.spec.model.v0_4.KerasHdf5WeightsDescr.type", "modulename": "bioimageio.spec.model.v0_4", "qualname": "KerasHdf5WeightsDescr.type", "kind": "variable", "doc": "
    \n", "default_value": "'keras_hdf5'"}, "bioimageio.spec.model.v0_4.KerasHdf5WeightsDescr.weights_format_name": {"fullname": "bioimageio.spec.model.v0_4.KerasHdf5WeightsDescr.weights_format_name", "modulename": "bioimageio.spec.model.v0_4", "qualname": "KerasHdf5WeightsDescr.weights_format_name", "kind": "variable", "doc": "
    \n", "annotation": ": ClassVar[str]", "default_value": "'Keras HDF5'"}, "bioimageio.spec.model.v0_4.KerasHdf5WeightsDescr.tensorflow_version": {"fullname": "bioimageio.spec.model.v0_4.KerasHdf5WeightsDescr.tensorflow_version", "modulename": "bioimageio.spec.model.v0_4", "qualname": "KerasHdf5WeightsDescr.tensorflow_version", "kind": "variable", "doc": "
    TensorFlow version used to create these weights
    \n", "annotation": ": Optional[bioimageio.spec._internal.version_type.Version]"}, "bioimageio.spec.model.v0_4.KerasHdf5WeightsDescr.model_config": {"fullname": "bioimageio.spec.model.v0_4.KerasHdf5WeightsDescr.model_config", "modulename": "bioimageio.spec.model.v0_4", "qualname": "KerasHdf5WeightsDescr.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_4.KerasHdf5WeightsDescr.model_fields": {"fullname": "bioimageio.spec.model.v0_4.KerasHdf5WeightsDescr.model_fields", "modulename": "bioimageio.spec.model.v0_4", "qualname": "KerasHdf5WeightsDescr.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'source': FieldInfo(annotation=Union[Annotated[Path, PathType], RelativeFilePath, HttpUrl, Annotated[Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], required=True, metadata=[AfterValidator(func=<function wo_special_file_name>), PlainSerializer(func=<function _package>, return_type=PydanticUndefined, when_used='unless-none')]), 'sha256': FieldInfo(annotation=Union[Sha256, NoneType], required=False), 'attachments': FieldInfo(annotation=Union[AttachmentsDescr, NoneType], required=False, metadata=[AfterWarner(func=<function as_warning.<locals>.wrapper>, severity=35, msg='Weights entry depends on additional attachments.', context={'typ': None})]), 'authors': FieldInfo(annotation=Union[List[Author], NoneType], required=False), 'dependencies': FieldInfo(annotation=Union[Dependencies, NoneType], required=False, examples=['conda:environment.yaml', 'maven:./pom.xml', 'pip:./requirements.txt'], metadata=[AfterWarner(func=<function as_warning.<locals>.wrapper>, severity=30, msg='Custom dependencies ({value}) specified. Avoid this whenever possible to allow execution in a wider range of software environments.', context={'typ': None})]), 'parent': FieldInfo(annotation=Union[Literal['keras_hdf5', 'onnx', 'pytorch_state_dict', 'tensorflow_js', 'tensorflow_saved_model_bundle', 'torchscript'], NoneType], required=False, examples=['pytorch_state_dict']), 'tensorflow_version': FieldInfo(annotation=Union[Version, NoneType], required=False)}"}, "bioimageio.spec.model.v0_4.KerasHdf5WeightsDescr.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_4.KerasHdf5WeightsDescr.model_computed_fields", "modulename": "bioimageio.spec.model.v0_4", "qualname": "KerasHdf5WeightsDescr.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_4.OnnxWeightsDescr": {"fullname": "bioimageio.spec.model.v0_4.OnnxWeightsDescr", "modulename": "bioimageio.spec.model.v0_4", "qualname": "OnnxWeightsDescr", "kind": "class", "doc": "
    Subpart of a resource description
    \n", "bases": "WeightsEntryDescrBase"}, "bioimageio.spec.model.v0_4.OnnxWeightsDescr.type": {"fullname": "bioimageio.spec.model.v0_4.OnnxWeightsDescr.type", "modulename": "bioimageio.spec.model.v0_4", "qualname": "OnnxWeightsDescr.type", "kind": "variable", "doc": "
    \n", "default_value": "'onnx'"}, "bioimageio.spec.model.v0_4.OnnxWeightsDescr.weights_format_name": {"fullname": "bioimageio.spec.model.v0_4.OnnxWeightsDescr.weights_format_name", "modulename": "bioimageio.spec.model.v0_4", "qualname": "OnnxWeightsDescr.weights_format_name", "kind": "variable", "doc": "
    \n", "annotation": ": ClassVar[str]", "default_value": "'ONNX'"}, "bioimageio.spec.model.v0_4.OnnxWeightsDescr.opset_version": {"fullname": "bioimageio.spec.model.v0_4.OnnxWeightsDescr.opset_version", "modulename": "bioimageio.spec.model.v0_4", "qualname": "OnnxWeightsDescr.opset_version", "kind": "variable", "doc": "
    ONNX opset version
    \n", "annotation": ": Optional[Annotated[int, Ge(ge=7)]]"}, "bioimageio.spec.model.v0_4.OnnxWeightsDescr.model_config": {"fullname": "bioimageio.spec.model.v0_4.OnnxWeightsDescr.model_config", "modulename": "bioimageio.spec.model.v0_4", "qualname": "OnnxWeightsDescr.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_4.OnnxWeightsDescr.model_fields": {"fullname": "bioimageio.spec.model.v0_4.OnnxWeightsDescr.model_fields", "modulename": "bioimageio.spec.model.v0_4", "qualname": "OnnxWeightsDescr.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'source': FieldInfo(annotation=Union[Annotated[Path, PathType], RelativeFilePath, HttpUrl, Annotated[Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], required=True, metadata=[AfterValidator(func=<function wo_special_file_name>), PlainSerializer(func=<function _package>, return_type=PydanticUndefined, when_used='unless-none')]), 'sha256': FieldInfo(annotation=Union[Sha256, NoneType], required=False), 'attachments': FieldInfo(annotation=Union[AttachmentsDescr, NoneType], required=False, metadata=[AfterWarner(func=<function as_warning.<locals>.wrapper>, severity=35, msg='Weights entry depends on additional attachments.', context={'typ': None})]), 'authors': FieldInfo(annotation=Union[List[Author], NoneType], required=False), 'dependencies': FieldInfo(annotation=Union[Dependencies, NoneType], required=False, examples=['conda:environment.yaml', 'maven:./pom.xml', 'pip:./requirements.txt'], metadata=[AfterWarner(func=<function as_warning.<locals>.wrapper>, severity=30, msg='Custom dependencies ({value}) specified. Avoid this whenever possible to allow execution in a wider range of software environments.', context={'typ': None})]), 'parent': FieldInfo(annotation=Union[Literal['keras_hdf5', 'onnx', 'pytorch_state_dict', 'tensorflow_js', 'tensorflow_saved_model_bundle', 'torchscript'], NoneType], required=False, examples=['pytorch_state_dict']), 'opset_version': FieldInfo(annotation=Union[Annotated[int, Ge], NoneType], required=False)}"}, "bioimageio.spec.model.v0_4.OnnxWeightsDescr.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_4.OnnxWeightsDescr.model_computed_fields", "modulename": "bioimageio.spec.model.v0_4", "qualname": "OnnxWeightsDescr.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_4.PytorchStateDictWeightsDescr": {"fullname": "bioimageio.spec.model.v0_4.PytorchStateDictWeightsDescr", "modulename": "bioimageio.spec.model.v0_4", "qualname": "PytorchStateDictWeightsDescr", "kind": "class", "doc": "
    Subpart of a resource description
    \n", "bases": "WeightsEntryDescrBase"}, "bioimageio.spec.model.v0_4.PytorchStateDictWeightsDescr.type": {"fullname": "bioimageio.spec.model.v0_4.PytorchStateDictWeightsDescr.type", "modulename": "bioimageio.spec.model.v0_4", "qualname": "PytorchStateDictWeightsDescr.type", "kind": "variable", "doc": "
    \n", "default_value": "'pytorch_state_dict'"}, "bioimageio.spec.model.v0_4.PytorchStateDictWeightsDescr.weights_format_name": {"fullname": "bioimageio.spec.model.v0_4.PytorchStateDictWeightsDescr.weights_format_name", "modulename": "bioimageio.spec.model.v0_4", "qualname": "PytorchStateDictWeightsDescr.weights_format_name", "kind": "variable", "doc": "
    \n", "annotation": ": ClassVar[str]", "default_value": "'Pytorch State Dict'"}, "bioimageio.spec.model.v0_4.PytorchStateDictWeightsDescr.architecture": {"fullname": "bioimageio.spec.model.v0_4.PytorchStateDictWeightsDescr.architecture", "modulename": "bioimageio.spec.model.v0_4", "qualname": "PytorchStateDictWeightsDescr.architecture", "kind": "variable", "doc": "
    callable returning a torch.nn.Module instance.\nLocal implementation: <relative path to file>:<identifier of implementation within the file>.\nImplementation in a dependency: <dependency-package>.<[dependency-module]>.<identifier>.
    \n", "annotation": ": Union[bioimageio.spec.model.v0_4.CallableFromFile, bioimageio.spec.model.v0_4.CallableFromDepencency]"}, "bioimageio.spec.model.v0_4.PytorchStateDictWeightsDescr.architecture_sha256": {"fullname": "bioimageio.spec.model.v0_4.PytorchStateDictWeightsDescr.architecture_sha256", "modulename": "bioimageio.spec.model.v0_4", "qualname": "PytorchStateDictWeightsDescr.architecture_sha256", "kind": "variable", "doc": "
    The SHA256 of the architecture source file,\nif the architecture is not defined in a module listed in dependencies
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    \n", "signature": "(self) -> Self:", "funcdef": "def"}, "bioimageio.spec.model.v0_4.PytorchStateDictWeightsDescr.kwargs": {"fullname": "bioimageio.spec.model.v0_4.PytorchStateDictWeightsDescr.kwargs", "modulename": "bioimageio.spec.model.v0_4", "qualname": "PytorchStateDictWeightsDescr.kwargs", "kind": "variable", "doc": "
    key word arguments for the architecture callable
    \n", "annotation": ": Dict[str, Any]"}, "bioimageio.spec.model.v0_4.PytorchStateDictWeightsDescr.pytorch_version": {"fullname": "bioimageio.spec.model.v0_4.PytorchStateDictWeightsDescr.pytorch_version", "modulename": "bioimageio.spec.model.v0_4", "qualname": "PytorchStateDictWeightsDescr.pytorch_version", "kind": "variable", "doc": "
    Version of the PyTorch library used.\nIf depencencies is specified it should include pytorch and the verison has to match.\n(dependencies overrules pytorch_version)
    \n", "annotation": ": Optional[bioimageio.spec._internal.version_type.Version]"}, "bioimageio.spec.model.v0_4.PytorchStateDictWeightsDescr.model_config": {"fullname": "bioimageio.spec.model.v0_4.PytorchStateDictWeightsDescr.model_config", "modulename": "bioimageio.spec.model.v0_4", "qualname": "PytorchStateDictWeightsDescr.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_4.PytorchStateDictWeightsDescr.model_fields": {"fullname": "bioimageio.spec.model.v0_4.PytorchStateDictWeightsDescr.model_fields", "modulename": "bioimageio.spec.model.v0_4", "qualname": "PytorchStateDictWeightsDescr.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'source': FieldInfo(annotation=Union[Annotated[Path, PathType], RelativeFilePath, HttpUrl, Annotated[Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], required=True, metadata=[AfterValidator(func=<function wo_special_file_name>), PlainSerializer(func=<function _package>, return_type=PydanticUndefined, when_used='unless-none')]), 'sha256': FieldInfo(annotation=Union[Sha256, NoneType], required=False), 'attachments': FieldInfo(annotation=Union[AttachmentsDescr, NoneType], required=False, metadata=[AfterWarner(func=<function as_warning.<locals>.wrapper>, severity=35, msg='Weights entry depends on additional attachments.', context={'typ': None})]), 'authors': FieldInfo(annotation=Union[List[Author], NoneType], required=False), 'dependencies': FieldInfo(annotation=Union[Dependencies, NoneType], required=False, examples=['conda:environment.yaml', 'maven:./pom.xml', 'pip:./requirements.txt'], metadata=[AfterWarner(func=<function as_warning.<locals>.wrapper>, severity=30, msg='Custom dependencies ({value}) specified. Avoid this whenever possible to allow execution in a wider range of software environments.', context={'typ': None})]), 'parent': FieldInfo(annotation=Union[Literal['keras_hdf5', 'onnx', 'pytorch_state_dict', 'tensorflow_js', 'tensorflow_saved_model_bundle', 'torchscript'], NoneType], required=False, examples=['pytorch_state_dict']), 'architecture': FieldInfo(annotation=Union[CallableFromFile, CallableFromDepencency], required=True, examples=['my_function.py:MyNetworkClass', 'my_module.submodule.get_my_model']), 'architecture_sha256': FieldInfo(annotation=Union[Sha256, NoneType], required=False, description="The SHA256 of the architecture source file, if the architecture is not defined in a module listed in `dependencies`\\nYou can drag and drop your file to this\\n[online tool](http://emn178.github.io/online-tools/sha256_checksum.html) to generate a SHA256 in your browser.\\nOr you can generate a SHA256 checksum with Python's `hashlib`,\\n[here is a codesnippet](https://gist.github.com/FynnBe/e64460463df89439cff218bbf59c1100)."), 'kwargs': FieldInfo(annotation=Dict[str, Any], required=False, default_factory=dict), 'pytorch_version': FieldInfo(annotation=Union[Version, NoneType], required=False)}"}, "bioimageio.spec.model.v0_4.PytorchStateDictWeightsDescr.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_4.PytorchStateDictWeightsDescr.model_computed_fields", "modulename": "bioimageio.spec.model.v0_4", "qualname": "PytorchStateDictWeightsDescr.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_4.TorchscriptWeightsDescr": {"fullname": "bioimageio.spec.model.v0_4.TorchscriptWeightsDescr", "modulename": "bioimageio.spec.model.v0_4", "qualname": "TorchscriptWeightsDescr", "kind": "class", "doc": "
    Subpart of a resource description
    \n", "bases": "WeightsEntryDescrBase"}, "bioimageio.spec.model.v0_4.TorchscriptWeightsDescr.type": {"fullname": "bioimageio.spec.model.v0_4.TorchscriptWeightsDescr.type", "modulename": "bioimageio.spec.model.v0_4", "qualname": "TorchscriptWeightsDescr.type", "kind": "variable", "doc": "
    \n", "default_value": "'torchscript'"}, "bioimageio.spec.model.v0_4.TorchscriptWeightsDescr.weights_format_name": {"fullname": "bioimageio.spec.model.v0_4.TorchscriptWeightsDescr.weights_format_name", "modulename": "bioimageio.spec.model.v0_4", "qualname": "TorchscriptWeightsDescr.weights_format_name", "kind": "variable", "doc": "
    \n", "annotation": ": ClassVar[str]", "default_value": "'TorchScript'"}, "bioimageio.spec.model.v0_4.TorchscriptWeightsDescr.pytorch_version": {"fullname": "bioimageio.spec.model.v0_4.TorchscriptWeightsDescr.pytorch_version", "modulename": "bioimageio.spec.model.v0_4", "qualname": "TorchscriptWeightsDescr.pytorch_version", "kind": "variable", "doc": "
    Version of the PyTorch library used.
    \n", "annotation": ": Optional[bioimageio.spec._internal.version_type.Version]"}, "bioimageio.spec.model.v0_4.TorchscriptWeightsDescr.model_config": {"fullname": "bioimageio.spec.model.v0_4.TorchscriptWeightsDescr.model_config", "modulename": "bioimageio.spec.model.v0_4", "qualname": "TorchscriptWeightsDescr.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_4.TorchscriptWeightsDescr.model_fields": {"fullname": "bioimageio.spec.model.v0_4.TorchscriptWeightsDescr.model_fields", "modulename": "bioimageio.spec.model.v0_4", "qualname": "TorchscriptWeightsDescr.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'source': FieldInfo(annotation=Union[Annotated[Path, PathType], RelativeFilePath, HttpUrl, Annotated[Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], required=True, metadata=[AfterValidator(func=<function wo_special_file_name>), PlainSerializer(func=<function _package>, return_type=PydanticUndefined, when_used='unless-none')]), 'sha256': FieldInfo(annotation=Union[Sha256, NoneType], required=False), 'attachments': FieldInfo(annotation=Union[AttachmentsDescr, NoneType], required=False, metadata=[AfterWarner(func=<function as_warning.<locals>.wrapper>, severity=35, msg='Weights entry depends on additional attachments.', context={'typ': None})]), 'authors': FieldInfo(annotation=Union[List[Author], NoneType], required=False), 'dependencies': FieldInfo(annotation=Union[Dependencies, NoneType], required=False, examples=['conda:environment.yaml', 'maven:./pom.xml', 'pip:./requirements.txt'], metadata=[AfterWarner(func=<function as_warning.<locals>.wrapper>, severity=30, msg='Custom dependencies ({value}) specified. Avoid this whenever possible to allow execution in a wider range of software environments.', context={'typ': None})]), 'parent': FieldInfo(annotation=Union[Literal['keras_hdf5', 'onnx', 'pytorch_state_dict', 'tensorflow_js', 'tensorflow_saved_model_bundle', 'torchscript'], NoneType], required=False, examples=['pytorch_state_dict']), 'pytorch_version': FieldInfo(annotation=Union[Version, NoneType], required=False)}"}, "bioimageio.spec.model.v0_4.TorchscriptWeightsDescr.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_4.TorchscriptWeightsDescr.model_computed_fields", "modulename": "bioimageio.spec.model.v0_4", "qualname": "TorchscriptWeightsDescr.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_4.TensorflowJsWeightsDescr": {"fullname": "bioimageio.spec.model.v0_4.TensorflowJsWeightsDescr", "modulename": "bioimageio.spec.model.v0_4", "qualname": "TensorflowJsWeightsDescr", "kind": "class", "doc": "
    Subpart of a resource description
    \n", "bases": "WeightsEntryDescrBase"}, "bioimageio.spec.model.v0_4.TensorflowJsWeightsDescr.type": {"fullname": "bioimageio.spec.model.v0_4.TensorflowJsWeightsDescr.type", "modulename": "bioimageio.spec.model.v0_4", "qualname": "TensorflowJsWeightsDescr.type", "kind": "variable", "doc": "
    \n", "default_value": "'tensorflow_js'"}, "bioimageio.spec.model.v0_4.TensorflowJsWeightsDescr.weights_format_name": {"fullname": "bioimageio.spec.model.v0_4.TensorflowJsWeightsDescr.weights_format_name", "modulename": "bioimageio.spec.model.v0_4", "qualname": "TensorflowJsWeightsDescr.weights_format_name", "kind": "variable", "doc": "
    \n", "annotation": ": ClassVar[str]", "default_value": "'Tensorflow.js'"}, "bioimageio.spec.model.v0_4.TensorflowJsWeightsDescr.tensorflow_version": {"fullname": "bioimageio.spec.model.v0_4.TensorflowJsWeightsDescr.tensorflow_version", "modulename": "bioimageio.spec.model.v0_4", "qualname": "TensorflowJsWeightsDescr.tensorflow_version", "kind": "variable", "doc": "
    Version of the TensorFlow library used.
    \n", "annotation": ": Optional[bioimageio.spec._internal.version_type.Version]"}, "bioimageio.spec.model.v0_4.TensorflowJsWeightsDescr.source": {"fullname": "bioimageio.spec.model.v0_4.TensorflowJsWeightsDescr.source", "modulename": "bioimageio.spec.model.v0_4", "qualname": "TensorflowJsWeightsDescr.source", "kind": "variable", "doc": "
    \u2208\ud83d\udce6 The multi-file weights.\nAll required files/folders should be a zip archive.
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    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_4.TensorflowJsWeightsDescr.model_fields": {"fullname": "bioimageio.spec.model.v0_4.TensorflowJsWeightsDescr.model_fields", "modulename": "bioimageio.spec.model.v0_4", "qualname": "TensorflowJsWeightsDescr.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'source': FieldInfo(annotation=Union[Annotated[Path, PathType], RelativeFilePath, HttpUrl, Annotated[Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], required=True, metadata=[AfterValidator(func=<function wo_special_file_name>), PlainSerializer(func=<function _package>, return_type=PydanticUndefined, when_used='unless-none')]), 'sha256': FieldInfo(annotation=Union[Sha256, NoneType], required=False), 'attachments': FieldInfo(annotation=Union[AttachmentsDescr, NoneType], required=False, metadata=[AfterWarner(func=<function as_warning.<locals>.wrapper>, severity=35, msg='Weights entry depends on additional attachments.', context={'typ': None})]), 'authors': FieldInfo(annotation=Union[List[Author], NoneType], required=False), 'dependencies': FieldInfo(annotation=Union[Dependencies, NoneType], required=False, examples=['conda:environment.yaml', 'maven:./pom.xml', 'pip:./requirements.txt'], metadata=[AfterWarner(func=<function as_warning.<locals>.wrapper>, severity=30, msg='Custom dependencies ({value}) specified. Avoid this whenever possible to allow execution in a wider range of software environments.', context={'typ': None})]), 'parent': FieldInfo(annotation=Union[Literal['keras_hdf5', 'onnx', 'pytorch_state_dict', 'tensorflow_js', 'tensorflow_saved_model_bundle', 'torchscript'], NoneType], required=False, examples=['pytorch_state_dict']), 'tensorflow_version': FieldInfo(annotation=Union[Version, NoneType], required=False)}"}, "bioimageio.spec.model.v0_4.TensorflowJsWeightsDescr.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_4.TensorflowJsWeightsDescr.model_computed_fields", "modulename": "bioimageio.spec.model.v0_4", "qualname": "TensorflowJsWeightsDescr.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_4.TensorflowSavedModelBundleWeightsDescr": {"fullname": "bioimageio.spec.model.v0_4.TensorflowSavedModelBundleWeightsDescr", "modulename": "bioimageio.spec.model.v0_4", "qualname": "TensorflowSavedModelBundleWeightsDescr", "kind": "class", "doc": "
    Subpart of a resource description
    \n", "bases": "WeightsEntryDescrBase"}, "bioimageio.spec.model.v0_4.TensorflowSavedModelBundleWeightsDescr.type": {"fullname": "bioimageio.spec.model.v0_4.TensorflowSavedModelBundleWeightsDescr.type", "modulename": "bioimageio.spec.model.v0_4", "qualname": "TensorflowSavedModelBundleWeightsDescr.type", "kind": "variable", "doc": "
    \n", "default_value": "'tensorflow_saved_model_bundle'"}, "bioimageio.spec.model.v0_4.TensorflowSavedModelBundleWeightsDescr.weights_format_name": {"fullname": "bioimageio.spec.model.v0_4.TensorflowSavedModelBundleWeightsDescr.weights_format_name", "modulename": "bioimageio.spec.model.v0_4", "qualname": "TensorflowSavedModelBundleWeightsDescr.weights_format_name", "kind": "variable", "doc": "
    \n", "annotation": ": ClassVar[str]", "default_value": "'Tensorflow Saved Model'"}, "bioimageio.spec.model.v0_4.TensorflowSavedModelBundleWeightsDescr.tensorflow_version": {"fullname": "bioimageio.spec.model.v0_4.TensorflowSavedModelBundleWeightsDescr.tensorflow_version", "modulename": "bioimageio.spec.model.v0_4", "qualname": "TensorflowSavedModelBundleWeightsDescr.tensorflow_version", "kind": "variable", "doc": "
    Version of the TensorFlow library used.
    \n", "annotation": ": Optional[bioimageio.spec._internal.version_type.Version]"}, "bioimageio.spec.model.v0_4.TensorflowSavedModelBundleWeightsDescr.model_config": {"fullname": "bioimageio.spec.model.v0_4.TensorflowSavedModelBundleWeightsDescr.model_config", "modulename": "bioimageio.spec.model.v0_4", "qualname": "TensorflowSavedModelBundleWeightsDescr.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_4.TensorflowSavedModelBundleWeightsDescr.model_fields": {"fullname": "bioimageio.spec.model.v0_4.TensorflowSavedModelBundleWeightsDescr.model_fields", "modulename": "bioimageio.spec.model.v0_4", "qualname": "TensorflowSavedModelBundleWeightsDescr.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'source': FieldInfo(annotation=Union[Annotated[Path, PathType], RelativeFilePath, HttpUrl, Annotated[Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], required=True, metadata=[AfterValidator(func=<function wo_special_file_name>), PlainSerializer(func=<function _package>, return_type=PydanticUndefined, when_used='unless-none')]), 'sha256': FieldInfo(annotation=Union[Sha256, NoneType], required=False), 'attachments': FieldInfo(annotation=Union[AttachmentsDescr, NoneType], required=False, metadata=[AfterWarner(func=<function as_warning.<locals>.wrapper>, severity=35, msg='Weights entry depends on additional attachments.', context={'typ': None})]), 'authors': FieldInfo(annotation=Union[List[Author], NoneType], required=False), 'dependencies': FieldInfo(annotation=Union[Dependencies, NoneType], required=False, examples=['conda:environment.yaml', 'maven:./pom.xml', 'pip:./requirements.txt'], metadata=[AfterWarner(func=<function as_warning.<locals>.wrapper>, severity=30, msg='Custom dependencies ({value}) specified. Avoid this whenever possible to allow execution in a wider range of software environments.', context={'typ': None})]), 'parent': FieldInfo(annotation=Union[Literal['keras_hdf5', 'onnx', 'pytorch_state_dict', 'tensorflow_js', 'tensorflow_saved_model_bundle', 'torchscript'], NoneType], required=False, examples=['pytorch_state_dict']), 'tensorflow_version': FieldInfo(annotation=Union[Version, NoneType], required=False)}"}, "bioimageio.spec.model.v0_4.TensorflowSavedModelBundleWeightsDescr.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_4.TensorflowSavedModelBundleWeightsDescr.model_computed_fields", "modulename": "bioimageio.spec.model.v0_4", "qualname": "TensorflowSavedModelBundleWeightsDescr.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_4.ParameterizedInputShape": {"fullname": "bioimageio.spec.model.v0_4.ParameterizedInputShape", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ParameterizedInputShape", "kind": "class", "doc": "
    A sequence of valid shapes given by shape_k = min + k * step for k in {0, 1, ...}.
    \n", "bases": "bioimageio.spec._internal.node.Node"}, "bioimageio.spec.model.v0_4.ParameterizedInputShape.min": {"fullname": "bioimageio.spec.model.v0_4.ParameterizedInputShape.min", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ParameterizedInputShape.min", "kind": "variable", "doc": "
    The minimum input shape
    \n", "annotation": ": Annotated[List[int], MinLen(min_length=1)]"}, "bioimageio.spec.model.v0_4.ParameterizedInputShape.step": {"fullname": "bioimageio.spec.model.v0_4.ParameterizedInputShape.step", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ParameterizedInputShape.step", "kind": "variable", "doc": "
    The minimum shape change
    \n", "annotation": ": Annotated[List[int], MinLen(min_length=1)]"}, "bioimageio.spec.model.v0_4.ParameterizedInputShape.matching_lengths": {"fullname": "bioimageio.spec.model.v0_4.ParameterizedInputShape.matching_lengths", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ParameterizedInputShape.matching_lengths", "kind": "function", "doc": "
    \n", "signature": "(self) -> Self:", "funcdef": "def"}, "bioimageio.spec.model.v0_4.ParameterizedInputShape.model_config": {"fullname": "bioimageio.spec.model.v0_4.ParameterizedInputShape.model_config", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ParameterizedInputShape.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_4.ParameterizedInputShape.model_fields": {"fullname": "bioimageio.spec.model.v0_4.ParameterizedInputShape.model_fields", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ParameterizedInputShape.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'min': FieldInfo(annotation=List[int], required=True, metadata=[MinLen(min_length=1)]), 'step': FieldInfo(annotation=List[int], required=True, metadata=[MinLen(min_length=1)])}"}, "bioimageio.spec.model.v0_4.ParameterizedInputShape.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_4.ParameterizedInputShape.model_computed_fields", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ParameterizedInputShape.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_4.ImplicitOutputShape": {"fullname": "bioimageio.spec.model.v0_4.ImplicitOutputShape", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ImplicitOutputShape", "kind": "class", "doc": "
    Output tensor shape depending on an input tensor shape.\nshape(output_tensor) = shape(input_tensor) * scale + 2 * offset
    \n", "bases": "bioimageio.spec._internal.node.Node"}, "bioimageio.spec.model.v0_4.ImplicitOutputShape.reference_tensor": {"fullname": "bioimageio.spec.model.v0_4.ImplicitOutputShape.reference_tensor", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ImplicitOutputShape.reference_tensor", "kind": "variable", "doc": "
    Name of the reference tensor.
    \n", "annotation": ": bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate]]]"}, "bioimageio.spec.model.v0_4.ImplicitOutputShape.scale": {"fullname": "bioimageio.spec.model.v0_4.ImplicitOutputShape.scale", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ImplicitOutputShape.scale", "kind": "variable", "doc": "
    output_pix/input_pix for each dimension.\n'null' values indicate new dimensions, whose length is defined by 2*offset
    \n", "annotation": ": Annotated[List[Optional[float]], MinLen(min_length=1)]"}, "bioimageio.spec.model.v0_4.ImplicitOutputShape.offset": {"fullname": "bioimageio.spec.model.v0_4.ImplicitOutputShape.offset", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ImplicitOutputShape.offset", "kind": "variable", "doc": "
    Position of origin wrt to input.
    \n", "annotation": ": Annotated[List[Union[int, Annotated[float, MultipleOf(multiple_of=0.5)]]], MinLen(min_length=1)]"}, "bioimageio.spec.model.v0_4.ImplicitOutputShape.matching_lengths": {"fullname": "bioimageio.spec.model.v0_4.ImplicitOutputShape.matching_lengths", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ImplicitOutputShape.matching_lengths", "kind": "function", "doc": "
    \n", "signature": "(self) -> Self:", "funcdef": "def"}, "bioimageio.spec.model.v0_4.ImplicitOutputShape.model_config": {"fullname": "bioimageio.spec.model.v0_4.ImplicitOutputShape.model_config", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ImplicitOutputShape.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_4.ImplicitOutputShape.model_fields": {"fullname": "bioimageio.spec.model.v0_4.ImplicitOutputShape.model_fields", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ImplicitOutputShape.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'reference_tensor': FieldInfo(annotation=ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate]]], required=True), 'scale': FieldInfo(annotation=List[Union[float, NoneType]], required=True, metadata=[MinLen(min_length=1)]), 'offset': FieldInfo(annotation=List[Union[int, Annotated[float, MultipleOf]]], required=True, metadata=[MinLen(min_length=1)])}"}, "bioimageio.spec.model.v0_4.ImplicitOutputShape.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_4.ImplicitOutputShape.model_computed_fields", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ImplicitOutputShape.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_4.TensorDescrBase": {"fullname": "bioimageio.spec.model.v0_4.TensorDescrBase", "modulename": "bioimageio.spec.model.v0_4", "qualname": "TensorDescrBase", "kind": "class", "doc": "
    Subpart of a resource description
    \n", "bases": "bioimageio.spec._internal.node.Node"}, "bioimageio.spec.model.v0_4.TensorDescrBase.name": {"fullname": "bioimageio.spec.model.v0_4.TensorDescrBase.name", "modulename": "bioimageio.spec.model.v0_4", "qualname": "TensorDescrBase.name", "kind": "variable", "doc": "
    Tensor name. No duplicates are allowed.
    \n", "annotation": ": bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate]]]"}, "bioimageio.spec.model.v0_4.TensorDescrBase.description": {"fullname": "bioimageio.spec.model.v0_4.TensorDescrBase.description", "modulename": "bioimageio.spec.model.v0_4", "qualname": "TensorDescrBase.description", "kind": "variable", "doc": "
    \n", "annotation": ": str"}, "bioimageio.spec.model.v0_4.TensorDescrBase.axes": {"fullname": "bioimageio.spec.model.v0_4.TensorDescrBase.axes", "modulename": "bioimageio.spec.model.v0_4", "qualname": "TensorDescrBase.axes", "kind": "variable", "doc": "
    Axes identifying characters. Same length and order as the axes in shape.\n| axis | description |\n| --- | --- |\n|  b  |  batch (groups multiple samples) |\n|  i  |  instance/index/element |\n|  t  |  time |\n|  c  |  channel |\n|  z  |  spatial dimension z |\n|  y  |  spatial dimension y |\n|  x  |  spatial dimension x |
    \n", "annotation": ": Annotated[str, RestrictCharacters(alphabet='bitczyx'), AfterValidator(func=<function validate_unique_entries at 0x7f1c21c7a340>)]"}, "bioimageio.spec.model.v0_4.TensorDescrBase.data_range": {"fullname": "bioimageio.spec.model.v0_4.TensorDescrBase.data_range", "modulename": "bioimageio.spec.model.v0_4", "qualname": "TensorDescrBase.data_range", "kind": "variable", "doc": "
    Tuple (minimum, maximum) specifying the allowed range of the data in this tensor.\nIf not specified, the full data range that can be expressed in data_type is allowed.
    \n", "annotation": ": Optional[Tuple[Annotated[float, AllowInfNan(allow_inf_nan=True)], Annotated[float, AllowInfNan(allow_inf_nan=True)]]]"}, "bioimageio.spec.model.v0_4.TensorDescrBase.model_config": {"fullname": "bioimageio.spec.model.v0_4.TensorDescrBase.model_config", "modulename": "bioimageio.spec.model.v0_4", "qualname": "TensorDescrBase.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_4.TensorDescrBase.model_fields": {"fullname": "bioimageio.spec.model.v0_4.TensorDescrBase.model_fields", "modulename": "bioimageio.spec.model.v0_4", "qualname": "TensorDescrBase.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'name': FieldInfo(annotation=ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate]]], required=True), 'description': FieldInfo(annotation=str, required=False, default=''), 'axes': FieldInfo(annotation=str, required=True, metadata=[RestrictCharacters(alphabet='bitczyx'), AfterValidator(func=<function validate_unique_entries>)]), 'data_range': FieldInfo(annotation=Union[Tuple[Annotated[float, AllowInfNan(allow_inf_nan=True)], Annotated[float, AllowInfNan(allow_inf_nan=True)]], NoneType], required=False)}"}, "bioimageio.spec.model.v0_4.TensorDescrBase.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_4.TensorDescrBase.model_computed_fields", "modulename": "bioimageio.spec.model.v0_4", "qualname": "TensorDescrBase.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_4.ProcessingKwargs": {"fullname": "bioimageio.spec.model.v0_4.ProcessingKwargs", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ProcessingKwargs", "kind": "class", "doc": "
    base class for pre-/postprocessing key word arguments
    \n", "bases": "bioimageio.spec._internal.common_nodes.KwargsNode"}, "bioimageio.spec.model.v0_4.ProcessingKwargs.model_config": {"fullname": "bioimageio.spec.model.v0_4.ProcessingKwargs.model_config", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ProcessingKwargs.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_4.ProcessingKwargs.model_fields": {"fullname": "bioimageio.spec.model.v0_4.ProcessingKwargs.model_fields", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ProcessingKwargs.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_4.ProcessingKwargs.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_4.ProcessingKwargs.model_computed_fields", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ProcessingKwargs.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_4.ProcessingDescrBase": {"fullname": "bioimageio.spec.model.v0_4.ProcessingDescrBase", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ProcessingDescrBase", "kind": "class", "doc": "
    processing base class
    \n", "bases": "bioimageio.spec._internal.common_nodes.NodeWithExplicitlySetFields"}, "bioimageio.spec.model.v0_4.ProcessingDescrBase.fields_to_set_explicitly": {"fullname": "bioimageio.spec.model.v0_4.ProcessingDescrBase.fields_to_set_explicitly", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ProcessingDescrBase.fields_to_set_explicitly", "kind": "variable", "doc": "
    set set these fields explicitly with their default value if they are not set,\nsuch that they are always included even when dumping with 'exlude_unset'
    \n", "annotation": ": ClassVar[FrozenSet[LiteralString]]", "default_value": "frozenset({'name'})"}, "bioimageio.spec.model.v0_4.ProcessingDescrBase.model_config": {"fullname": "bioimageio.spec.model.v0_4.ProcessingDescrBase.model_config", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ProcessingDescrBase.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_4.ProcessingDescrBase.model_fields": {"fullname": "bioimageio.spec.model.v0_4.ProcessingDescrBase.model_fields", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ProcessingDescrBase.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_4.ProcessingDescrBase.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_4.ProcessingDescrBase.model_computed_fields", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ProcessingDescrBase.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_4.BinarizeKwargs": {"fullname": "bioimageio.spec.model.v0_4.BinarizeKwargs", "modulename": "bioimageio.spec.model.v0_4", "qualname": "BinarizeKwargs", "kind": "class", "doc": "
    base class for pre-/postprocessing key word arguments
    \n", "bases": "ProcessingKwargs"}, "bioimageio.spec.model.v0_4.BinarizeKwargs.threshold": {"fullname": "bioimageio.spec.model.v0_4.BinarizeKwargs.threshold", "modulename": "bioimageio.spec.model.v0_4", "qualname": "BinarizeKwargs.threshold", "kind": "variable", "doc": "
    The fixed threshold
    \n", "annotation": ": float"}, "bioimageio.spec.model.v0_4.BinarizeKwargs.model_config": {"fullname": "bioimageio.spec.model.v0_4.BinarizeKwargs.model_config", "modulename": "bioimageio.spec.model.v0_4", "qualname": "BinarizeKwargs.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_4.BinarizeKwargs.model_fields": {"fullname": "bioimageio.spec.model.v0_4.BinarizeKwargs.model_fields", "modulename": "bioimageio.spec.model.v0_4", "qualname": "BinarizeKwargs.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'threshold': FieldInfo(annotation=float, required=True)}"}, "bioimageio.spec.model.v0_4.BinarizeKwargs.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_4.BinarizeKwargs.model_computed_fields", "modulename": "bioimageio.spec.model.v0_4", "qualname": "BinarizeKwargs.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_4.BinarizeDescr": {"fullname": "bioimageio.spec.model.v0_4.BinarizeDescr", "modulename": "bioimageio.spec.model.v0_4", "qualname": "BinarizeDescr", "kind": "class", "doc": "
    BinarizeDescr the tensor with a fixed threshold.\nValues above the threshold will be set to one, values below the threshold to zero.
    \n", "bases": "ProcessingDescrBase"}, "bioimageio.spec.model.v0_4.BinarizeDescr.name": {"fullname": "bioimageio.spec.model.v0_4.BinarizeDescr.name", "modulename": "bioimageio.spec.model.v0_4", "qualname": "BinarizeDescr.name", "kind": "variable", "doc": "
    \n", "annotation": ": Literal['binarize']"}, "bioimageio.spec.model.v0_4.BinarizeDescr.kwargs": {"fullname": "bioimageio.spec.model.v0_4.BinarizeDescr.kwargs", "modulename": "bioimageio.spec.model.v0_4", "qualname": "BinarizeDescr.kwargs", "kind": "variable", "doc": "
    \n", "annotation": ": bioimageio.spec.model.v0_4.BinarizeKwargs"}, "bioimageio.spec.model.v0_4.BinarizeDescr.model_config": {"fullname": "bioimageio.spec.model.v0_4.BinarizeDescr.model_config", "modulename": "bioimageio.spec.model.v0_4", "qualname": "BinarizeDescr.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_4.BinarizeDescr.model_fields": {"fullname": "bioimageio.spec.model.v0_4.BinarizeDescr.model_fields", "modulename": "bioimageio.spec.model.v0_4", "qualname": "BinarizeDescr.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'name': FieldInfo(annotation=Literal['binarize'], required=False, default='binarize'), 'kwargs': FieldInfo(annotation=BinarizeKwargs, required=True)}"}, "bioimageio.spec.model.v0_4.BinarizeDescr.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_4.BinarizeDescr.model_computed_fields", "modulename": "bioimageio.spec.model.v0_4", "qualname": "BinarizeDescr.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_4.ClipKwargs": {"fullname": "bioimageio.spec.model.v0_4.ClipKwargs", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ClipKwargs", "kind": "class", "doc": "
    base class for pre-/postprocessing key word arguments
    \n", "bases": "ProcessingKwargs"}, "bioimageio.spec.model.v0_4.ClipKwargs.min": {"fullname": "bioimageio.spec.model.v0_4.ClipKwargs.min", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ClipKwargs.min", "kind": "variable", "doc": "
    minimum value for clipping
    \n", "annotation": ": float"}, "bioimageio.spec.model.v0_4.ClipKwargs.max": {"fullname": "bioimageio.spec.model.v0_4.ClipKwargs.max", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ClipKwargs.max", "kind": "variable", "doc": "
    maximum value for clipping
    \n", "annotation": ": float"}, "bioimageio.spec.model.v0_4.ClipKwargs.model_config": {"fullname": "bioimageio.spec.model.v0_4.ClipKwargs.model_config", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ClipKwargs.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_4.ClipKwargs.model_fields": {"fullname": "bioimageio.spec.model.v0_4.ClipKwargs.model_fields", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ClipKwargs.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'min': FieldInfo(annotation=float, required=True), 'max': FieldInfo(annotation=float, required=True)}"}, "bioimageio.spec.model.v0_4.ClipKwargs.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_4.ClipKwargs.model_computed_fields", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ClipKwargs.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_4.ClipDescr": {"fullname": "bioimageio.spec.model.v0_4.ClipDescr", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ClipDescr", "kind": "class", "doc": "
    Set tensor values below min to min and above max to max.
    \n", "bases": "ProcessingDescrBase"}, "bioimageio.spec.model.v0_4.ClipDescr.name": {"fullname": "bioimageio.spec.model.v0_4.ClipDescr.name", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ClipDescr.name", "kind": "variable", "doc": "
    \n", "annotation": ": Literal['clip']"}, "bioimageio.spec.model.v0_4.ClipDescr.kwargs": {"fullname": "bioimageio.spec.model.v0_4.ClipDescr.kwargs", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ClipDescr.kwargs", "kind": "variable", "doc": "
    \n", "annotation": ": bioimageio.spec.model.v0_4.ClipKwargs"}, "bioimageio.spec.model.v0_4.ClipDescr.model_config": {"fullname": "bioimageio.spec.model.v0_4.ClipDescr.model_config", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ClipDescr.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_4.ClipDescr.model_fields": {"fullname": "bioimageio.spec.model.v0_4.ClipDescr.model_fields", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ClipDescr.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'name': FieldInfo(annotation=Literal['clip'], required=False, default='clip'), 'kwargs': FieldInfo(annotation=ClipKwargs, required=True)}"}, "bioimageio.spec.model.v0_4.ClipDescr.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_4.ClipDescr.model_computed_fields", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ClipDescr.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_4.ScaleLinearKwargs": {"fullname": "bioimageio.spec.model.v0_4.ScaleLinearKwargs", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ScaleLinearKwargs", "kind": "class", "doc": "
    base class for pre-/postprocessing key word arguments
    \n", "bases": "ProcessingKwargs"}, "bioimageio.spec.model.v0_4.ScaleLinearKwargs.axes": {"fullname": "bioimageio.spec.model.v0_4.ScaleLinearKwargs.axes", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ScaleLinearKwargs.axes", "kind": "variable", "doc": "
    The subset of axes to scale jointly.\nFor example xy to scale the two image axes for 2d data jointly.
    \n", "annotation": ": Annotated[Optional[Annotated[str, RestrictCharacters(alphabet='czyx'), AfterValidator(func=<function validate_unique_entries at 0x7f1c21c7a340>)]], FieldInfo(annotation=NoneType, required=True, examples=['xy'])]"}, "bioimageio.spec.model.v0_4.ScaleLinearKwargs.gain": {"fullname": "bioimageio.spec.model.v0_4.ScaleLinearKwargs.gain", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ScaleLinearKwargs.gain", "kind": "variable", "doc": "
    multiplicative factor
    \n", "annotation": ": Union[float, List[float]]"}, "bioimageio.spec.model.v0_4.ScaleLinearKwargs.offset": {"fullname": "bioimageio.spec.model.v0_4.ScaleLinearKwargs.offset", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ScaleLinearKwargs.offset", "kind": "variable", "doc": "
    additive term
    \n", "annotation": ": Union[float, List[float]]"}, "bioimageio.spec.model.v0_4.ScaleLinearKwargs.either_gain_or_offset": {"fullname": "bioimageio.spec.model.v0_4.ScaleLinearKwargs.either_gain_or_offset", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ScaleLinearKwargs.either_gain_or_offset", "kind": "function", "doc": "
    \n", "signature": "(self) -> Self:", "funcdef": "def"}, "bioimageio.spec.model.v0_4.ScaleLinearKwargs.model_config": {"fullname": "bioimageio.spec.model.v0_4.ScaleLinearKwargs.model_config", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ScaleLinearKwargs.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_4.ScaleLinearKwargs.model_fields": {"fullname": "bioimageio.spec.model.v0_4.ScaleLinearKwargs.model_fields", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ScaleLinearKwargs.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'axes': FieldInfo(annotation=Union[Annotated[str, RestrictCharacters, AfterValidator], NoneType], required=False, examples=['xy']), 'gain': FieldInfo(annotation=Union[float, List[float]], required=False, default=1.0), 'offset': FieldInfo(annotation=Union[float, List[float]], required=False, default=0.0)}"}, "bioimageio.spec.model.v0_4.ScaleLinearKwargs.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_4.ScaleLinearKwargs.model_computed_fields", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ScaleLinearKwargs.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_4.ScaleLinearDescr": {"fullname": "bioimageio.spec.model.v0_4.ScaleLinearDescr", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ScaleLinearDescr", "kind": "class", "doc": "
    Fixed linear scaling.
    \n", "bases": "ProcessingDescrBase"}, "bioimageio.spec.model.v0_4.ScaleLinearDescr.name": {"fullname": "bioimageio.spec.model.v0_4.ScaleLinearDescr.name", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ScaleLinearDescr.name", "kind": "variable", "doc": "
    \n", "annotation": ": Literal['scale_linear']"}, "bioimageio.spec.model.v0_4.ScaleLinearDescr.kwargs": {"fullname": "bioimageio.spec.model.v0_4.ScaleLinearDescr.kwargs", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ScaleLinearDescr.kwargs", "kind": "variable", "doc": "
    \n", "annotation": ": bioimageio.spec.model.v0_4.ScaleLinearKwargs"}, "bioimageio.spec.model.v0_4.ScaleLinearDescr.model_config": {"fullname": "bioimageio.spec.model.v0_4.ScaleLinearDescr.model_config", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ScaleLinearDescr.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_4.ScaleLinearDescr.model_fields": {"fullname": "bioimageio.spec.model.v0_4.ScaleLinearDescr.model_fields", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ScaleLinearDescr.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'name': FieldInfo(annotation=Literal['scale_linear'], required=False, default='scale_linear'), 'kwargs': FieldInfo(annotation=ScaleLinearKwargs, required=True)}"}, "bioimageio.spec.model.v0_4.ScaleLinearDescr.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_4.ScaleLinearDescr.model_computed_fields", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ScaleLinearDescr.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_4.SigmoidDescr": {"fullname": "bioimageio.spec.model.v0_4.SigmoidDescr", "modulename": "bioimageio.spec.model.v0_4", "qualname": "SigmoidDescr", "kind": "class", "doc": "
    The logistic sigmoid funciton, a.k.a. expit function.
    \n", "bases": "ProcessingDescrBase"}, "bioimageio.spec.model.v0_4.SigmoidDescr.name": {"fullname": "bioimageio.spec.model.v0_4.SigmoidDescr.name", "modulename": "bioimageio.spec.model.v0_4", "qualname": "SigmoidDescr.name", "kind": "variable", "doc": "
    \n", "annotation": ": Literal['sigmoid']"}, "bioimageio.spec.model.v0_4.SigmoidDescr.kwargs": {"fullname": "bioimageio.spec.model.v0_4.SigmoidDescr.kwargs", "modulename": "bioimageio.spec.model.v0_4", "qualname": "SigmoidDescr.kwargs", "kind": "variable", "doc": "
    empty kwargs
    \n", "annotation": ": bioimageio.spec.model.v0_4.ProcessingKwargs"}, "bioimageio.spec.model.v0_4.SigmoidDescr.model_config": {"fullname": "bioimageio.spec.model.v0_4.SigmoidDescr.model_config", "modulename": "bioimageio.spec.model.v0_4", "qualname": "SigmoidDescr.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_4.SigmoidDescr.model_fields": {"fullname": "bioimageio.spec.model.v0_4.SigmoidDescr.model_fields", "modulename": "bioimageio.spec.model.v0_4", "qualname": "SigmoidDescr.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'name': FieldInfo(annotation=Literal['sigmoid'], required=False, default='sigmoid')}"}, "bioimageio.spec.model.v0_4.SigmoidDescr.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_4.SigmoidDescr.model_computed_fields", "modulename": "bioimageio.spec.model.v0_4", "qualname": "SigmoidDescr.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_4.ZeroMeanUnitVarianceKwargs": {"fullname": "bioimageio.spec.model.v0_4.ZeroMeanUnitVarianceKwargs", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ZeroMeanUnitVarianceKwargs", "kind": "class", "doc": "
    base class for pre-/postprocessing key word arguments
    \n", "bases": "ProcessingKwargs"}, "bioimageio.spec.model.v0_4.ZeroMeanUnitVarianceKwargs.mode": {"fullname": "bioimageio.spec.model.v0_4.ZeroMeanUnitVarianceKwargs.mode", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ZeroMeanUnitVarianceKwargs.mode", "kind": "variable", "doc": "
    Mode for computing mean and variance.\n|     mode    |             description              |\n| ----------- | ------------------------------------ |\n|   fixed     | Fixed values for mean and variance   |\n| per_dataset | Compute for the entire dataset       |\n| per_sample  | Compute for each sample individually |
    \n", "annotation": ": Literal['fixed', 'per_dataset', 'per_sample']"}, "bioimageio.spec.model.v0_4.ZeroMeanUnitVarianceKwargs.axes": {"fullname": "bioimageio.spec.model.v0_4.ZeroMeanUnitVarianceKwargs.axes", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ZeroMeanUnitVarianceKwargs.axes", "kind": "variable", "doc": "
    The subset of axes to normalize jointly.\nFor example xy to normalize the two image axes for 2d data jointly.
    \n", "annotation": ": Annotated[str, RestrictCharacters(alphabet='czyx'), AfterValidator(func=<function validate_unique_entries at 0x7f1c21c7a340>), FieldInfo(annotation=NoneType, required=True, examples=['xy'])]"}, "bioimageio.spec.model.v0_4.ZeroMeanUnitVarianceKwargs.mean": {"fullname": "bioimageio.spec.model.v0_4.ZeroMeanUnitVarianceKwargs.mean", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ZeroMeanUnitVarianceKwargs.mean", "kind": "variable", "doc": "
    The mean value(s) to use for mode: fixed.\nFor example [1.1, 2.2, 3.3] in the case of a 3 channel image with axes: xy.
    \n", "annotation": ": Annotated[Union[float, Annotated[List[float], MinLen(min_length=1)], NoneType], FieldInfo(annotation=NoneType, required=True, examples=[(1.1, 2.2, 3.3)])]"}, "bioimageio.spec.model.v0_4.ZeroMeanUnitVarianceKwargs.std": {"fullname": "bioimageio.spec.model.v0_4.ZeroMeanUnitVarianceKwargs.std", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ZeroMeanUnitVarianceKwargs.std", "kind": "variable", "doc": "
    The standard deviation values to use for mode: fixed. Analogous to mean.
    \n", "annotation": ": Annotated[Union[float, Annotated[List[float], MinLen(min_length=1)], NoneType], FieldInfo(annotation=NoneType, required=True, examples=[(0.1, 0.2, 0.3)])]"}, "bioimageio.spec.model.v0_4.ZeroMeanUnitVarianceKwargs.eps": {"fullname": "bioimageio.spec.model.v0_4.ZeroMeanUnitVarianceKwargs.eps", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ZeroMeanUnitVarianceKwargs.eps", "kind": "variable", "doc": "
    epsilon for numeric stability: out = (tensor - mean) / (std + eps).
    \n", "annotation": ": Annotated[float, Interval(gt=0, ge=None, lt=None, le=0.1)]"}, "bioimageio.spec.model.v0_4.ZeroMeanUnitVarianceKwargs.mean_and_std_match_mode": {"fullname": "bioimageio.spec.model.v0_4.ZeroMeanUnitVarianceKwargs.mean_and_std_match_mode", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ZeroMeanUnitVarianceKwargs.mean_and_std_match_mode", "kind": "function", "doc": "
    \n", "signature": "(self) -> Self:", "funcdef": "def"}, "bioimageio.spec.model.v0_4.ZeroMeanUnitVarianceKwargs.model_config": {"fullname": "bioimageio.spec.model.v0_4.ZeroMeanUnitVarianceKwargs.model_config", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ZeroMeanUnitVarianceKwargs.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_4.ZeroMeanUnitVarianceKwargs.model_fields": {"fullname": "bioimageio.spec.model.v0_4.ZeroMeanUnitVarianceKwargs.model_fields", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ZeroMeanUnitVarianceKwargs.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'mode': FieldInfo(annotation=Literal['fixed', 'per_dataset', 'per_sample'], required=False, default='fixed'), 'axes': FieldInfo(annotation=str, required=True, examples=['xy'], metadata=[RestrictCharacters(alphabet='czyx'), AfterValidator(func=<function validate_unique_entries>)]), 'mean': FieldInfo(annotation=Union[float, Annotated[List[float], MinLen], NoneType], required=False, examples=[(1.1, 2.2, 3.3)]), 'std': FieldInfo(annotation=Union[float, Annotated[List[float], MinLen], NoneType], required=False, examples=[(0.1, 0.2, 0.3)]), 'eps': FieldInfo(annotation=float, required=False, default=1e-06, metadata=[Interval(gt=0, ge=None, lt=None, le=0.1)])}"}, "bioimageio.spec.model.v0_4.ZeroMeanUnitVarianceKwargs.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_4.ZeroMeanUnitVarianceKwargs.model_computed_fields", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ZeroMeanUnitVarianceKwargs.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_4.ZeroMeanUnitVarianceDescr": {"fullname": "bioimageio.spec.model.v0_4.ZeroMeanUnitVarianceDescr", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ZeroMeanUnitVarianceDescr", "kind": "class", "doc": "
    Subtract mean and divide by variance.
    \n", "bases": "ProcessingDescrBase"}, "bioimageio.spec.model.v0_4.ZeroMeanUnitVarianceDescr.name": {"fullname": "bioimageio.spec.model.v0_4.ZeroMeanUnitVarianceDescr.name", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ZeroMeanUnitVarianceDescr.name", "kind": "variable", "doc": "
    \n", "annotation": ": Literal['zero_mean_unit_variance']"}, "bioimageio.spec.model.v0_4.ZeroMeanUnitVarianceDescr.kwargs": {"fullname": "bioimageio.spec.model.v0_4.ZeroMeanUnitVarianceDescr.kwargs", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ZeroMeanUnitVarianceDescr.kwargs", "kind": "variable", "doc": "
    \n", "annotation": ": bioimageio.spec.model.v0_4.ZeroMeanUnitVarianceKwargs"}, "bioimageio.spec.model.v0_4.ZeroMeanUnitVarianceDescr.model_config": {"fullname": "bioimageio.spec.model.v0_4.ZeroMeanUnitVarianceDescr.model_config", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ZeroMeanUnitVarianceDescr.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_4.ZeroMeanUnitVarianceDescr.model_fields": {"fullname": "bioimageio.spec.model.v0_4.ZeroMeanUnitVarianceDescr.model_fields", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ZeroMeanUnitVarianceDescr.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'name': FieldInfo(annotation=Literal['zero_mean_unit_variance'], required=False, default='zero_mean_unit_variance'), 'kwargs': FieldInfo(annotation=ZeroMeanUnitVarianceKwargs, required=True)}"}, "bioimageio.spec.model.v0_4.ZeroMeanUnitVarianceDescr.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_4.ZeroMeanUnitVarianceDescr.model_computed_fields", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ZeroMeanUnitVarianceDescr.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_4.ScaleRangeKwargs": {"fullname": "bioimageio.spec.model.v0_4.ScaleRangeKwargs", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ScaleRangeKwargs", "kind": "class", "doc": "
    base class for pre-/postprocessing key word arguments
    \n", "bases": "ProcessingKwargs"}, "bioimageio.spec.model.v0_4.ScaleRangeKwargs.mode": {"fullname": "bioimageio.spec.model.v0_4.ScaleRangeKwargs.mode", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ScaleRangeKwargs.mode", "kind": "variable", "doc": "
    Mode for computing percentiles.\n|     mode    |             description              |\n| ----------- | ------------------------------------ |\n| per_dataset | compute for the entire dataset       |\n| per_sample  | compute for each sample individually |
    \n", "annotation": ": Literal['per_dataset', 'per_sample']"}, "bioimageio.spec.model.v0_4.ScaleRangeKwargs.axes": {"fullname": "bioimageio.spec.model.v0_4.ScaleRangeKwargs.axes", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ScaleRangeKwargs.axes", "kind": "variable", "doc": "
    The subset of axes to normalize jointly.\nFor example xy to normalize the two image axes for 2d data jointly.
    \n", "annotation": ": Annotated[str, RestrictCharacters(alphabet='czyx'), AfterValidator(func=<function validate_unique_entries at 0x7f1c21c7a340>), FieldInfo(annotation=NoneType, required=True, examples=['xy'])]"}, "bioimageio.spec.model.v0_4.ScaleRangeKwargs.min_percentile": {"fullname": "bioimageio.spec.model.v0_4.ScaleRangeKwargs.min_percentile", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ScaleRangeKwargs.min_percentile", "kind": "variable", "doc": "
    The lower percentile used for normalization.
    \n", "annotation": ": Annotated[Union[int, float], Interval(gt=None, ge=0, lt=100, le=None)]"}, "bioimageio.spec.model.v0_4.ScaleRangeKwargs.max_percentile": {"fullname": "bioimageio.spec.model.v0_4.ScaleRangeKwargs.max_percentile", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ScaleRangeKwargs.max_percentile", "kind": "variable", "doc": "
    The upper percentile used for normalization\nHas to be bigger than min_percentile.\nThe range is 1 to 100 instead of 0 to 100 to avoid mistakenly\naccepting percentiles specified in the range 0.0 to 1.0.
    \n", "annotation": ": Annotated[Union[int, float], Interval(gt=1, ge=None, lt=None, le=100)]"}, "bioimageio.spec.model.v0_4.ScaleRangeKwargs.min_smaller_max": {"fullname": "bioimageio.spec.model.v0_4.ScaleRangeKwargs.min_smaller_max", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ScaleRangeKwargs.min_smaller_max", "kind": "function", "doc": "
    \n", "signature": "(self, info: pydantic_core.core_schema.ValidationInfo) -> Self:", "funcdef": "def"}, "bioimageio.spec.model.v0_4.ScaleRangeKwargs.eps": {"fullname": "bioimageio.spec.model.v0_4.ScaleRangeKwargs.eps", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ScaleRangeKwargs.eps", "kind": "variable", "doc": "
    Epsilon for numeric stability.\nout = (tensor - v_lower) / (v_upper - v_lower + eps);\nwith v_lower,v_upper values at the respective percentiles.
    \n", "annotation": ": Annotated[float, Interval(gt=0, ge=None, lt=None, le=0.1)]"}, "bioimageio.spec.model.v0_4.ScaleRangeKwargs.reference_tensor": {"fullname": "bioimageio.spec.model.v0_4.ScaleRangeKwargs.reference_tensor", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ScaleRangeKwargs.reference_tensor", "kind": "variable", "doc": "
    Tensor name to compute the percentiles from. Default: The tensor itself.\nFor any tensor in inputs only input tensor references are allowed.\nFor a tensor in outputs only input tensor refereences are allowed if mode: per_dataset
    \n", "annotation": ": Optional[bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate]]]]"}, "bioimageio.spec.model.v0_4.ScaleRangeKwargs.model_config": {"fullname": "bioimageio.spec.model.v0_4.ScaleRangeKwargs.model_config", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ScaleRangeKwargs.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_4.ScaleRangeKwargs.model_fields": {"fullname": "bioimageio.spec.model.v0_4.ScaleRangeKwargs.model_fields", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ScaleRangeKwargs.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'mode': FieldInfo(annotation=Literal['per_dataset', 'per_sample'], required=True), 'axes': FieldInfo(annotation=str, required=True, examples=['xy'], metadata=[RestrictCharacters(alphabet='czyx'), AfterValidator(func=<function validate_unique_entries>)]), 'min_percentile': FieldInfo(annotation=Union[int, float], required=False, default=0.0, metadata=[Interval(gt=None, ge=0, lt=100, le=None)]), 'max_percentile': FieldInfo(annotation=Union[int, float], required=False, default=100.0, metadata=[Interval(gt=1, ge=None, lt=None, le=100)]), 'eps': FieldInfo(annotation=float, required=False, default=1e-06, metadata=[Interval(gt=0, ge=None, lt=None, le=0.1)]), 'reference_tensor': FieldInfo(annotation=Union[ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate]]], NoneType], required=False)}"}, "bioimageio.spec.model.v0_4.ScaleRangeKwargs.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_4.ScaleRangeKwargs.model_computed_fields", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ScaleRangeKwargs.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_4.ScaleRangeDescr": {"fullname": "bioimageio.spec.model.v0_4.ScaleRangeDescr", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ScaleRangeDescr", "kind": "class", "doc": "
    Scale with percentiles.
    \n", "bases": "ProcessingDescrBase"}, "bioimageio.spec.model.v0_4.ScaleRangeDescr.name": {"fullname": "bioimageio.spec.model.v0_4.ScaleRangeDescr.name", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ScaleRangeDescr.name", "kind": "variable", "doc": "
    \n", "annotation": ": Literal['scale_range']"}, "bioimageio.spec.model.v0_4.ScaleRangeDescr.kwargs": {"fullname": "bioimageio.spec.model.v0_4.ScaleRangeDescr.kwargs", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ScaleRangeDescr.kwargs", "kind": "variable", "doc": "
    \n", "annotation": ": bioimageio.spec.model.v0_4.ScaleRangeKwargs"}, "bioimageio.spec.model.v0_4.ScaleRangeDescr.model_config": {"fullname": "bioimageio.spec.model.v0_4.ScaleRangeDescr.model_config", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ScaleRangeDescr.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_4.ScaleRangeDescr.model_fields": {"fullname": "bioimageio.spec.model.v0_4.ScaleRangeDescr.model_fields", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ScaleRangeDescr.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'name': FieldInfo(annotation=Literal['scale_range'], required=False, default='scale_range'), 'kwargs': FieldInfo(annotation=ScaleRangeKwargs, required=True)}"}, "bioimageio.spec.model.v0_4.ScaleRangeDescr.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_4.ScaleRangeDescr.model_computed_fields", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ScaleRangeDescr.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_4.ScaleMeanVarianceKwargs": {"fullname": "bioimageio.spec.model.v0_4.ScaleMeanVarianceKwargs", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ScaleMeanVarianceKwargs", "kind": "class", "doc": "
    base class for pre-/postprocessing key word arguments
    \n", "bases": "ProcessingKwargs"}, "bioimageio.spec.model.v0_4.ScaleMeanVarianceKwargs.mode": {"fullname": "bioimageio.spec.model.v0_4.ScaleMeanVarianceKwargs.mode", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ScaleMeanVarianceKwargs.mode", "kind": "variable", "doc": "
    Mode for computing mean and variance.\n|     mode    |             description              |\n| ----------- | ------------------------------------ |\n| per_dataset | Compute for the entire dataset       |\n| per_sample  | Compute for each sample individually |
    \n", "annotation": ": Literal['per_dataset', 'per_sample']"}, "bioimageio.spec.model.v0_4.ScaleMeanVarianceKwargs.reference_tensor": {"fullname": "bioimageio.spec.model.v0_4.ScaleMeanVarianceKwargs.reference_tensor", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ScaleMeanVarianceKwargs.reference_tensor", "kind": "variable", "doc": "
    Name of tensor to match.
    \n", "annotation": ": bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate]]]"}, "bioimageio.spec.model.v0_4.ScaleMeanVarianceKwargs.axes": {"fullname": "bioimageio.spec.model.v0_4.ScaleMeanVarianceKwargs.axes", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ScaleMeanVarianceKwargs.axes", "kind": "variable", "doc": "
    The subset of axes to scale jointly.\nFor example xy to normalize the two image axes for 2d data jointly.\nDefault: scale all non-batch axes jointly.
    \n", "annotation": ": Annotated[Optional[Annotated[str, RestrictCharacters(alphabet='czyx'), AfterValidator(func=<function validate_unique_entries at 0x7f1c21c7a340>)]], FieldInfo(annotation=NoneType, required=True, examples=['xy'])]"}, "bioimageio.spec.model.v0_4.ScaleMeanVarianceKwargs.eps": {"fullname": "bioimageio.spec.model.v0_4.ScaleMeanVarianceKwargs.eps", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ScaleMeanVarianceKwargs.eps", "kind": "variable", "doc": "
    Epsilon for numeric stability:\n\"`out  = (tensor - mean) / (std + eps) * (ref_std + eps) + ref_mean.
    \n", "annotation": ": Annotated[float, Interval(gt=0, ge=None, lt=None, le=0.1)]"}, "bioimageio.spec.model.v0_4.ScaleMeanVarianceKwargs.model_config": {"fullname": "bioimageio.spec.model.v0_4.ScaleMeanVarianceKwargs.model_config", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ScaleMeanVarianceKwargs.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_4.ScaleMeanVarianceKwargs.model_fields": {"fullname": "bioimageio.spec.model.v0_4.ScaleMeanVarianceKwargs.model_fields", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ScaleMeanVarianceKwargs.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'mode': FieldInfo(annotation=Literal['per_dataset', 'per_sample'], required=True), 'reference_tensor': FieldInfo(annotation=ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate]]], required=True), 'axes': FieldInfo(annotation=Union[Annotated[str, RestrictCharacters, AfterValidator], NoneType], required=False, examples=['xy']), 'eps': FieldInfo(annotation=float, required=False, default=1e-06, metadata=[Interval(gt=0, ge=None, lt=None, le=0.1)])}"}, "bioimageio.spec.model.v0_4.ScaleMeanVarianceKwargs.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_4.ScaleMeanVarianceKwargs.model_computed_fields", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ScaleMeanVarianceKwargs.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_4.ScaleMeanVarianceDescr": {"fullname": "bioimageio.spec.model.v0_4.ScaleMeanVarianceDescr", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ScaleMeanVarianceDescr", "kind": "class", "doc": "
    Scale the tensor s.t. its mean and variance match a reference tensor.
    \n", "bases": "ProcessingDescrBase"}, "bioimageio.spec.model.v0_4.ScaleMeanVarianceDescr.name": {"fullname": "bioimageio.spec.model.v0_4.ScaleMeanVarianceDescr.name", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ScaleMeanVarianceDescr.name", "kind": "variable", "doc": "
    \n", "annotation": ": Literal['scale_mean_variance']"}, "bioimageio.spec.model.v0_4.ScaleMeanVarianceDescr.kwargs": {"fullname": "bioimageio.spec.model.v0_4.ScaleMeanVarianceDescr.kwargs", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ScaleMeanVarianceDescr.kwargs", "kind": "variable", "doc": "
    \n", "annotation": ": bioimageio.spec.model.v0_4.ScaleMeanVarianceKwargs"}, "bioimageio.spec.model.v0_4.ScaleMeanVarianceDescr.model_config": {"fullname": "bioimageio.spec.model.v0_4.ScaleMeanVarianceDescr.model_config", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ScaleMeanVarianceDescr.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_4.ScaleMeanVarianceDescr.model_fields": {"fullname": "bioimageio.spec.model.v0_4.ScaleMeanVarianceDescr.model_fields", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ScaleMeanVarianceDescr.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'name': FieldInfo(annotation=Literal['scale_mean_variance'], required=False, default='scale_mean_variance'), 'kwargs': FieldInfo(annotation=ScaleMeanVarianceKwargs, required=True)}"}, "bioimageio.spec.model.v0_4.ScaleMeanVarianceDescr.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_4.ScaleMeanVarianceDescr.model_computed_fields", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ScaleMeanVarianceDescr.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_4.PreprocessingDescr": {"fullname": "bioimageio.spec.model.v0_4.PreprocessingDescr", "modulename": "bioimageio.spec.model.v0_4", "qualname": "PreprocessingDescr", "kind": "variable", "doc": "
    \n", "default_value": "typing.Annotated[typing.Union[bioimageio.spec.model.v0_4.BinarizeDescr, bioimageio.spec.model.v0_4.ClipDescr, bioimageio.spec.model.v0_4.ScaleLinearDescr, bioimageio.spec.model.v0_4.SigmoidDescr, bioimageio.spec.model.v0_4.ZeroMeanUnitVarianceDescr, bioimageio.spec.model.v0_4.ScaleRangeDescr], FieldInfo(annotation=NoneType, required=True, discriminator='name')]"}, "bioimageio.spec.model.v0_4.PostprocessingDescr": {"fullname": "bioimageio.spec.model.v0_4.PostprocessingDescr", "modulename": "bioimageio.spec.model.v0_4", "qualname": "PostprocessingDescr", "kind": "variable", "doc": "
    \n", "default_value": "typing.Annotated[typing.Union[bioimageio.spec.model.v0_4.BinarizeDescr, bioimageio.spec.model.v0_4.ClipDescr, bioimageio.spec.model.v0_4.ScaleLinearDescr, bioimageio.spec.model.v0_4.SigmoidDescr, bioimageio.spec.model.v0_4.ZeroMeanUnitVarianceDescr, bioimageio.spec.model.v0_4.ScaleRangeDescr, bioimageio.spec.model.v0_4.ScaleMeanVarianceDescr], FieldInfo(annotation=NoneType, required=True, discriminator='name')]"}, "bioimageio.spec.model.v0_4.InputTensorDescr": {"fullname": "bioimageio.spec.model.v0_4.InputTensorDescr", "modulename": "bioimageio.spec.model.v0_4", "qualname": "InputTensorDescr", "kind": "class", "doc": "
    Subpart of a resource description
    \n", "bases": "TensorDescrBase"}, "bioimageio.spec.model.v0_4.InputTensorDescr.data_type": {"fullname": "bioimageio.spec.model.v0_4.InputTensorDescr.data_type", "modulename": "bioimageio.spec.model.v0_4", "qualname": "InputTensorDescr.data_type", "kind": "variable", "doc": "
    For now an input tensor is expected to be given as float32.\nThe data flow in bioimage.io models is explained\nin this diagram..
    \n", "annotation": ": Literal['float32', 'uint8', 'uint16']"}, "bioimageio.spec.model.v0_4.InputTensorDescr.shape": {"fullname": "bioimageio.spec.model.v0_4.InputTensorDescr.shape", "modulename": "bioimageio.spec.model.v0_4", "qualname": "InputTensorDescr.shape", "kind": "variable", "doc": "
    Specification of input tensor shape.
    \n", "annotation": ": Annotated[Union[Sequence[int], bioimageio.spec.model.v0_4.ParameterizedInputShape], FieldInfo(annotation=NoneType, required=True, examples=[(1, 512, 512, 1), {'min': (1, 64, 64, 1), 'step': (0, 32, 32, 0)}])]"}, "bioimageio.spec.model.v0_4.InputTensorDescr.preprocessing": {"fullname": "bioimageio.spec.model.v0_4.InputTensorDescr.preprocessing", "modulename": "bioimageio.spec.model.v0_4", "qualname": "InputTensorDescr.preprocessing", "kind": "variable", "doc": "
    Description of how this input should be preprocessed.
    \n", "annotation": ": List[Annotated[Union[bioimageio.spec.model.v0_4.BinarizeDescr, bioimageio.spec.model.v0_4.ClipDescr, bioimageio.spec.model.v0_4.ScaleLinearDescr, bioimageio.spec.model.v0_4.SigmoidDescr, bioimageio.spec.model.v0_4.ZeroMeanUnitVarianceDescr, bioimageio.spec.model.v0_4.ScaleRangeDescr], FieldInfo(annotation=NoneType, required=True, discriminator='name')]]"}, "bioimageio.spec.model.v0_4.InputTensorDescr.zero_batch_step_and_one_batch_size": {"fullname": "bioimageio.spec.model.v0_4.InputTensorDescr.zero_batch_step_and_one_batch_size", "modulename": "bioimageio.spec.model.v0_4", "qualname": "InputTensorDescr.zero_batch_step_and_one_batch_size", "kind": "function", "doc": "
    \n", "signature": "(self) -> Self:", "funcdef": "def"}, "bioimageio.spec.model.v0_4.InputTensorDescr.validate_preprocessing_kwargs": {"fullname": "bioimageio.spec.model.v0_4.InputTensorDescr.validate_preprocessing_kwargs", "modulename": "bioimageio.spec.model.v0_4", "qualname": "InputTensorDescr.validate_preprocessing_kwargs", "kind": "function", "doc": "
    \n", "signature": "(self) -> Self:", "funcdef": "def"}, "bioimageio.spec.model.v0_4.InputTensorDescr.model_config": {"fullname": "bioimageio.spec.model.v0_4.InputTensorDescr.model_config", "modulename": "bioimageio.spec.model.v0_4", "qualname": "InputTensorDescr.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_4.InputTensorDescr.model_fields": {"fullname": "bioimageio.spec.model.v0_4.InputTensorDescr.model_fields", "modulename": "bioimageio.spec.model.v0_4", "qualname": "InputTensorDescr.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'name': FieldInfo(annotation=ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate]]], required=True), 'description': FieldInfo(annotation=str, required=False, default=''), 'axes': FieldInfo(annotation=str, required=True, metadata=[RestrictCharacters(alphabet='bitczyx'), AfterValidator(func=<function validate_unique_entries>)]), 'data_range': FieldInfo(annotation=Union[Tuple[Annotated[float, AllowInfNan(allow_inf_nan=True)], Annotated[float, AllowInfNan(allow_inf_nan=True)]], NoneType], required=False), 'data_type': FieldInfo(annotation=Literal['float32', 'uint8', 'uint16'], required=True), 'shape': FieldInfo(annotation=Union[Sequence[int], ParameterizedInputShape], required=True, examples=[(1, 512, 512, 1), {'min': (1, 64, 64, 1), 'step': (0, 32, 32, 0)}]), 'preprocessing': FieldInfo(annotation=List[Annotated[Union[BinarizeDescr, ClipDescr, ScaleLinearDescr, SigmoidDescr, ZeroMeanUnitVarianceDescr, ScaleRangeDescr], FieldInfo(annotation=NoneType, required=True, discriminator='name')]], required=False, default_factory=list)}"}, "bioimageio.spec.model.v0_4.InputTensorDescr.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_4.InputTensorDescr.model_computed_fields", "modulename": "bioimageio.spec.model.v0_4", "qualname": "InputTensorDescr.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_4.OutputTensorDescr": {"fullname": "bioimageio.spec.model.v0_4.OutputTensorDescr", "modulename": "bioimageio.spec.model.v0_4", "qualname": "OutputTensorDescr", "kind": "class", "doc": "
    Subpart of a resource description
    \n", "bases": "TensorDescrBase"}, "bioimageio.spec.model.v0_4.OutputTensorDescr.data_type": {"fullname": "bioimageio.spec.model.v0_4.OutputTensorDescr.data_type", "modulename": "bioimageio.spec.model.v0_4", "qualname": "OutputTensorDescr.data_type", "kind": "variable", "doc": "
    Data type.\nThe data flow in bioimage.io models is explained\nin this diagram..
    \n", "annotation": ": Literal['float32', 'float64', 'uint8', 'int8', 'uint16', 'int16', 'uint32', 'int32', 'uint64', 'int64', 'bool']"}, "bioimageio.spec.model.v0_4.OutputTensorDescr.shape": {"fullname": "bioimageio.spec.model.v0_4.OutputTensorDescr.shape", "modulename": "bioimageio.spec.model.v0_4", "qualname": "OutputTensorDescr.shape", "kind": "variable", "doc": "
    Output tensor shape.
    \n", "annotation": ": Union[Sequence[int], bioimageio.spec.model.v0_4.ImplicitOutputShape]"}, "bioimageio.spec.model.v0_4.OutputTensorDescr.halo": {"fullname": "bioimageio.spec.model.v0_4.OutputTensorDescr.halo", "modulename": "bioimageio.spec.model.v0_4", "qualname": "OutputTensorDescr.halo", "kind": "variable", "doc": "
    The halo that should be cropped from the output tensor to avoid boundary effects.\nThe halo is to be cropped from both sides, i.e. shape_after_crop = shape - 2 * halo.\nTo document a halo that is already cropped by the model shape.offset has to be used instead.
    \n", "annotation": ": Optional[Sequence[int]]"}, "bioimageio.spec.model.v0_4.OutputTensorDescr.postprocessing": {"fullname": "bioimageio.spec.model.v0_4.OutputTensorDescr.postprocessing", "modulename": "bioimageio.spec.model.v0_4", "qualname": "OutputTensorDescr.postprocessing", "kind": "variable", "doc": "
    Description of how this output should be postprocessed.
    \n", "annotation": ": List[Annotated[Union[bioimageio.spec.model.v0_4.BinarizeDescr, bioimageio.spec.model.v0_4.ClipDescr, bioimageio.spec.model.v0_4.ScaleLinearDescr, bioimageio.spec.model.v0_4.SigmoidDescr, bioimageio.spec.model.v0_4.ZeroMeanUnitVarianceDescr, bioimageio.spec.model.v0_4.ScaleRangeDescr, bioimageio.spec.model.v0_4.ScaleMeanVarianceDescr], FieldInfo(annotation=NoneType, required=True, discriminator='name')]]"}, "bioimageio.spec.model.v0_4.OutputTensorDescr.matching_halo_length": {"fullname": "bioimageio.spec.model.v0_4.OutputTensorDescr.matching_halo_length", "modulename": "bioimageio.spec.model.v0_4", "qualname": "OutputTensorDescr.matching_halo_length", "kind": "function", "doc": "
    \n", "signature": "(self) -> Self:", "funcdef": "def"}, "bioimageio.spec.model.v0_4.OutputTensorDescr.validate_postprocessing_kwargs": {"fullname": "bioimageio.spec.model.v0_4.OutputTensorDescr.validate_postprocessing_kwargs", "modulename": "bioimageio.spec.model.v0_4", "qualname": "OutputTensorDescr.validate_postprocessing_kwargs", "kind": "function", "doc": "
    \n", "signature": "(self) -> Self:", "funcdef": "def"}, "bioimageio.spec.model.v0_4.OutputTensorDescr.model_config": {"fullname": "bioimageio.spec.model.v0_4.OutputTensorDescr.model_config", "modulename": "bioimageio.spec.model.v0_4", "qualname": "OutputTensorDescr.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_4.OutputTensorDescr.model_fields": {"fullname": "bioimageio.spec.model.v0_4.OutputTensorDescr.model_fields", "modulename": "bioimageio.spec.model.v0_4", "qualname": "OutputTensorDescr.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'name': FieldInfo(annotation=ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate]]], required=True), 'description': FieldInfo(annotation=str, required=False, default=''), 'axes': FieldInfo(annotation=str, required=True, metadata=[RestrictCharacters(alphabet='bitczyx'), AfterValidator(func=<function validate_unique_entries>)]), 'data_range': FieldInfo(annotation=Union[Tuple[Annotated[float, AllowInfNan(allow_inf_nan=True)], Annotated[float, AllowInfNan(allow_inf_nan=True)]], NoneType], required=False), 'data_type': FieldInfo(annotation=Literal['float32', 'float64', 'uint8', 'int8', 'uint16', 'int16', 'uint32', 'int32', 'uint64', 'int64', 'bool'], required=True), 'shape': FieldInfo(annotation=Union[Sequence[int], ImplicitOutputShape], required=True), 'halo': FieldInfo(annotation=Union[Sequence[int], NoneType], required=False), 'postprocessing': FieldInfo(annotation=List[Annotated[Union[BinarizeDescr, ClipDescr, ScaleLinearDescr, SigmoidDescr, ZeroMeanUnitVarianceDescr, ScaleRangeDescr, ScaleMeanVarianceDescr], FieldInfo(annotation=NoneType, required=True, discriminator='name')]], required=False, default_factory=list)}"}, "bioimageio.spec.model.v0_4.OutputTensorDescr.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_4.OutputTensorDescr.model_computed_fields", "modulename": "bioimageio.spec.model.v0_4", "qualname": "OutputTensorDescr.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_4.KnownRunMode": {"fullname": "bioimageio.spec.model.v0_4.KnownRunMode", "modulename": "bioimageio.spec.model.v0_4", "qualname": "KnownRunMode", "kind": "variable", "doc": "
    \n", "default_value": "typing.Literal['deepimagej']"}, "bioimageio.spec.model.v0_4.RunMode": {"fullname": "bioimageio.spec.model.v0_4.RunMode", "modulename": "bioimageio.spec.model.v0_4", "qualname": "RunMode", "kind": "class", "doc": "
    Subpart of a resource description
    \n", "bases": "bioimageio.spec._internal.node.Node"}, "bioimageio.spec.model.v0_4.RunMode.name": {"fullname": "bioimageio.spec.model.v0_4.RunMode.name", "modulename": "bioimageio.spec.model.v0_4", "qualname": "RunMode.name", "kind": "variable", "doc": "
    Run mode name
    \n", "annotation": ": Annotated[Union[Literal['deepimagej'], str], AfterWarner(func=<function as_warning.<locals>.wrapper at 0x7f1c131ef740>, severity=30, msg="Unknown run mode '{value}'.", context={'typ': Literal['deepimagej']})]"}, "bioimageio.spec.model.v0_4.RunMode.kwargs": {"fullname": "bioimageio.spec.model.v0_4.RunMode.kwargs", "modulename": "bioimageio.spec.model.v0_4", "qualname": "RunMode.kwargs", "kind": "variable", "doc": "
    Run mode specific key word arguments
    \n", "annotation": ": Dict[str, Any]"}, "bioimageio.spec.model.v0_4.RunMode.model_config": {"fullname": "bioimageio.spec.model.v0_4.RunMode.model_config", "modulename": "bioimageio.spec.model.v0_4", "qualname": "RunMode.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_4.RunMode.model_fields": {"fullname": "bioimageio.spec.model.v0_4.RunMode.model_fields", "modulename": "bioimageio.spec.model.v0_4", "qualname": "RunMode.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'name': FieldInfo(annotation=Union[Literal['deepimagej'], str], required=True, metadata=[AfterWarner(func=<function as_warning.<locals>.wrapper>, severity=30, msg="Unknown run mode '{value}'.", context={'typ': typing.Literal['deepimagej']})]), 'kwargs': FieldInfo(annotation=Dict[str, Any], required=False, default_factory=dict)}"}, "bioimageio.spec.model.v0_4.RunMode.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_4.RunMode.model_computed_fields", "modulename": "bioimageio.spec.model.v0_4", "qualname": "RunMode.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_4.LinkedModel": {"fullname": "bioimageio.spec.model.v0_4.LinkedModel", "modulename": "bioimageio.spec.model.v0_4", "qualname": "LinkedModel", "kind": "class", "doc": "
    Reference to a bioimage.io model.
    \n", "bases": "bioimageio.spec._internal.node.Node"}, "bioimageio.spec.model.v0_4.LinkedModel.id": {"fullname": "bioimageio.spec.model.v0_4.LinkedModel.id", "modulename": "bioimageio.spec.model.v0_4", "qualname": "LinkedModel.id", "kind": "variable", "doc": "
    A valid model id from the bioimage.io collection.
    \n", "annotation": ": bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]]"}, "bioimageio.spec.model.v0_4.LinkedModel.version_number": {"fullname": "bioimageio.spec.model.v0_4.LinkedModel.version_number", "modulename": "bioimageio.spec.model.v0_4", "qualname": "LinkedModel.version_number", "kind": "variable", "doc": "
    version number (n-th published version, not the semantic version) of linked model
    \n", "annotation": ": Optional[int]"}, "bioimageio.spec.model.v0_4.LinkedModel.model_config": {"fullname": "bioimageio.spec.model.v0_4.LinkedModel.model_config", "modulename": "bioimageio.spec.model.v0_4", "qualname": "LinkedModel.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_4.LinkedModel.model_fields": {"fullname": "bioimageio.spec.model.v0_4.LinkedModel.model_fields", "modulename": "bioimageio.spec.model.v0_4", "qualname": "LinkedModel.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'id': FieldInfo(annotation=ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]], required=True), 'version_number': FieldInfo(annotation=Union[int, NoneType], required=False)}"}, "bioimageio.spec.model.v0_4.LinkedModel.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_4.LinkedModel.model_computed_fields", "modulename": "bioimageio.spec.model.v0_4", "qualname": "LinkedModel.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_4.ModelDescr": {"fullname": "bioimageio.spec.model.v0_4.ModelDescr", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ModelDescr", "kind": "class", "doc": "
    Specification of the fields used in a bioimage.io-compliant RDF that describes AI models with pretrained weights.
    \n\n
    These fields are typically stored in a YAML file which we call a model resource description file (model RDF).
    \n", "bases": "bioimageio.spec.generic.v0_2.GenericModelDescrBase"}, "bioimageio.spec.model.v0_4.ModelDescr.format_version": {"fullname": "bioimageio.spec.model.v0_4.ModelDescr.format_version", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ModelDescr.format_version", "kind": "variable", "doc": "
    Version of the bioimage.io model description specification used.\nWhen creating a new model always use the latest micro/patch version described here.\nThe format_version is important for any consumer software to understand how to parse the fields.
    \n", "annotation": ": Literal['0.4.10']"}, "bioimageio.spec.model.v0_4.ModelDescr.type": {"fullname": "bioimageio.spec.model.v0_4.ModelDescr.type", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ModelDescr.type", "kind": "variable", "doc": "
    Specialized resource type 'model'
    \n", "annotation": ": Literal['model']"}, "bioimageio.spec.model.v0_4.ModelDescr.id": {"fullname": "bioimageio.spec.model.v0_4.ModelDescr.id", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ModelDescr.id", "kind": "variable", "doc": "
    Model zoo (bioimage.io) wide, unique identifier (assigned by bioimage.io)
    \n", "annotation": ": Optional[bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]]]"}, "bioimageio.spec.model.v0_4.ModelDescr.authors": {"fullname": "bioimageio.spec.model.v0_4.ModelDescr.authors", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ModelDescr.authors", "kind": "variable", "doc": "
    The authors are the creators of the model RDF and the primary points of contact.
    \n", "annotation": ": Annotated[List[bioimageio.spec.generic.v0_2.Author], MinLen(min_length=1)]"}, "bioimageio.spec.model.v0_4.ModelDescr.documentation": {"fullname": "bioimageio.spec.model.v0_4.ModelDescr.documentation", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ModelDescr.documentation", "kind": "variable", "doc": "
    \u2208\ud83d\udce6 URL or relative path to a markdown file with additional documentation.\nThe recommended documentation file name is README.md. An .md suffix is mandatory.\nThe documentation should include a '[#[#]]# Validation' (sub)section\nwith details on how to quantitatively validate the model on unseen data.
    \n", "annotation": ": Annotated[Union[Annotated[pathlib.Path, PathType(path_type='file')], bioimageio.spec._internal.io.RelativeFilePath, bioimageio.spec._internal.url.HttpUrl, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator(func=<function wo_special_file_name at 0x7f1c21c3ef20>), PlainSerializer(func=<function _package at 0x7f1c21c782c0>, return_type=PydanticUndefined, when_used='unless-none'), FieldInfo(annotation=NoneType, required=True, examples=['https://raw.githubusercontent.com/bioimage-io/spec-bioimage-io/main/example_descriptions/models/unet2d_nuclei_broad/README.md', 'README.md'])]"}, "bioimageio.spec.model.v0_4.ModelDescr.inputs": {"fullname": "bioimageio.spec.model.v0_4.ModelDescr.inputs", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ModelDescr.inputs", "kind": "variable", "doc": "
    Describes the input tensors expected by this model.
    \n", "annotation": ": Annotated[List[bioimageio.spec.model.v0_4.InputTensorDescr], MinLen(min_length=1)]"}, "bioimageio.spec.model.v0_4.ModelDescr.license": {"fullname": "bioimageio.spec.model.v0_4.ModelDescr.license", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ModelDescr.license", "kind": "variable", "doc": "
    A SPDX license identifier.\nWe do notsupport custom license beyond the SPDX license list, if you need that please\nopen a GitHub issue to discuss your intentions with the community.
    \n", "annotation": ": Annotated[Union[bioimageio.spec._internal.license_id.LicenseId, str], AfterWarner(func=<function as_warning.<locals>.wrapper at 0x7f1c131ef880>, severity=30, msg="Unknown license id '{value}'.", context={'typ': <class 'bioimageio.spec._internal.license_id.LicenseId'>}), FieldInfo(annotation=NoneType, required=True, examples=['CC-BY-4.0', 'MIT', 'BSD-2-Clause'])]"}, "bioimageio.spec.model.v0_4.ModelDescr.name": {"fullname": "bioimageio.spec.model.v0_4.ModelDescr.name", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ModelDescr.name", "kind": "variable", "doc": "
    A human-readable name of this model.\nIt should be no longer than 64 characters and only contain letter, number, underscore, minus or space characters.
    \n", "annotation": ": Annotated[str, MinLen(min_length=1), AfterWarner(func=<function as_warning.<locals>.wrapper at 0x7f1c130fd3a0>, severity=20, msg='Name shorter than 5 characters.', context={'typ': Annotated[Any, MinLen(min_length=5)]}), AfterWarner(func=<function as_warning.<locals>.wrapper at 0x7f1c130ff740>, severity=20, msg='Name longer than 64 characters.', context={'typ': Annotated[Any, MaxLen(max_length=64)]})]"}, "bioimageio.spec.model.v0_4.ModelDescr.outputs": {"fullname": "bioimageio.spec.model.v0_4.ModelDescr.outputs", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ModelDescr.outputs", "kind": "variable", "doc": "
    Describes the output tensors.
    \n", "annotation": ": Annotated[List[bioimageio.spec.model.v0_4.OutputTensorDescr], MinLen(min_length=1)]"}, "bioimageio.spec.model.v0_4.ModelDescr.unique_tensor_descr_names": {"fullname": "bioimageio.spec.model.v0_4.ModelDescr.unique_tensor_descr_names", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ModelDescr.unique_tensor_descr_names", "kind": "function", "doc": "
    \n", "signature": "(\tcls,\tvalue: Sequence[Union[bioimageio.spec.model.v0_4.InputTensorDescr, bioimageio.spec.model.v0_4.OutputTensorDescr]]) -> Sequence[Union[bioimageio.spec.model.v0_4.InputTensorDescr, bioimageio.spec.model.v0_4.OutputTensorDescr]]:", "funcdef": "def"}, "bioimageio.spec.model.v0_4.ModelDescr.unique_io_names": {"fullname": "bioimageio.spec.model.v0_4.ModelDescr.unique_io_names", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ModelDescr.unique_io_names", "kind": "function", "doc": "
    \n", "signature": "(self) -> Self:", "funcdef": "def"}, "bioimageio.spec.model.v0_4.ModelDescr.minimum_shape2valid_output": {"fullname": "bioimageio.spec.model.v0_4.ModelDescr.minimum_shape2valid_output", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ModelDescr.minimum_shape2valid_output", "kind": "function", "doc": "
    \n", "signature": "(self) -> Self:", "funcdef": "def"}, "bioimageio.spec.model.v0_4.ModelDescr.validate_tensor_references_in_inputs": {"fullname": "bioimageio.spec.model.v0_4.ModelDescr.validate_tensor_references_in_inputs", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ModelDescr.validate_tensor_references_in_inputs", "kind": "function", "doc": "
    \n", "signature": "(self) -> Self:", "funcdef": "def"}, "bioimageio.spec.model.v0_4.ModelDescr.validate_tensor_references_in_outputs": {"fullname": "bioimageio.spec.model.v0_4.ModelDescr.validate_tensor_references_in_outputs", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ModelDescr.validate_tensor_references_in_outputs", "kind": "function", "doc": "
    \n", "signature": "(self) -> Self:", "funcdef": "def"}, "bioimageio.spec.model.v0_4.ModelDescr.packaged_by": {"fullname": "bioimageio.spec.model.v0_4.ModelDescr.packaged_by", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ModelDescr.packaged_by", "kind": "variable", "doc": "
    The persons that have packaged and uploaded this model.\nOnly required if those persons differ from the authors.
    \n", "annotation": ": List[bioimageio.spec.generic.v0_2.Author]"}, "bioimageio.spec.model.v0_4.ModelDescr.parent": {"fullname": "bioimageio.spec.model.v0_4.ModelDescr.parent", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ModelDescr.parent", "kind": "variable", "doc": "
    The model from which this model is derived, e.g. by fine-tuning the weights.
    \n", "annotation": ": Optional[bioimageio.spec.model.v0_4.LinkedModel]"}, "bioimageio.spec.model.v0_4.ModelDescr.ignore_url_parent": {"fullname": "bioimageio.spec.model.v0_4.ModelDescr.ignore_url_parent", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ModelDescr.ignore_url_parent", "kind": "function", "doc": "
    \n", "signature": "(cls, parent: Any):", "funcdef": "def"}, "bioimageio.spec.model.v0_4.ModelDescr.run_mode": {"fullname": "bioimageio.spec.model.v0_4.ModelDescr.run_mode", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ModelDescr.run_mode", "kind": "variable", "doc": "
    Custom run mode for this model: for more complex prediction procedures like test time\ndata augmentation that currently cannot be expressed in the specification.\nNo standard run modes are defined yet.
    \n", "annotation": ": Optional[bioimageio.spec.model.v0_4.RunMode]"}, "bioimageio.spec.model.v0_4.ModelDescr.sample_inputs": {"fullname": "bioimageio.spec.model.v0_4.ModelDescr.sample_inputs", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ModelDescr.sample_inputs", "kind": "variable", "doc": "
    \u2208\ud83d\udce6 URLs/relative paths to sample inputs to illustrate possible inputs for the model,\nfor example stored as PNG or TIFF images.\nThe sample files primarily serve to inform a human user about an example use case
    \n", "annotation": ": List[Annotated[Union[Annotated[pathlib.Path, PathType(path_type='file')], bioimageio.spec._internal.io.RelativeFilePath, bioimageio.spec._internal.url.HttpUrl, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator(func=<function wo_special_file_name at 0x7f1c21c3ef20>), PlainSerializer(func=<function _package at 0x7f1c21c782c0>, return_type=PydanticUndefined, when_used='unless-none')]]"}, "bioimageio.spec.model.v0_4.ModelDescr.sample_outputs": {"fullname": "bioimageio.spec.model.v0_4.ModelDescr.sample_outputs", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ModelDescr.sample_outputs", "kind": "variable", "doc": "
    \u2208\ud83d\udce6 URLs/relative paths to sample outputs corresponding to the sample_inputs.
    \n", "annotation": ": List[Annotated[Union[Annotated[pathlib.Path, PathType(path_type='file')], bioimageio.spec._internal.io.RelativeFilePath, bioimageio.spec._internal.url.HttpUrl, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator(func=<function wo_special_file_name at 0x7f1c21c3ef20>), PlainSerializer(func=<function _package at 0x7f1c21c782c0>, return_type=PydanticUndefined, when_used='unless-none')]]"}, "bioimageio.spec.model.v0_4.ModelDescr.test_inputs": {"fullname": "bioimageio.spec.model.v0_4.ModelDescr.test_inputs", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ModelDescr.test_inputs", "kind": "variable", "doc": "
    \u2208\ud83d\udce6 Test input tensors compatible with the inputs description for a single test case.\nThis means if your model has more than one input, you should provide one URL/relative path for each input.\nEach test input should be a file with an ndarray in\nnumpy.lib file format.\nThe extension must be '.npy'.
    \n", "annotation": ": Annotated[List[Annotated[Union[Annotated[pathlib.Path, PathType(path_type='file')], bioimageio.spec._internal.io.RelativeFilePath, bioimageio.spec._internal.url.HttpUrl, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator(func=<function wo_special_file_name at 0x7f1c21c3ef20>), PlainSerializer(func=<function _package at 0x7f1c21c782c0>, return_type=PydanticUndefined, when_used='unless-none'), WithSuffix(suffix='.npy', case_sensitive=True)]], MinLen(min_length=1)]"}, "bioimageio.spec.model.v0_4.ModelDescr.test_outputs": {"fullname": "bioimageio.spec.model.v0_4.ModelDescr.test_outputs", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ModelDescr.test_outputs", "kind": "variable", "doc": "
    \u2208\ud83d\udce6 Analog to test_inputs.
    \n", "annotation": ": Annotated[List[Annotated[Union[Annotated[pathlib.Path, PathType(path_type='file')], bioimageio.spec._internal.io.RelativeFilePath, bioimageio.spec._internal.url.HttpUrl, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator(func=<function wo_special_file_name at 0x7f1c21c3ef20>), PlainSerializer(func=<function _package at 0x7f1c21c782c0>, return_type=PydanticUndefined, when_used='unless-none'), WithSuffix(suffix='.npy', case_sensitive=True)]], MinLen(min_length=1)]"}, "bioimageio.spec.model.v0_4.ModelDescr.timestamp": {"fullname": "bioimageio.spec.model.v0_4.ModelDescr.timestamp", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ModelDescr.timestamp", "kind": "variable", "doc": "
    Timestamp in ISO 8601 format\nwith a few restrictions listed here.
    \n", "annotation": ": bioimageio.spec._internal.types.Datetime"}, "bioimageio.spec.model.v0_4.ModelDescr.training_data": {"fullname": "bioimageio.spec.model.v0_4.ModelDescr.training_data", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ModelDescr.training_data", "kind": "variable", "doc": "
    The dataset used to train this model
    \n", "annotation": ": Union[bioimageio.spec.dataset.v0_2.LinkedDataset, bioimageio.spec.dataset.v0_2.DatasetDescr, NoneType]"}, "bioimageio.spec.model.v0_4.ModelDescr.weights": {"fullname": "bioimageio.spec.model.v0_4.ModelDescr.weights", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ModelDescr.weights", "kind": "variable", "doc": "
    The weights for this model.\nWeights can be given for different formats, but should otherwise be equivalent.\nThe available weight formats determine which consumers can use this model.
    \n", "annotation": ": bioimageio.spec.model.v0_4.WeightsDescr"}, "bioimageio.spec.model.v0_4.ModelDescr.get_input_test_arrays": {"fullname": "bioimageio.spec.model.v0_4.ModelDescr.get_input_test_arrays", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ModelDescr.get_input_test_arrays", "kind": "function", "doc": "
    \n", "signature": "(self) -> List[numpy.ndarray[Any, numpy.dtype[Any]]]:", "funcdef": "def"}, "bioimageio.spec.model.v0_4.ModelDescr.get_output_test_arrays": {"fullname": "bioimageio.spec.model.v0_4.ModelDescr.get_output_test_arrays", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ModelDescr.get_output_test_arrays", "kind": "function", "doc": "
    \n", "signature": "(self) -> List[numpy.ndarray[Any, numpy.dtype[Any]]]:", "funcdef": "def"}, "bioimageio.spec.model.v0_4.ModelDescr.implemented_format_version": {"fullname": "bioimageio.spec.model.v0_4.ModelDescr.implemented_format_version", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ModelDescr.implemented_format_version", "kind": "variable", "doc": "
    \n", "annotation": ": ClassVar[str]", "default_value": "'0.4.10'"}, "bioimageio.spec.model.v0_4.ModelDescr.implemented_format_version_tuple": {"fullname": "bioimageio.spec.model.v0_4.ModelDescr.implemented_format_version_tuple", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ModelDescr.implemented_format_version_tuple", "kind": "variable", "doc": "
    \n", "annotation": ": ClassVar[Tuple[int, int, int]]", "default_value": "(0, 4, 10)"}, "bioimageio.spec.model.v0_4.ModelDescr.model_config": {"fullname": "bioimageio.spec.model.v0_4.ModelDescr.model_config", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ModelDescr.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True, 'title': 'bioimage.io model specification'}"}, "bioimageio.spec.model.v0_4.ModelDescr.model_fields": {"fullname": "bioimageio.spec.model.v0_4.ModelDescr.model_fields", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ModelDescr.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'name': FieldInfo(annotation=str, required=True, metadata=[MinLen(min_length=1), AfterWarner(func=<function as_warning.<locals>.wrapper>, severity=20, msg='Name shorter than 5 characters.', context={'typ': typing.Annotated[typing.Any, MinLen(min_length=5)]}), AfterWarner(func=<function as_warning.<locals>.wrapper>, severity=20, msg='Name longer than 64 characters.', context={'typ': typing.Annotated[typing.Any, MaxLen(max_length=64)]})]), 'description': FieldInfo(annotation=str, required=True), 'covers': FieldInfo(annotation=List[Annotated[Union[HttpUrl, Annotated[Path, PathType, Predicate], RelativeFilePath], WithSuffix, PlainSerializer]], required=False, default_factory=list, description="Cover images. Please use an image smaller than 500KB and an aspect ratio width to height of 2:1.\\nThe supported image formats are: ('.gif', '.jpeg', '.jpg', '.png', '.svg')", examples=['cover.png']), 'id_emoji': FieldInfo(annotation=Union[Annotated[str, Len], NoneType], required=False), 'authors': FieldInfo(annotation=List[Author], required=True, metadata=[MinLen(min_length=1)]), 'attachments': FieldInfo(annotation=Union[AttachmentsDescr, NoneType], required=False), 'cite': FieldInfo(annotation=List[CiteEntry], required=False, default_factory=list), 'config': FieldInfo(annotation=Dict[str, YamlValue], required=False, default_factory=dict, examples=[{'bioimageio': {'my_custom_key': 3837283, 'another_key': {'nested': 'value'}}, 'imagej': {'macro_dir': 'path/to/macro/file'}}]), 'download_url': FieldInfo(annotation=Union[HttpUrl, NoneType], required=False), 'git_repo': FieldInfo(annotation=Union[str, NoneType], required=False, examples=['https://github.com/bioimage-io/spec-bioimage-io/tree/main/example_descriptions/models/unet2d_nuclei_broad']), 'icon': FieldInfo(annotation=Union[Annotated[Union[Annotated[Path, PathType], RelativeFilePath, HttpUrl, Annotated[Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator, PlainSerializer], Annotated[str, Len], NoneType], required=False), 'links': FieldInfo(annotation=List[str], required=False, default_factory=list, examples=[('ilastik/ilastik', 'deepimagej/deepimagej', 'zero/notebook_u-net_3d_zerocostdl4mic')]), 'uploader': FieldInfo(annotation=Union[Uploader, NoneType], required=False), 'maintainers': FieldInfo(annotation=List[Maintainer], required=False, default_factory=list), 'rdf_source': FieldInfo(annotation=Union[Annotated[Path, PathType], RelativeFilePath, HttpUrl, Annotated[Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)], NoneType], required=False), 'tags': FieldInfo(annotation=List[str], required=False, default_factory=list, examples=[('unet2d', 'pytorch', 'nucleus', 'segmentation', 'dsb2018')]), 'version': FieldInfo(annotation=Union[Version, NoneType], required=False), 'version_number': FieldInfo(annotation=Union[int, NoneType], required=False), 'format_version': FieldInfo(annotation=Literal['0.4.10'], required=False, default='0.4.10'), 'type': FieldInfo(annotation=Literal['model'], required=False, default='model'), 'id': FieldInfo(annotation=Union[ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]], NoneType], required=False), 'documentation': FieldInfo(annotation=Union[Annotated[Path, PathType], RelativeFilePath, HttpUrl, Annotated[Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], required=True, examples=['https://raw.githubusercontent.com/bioimage-io/spec-bioimage-io/main/example_descriptions/models/unet2d_nuclei_broad/README.md', 'README.md'], metadata=[AfterValidator(func=<function wo_special_file_name>), PlainSerializer(func=<function _package>, return_type=PydanticUndefined, when_used='unless-none')]), 'inputs': FieldInfo(annotation=List[InputTensorDescr], required=True, metadata=[MinLen(min_length=1)]), 'license': FieldInfo(annotation=Union[LicenseId, str], required=True, examples=['CC-BY-4.0', 'MIT', 'BSD-2-Clause'], metadata=[AfterWarner(func=<function as_warning.<locals>.wrapper>, severity=30, msg="Unknown license id '{value}'.", context={'typ': <class 'bioimageio.spec._internal.license_id.LicenseId'>})]), 'outputs': FieldInfo(annotation=List[OutputTensorDescr], required=True, metadata=[MinLen(min_length=1)]), 'packaged_by': FieldInfo(annotation=List[Author], required=False, default_factory=list), 'parent': FieldInfo(annotation=Union[LinkedModel, NoneType], required=False), 'run_mode': FieldInfo(annotation=Union[RunMode, NoneType], required=False), 'sample_inputs': FieldInfo(annotation=List[Annotated[Union[Annotated[Path, PathType], RelativeFilePath, HttpUrl, Annotated[Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator, PlainSerializer]], required=False, default_factory=list), 'sample_outputs': FieldInfo(annotation=List[Annotated[Union[Annotated[Path, PathType], RelativeFilePath, HttpUrl, Annotated[Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator, PlainSerializer]], required=False, default_factory=list), 'test_inputs': FieldInfo(annotation=List[Annotated[Union[Annotated[Path, PathType], RelativeFilePath, HttpUrl, Annotated[Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator, PlainSerializer, WithSuffix]], required=True, metadata=[MinLen(min_length=1)]), 'test_outputs': FieldInfo(annotation=List[Annotated[Union[Annotated[Path, PathType], RelativeFilePath, HttpUrl, Annotated[Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator, PlainSerializer, WithSuffix]], required=True, metadata=[MinLen(min_length=1)]), 'timestamp': FieldInfo(annotation=Datetime, required=True), 'training_data': FieldInfo(annotation=Union[LinkedDataset, DatasetDescr, NoneType], required=False), 'weights': FieldInfo(annotation=WeightsDescr, required=True)}"}, "bioimageio.spec.model.v0_4.ModelDescr.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_4.ModelDescr.model_computed_fields", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ModelDescr.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_5": {"fullname": "bioimageio.spec.model.v0_5", "modulename": "bioimageio.spec.model.v0_5", "kind": "module", "doc": "
    \n"}, "bioimageio.spec.model.v0_5.SpaceUnit": {"fullname": "bioimageio.spec.model.v0_5.SpaceUnit", "modulename": "bioimageio.spec.model.v0_5", "qualname": "SpaceUnit", "kind": "variable", "doc": "
    \n", "default_value": "typing.Literal['attometer', 'angstrom', 'centimeter', 'decimeter', 'exameter', 'femtometer', 'foot', 'gigameter', 'hectometer', 'inch', 'kilometer', 'megameter', 'meter', 'micrometer', 'mile', 'millimeter', 'nanometer', 'parsec', 'petameter', 'picometer', 'terameter', 'yard', 'yoctometer', 'yottameter', 'zeptometer', 'zettameter']"}, "bioimageio.spec.model.v0_5.TimeUnit": {"fullname": "bioimageio.spec.model.v0_5.TimeUnit", "modulename": "bioimageio.spec.model.v0_5", "qualname": "TimeUnit", "kind": "variable", "doc": "
    \n", "default_value": "typing.Literal['attosecond', 'centisecond', 'day', 'decisecond', 'exasecond', 'femtosecond', 'gigasecond', 'hectosecond', 'hour', 'kilosecond', 'megasecond', 'microsecond', 'millisecond', 'minute', 'nanosecond', 'petasecond', 'picosecond', 'second', 'terasecond', 'yoctosecond', 'yottasecond', 'zeptosecond', 'zettasecond']"}, "bioimageio.spec.model.v0_5.AxisType": {"fullname": "bioimageio.spec.model.v0_5.AxisType", "modulename": "bioimageio.spec.model.v0_5", "qualname": "AxisType", "kind": "variable", "doc": "
    \n", "default_value": "typing.Literal['batch', 'channel', 'index', 'time', 'space']"}, "bioimageio.spec.model.v0_5.TensorId": {"fullname": "bioimageio.spec.model.v0_5.TensorId", "modulename": "bioimageio.spec.model.v0_5", "qualname": "TensorId", "kind": "variable", "doc": "
    \n", "default_value": "<class 'bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]'>"}, "bioimageio.spec.model.v0_5.AxisId": {"fullname": "bioimageio.spec.model.v0_5.AxisId", "modulename": "bioimageio.spec.model.v0_5", "qualname": "AxisId", "kind": "variable", "doc": "
    \n", "default_value": "<class 'bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]'>"}, "bioimageio.spec.model.v0_5.NonBatchAxisId": {"fullname": "bioimageio.spec.model.v0_5.NonBatchAxisId", "modulename": "bioimageio.spec.model.v0_5", "qualname": "NonBatchAxisId", "kind": "variable", "doc": "
    \n", "default_value": "typing.Annotated[bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]], Predicate(func=<function <lambda>>)]"}, "bioimageio.spec.model.v0_5.PostprocessingId": {"fullname": "bioimageio.spec.model.v0_5.PostprocessingId", "modulename": "bioimageio.spec.model.v0_5", "qualname": "PostprocessingId", "kind": "variable", "doc": "
    \n", "default_value": "typing.Literal['binarize', 'clip', 'ensure_dtype', 'fixed_zero_mean_unit_variance', 'scale_linear', 'scale_mean_variance', 'scale_range', 'sigmoid', 'zero_mean_unit_variance']"}, "bioimageio.spec.model.v0_5.PreprocessingId": {"fullname": "bioimageio.spec.model.v0_5.PreprocessingId", "modulename": "bioimageio.spec.model.v0_5", "qualname": "PreprocessingId", "kind": "variable", "doc": "
    \n", "default_value": "typing.Literal['binarize', 'clip', 'ensure_dtype', 'scale_linear', 'sigmoid', 'zero_mean_unit_variance', 'scale_range']"}, "bioimageio.spec.model.v0_5.SAME_AS_TYPE": {"fullname": "bioimageio.spec.model.v0_5.SAME_AS_TYPE", "modulename": "bioimageio.spec.model.v0_5", "qualname": "SAME_AS_TYPE", "kind": "variable", "doc": "
    \n", "default_value": "'<same as type>'"}, "bioimageio.spec.model.v0_5.ParameterizedSize": {"fullname": "bioimageio.spec.model.v0_5.ParameterizedSize", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ParameterizedSize", "kind": "class", "doc": "
    Describes a range of valid tensor axis sizes as size = min + n*step.\nn in this equation is the same for all axis parameterized in this manner across the whole model.
    \n", "bases": "bioimageio.spec._internal.node.Node"}, "bioimageio.spec.model.v0_5.ParameterizedSize.N": {"fullname": "bioimageio.spec.model.v0_5.ParameterizedSize.N", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ParameterizedSize.N", "kind": "variable", "doc": "
    integer to parameterize all axes with a ParameterizedSize
    \n", "annotation": ": ClassVar[Type[int]]", "default_value": "<class 'int'>"}, "bioimageio.spec.model.v0_5.ParameterizedSize.min": {"fullname": "bioimageio.spec.model.v0_5.ParameterizedSize.min", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ParameterizedSize.min", "kind": "variable", "doc": "
    \n", "annotation": ": Annotated[int, Gt(gt=0)]"}, "bioimageio.spec.model.v0_5.ParameterizedSize.step": {"fullname": "bioimageio.spec.model.v0_5.ParameterizedSize.step", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ParameterizedSize.step", "kind": "variable", "doc": "
    \n", "annotation": ": Annotated[int, Gt(gt=0)]"}, "bioimageio.spec.model.v0_5.ParameterizedSize.validate_size": {"fullname": "bioimageio.spec.model.v0_5.ParameterizedSize.validate_size", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ParameterizedSize.validate_size", "kind": "function", "doc": "
    \n", "signature": "(self, size: int) -> int:", "funcdef": "def"}, "bioimageio.spec.model.v0_5.ParameterizedSize.get_size": {"fullname": "bioimageio.spec.model.v0_5.ParameterizedSize.get_size", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ParameterizedSize.get_size", "kind": "function", "doc": "
    \n", "signature": "(self, n: int) -> int:", "funcdef": "def"}, "bioimageio.spec.model.v0_5.ParameterizedSize.model_config": {"fullname": "bioimageio.spec.model.v0_5.ParameterizedSize.model_config", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ParameterizedSize.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_5.ParameterizedSize.model_fields": {"fullname": "bioimageio.spec.model.v0_5.ParameterizedSize.model_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ParameterizedSize.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'min': FieldInfo(annotation=int, required=True, metadata=[Gt(gt=0)]), 'step': FieldInfo(annotation=int, required=True, metadata=[Gt(gt=0)])}"}, "bioimageio.spec.model.v0_5.ParameterizedSize.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_5.ParameterizedSize.model_computed_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ParameterizedSize.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_5.SizeReference": {"fullname": "bioimageio.spec.model.v0_5.SizeReference", "modulename": "bioimageio.spec.model.v0_5", "qualname": "SizeReference", "kind": "class", "doc": "
    A tensor axis size (extent in pixels/frames) defined in relation to a reference axis.
    \n\n
    axis.size = reference.size * reference.scale / axis.scale + offset
    \n\n
    note:
    \n\n
      \n
    1. The axis and the referenced axis need to have the same unit (or no unit).
      2. \n
    2. Batch axes may not be referenced.
      3. \n
    3. Fractions are rounded down.
      4. \n
    \n\n
    example:\nAn unisotropic input image of wh=10049 pixels depicts a phsical space of 200196mm\u00b2.\nLet's assume that we want to express the image height h in relation to its width w\ninstead of only accepting input images of exactly 10049 pixels\n(for example to express a range of valid image shapes by parametrizing w, see ParameterizedSize).
    \n\n
    \n
    >>> w = SpaceInputAxis(id=AxisId("w"), size=100, unit="millimeter", scale=2)\n>>> h = SpaceInputAxis(\n...     id=AxisId("h"),\n...     size=SizeReference(tensor_id=TensorId("input"), axis_id=AxisId("w"), offset=-1),\n...     unit="millimeter",\n...     scale=4,\n... )\n>>> print(h.size.compute(h, w))\n49\n
    \n
    \n\n
    -> h = w * w.scale / h.scale + offset = 100 * 2mm / 4mm - 1 = 49
    \n", "bases": "bioimageio.spec._internal.node.Node"}, "bioimageio.spec.model.v0_5.SizeReference.tensor_id": {"fullname": "bioimageio.spec.model.v0_5.SizeReference.tensor_id", "modulename": "bioimageio.spec.model.v0_5", "qualname": "SizeReference.tensor_id", "kind": "variable", "doc": "
    tensor id of the reference axis
    \n", "annotation": ": bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]"}, "bioimageio.spec.model.v0_5.SizeReference.axis_id": {"fullname": "bioimageio.spec.model.v0_5.SizeReference.axis_id", "modulename": "bioimageio.spec.model.v0_5", "qualname": "SizeReference.axis_id", "kind": "variable", "doc": "
    axis id of the reference axis
    \n", "annotation": ": bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]"}, "bioimageio.spec.model.v0_5.SizeReference.offset": {"fullname": "bioimageio.spec.model.v0_5.SizeReference.offset", "modulename": "bioimageio.spec.model.v0_5", "qualname": "SizeReference.offset", "kind": "variable", "doc": "
    \n", "annotation": ": int"}, "bioimageio.spec.model.v0_5.SizeReference.get_size": {"fullname": "bioimageio.spec.model.v0_5.SizeReference.get_size", "modulename": "bioimageio.spec.model.v0_5", "qualname": "SizeReference.get_size", "kind": "function", "doc": "
    helper method to compute concrete size for a given axis and its reference axis.\nIf the reference axis is parameterized, n is used to compute the concrete size of it, see ParameterizedSize.
    \n", "signature": "(\tself,\taxis: Union[bioimageio.spec.model.v0_5.ChannelAxis, bioimageio.spec.model.v0_5.IndexAxis, bioimageio.spec.model.v0_5.TimeInputAxis, bioimageio.spec.model.v0_5.SpaceInputAxis, bioimageio.spec.model.v0_5.TimeOutputAxis, bioimageio.spec.model.v0_5.SpaceOutputAxis],\tref_axis: Union[bioimageio.spec.model.v0_5.ChannelAxis, bioimageio.spec.model.v0_5.IndexAxis, bioimageio.spec.model.v0_5.TimeInputAxis, bioimageio.spec.model.v0_5.SpaceInputAxis, bioimageio.spec.model.v0_5.TimeOutputAxis, bioimageio.spec.model.v0_5.SpaceOutputAxis],\tn: int):", "funcdef": "def"}, "bioimageio.spec.model.v0_5.SizeReference.model_config": {"fullname": "bioimageio.spec.model.v0_5.SizeReference.model_config", "modulename": "bioimageio.spec.model.v0_5", "qualname": "SizeReference.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_5.SizeReference.model_fields": {"fullname": "bioimageio.spec.model.v0_5.SizeReference.model_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "SizeReference.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'tensor_id': FieldInfo(annotation=ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]], required=True), 'axis_id': FieldInfo(annotation=ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]], required=True), 'offset': FieldInfo(annotation=int, required=False, default=0)}"}, "bioimageio.spec.model.v0_5.SizeReference.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_5.SizeReference.model_computed_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "SizeReference.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_5.AxisBase": {"fullname": "bioimageio.spec.model.v0_5.AxisBase", "modulename": "bioimageio.spec.model.v0_5", "qualname": "AxisBase", "kind": "class", "doc": "
    Subpart of a resource description
    \n", "bases": "bioimageio.spec._internal.common_nodes.NodeWithExplicitlySetFields"}, "bioimageio.spec.model.v0_5.AxisBase.fields_to_set_explicitly": {"fullname": "bioimageio.spec.model.v0_5.AxisBase.fields_to_set_explicitly", "modulename": "bioimageio.spec.model.v0_5", "qualname": "AxisBase.fields_to_set_explicitly", "kind": "variable", "doc": "
    set set these fields explicitly with their default value if they are not set,\nsuch that they are always included even when dumping with 'exlude_unset'
    \n", "annotation": ": ClassVar[FrozenSet[LiteralString]]", "default_value": "frozenset({'type'})"}, "bioimageio.spec.model.v0_5.AxisBase.id": {"fullname": "bioimageio.spec.model.v0_5.AxisBase.id", "modulename": "bioimageio.spec.model.v0_5", "qualname": "AxisBase.id", "kind": "variable", "doc": "
    An axis id unique across all axes of one tensor.
    \n", "annotation": ": bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]"}, "bioimageio.spec.model.v0_5.AxisBase.description": {"fullname": "bioimageio.spec.model.v0_5.AxisBase.description", "modulename": "bioimageio.spec.model.v0_5", "qualname": "AxisBase.description", "kind": "variable", "doc": "
    \n", "annotation": ": Annotated[str, MaxLen(max_length=128)]"}, "bioimageio.spec.model.v0_5.AxisBase.model_config": {"fullname": "bioimageio.spec.model.v0_5.AxisBase.model_config", "modulename": "bioimageio.spec.model.v0_5", "qualname": "AxisBase.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_5.AxisBase.model_fields": {"fullname": "bioimageio.spec.model.v0_5.AxisBase.model_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "AxisBase.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'id': FieldInfo(annotation=ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]], required=True), 'description': FieldInfo(annotation=str, required=False, default='', metadata=[MaxLen(max_length=128)])}"}, "bioimageio.spec.model.v0_5.AxisBase.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_5.AxisBase.model_computed_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "AxisBase.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_5.WithHalo": {"fullname": "bioimageio.spec.model.v0_5.WithHalo", "modulename": "bioimageio.spec.model.v0_5", "qualname": "WithHalo", "kind": "class", "doc": "
    Subpart of a resource description
    \n", "bases": "bioimageio.spec._internal.node.Node"}, "bioimageio.spec.model.v0_5.WithHalo.halo": {"fullname": "bioimageio.spec.model.v0_5.WithHalo.halo", "modulename": "bioimageio.spec.model.v0_5", "qualname": "WithHalo.halo", "kind": "variable", "doc": "
    The halo should be cropped from the output tensor to avoid boundary effects.\nIt is to be cropped from both sides, i.e. size_after_crop = size - 2 * halo.\nTo document a halo that is already cropped by the model use size.offset instead.
    \n", "annotation": ": Annotated[int, Ge(ge=0)]"}, "bioimageio.spec.model.v0_5.WithHalo.model_config": {"fullname": "bioimageio.spec.model.v0_5.WithHalo.model_config", "modulename": "bioimageio.spec.model.v0_5", "qualname": "WithHalo.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_5.WithHalo.model_fields": {"fullname": "bioimageio.spec.model.v0_5.WithHalo.model_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "WithHalo.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'halo': FieldInfo(annotation=int, required=False, default=0, metadata=[Ge(ge=0)])}"}, "bioimageio.spec.model.v0_5.WithHalo.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_5.WithHalo.model_computed_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "WithHalo.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_5.BatchAxis": {"fullname": "bioimageio.spec.model.v0_5.BatchAxis", "modulename": "bioimageio.spec.model.v0_5", "qualname": "BatchAxis", "kind": "class", "doc": "
    Subpart of a resource description
    \n", "bases": "AxisBase"}, "bioimageio.spec.model.v0_5.BatchAxis.type": {"fullname": "bioimageio.spec.model.v0_5.BatchAxis.type", "modulename": "bioimageio.spec.model.v0_5", "qualname": "BatchAxis.type", "kind": "variable", "doc": "
    \n", "annotation": ": Literal['batch']"}, "bioimageio.spec.model.v0_5.BatchAxis.id": {"fullname": "bioimageio.spec.model.v0_5.BatchAxis.id", "modulename": "bioimageio.spec.model.v0_5", "qualname": "BatchAxis.id", "kind": "variable", "doc": "
    An axis id unique across all axes of one tensor.
    \n", "annotation": ": Annotated[bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]], Predicate(func=<function <lambda> at 0x7f1c1306d4e0>)]"}, "bioimageio.spec.model.v0_5.BatchAxis.size": {"fullname": "bioimageio.spec.model.v0_5.BatchAxis.size", "modulename": "bioimageio.spec.model.v0_5", "qualname": "BatchAxis.size", "kind": "variable", "doc": "
    The batch size may be fixed to 1,\notherwise (the default) it may be chosen arbitrarily depending on available memory
    \n", "annotation": ": Optional[Literal[1]]"}, "bioimageio.spec.model.v0_5.BatchAxis.scale": {"fullname": "bioimageio.spec.model.v0_5.BatchAxis.scale", "modulename": "bioimageio.spec.model.v0_5", "qualname": "BatchAxis.scale", "kind": "variable", "doc": "
    \n"}, "bioimageio.spec.model.v0_5.BatchAxis.unit": {"fullname": "bioimageio.spec.model.v0_5.BatchAxis.unit", "modulename": "bioimageio.spec.model.v0_5", "qualname": "BatchAxis.unit", "kind": "variable", "doc": "
    \n"}, "bioimageio.spec.model.v0_5.BatchAxis.model_config": {"fullname": "bioimageio.spec.model.v0_5.BatchAxis.model_config", "modulename": "bioimageio.spec.model.v0_5", "qualname": "BatchAxis.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_5.BatchAxis.model_fields": {"fullname": "bioimageio.spec.model.v0_5.BatchAxis.model_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "BatchAxis.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'id': FieldInfo(annotation=ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]], required=False, default=ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]](root='batch'), metadata=[Predicate(func=<function <lambda>>)]), 'description': FieldInfo(annotation=str, required=False, default='', metadata=[MaxLen(max_length=128)]), 'type': FieldInfo(annotation=Literal['batch'], required=False, default='batch'), 'size': FieldInfo(annotation=Union[Literal[1], NoneType], required=False)}"}, "bioimageio.spec.model.v0_5.BatchAxis.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_5.BatchAxis.model_computed_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "BatchAxis.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_5.ChannelAxis": {"fullname": "bioimageio.spec.model.v0_5.ChannelAxis", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ChannelAxis", "kind": "class", "doc": "
    Subpart of a resource description
    \n", "bases": "AxisBase"}, "bioimageio.spec.model.v0_5.ChannelAxis.type": {"fullname": "bioimageio.spec.model.v0_5.ChannelAxis.type", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ChannelAxis.type", "kind": "variable", "doc": "
    \n", "annotation": ": Literal['channel']"}, "bioimageio.spec.model.v0_5.ChannelAxis.id": {"fullname": "bioimageio.spec.model.v0_5.ChannelAxis.id", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ChannelAxis.id", "kind": "variable", "doc": "
    An axis id unique across all axes of one tensor.
    \n", "annotation": ": Annotated[bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]], Predicate(func=<function <lambda> at 0x7f1c1523f380>)]"}, "bioimageio.spec.model.v0_5.ChannelAxis.channel_names": {"fullname": "bioimageio.spec.model.v0_5.ChannelAxis.channel_names", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ChannelAxis.channel_names", "kind": "variable", "doc": "
    \n", "annotation": ": List[bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator]]]"}, "bioimageio.spec.model.v0_5.ChannelAxis.size": {"fullname": "bioimageio.spec.model.v0_5.ChannelAxis.size", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ChannelAxis.size", "kind": "variable", "doc": "
    \n", "annotation": ": int"}, "bioimageio.spec.model.v0_5.ChannelAxis.scale": {"fullname": "bioimageio.spec.model.v0_5.ChannelAxis.scale", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ChannelAxis.scale", "kind": "variable", "doc": "
    \n", "annotation": ": float"}, "bioimageio.spec.model.v0_5.ChannelAxis.unit": {"fullname": "bioimageio.spec.model.v0_5.ChannelAxis.unit", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ChannelAxis.unit", "kind": "variable", "doc": "
    \n"}, "bioimageio.spec.model.v0_5.ChannelAxis.model_config": {"fullname": "bioimageio.spec.model.v0_5.ChannelAxis.model_config", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ChannelAxis.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_5.ChannelAxis.model_fields": {"fullname": "bioimageio.spec.model.v0_5.ChannelAxis.model_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ChannelAxis.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'id': FieldInfo(annotation=ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]], required=False, default=ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]](root='channel'), metadata=[Predicate(func=<function <lambda>>)]), 'description': FieldInfo(annotation=str, required=False, default='', metadata=[MaxLen(max_length=128)]), 'type': FieldInfo(annotation=Literal['channel'], required=False, default='channel'), 'channel_names': FieldInfo(annotation=List[ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator]]], required=True)}"}, "bioimageio.spec.model.v0_5.ChannelAxis.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_5.ChannelAxis.model_computed_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ChannelAxis.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_5.IndexTimeSpaceAxisBase": {"fullname": "bioimageio.spec.model.v0_5.IndexTimeSpaceAxisBase", "modulename": "bioimageio.spec.model.v0_5", "qualname": "IndexTimeSpaceAxisBase", "kind": "class", "doc": "
    Subpart of a resource description
    \n", "bases": "AxisBase"}, "bioimageio.spec.model.v0_5.IndexTimeSpaceAxisBase.size": {"fullname": "bioimageio.spec.model.v0_5.IndexTimeSpaceAxisBase.size", "modulename": "bioimageio.spec.model.v0_5", "qualname": "IndexTimeSpaceAxisBase.size", "kind": "variable", "doc": "
    The size/length of an axis can be specified as
    \n\n
      \n
    • fixed integer
      • \n
    • parameterized series of valid sizes (ParameterizedSize)
      • \n
    • reference to another axis with an optional offset (SizeReference)
      • \n
    \n", "annotation": ": Annotated[Union[Annotated[int, Gt(gt=0)], bioimageio.spec.model.v0_5.ParameterizedSize, bioimageio.spec.model.v0_5.SizeReference], FieldInfo(annotation=NoneType, required=True, examples=[10, {'min': 32, 'step': 16}, {'tensor_id': 't', 'axis_id': 'a', 'offset': 5}])]"}, "bioimageio.spec.model.v0_5.IndexTimeSpaceAxisBase.model_config": {"fullname": "bioimageio.spec.model.v0_5.IndexTimeSpaceAxisBase.model_config", "modulename": "bioimageio.spec.model.v0_5", "qualname": "IndexTimeSpaceAxisBase.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_5.IndexTimeSpaceAxisBase.model_fields": {"fullname": "bioimageio.spec.model.v0_5.IndexTimeSpaceAxisBase.model_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "IndexTimeSpaceAxisBase.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'id': FieldInfo(annotation=ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]], required=True), 'description': FieldInfo(annotation=str, required=False, default='', metadata=[MaxLen(max_length=128)]), 'size': FieldInfo(annotation=Union[Annotated[int, Gt], ParameterizedSize, SizeReference], required=True, examples=[10, {'min': 32, 'step': 16}, {'tensor_id': 't', 'axis_id': 'a', 'offset': 5}])}"}, "bioimageio.spec.model.v0_5.IndexTimeSpaceAxisBase.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_5.IndexTimeSpaceAxisBase.model_computed_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "IndexTimeSpaceAxisBase.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_5.IndexAxis": {"fullname": "bioimageio.spec.model.v0_5.IndexAxis", "modulename": "bioimageio.spec.model.v0_5", "qualname": "IndexAxis", "kind": "class", "doc": "
    Subpart of a resource description
    \n", "bases": "IndexTimeSpaceAxisBase"}, "bioimageio.spec.model.v0_5.IndexAxis.type": {"fullname": "bioimageio.spec.model.v0_5.IndexAxis.type", "modulename": "bioimageio.spec.model.v0_5", "qualname": "IndexAxis.type", "kind": "variable", "doc": "
    \n", "annotation": ": Literal['index']"}, "bioimageio.spec.model.v0_5.IndexAxis.id": {"fullname": "bioimageio.spec.model.v0_5.IndexAxis.id", "modulename": "bioimageio.spec.model.v0_5", "qualname": "IndexAxis.id", "kind": "variable", "doc": "
    An axis id unique across all axes of one tensor.
    \n", "annotation": ": Annotated[bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]], Predicate(func=<function <lambda> at 0x7f1c1523f380>)]"}, "bioimageio.spec.model.v0_5.IndexAxis.scale": {"fullname": "bioimageio.spec.model.v0_5.IndexAxis.scale", "modulename": "bioimageio.spec.model.v0_5", "qualname": "IndexAxis.scale", "kind": "variable", "doc": "
    \n", "annotation": ": float"}, "bioimageio.spec.model.v0_5.IndexAxis.unit": {"fullname": "bioimageio.spec.model.v0_5.IndexAxis.unit", "modulename": "bioimageio.spec.model.v0_5", "qualname": "IndexAxis.unit", "kind": "variable", "doc": "
    \n"}, "bioimageio.spec.model.v0_5.IndexAxis.model_config": {"fullname": "bioimageio.spec.model.v0_5.IndexAxis.model_config", "modulename": "bioimageio.spec.model.v0_5", "qualname": "IndexAxis.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_5.IndexAxis.model_fields": {"fullname": "bioimageio.spec.model.v0_5.IndexAxis.model_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "IndexAxis.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'id': FieldInfo(annotation=ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]], required=False, default=ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]](root='index'), metadata=[Predicate(func=<function <lambda>>)]), 'description': FieldInfo(annotation=str, required=False, default='', metadata=[MaxLen(max_length=128)]), 'size': FieldInfo(annotation=Union[Annotated[int, Gt], ParameterizedSize, SizeReference], required=True, examples=[10, {'min': 32, 'step': 16}, {'tensor_id': 't', 'axis_id': 'a', 'offset': 5}]), 'type': FieldInfo(annotation=Literal['index'], required=False, default='index')}"}, "bioimageio.spec.model.v0_5.IndexAxis.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_5.IndexAxis.model_computed_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "IndexAxis.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_5.TimeAxisBase": {"fullname": "bioimageio.spec.model.v0_5.TimeAxisBase", "modulename": "bioimageio.spec.model.v0_5", "qualname": "TimeAxisBase", "kind": "class", "doc": "
    Subpart of a resource description
    \n", "bases": "IndexTimeSpaceAxisBase"}, "bioimageio.spec.model.v0_5.TimeAxisBase.type": {"fullname": "bioimageio.spec.model.v0_5.TimeAxisBase.type", "modulename": "bioimageio.spec.model.v0_5", "qualname": "TimeAxisBase.type", "kind": "variable", "doc": "
    \n", "annotation": ": Literal['time']"}, "bioimageio.spec.model.v0_5.TimeAxisBase.id": {"fullname": "bioimageio.spec.model.v0_5.TimeAxisBase.id", "modulename": "bioimageio.spec.model.v0_5", "qualname": "TimeAxisBase.id", "kind": "variable", "doc": "
    An axis id unique across all axes of one tensor.
    \n", "annotation": ": Annotated[bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]], Predicate(func=<function <lambda> at 0x7f1c1523f380>)]"}, "bioimageio.spec.model.v0_5.TimeAxisBase.unit": {"fullname": "bioimageio.spec.model.v0_5.TimeAxisBase.unit", "modulename": "bioimageio.spec.model.v0_5", "qualname": "TimeAxisBase.unit", "kind": "variable", "doc": "
    \n", "annotation": ": Optional[Literal['attosecond', 'centisecond', 'day', 'decisecond', 'exasecond', 'femtosecond', 'gigasecond', 'hectosecond', 'hour', 'kilosecond', 'megasecond', 'microsecond', 'millisecond', 'minute', 'nanosecond', 'petasecond', 'picosecond', 'second', 'terasecond', 'yoctosecond', 'yottasecond', 'zeptosecond', 'zettasecond']]"}, "bioimageio.spec.model.v0_5.TimeAxisBase.scale": {"fullname": "bioimageio.spec.model.v0_5.TimeAxisBase.scale", "modulename": "bioimageio.spec.model.v0_5", "qualname": "TimeAxisBase.scale", "kind": "variable", "doc": "
    \n", "annotation": ": Annotated[float, Gt(gt=0)]"}, "bioimageio.spec.model.v0_5.TimeAxisBase.model_config": {"fullname": "bioimageio.spec.model.v0_5.TimeAxisBase.model_config", "modulename": "bioimageio.spec.model.v0_5", "qualname": "TimeAxisBase.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_5.TimeAxisBase.model_fields": {"fullname": "bioimageio.spec.model.v0_5.TimeAxisBase.model_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "TimeAxisBase.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'id': FieldInfo(annotation=ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]], required=False, default=ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]](root='time'), metadata=[Predicate(func=<function <lambda>>)]), 'description': FieldInfo(annotation=str, required=False, default='', metadata=[MaxLen(max_length=128)]), 'size': FieldInfo(annotation=Union[Annotated[int, Gt], ParameterizedSize, SizeReference], required=True, examples=[10, {'min': 32, 'step': 16}, {'tensor_id': 't', 'axis_id': 'a', 'offset': 5}]), 'type': FieldInfo(annotation=Literal['time'], required=False, default='time'), 'unit': FieldInfo(annotation=Union[Literal['attosecond', 'centisecond', 'day', 'decisecond', 'exasecond', 'femtosecond', 'gigasecond', 'hectosecond', 'hour', 'kilosecond', 'megasecond', 'microsecond', 'millisecond', 'minute', 'nanosecond', 'petasecond', 'picosecond', 'second', 'terasecond', 'yoctosecond', 'yottasecond', 'zeptosecond', 'zettasecond'], NoneType], required=False), 'scale': FieldInfo(annotation=float, required=False, default=1.0, metadata=[Gt(gt=0)])}"}, "bioimageio.spec.model.v0_5.TimeAxisBase.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_5.TimeAxisBase.model_computed_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "TimeAxisBase.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_5.TimeInputAxis": {"fullname": "bioimageio.spec.model.v0_5.TimeInputAxis", "modulename": "bioimageio.spec.model.v0_5", "qualname": "TimeInputAxis", "kind": "class", "doc": "
    Subpart of a resource description
    \n", "bases": "TimeAxisBase"}, "bioimageio.spec.model.v0_5.TimeInputAxis.model_config": {"fullname": "bioimageio.spec.model.v0_5.TimeInputAxis.model_config", "modulename": "bioimageio.spec.model.v0_5", "qualname": "TimeInputAxis.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_5.TimeInputAxis.model_fields": {"fullname": "bioimageio.spec.model.v0_5.TimeInputAxis.model_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "TimeInputAxis.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'id': FieldInfo(annotation=ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]], required=False, default=ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]](root='time'), metadata=[Predicate(func=<function <lambda>>)]), 'description': FieldInfo(annotation=str, required=False, default='', metadata=[MaxLen(max_length=128)]), 'size': FieldInfo(annotation=Union[Annotated[int, Gt], ParameterizedSize, SizeReference], required=True, examples=[10, {'min': 32, 'step': 16}, {'tensor_id': 't', 'axis_id': 'a', 'offset': 5}]), 'type': FieldInfo(annotation=Literal['time'], required=False, default='time'), 'unit': FieldInfo(annotation=Union[Literal['attosecond', 'centisecond', 'day', 'decisecond', 'exasecond', 'femtosecond', 'gigasecond', 'hectosecond', 'hour', 'kilosecond', 'megasecond', 'microsecond', 'millisecond', 'minute', 'nanosecond', 'petasecond', 'picosecond', 'second', 'terasecond', 'yoctosecond', 'yottasecond', 'zeptosecond', 'zettasecond'], NoneType], required=False), 'scale': FieldInfo(annotation=float, required=False, default=1.0, metadata=[Gt(gt=0)])}"}, "bioimageio.spec.model.v0_5.TimeInputAxis.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_5.TimeInputAxis.model_computed_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "TimeInputAxis.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_5.SpaceAxisBase": {"fullname": "bioimageio.spec.model.v0_5.SpaceAxisBase", "modulename": "bioimageio.spec.model.v0_5", "qualname": "SpaceAxisBase", "kind": "class", "doc": "
    Subpart of a resource description
    \n", "bases": "IndexTimeSpaceAxisBase"}, "bioimageio.spec.model.v0_5.SpaceAxisBase.type": {"fullname": "bioimageio.spec.model.v0_5.SpaceAxisBase.type", "modulename": "bioimageio.spec.model.v0_5", "qualname": "SpaceAxisBase.type", "kind": "variable", "doc": "
    \n", "annotation": ": Literal['space']"}, "bioimageio.spec.model.v0_5.SpaceAxisBase.id": {"fullname": "bioimageio.spec.model.v0_5.SpaceAxisBase.id", "modulename": "bioimageio.spec.model.v0_5", "qualname": "SpaceAxisBase.id", "kind": "variable", "doc": "
    An axis id unique across all axes of one tensor.
    \n", "annotation": ": Annotated[bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]], Predicate(func=<function <lambda> at 0x7f1c1523f380>), FieldInfo(annotation=NoneType, required=True, examples=['x', 'y', 'z'])]"}, "bioimageio.spec.model.v0_5.SpaceAxisBase.unit": {"fullname": "bioimageio.spec.model.v0_5.SpaceAxisBase.unit", "modulename": "bioimageio.spec.model.v0_5", "qualname": "SpaceAxisBase.unit", "kind": "variable", "doc": "
    \n", "annotation": ": Optional[Literal['attometer', 'angstrom', 'centimeter', 'decimeter', 'exameter', 'femtometer', 'foot', 'gigameter', 'hectometer', 'inch', 'kilometer', 'megameter', 'meter', 'micrometer', 'mile', 'millimeter', 'nanometer', 'parsec', 'petameter', 'picometer', 'terameter', 'yard', 'yoctometer', 'yottameter', 'zeptometer', 'zettameter']]"}, "bioimageio.spec.model.v0_5.SpaceAxisBase.scale": {"fullname": "bioimageio.spec.model.v0_5.SpaceAxisBase.scale", "modulename": "bioimageio.spec.model.v0_5", "qualname": "SpaceAxisBase.scale", "kind": "variable", "doc": "
    \n", "annotation": ": Annotated[float, Gt(gt=0)]"}, "bioimageio.spec.model.v0_5.SpaceAxisBase.model_config": {"fullname": "bioimageio.spec.model.v0_5.SpaceAxisBase.model_config", "modulename": "bioimageio.spec.model.v0_5", "qualname": "SpaceAxisBase.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_5.SpaceAxisBase.model_fields": {"fullname": "bioimageio.spec.model.v0_5.SpaceAxisBase.model_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "SpaceAxisBase.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'id': FieldInfo(annotation=ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]], required=False, default=ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]](root='x'), examples=['x', 'y', 'z'], metadata=[Predicate(func=<function <lambda>>)]), 'description': FieldInfo(annotation=str, required=False, default='', metadata=[MaxLen(max_length=128)]), 'size': FieldInfo(annotation=Union[Annotated[int, Gt], ParameterizedSize, SizeReference], required=True, examples=[10, {'min': 32, 'step': 16}, {'tensor_id': 't', 'axis_id': 'a', 'offset': 5}]), 'type': FieldInfo(annotation=Literal['space'], required=False, default='space'), 'unit': FieldInfo(annotation=Union[Literal['attometer', 'angstrom', 'centimeter', 'decimeter', 'exameter', 'femtometer', 'foot', 'gigameter', 'hectometer', 'inch', 'kilometer', 'megameter', 'meter', 'micrometer', 'mile', 'millimeter', 'nanometer', 'parsec', 'petameter', 'picometer', 'terameter', 'yard', 'yoctometer', 'yottameter', 'zeptometer', 'zettameter'], NoneType], required=False), 'scale': FieldInfo(annotation=float, required=False, default=1.0, metadata=[Gt(gt=0)])}"}, "bioimageio.spec.model.v0_5.SpaceAxisBase.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_5.SpaceAxisBase.model_computed_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "SpaceAxisBase.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_5.SpaceInputAxis": {"fullname": "bioimageio.spec.model.v0_5.SpaceInputAxis", "modulename": "bioimageio.spec.model.v0_5", "qualname": "SpaceInputAxis", "kind": "class", "doc": "
    Subpart of a resource description
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    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_5.SpaceInputAxis.model_fields": {"fullname": "bioimageio.spec.model.v0_5.SpaceInputAxis.model_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "SpaceInputAxis.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'id': FieldInfo(annotation=ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]], required=False, default=ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]](root='x'), examples=['x', 'y', 'z'], metadata=[Predicate(func=<function <lambda>>)]), 'description': FieldInfo(annotation=str, required=False, default='', metadata=[MaxLen(max_length=128)]), 'size': FieldInfo(annotation=Union[Annotated[int, Gt], ParameterizedSize, SizeReference], required=True, examples=[10, {'min': 32, 'step': 16}, {'tensor_id': 't', 'axis_id': 'a', 'offset': 5}]), 'type': FieldInfo(annotation=Literal['space'], required=False, default='space'), 'unit': FieldInfo(annotation=Union[Literal['attometer', 'angstrom', 'centimeter', 'decimeter', 'exameter', 'femtometer', 'foot', 'gigameter', 'hectometer', 'inch', 'kilometer', 'megameter', 'meter', 'micrometer', 'mile', 'millimeter', 'nanometer', 'parsec', 'petameter', 'picometer', 'terameter', 'yard', 'yoctometer', 'yottameter', 'zeptometer', 'zettameter'], NoneType], required=False), 'scale': FieldInfo(annotation=float, required=False, default=1.0, metadata=[Gt(gt=0)])}"}, "bioimageio.spec.model.v0_5.SpaceInputAxis.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_5.SpaceInputAxis.model_computed_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "SpaceInputAxis.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_5.InputAxis": {"fullname": "bioimageio.spec.model.v0_5.InputAxis", "modulename": "bioimageio.spec.model.v0_5", "qualname": "InputAxis", "kind": "variable", "doc": "
    \n", "default_value": "typing.Annotated[typing.Union[bioimageio.spec.model.v0_5.BatchAxis, bioimageio.spec.model.v0_5.ChannelAxis, bioimageio.spec.model.v0_5.IndexAxis, bioimageio.spec.model.v0_5.TimeInputAxis, bioimageio.spec.model.v0_5.SpaceInputAxis], FieldInfo(annotation=NoneType, required=True, discriminator='type')]"}, "bioimageio.spec.model.v0_5.TimeOutputAxis": {"fullname": "bioimageio.spec.model.v0_5.TimeOutputAxis", "modulename": "bioimageio.spec.model.v0_5", "qualname": "TimeOutputAxis", "kind": "class", "doc": "
    Subpart of a resource description
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    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_5.TimeOutputAxis.model_fields": {"fullname": "bioimageio.spec.model.v0_5.TimeOutputAxis.model_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "TimeOutputAxis.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'halo': FieldInfo(annotation=int, required=False, default=0, metadata=[Ge(ge=0)]), 'id': FieldInfo(annotation=ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]], required=False, default=ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]](root='time'), metadata=[Predicate(func=<function <lambda>>)]), 'description': FieldInfo(annotation=str, required=False, default='', metadata=[MaxLen(max_length=128)]), 'size': FieldInfo(annotation=Union[Annotated[int, Gt], ParameterizedSize, SizeReference], required=True, examples=[10, {'min': 32, 'step': 16}, {'tensor_id': 't', 'axis_id': 'a', 'offset': 5}]), 'type': FieldInfo(annotation=Literal['time'], required=False, default='time'), 'unit': FieldInfo(annotation=Union[Literal['attosecond', 'centisecond', 'day', 'decisecond', 'exasecond', 'femtosecond', 'gigasecond', 'hectosecond', 'hour', 'kilosecond', 'megasecond', 'microsecond', 'millisecond', 'minute', 'nanosecond', 'petasecond', 'picosecond', 'second', 'terasecond', 'yoctosecond', 'yottasecond', 'zeptosecond', 'zettasecond'], NoneType], required=False), 'scale': FieldInfo(annotation=float, required=False, default=1.0, metadata=[Gt(gt=0)])}"}, "bioimageio.spec.model.v0_5.TimeOutputAxis.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_5.TimeOutputAxis.model_computed_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "TimeOutputAxis.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_5.SpaceOutputAxis": {"fullname": "bioimageio.spec.model.v0_5.SpaceOutputAxis", "modulename": "bioimageio.spec.model.v0_5", "qualname": "SpaceOutputAxis", "kind": "class", "doc": "
    Subpart of a resource description
    \n", "bases": "SpaceAxisBase, WithHalo"}, "bioimageio.spec.model.v0_5.SpaceOutputAxis.model_config": {"fullname": "bioimageio.spec.model.v0_5.SpaceOutputAxis.model_config", "modulename": "bioimageio.spec.model.v0_5", "qualname": "SpaceOutputAxis.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_5.SpaceOutputAxis.model_fields": {"fullname": "bioimageio.spec.model.v0_5.SpaceOutputAxis.model_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "SpaceOutputAxis.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'halo': FieldInfo(annotation=int, required=False, default=0, metadata=[Ge(ge=0)]), 'id': FieldInfo(annotation=ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]], required=False, default=ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]](root='x'), examples=['x', 'y', 'z'], metadata=[Predicate(func=<function <lambda>>)]), 'description': FieldInfo(annotation=str, required=False, default='', metadata=[MaxLen(max_length=128)]), 'size': FieldInfo(annotation=Union[Annotated[int, Gt], ParameterizedSize, SizeReference], required=True, examples=[10, {'min': 32, 'step': 16}, {'tensor_id': 't', 'axis_id': 'a', 'offset': 5}]), 'type': FieldInfo(annotation=Literal['space'], required=False, default='space'), 'unit': FieldInfo(annotation=Union[Literal['attometer', 'angstrom', 'centimeter', 'decimeter', 'exameter', 'femtometer', 'foot', 'gigameter', 'hectometer', 'inch', 'kilometer', 'megameter', 'meter', 'micrometer', 'mile', 'millimeter', 'nanometer', 'parsec', 'petameter', 'picometer', 'terameter', 'yard', 'yoctometer', 'yottameter', 'zeptometer', 'zettameter'], NoneType], required=False), 'scale': FieldInfo(annotation=float, required=False, default=1.0, metadata=[Gt(gt=0)])}"}, "bioimageio.spec.model.v0_5.SpaceOutputAxis.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_5.SpaceOutputAxis.model_computed_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "SpaceOutputAxis.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_5.OutputAxis": {"fullname": "bioimageio.spec.model.v0_5.OutputAxis", "modulename": "bioimageio.spec.model.v0_5", "qualname": "OutputAxis", "kind": "variable", "doc": "
    \n", "default_value": "typing.Annotated[typing.Union[bioimageio.spec.model.v0_5.BatchAxis, bioimageio.spec.model.v0_5.ChannelAxis, bioimageio.spec.model.v0_5.IndexAxis, bioimageio.spec.model.v0_5.TimeOutputAxis, bioimageio.spec.model.v0_5.SpaceOutputAxis], FieldInfo(annotation=NoneType, required=True, discriminator='type')]"}, "bioimageio.spec.model.v0_5.AnyAxis": {"fullname": "bioimageio.spec.model.v0_5.AnyAxis", "modulename": "bioimageio.spec.model.v0_5", "qualname": "AnyAxis", "kind": "variable", "doc": "
    \n", "default_value": "typing.Union[typing.Annotated[typing.Union[bioimageio.spec.model.v0_5.BatchAxis, bioimageio.spec.model.v0_5.ChannelAxis, bioimageio.spec.model.v0_5.IndexAxis, bioimageio.spec.model.v0_5.TimeInputAxis, bioimageio.spec.model.v0_5.SpaceInputAxis], FieldInfo(annotation=NoneType, required=True, discriminator='type')], typing.Annotated[typing.Union[bioimageio.spec.model.v0_5.BatchAxis, bioimageio.spec.model.v0_5.ChannelAxis, bioimageio.spec.model.v0_5.IndexAxis, bioimageio.spec.model.v0_5.TimeOutputAxis, bioimageio.spec.model.v0_5.SpaceOutputAxis], FieldInfo(annotation=NoneType, required=True, discriminator='type')]]"}, "bioimageio.spec.model.v0_5.TVs": {"fullname": "bioimageio.spec.model.v0_5.TVs", "modulename": "bioimageio.spec.model.v0_5", "qualname": "TVs", "kind": "variable", "doc": "
    \n", "default_value": "typing.Union[typing.Annotated[typing.List[int], MinLen(min_length=1)], typing.Annotated[typing.List[float], MinLen(min_length=1)], typing.Annotated[typing.List[bool], MinLen(min_length=1)], typing.Annotated[typing.List[str], MinLen(min_length=1)]]"}, "bioimageio.spec.model.v0_5.NominalOrOrdinalDType": {"fullname": "bioimageio.spec.model.v0_5.NominalOrOrdinalDType", "modulename": "bioimageio.spec.model.v0_5", "qualname": "NominalOrOrdinalDType", "kind": "variable", "doc": "
    \n", "default_value": "typing.Literal['float32', 'float64', 'uint8', 'int8', 'uint16', 'int16', 'uint32', 'int32', 'uint64', 'int64', 'bool']"}, "bioimageio.spec.model.v0_5.NominalOrOrdinalDataDescr": {"fullname": "bioimageio.spec.model.v0_5.NominalOrOrdinalDataDescr", "modulename": "bioimageio.spec.model.v0_5", "qualname": "NominalOrOrdinalDataDescr", "kind": "class", "doc": "
    Subpart of a resource description
    \n", "bases": "bioimageio.spec._internal.node.Node"}, "bioimageio.spec.model.v0_5.NominalOrOrdinalDataDescr.values": {"fullname": "bioimageio.spec.model.v0_5.NominalOrOrdinalDataDescr.values", "modulename": "bioimageio.spec.model.v0_5", "qualname": "NominalOrOrdinalDataDescr.values", "kind": "variable", "doc": "
    A fixed set of nominal or an ascending sequence of ordinal values.\nIn this case data_type is required to be an unsigend integer type, e.g. 'uint8'.\nString values are interpreted as labels for tensor values 0, ..., N.\nNote: as YAML 1.2 does not natively support a \"set\" datatype,\nnominal values should be given as a sequence (aka list/array) as well.
    \n", "annotation": ": Union[Annotated[List[int], MinLen(min_length=1)], Annotated[List[float], MinLen(min_length=1)], Annotated[List[bool], MinLen(min_length=1)], Annotated[List[str], MinLen(min_length=1)]]"}, "bioimageio.spec.model.v0_5.NominalOrOrdinalDataDescr.type": {"fullname": "bioimageio.spec.model.v0_5.NominalOrOrdinalDataDescr.type", "modulename": "bioimageio.spec.model.v0_5", "qualname": "NominalOrOrdinalDataDescr.type", "kind": "variable", "doc": "
    \n", "annotation": ": Annotated[Literal['float32', 'float64', 'uint8', 'int8', 'uint16', 'int16', 'uint32', 'int32', 'uint64', 'int64', 'bool'], FieldInfo(annotation=NoneType, required=True, examples=['float32', 'uint8', 'uint16', 'int64', 'bool'])]"}, "bioimageio.spec.model.v0_5.NominalOrOrdinalDataDescr.unit": {"fullname": "bioimageio.spec.model.v0_5.NominalOrOrdinalDataDescr.unit", "modulename": "bioimageio.spec.model.v0_5", "qualname": "NominalOrOrdinalDataDescr.unit", "kind": "variable", "doc": "
    \n", "annotation": ": Union[Literal['arbitrary unit'], bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, StringConstraints, BeforeValidator]], NoneType]"}, "bioimageio.spec.model.v0_5.NominalOrOrdinalDataDescr.range": {"fullname": "bioimageio.spec.model.v0_5.NominalOrOrdinalDataDescr.range", "modulename": "bioimageio.spec.model.v0_5", "qualname": "NominalOrOrdinalDataDescr.range", "kind": "variable", "doc": "
    \n"}, "bioimageio.spec.model.v0_5.NominalOrOrdinalDataDescr.model_config": {"fullname": "bioimageio.spec.model.v0_5.NominalOrOrdinalDataDescr.model_config", "modulename": "bioimageio.spec.model.v0_5", "qualname": "NominalOrOrdinalDataDescr.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_5.NominalOrOrdinalDataDescr.model_fields": {"fullname": "bioimageio.spec.model.v0_5.NominalOrOrdinalDataDescr.model_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "NominalOrOrdinalDataDescr.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'values': FieldInfo(annotation=Union[Annotated[List[int], MinLen], Annotated[List[float], MinLen], Annotated[List[bool], MinLen], Annotated[List[str], MinLen]], required=True), 'type': FieldInfo(annotation=Literal['float32', 'float64', 'uint8', 'int8', 'uint16', 'int16', 'uint32', 'int32', 'uint64', 'int64', 'bool'], required=False, default='uint8', examples=['float32', 'uint8', 'uint16', 'int64', 'bool']), 'unit': FieldInfo(annotation=Union[Literal['arbitrary unit'], ValidatedString[Annotated[str, StringConstraints, BeforeValidator]], NoneType], required=False)}"}, "bioimageio.spec.model.v0_5.NominalOrOrdinalDataDescr.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_5.NominalOrOrdinalDataDescr.model_computed_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "NominalOrOrdinalDataDescr.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_5.IntervalOrRatioDType": {"fullname": "bioimageio.spec.model.v0_5.IntervalOrRatioDType", "modulename": "bioimageio.spec.model.v0_5", "qualname": "IntervalOrRatioDType", "kind": "variable", "doc": "
    \n", "default_value": "typing.Literal['float32', 'float64', 'uint8', 'int8', 'uint16', 'int16', 'uint32', 'int32', 'uint64', 'int64']"}, "bioimageio.spec.model.v0_5.IntervalOrRatioDataDescr": {"fullname": "bioimageio.spec.model.v0_5.IntervalOrRatioDataDescr", "modulename": "bioimageio.spec.model.v0_5", "qualname": "IntervalOrRatioDataDescr", "kind": "class", "doc": "
    Subpart of a resource description
    \n", "bases": "bioimageio.spec._internal.node.Node"}, "bioimageio.spec.model.v0_5.IntervalOrRatioDataDescr.type": {"fullname": "bioimageio.spec.model.v0_5.IntervalOrRatioDataDescr.type", "modulename": "bioimageio.spec.model.v0_5", "qualname": "IntervalOrRatioDataDescr.type", "kind": "variable", "doc": "
    \n", "annotation": ": Annotated[Literal['float32', 'float64', 'uint8', 'int8', 'uint16', 'int16', 'uint32', 'int32', 'uint64', 'int64'], FieldInfo(annotation=NoneType, required=True, examples=['float32', 'float64', 'uint8', 'uint16'])]"}, "bioimageio.spec.model.v0_5.IntervalOrRatioDataDescr.range": {"fullname": "bioimageio.spec.model.v0_5.IntervalOrRatioDataDescr.range", "modulename": "bioimageio.spec.model.v0_5", "qualname": "IntervalOrRatioDataDescr.range", "kind": "variable", "doc": "
    Tuple (minimum, maximum) specifying the allowed range of the data in this tensor.\nNone corresponds to min/max of what can be expressed by data_type.
    \n", "annotation": ": Tuple[Optional[float], Optional[float]]"}, "bioimageio.spec.model.v0_5.IntervalOrRatioDataDescr.unit": {"fullname": "bioimageio.spec.model.v0_5.IntervalOrRatioDataDescr.unit", "modulename": "bioimageio.spec.model.v0_5", "qualname": "IntervalOrRatioDataDescr.unit", "kind": "variable", "doc": "
    \n", "annotation": ": Union[Literal['arbitrary unit'], bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, StringConstraints, BeforeValidator]]]"}, "bioimageio.spec.model.v0_5.IntervalOrRatioDataDescr.scale": {"fullname": "bioimageio.spec.model.v0_5.IntervalOrRatioDataDescr.scale", "modulename": "bioimageio.spec.model.v0_5", "qualname": "IntervalOrRatioDataDescr.scale", "kind": "variable", "doc": "
    Scale for data on an interval (or ratio) scale.
    \n", "annotation": ": float"}, "bioimageio.spec.model.v0_5.IntervalOrRatioDataDescr.offset": {"fullname": "bioimageio.spec.model.v0_5.IntervalOrRatioDataDescr.offset", "modulename": "bioimageio.spec.model.v0_5", "qualname": "IntervalOrRatioDataDescr.offset", "kind": "variable", "doc": "
    Offset for data on a ratio scale.
    \n", "annotation": ": Optional[float]"}, "bioimageio.spec.model.v0_5.IntervalOrRatioDataDescr.model_config": {"fullname": "bioimageio.spec.model.v0_5.IntervalOrRatioDataDescr.model_config", "modulename": "bioimageio.spec.model.v0_5", "qualname": "IntervalOrRatioDataDescr.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_5.IntervalOrRatioDataDescr.model_fields": {"fullname": "bioimageio.spec.model.v0_5.IntervalOrRatioDataDescr.model_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "IntervalOrRatioDataDescr.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'type': FieldInfo(annotation=Literal['float32', 'float64', 'uint8', 'int8', 'uint16', 'int16', 'uint32', 'int32', 'uint64', 'int64'], required=False, default='float32', examples=['float32', 'float64', 'uint8', 'uint16']), 'range': FieldInfo(annotation=Tuple[Union[float, NoneType], Union[float, NoneType]], required=False, default=(None, None)), 'unit': FieldInfo(annotation=Union[Literal['arbitrary unit'], ValidatedString[Annotated[str, StringConstraints, BeforeValidator]]], required=False, default='arbitrary unit'), 'scale': FieldInfo(annotation=float, required=False, default=1.0), 'offset': FieldInfo(annotation=Union[float, NoneType], required=False)}"}, "bioimageio.spec.model.v0_5.IntervalOrRatioDataDescr.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_5.IntervalOrRatioDataDescr.model_computed_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "IntervalOrRatioDataDescr.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_5.TensorDataDescr": {"fullname": "bioimageio.spec.model.v0_5.TensorDataDescr", "modulename": "bioimageio.spec.model.v0_5", "qualname": "TensorDataDescr", "kind": "variable", "doc": "
    \n", "default_value": "typing.Union[bioimageio.spec.model.v0_5.NominalOrOrdinalDataDescr, bioimageio.spec.model.v0_5.IntervalOrRatioDataDescr]"}, "bioimageio.spec.model.v0_5.ProcessingDescrBase": {"fullname": "bioimageio.spec.model.v0_5.ProcessingDescrBase", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ProcessingDescrBase", "kind": "class", "doc": "
    processing base class
    \n", "bases": "bioimageio.spec._internal.common_nodes.NodeWithExplicitlySetFields, abc.ABC"}, "bioimageio.spec.model.v0_5.ProcessingDescrBase.fields_to_set_explicitly": {"fullname": "bioimageio.spec.model.v0_5.ProcessingDescrBase.fields_to_set_explicitly", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ProcessingDescrBase.fields_to_set_explicitly", "kind": "variable", "doc": "
    set set these fields explicitly with their default value if they are not set,\nsuch that they are always included even when dumping with 'exlude_unset'
    \n", "annotation": ": ClassVar[FrozenSet[LiteralString]]", "default_value": "frozenset({'id'})"}, "bioimageio.spec.model.v0_5.ProcessingDescrBase.model_config": {"fullname": "bioimageio.spec.model.v0_5.ProcessingDescrBase.model_config", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ProcessingDescrBase.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_5.ProcessingDescrBase.model_fields": {"fullname": "bioimageio.spec.model.v0_5.ProcessingDescrBase.model_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ProcessingDescrBase.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_5.ProcessingDescrBase.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_5.ProcessingDescrBase.model_computed_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ProcessingDescrBase.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_5.BinarizeDescr": {"fullname": "bioimageio.spec.model.v0_5.BinarizeDescr", "modulename": "bioimageio.spec.model.v0_5", "qualname": "BinarizeDescr", "kind": "class", "doc": "
    Binarize the tensor with a fixed threshold.\nValues above the threshold will be set to one, values below the threshold to zero.
    \n", "bases": "ProcessingDescrBase"}, "bioimageio.spec.model.v0_5.BinarizeDescr.id": {"fullname": "bioimageio.spec.model.v0_5.BinarizeDescr.id", "modulename": "bioimageio.spec.model.v0_5", "qualname": "BinarizeDescr.id", "kind": "variable", "doc": "
    \n", "annotation": ": Literal['binarize']"}, "bioimageio.spec.model.v0_5.BinarizeDescr.kwargs": {"fullname": "bioimageio.spec.model.v0_5.BinarizeDescr.kwargs", "modulename": "bioimageio.spec.model.v0_5", "qualname": "BinarizeDescr.kwargs", "kind": "variable", "doc": "
    \n", "annotation": ": bioimageio.spec.model.v0_4.BinarizeKwargs"}, "bioimageio.spec.model.v0_5.BinarizeDescr.model_config": {"fullname": "bioimageio.spec.model.v0_5.BinarizeDescr.model_config", "modulename": "bioimageio.spec.model.v0_5", "qualname": "BinarizeDescr.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_5.BinarizeDescr.model_fields": {"fullname": "bioimageio.spec.model.v0_5.BinarizeDescr.model_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "BinarizeDescr.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'id': FieldInfo(annotation=Literal['binarize'], required=False, default='binarize'), 'kwargs': FieldInfo(annotation=BinarizeKwargs, required=True)}"}, "bioimageio.spec.model.v0_5.BinarizeDescr.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_5.BinarizeDescr.model_computed_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "BinarizeDescr.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_5.ClipDescr": {"fullname": "bioimageio.spec.model.v0_5.ClipDescr", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ClipDescr", "kind": "class", "doc": "
    Set tensor values below min to min and above max to max.
    \n", "bases": "ProcessingDescrBase"}, "bioimageio.spec.model.v0_5.ClipDescr.id": {"fullname": "bioimageio.spec.model.v0_5.ClipDescr.id", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ClipDescr.id", "kind": "variable", "doc": "
    \n", "annotation": ": Literal['clip']"}, "bioimageio.spec.model.v0_5.ClipDescr.kwargs": {"fullname": "bioimageio.spec.model.v0_5.ClipDescr.kwargs", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ClipDescr.kwargs", "kind": "variable", "doc": "
    \n", "annotation": ": bioimageio.spec.model.v0_4.ClipKwargs"}, "bioimageio.spec.model.v0_5.ClipDescr.model_config": {"fullname": "bioimageio.spec.model.v0_5.ClipDescr.model_config", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ClipDescr.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_5.ClipDescr.model_fields": {"fullname": "bioimageio.spec.model.v0_5.ClipDescr.model_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ClipDescr.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'id': FieldInfo(annotation=Literal['clip'], required=False, default='clip'), 'kwargs': FieldInfo(annotation=ClipKwargs, required=True)}"}, "bioimageio.spec.model.v0_5.ClipDescr.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_5.ClipDescr.model_computed_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ClipDescr.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_5.EnsureDtypeKwargs": {"fullname": "bioimageio.spec.model.v0_5.EnsureDtypeKwargs", "modulename": "bioimageio.spec.model.v0_5", "qualname": "EnsureDtypeKwargs", "kind": "class", "doc": "
    base class for pre-/postprocessing key word arguments
    \n", "bases": "bioimageio.spec.model.v0_4.ProcessingKwargs"}, "bioimageio.spec.model.v0_5.EnsureDtypeKwargs.dtype": {"fullname": "bioimageio.spec.model.v0_5.EnsureDtypeKwargs.dtype", "modulename": "bioimageio.spec.model.v0_5", "qualname": "EnsureDtypeKwargs.dtype", "kind": "variable", "doc": "
    \n", "annotation": ": str"}, "bioimageio.spec.model.v0_5.EnsureDtypeKwargs.model_config": {"fullname": "bioimageio.spec.model.v0_5.EnsureDtypeKwargs.model_config", "modulename": "bioimageio.spec.model.v0_5", "qualname": "EnsureDtypeKwargs.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_5.EnsureDtypeKwargs.model_fields": {"fullname": "bioimageio.spec.model.v0_5.EnsureDtypeKwargs.model_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "EnsureDtypeKwargs.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'dtype': FieldInfo(annotation=str, required=True)}"}, "bioimageio.spec.model.v0_5.EnsureDtypeKwargs.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_5.EnsureDtypeKwargs.model_computed_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "EnsureDtypeKwargs.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_5.EnsureDtypeDescr": {"fullname": "bioimageio.spec.model.v0_5.EnsureDtypeDescr", "modulename": "bioimageio.spec.model.v0_5", "qualname": "EnsureDtypeDescr", "kind": "class", "doc": "
    processing base class
    \n", "bases": "ProcessingDescrBase"}, "bioimageio.spec.model.v0_5.EnsureDtypeDescr.id": {"fullname": "bioimageio.spec.model.v0_5.EnsureDtypeDescr.id", "modulename": "bioimageio.spec.model.v0_5", "qualname": "EnsureDtypeDescr.id", "kind": "variable", "doc": "
    \n", "annotation": ": Literal['ensure_dtype']"}, "bioimageio.spec.model.v0_5.EnsureDtypeDescr.kwargs": {"fullname": "bioimageio.spec.model.v0_5.EnsureDtypeDescr.kwargs", "modulename": "bioimageio.spec.model.v0_5", "qualname": "EnsureDtypeDescr.kwargs", "kind": "variable", "doc": "
    \n", "annotation": ": bioimageio.spec.model.v0_5.EnsureDtypeKwargs"}, "bioimageio.spec.model.v0_5.EnsureDtypeDescr.model_config": {"fullname": "bioimageio.spec.model.v0_5.EnsureDtypeDescr.model_config", "modulename": "bioimageio.spec.model.v0_5", "qualname": "EnsureDtypeDescr.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_5.EnsureDtypeDescr.model_fields": {"fullname": "bioimageio.spec.model.v0_5.EnsureDtypeDescr.model_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "EnsureDtypeDescr.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'id': FieldInfo(annotation=Literal['ensure_dtype'], required=False, default='ensure_dtype'), 'kwargs': FieldInfo(annotation=EnsureDtypeKwargs, required=True)}"}, "bioimageio.spec.model.v0_5.EnsureDtypeDescr.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_5.EnsureDtypeDescr.model_computed_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "EnsureDtypeDescr.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_5.ScaleLinearKwargs": {"fullname": "bioimageio.spec.model.v0_5.ScaleLinearKwargs", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ScaleLinearKwargs", "kind": "class", "doc": "
    base class for pre-/postprocessing key word arguments
    \n", "bases": "bioimageio.spec.model.v0_4.ProcessingKwargs"}, "bioimageio.spec.model.v0_5.ScaleLinearKwargs.axis": {"fullname": "bioimageio.spec.model.v0_5.ScaleLinearKwargs.axis", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ScaleLinearKwargs.axis", "kind": "variable", "doc": "
    The axis of non-scalar gains/offsets.\nInvalid for scalar gains/offsets.
    \n", "annotation": ": Annotated[Optional[Annotated[bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]], Predicate(func=<function <lambda> at 0x7f1c1523f380>)]], FieldInfo(annotation=NoneType, required=True, examples=['channel'])]"}, "bioimageio.spec.model.v0_5.ScaleLinearKwargs.gain": {"fullname": "bioimageio.spec.model.v0_5.ScaleLinearKwargs.gain", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ScaleLinearKwargs.gain", "kind": "variable", "doc": "
    multiplicative factor
    \n", "annotation": ": Union[float, Annotated[List[float], MinLen(min_length=1)]]"}, "bioimageio.spec.model.v0_5.ScaleLinearKwargs.offset": {"fullname": "bioimageio.spec.model.v0_5.ScaleLinearKwargs.offset", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ScaleLinearKwargs.offset", "kind": "variable", "doc": "
    additive term
    \n", "annotation": ": Union[float, Annotated[List[float], MinLen(min_length=1)]]"}, "bioimageio.spec.model.v0_5.ScaleLinearKwargs.either_gain_or_offset": {"fullname": "bioimageio.spec.model.v0_5.ScaleLinearKwargs.either_gain_or_offset", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ScaleLinearKwargs.either_gain_or_offset", "kind": "function", "doc": "
    \n", "signature": "(self) -> Self:", "funcdef": "def"}, "bioimageio.spec.model.v0_5.ScaleLinearKwargs.model_config": {"fullname": "bioimageio.spec.model.v0_5.ScaleLinearKwargs.model_config", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ScaleLinearKwargs.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_5.ScaleLinearKwargs.model_fields": {"fullname": "bioimageio.spec.model.v0_5.ScaleLinearKwargs.model_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ScaleLinearKwargs.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'axis': FieldInfo(annotation=Union[Annotated[ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]], Predicate], NoneType], required=False, examples=['channel']), 'gain': FieldInfo(annotation=Union[float, Annotated[List[float], MinLen]], required=False, default=1.0), 'offset': FieldInfo(annotation=Union[float, Annotated[List[float], MinLen]], required=False, default=0.0)}"}, "bioimageio.spec.model.v0_5.ScaleLinearKwargs.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_5.ScaleLinearKwargs.model_computed_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ScaleLinearKwargs.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_5.ScaleLinearDescr": {"fullname": "bioimageio.spec.model.v0_5.ScaleLinearDescr", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ScaleLinearDescr", "kind": "class", "doc": "
    Fixed linear scaling.
    \n", "bases": "ProcessingDescrBase"}, "bioimageio.spec.model.v0_5.ScaleLinearDescr.id": {"fullname": "bioimageio.spec.model.v0_5.ScaleLinearDescr.id", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ScaleLinearDescr.id", "kind": "variable", "doc": "
    \n", "annotation": ": Literal['scale_linear']"}, "bioimageio.spec.model.v0_5.ScaleLinearDescr.kwargs": {"fullname": "bioimageio.spec.model.v0_5.ScaleLinearDescr.kwargs", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ScaleLinearDescr.kwargs", "kind": "variable", "doc": "
    \n", "annotation": ": bioimageio.spec.model.v0_5.ScaleLinearKwargs"}, "bioimageio.spec.model.v0_5.ScaleLinearDescr.model_config": {"fullname": "bioimageio.spec.model.v0_5.ScaleLinearDescr.model_config", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ScaleLinearDescr.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_5.ScaleLinearDescr.model_fields": {"fullname": "bioimageio.spec.model.v0_5.ScaleLinearDescr.model_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ScaleLinearDescr.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'id': FieldInfo(annotation=Literal['scale_linear'], required=False, default='scale_linear'), 'kwargs': FieldInfo(annotation=ScaleLinearKwargs, required=True)}"}, "bioimageio.spec.model.v0_5.ScaleLinearDescr.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_5.ScaleLinearDescr.model_computed_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ScaleLinearDescr.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_5.SigmoidDescr": {"fullname": "bioimageio.spec.model.v0_5.SigmoidDescr", "modulename": "bioimageio.spec.model.v0_5", "qualname": "SigmoidDescr", "kind": "class", "doc": "
    The logistic sigmoid funciton, a.k.a. expit function.
    \n", "bases": "ProcessingDescrBase"}, "bioimageio.spec.model.v0_5.SigmoidDescr.id": {"fullname": "bioimageio.spec.model.v0_5.SigmoidDescr.id", "modulename": "bioimageio.spec.model.v0_5", "qualname": "SigmoidDescr.id", "kind": "variable", "doc": "
    \n", "annotation": ": Literal['sigmoid']"}, "bioimageio.spec.model.v0_5.SigmoidDescr.kwargs": {"fullname": "bioimageio.spec.model.v0_5.SigmoidDescr.kwargs", "modulename": "bioimageio.spec.model.v0_5", "qualname": "SigmoidDescr.kwargs", "kind": "variable", "doc": "
    empty kwargs
    \n", "annotation": ": bioimageio.spec.model.v0_4.ProcessingKwargs"}, "bioimageio.spec.model.v0_5.SigmoidDescr.model_config": {"fullname": "bioimageio.spec.model.v0_5.SigmoidDescr.model_config", "modulename": "bioimageio.spec.model.v0_5", "qualname": "SigmoidDescr.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_5.SigmoidDescr.model_fields": {"fullname": "bioimageio.spec.model.v0_5.SigmoidDescr.model_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "SigmoidDescr.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'id': FieldInfo(annotation=Literal['sigmoid'], required=False, default='sigmoid')}"}, "bioimageio.spec.model.v0_5.SigmoidDescr.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_5.SigmoidDescr.model_computed_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "SigmoidDescr.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_5.FixedZeroMeanUnitVarianceKwargs": {"fullname": "bioimageio.spec.model.v0_5.FixedZeroMeanUnitVarianceKwargs", "modulename": "bioimageio.spec.model.v0_5", "qualname": "FixedZeroMeanUnitVarianceKwargs", "kind": "class", "doc": "
    Normalize with fixed, precomputed values for mean and variance.\nSee zero_mean_unit_variance for data dependent normalization.
    \n", "bases": "bioimageio.spec.model.v0_4.ProcessingKwargs"}, "bioimageio.spec.model.v0_5.FixedZeroMeanUnitVarianceKwargs.mean": {"fullname": "bioimageio.spec.model.v0_5.FixedZeroMeanUnitVarianceKwargs.mean", "modulename": "bioimageio.spec.model.v0_5", "qualname": "FixedZeroMeanUnitVarianceKwargs.mean", "kind": "variable", "doc": "
    The mean value(s) to normalize with. Specify axis for a sequence of mean values
    \n", "annotation": ": Annotated[Union[float, Annotated[Tuple[float, ...], MinLen(min_length=1)]], FieldInfo(annotation=NoneType, required=True, examples=[3.14, (1.1, -2.2, 3.3)])]"}, "bioimageio.spec.model.v0_5.FixedZeroMeanUnitVarianceKwargs.std": {"fullname": "bioimageio.spec.model.v0_5.FixedZeroMeanUnitVarianceKwargs.std", "modulename": "bioimageio.spec.model.v0_5", "qualname": "FixedZeroMeanUnitVarianceKwargs.std", "kind": "variable", "doc": "
    The standard deviation value(s) to normalize with. Size must match mean values.
    \n", "annotation": ": Annotated[Union[Annotated[float, Ge(ge=1e-06)], Annotated[Tuple[Annotated[float, Ge(ge=1e-06)], ...], MinLen(min_length=1)]], FieldInfo(annotation=NoneType, required=True, examples=[1.05, (0.1, 0.2, 0.3)])]"}, "bioimageio.spec.model.v0_5.FixedZeroMeanUnitVarianceKwargs.axis": {"fullname": "bioimageio.spec.model.v0_5.FixedZeroMeanUnitVarianceKwargs.axis", "modulename": "bioimageio.spec.model.v0_5", "qualname": "FixedZeroMeanUnitVarianceKwargs.axis", "kind": "variable", "doc": "
    The axis of the mean/std values to normalize each entry along that dimension separately.\nInvalid for scalar gains/offsets.
    \n", "annotation": ": Annotated[Optional[Annotated[bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]], Predicate(func=<function <lambda> at 0x7f1c1523f380>)]], FieldInfo(annotation=NoneType, required=True, examples=['channel', 'index'])]"}, "bioimageio.spec.model.v0_5.FixedZeroMeanUnitVarianceKwargs.mean_and_std_match": {"fullname": "bioimageio.spec.model.v0_5.FixedZeroMeanUnitVarianceKwargs.mean_and_std_match", "modulename": "bioimageio.spec.model.v0_5", "qualname": "FixedZeroMeanUnitVarianceKwargs.mean_and_std_match", "kind": "function", "doc": "
    \n", "signature": "(self) -> Self:", "funcdef": "def"}, "bioimageio.spec.model.v0_5.FixedZeroMeanUnitVarianceKwargs.model_config": {"fullname": "bioimageio.spec.model.v0_5.FixedZeroMeanUnitVarianceKwargs.model_config", "modulename": "bioimageio.spec.model.v0_5", "qualname": "FixedZeroMeanUnitVarianceKwargs.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_5.FixedZeroMeanUnitVarianceKwargs.model_fields": {"fullname": "bioimageio.spec.model.v0_5.FixedZeroMeanUnitVarianceKwargs.model_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "FixedZeroMeanUnitVarianceKwargs.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'mean': FieldInfo(annotation=Union[float, Annotated[Tuple[float, ...], MinLen]], required=True, examples=[3.14, (1.1, -2.2, 3.3)]), 'std': FieldInfo(annotation=Union[Annotated[float, Ge], Annotated[Tuple[Annotated[float, Ge], ...], MinLen]], required=True, examples=[1.05, (0.1, 0.2, 0.3)]), 'axis': FieldInfo(annotation=Union[Annotated[ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]], Predicate], NoneType], required=False, examples=['channel', 'index'])}"}, "bioimageio.spec.model.v0_5.FixedZeroMeanUnitVarianceKwargs.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_5.FixedZeroMeanUnitVarianceKwargs.model_computed_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "FixedZeroMeanUnitVarianceKwargs.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_5.FixedZeroMeanUnitVarianceDescr": {"fullname": "bioimageio.spec.model.v0_5.FixedZeroMeanUnitVarianceDescr", "modulename": "bioimageio.spec.model.v0_5", "qualname": "FixedZeroMeanUnitVarianceDescr", "kind": "class", "doc": "
    Subtract a given mean and divide by a given variance.
    \n", "bases": "ProcessingDescrBase"}, "bioimageio.spec.model.v0_5.FixedZeroMeanUnitVarianceDescr.id": {"fullname": "bioimageio.spec.model.v0_5.FixedZeroMeanUnitVarianceDescr.id", "modulename": "bioimageio.spec.model.v0_5", "qualname": "FixedZeroMeanUnitVarianceDescr.id", "kind": "variable", "doc": "
    \n", "annotation": ": Literal['fixed_zero_mean_unit_variance']"}, "bioimageio.spec.model.v0_5.FixedZeroMeanUnitVarianceDescr.kwargs": {"fullname": "bioimageio.spec.model.v0_5.FixedZeroMeanUnitVarianceDescr.kwargs", "modulename": "bioimageio.spec.model.v0_5", "qualname": "FixedZeroMeanUnitVarianceDescr.kwargs", "kind": "variable", "doc": "
    \n", "annotation": ": bioimageio.spec.model.v0_5.FixedZeroMeanUnitVarianceKwargs"}, "bioimageio.spec.model.v0_5.FixedZeroMeanUnitVarianceDescr.model_config": {"fullname": "bioimageio.spec.model.v0_5.FixedZeroMeanUnitVarianceDescr.model_config", "modulename": "bioimageio.spec.model.v0_5", "qualname": "FixedZeroMeanUnitVarianceDescr.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_5.FixedZeroMeanUnitVarianceDescr.model_fields": {"fullname": "bioimageio.spec.model.v0_5.FixedZeroMeanUnitVarianceDescr.model_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "FixedZeroMeanUnitVarianceDescr.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'id': FieldInfo(annotation=Literal['fixed_zero_mean_unit_variance'], required=False, default='fixed_zero_mean_unit_variance'), 'kwargs': FieldInfo(annotation=FixedZeroMeanUnitVarianceKwargs, required=True)}"}, "bioimageio.spec.model.v0_5.FixedZeroMeanUnitVarianceDescr.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_5.FixedZeroMeanUnitVarianceDescr.model_computed_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "FixedZeroMeanUnitVarianceDescr.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_5.ZeroMeanUnitVarianceKwargs": {"fullname": "bioimageio.spec.model.v0_5.ZeroMeanUnitVarianceKwargs", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ZeroMeanUnitVarianceKwargs", "kind": "class", "doc": "
    base class for pre-/postprocessing key word arguments
    \n", "bases": "bioimageio.spec.model.v0_4.ProcessingKwargs"}, "bioimageio.spec.model.v0_5.ZeroMeanUnitVarianceKwargs.axes": {"fullname": "bioimageio.spec.model.v0_5.ZeroMeanUnitVarianceKwargs.axes", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ZeroMeanUnitVarianceKwargs.axes", "kind": "variable", "doc": "
    The subset of axes to normalize jointly, i.e. axes to reduce to compute mean/std.\nFor example to normalize 'batch', 'x' and 'y' jointly in a tensor ('batch', 'channel', 'y', 'x')\nresulting in a tensor of equal shape normalized per channel, specify axes=('batch', 'x', 'y').\nTo normalize each sample independently leave out the 'batch' axis.\nDefault: Scale all axes jointly.
    \n", "annotation": ": Annotated[Optional[Sequence[bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]]], FieldInfo(annotation=NoneType, required=True, examples=[('batch', 'x', 'y')])]"}, "bioimageio.spec.model.v0_5.ZeroMeanUnitVarianceKwargs.eps": {"fullname": "bioimageio.spec.model.v0_5.ZeroMeanUnitVarianceKwargs.eps", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ZeroMeanUnitVarianceKwargs.eps", "kind": "variable", "doc": "
    epsilon for numeric stability: out = (tensor - mean) / (std + eps).
    \n", "annotation": ": Annotated[float, Interval(gt=0, ge=None, lt=None, le=0.1)]"}, "bioimageio.spec.model.v0_5.ZeroMeanUnitVarianceKwargs.model_config": {"fullname": "bioimageio.spec.model.v0_5.ZeroMeanUnitVarianceKwargs.model_config", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ZeroMeanUnitVarianceKwargs.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_5.ZeroMeanUnitVarianceKwargs.model_fields": {"fullname": "bioimageio.spec.model.v0_5.ZeroMeanUnitVarianceKwargs.model_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ZeroMeanUnitVarianceKwargs.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'axes': FieldInfo(annotation=Union[Sequence[ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]], NoneType], required=False, examples=[('batch', 'x', 'y')]), 'eps': FieldInfo(annotation=float, required=False, default=1e-06, metadata=[Interval(gt=0, ge=None, lt=None, le=0.1)])}"}, "bioimageio.spec.model.v0_5.ZeroMeanUnitVarianceKwargs.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_5.ZeroMeanUnitVarianceKwargs.model_computed_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ZeroMeanUnitVarianceKwargs.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_5.ZeroMeanUnitVarianceDescr": {"fullname": "bioimageio.spec.model.v0_5.ZeroMeanUnitVarianceDescr", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ZeroMeanUnitVarianceDescr", "kind": "class", "doc": "
    Subtract mean and divide by variance.
    \n", "bases": "ProcessingDescrBase"}, "bioimageio.spec.model.v0_5.ZeroMeanUnitVarianceDescr.id": {"fullname": "bioimageio.spec.model.v0_5.ZeroMeanUnitVarianceDescr.id", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ZeroMeanUnitVarianceDescr.id", "kind": "variable", "doc": "
    \n", "annotation": ": Literal['zero_mean_unit_variance']"}, "bioimageio.spec.model.v0_5.ZeroMeanUnitVarianceDescr.kwargs": {"fullname": "bioimageio.spec.model.v0_5.ZeroMeanUnitVarianceDescr.kwargs", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ZeroMeanUnitVarianceDescr.kwargs", "kind": "variable", "doc": "
    \n", "annotation": ": bioimageio.spec.model.v0_5.ZeroMeanUnitVarianceKwargs"}, "bioimageio.spec.model.v0_5.ZeroMeanUnitVarianceDescr.model_config": {"fullname": "bioimageio.spec.model.v0_5.ZeroMeanUnitVarianceDescr.model_config", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ZeroMeanUnitVarianceDescr.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_5.ZeroMeanUnitVarianceDescr.model_fields": {"fullname": "bioimageio.spec.model.v0_5.ZeroMeanUnitVarianceDescr.model_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ZeroMeanUnitVarianceDescr.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'id': FieldInfo(annotation=Literal['zero_mean_unit_variance'], required=False, default='zero_mean_unit_variance'), 'kwargs': FieldInfo(annotation=ZeroMeanUnitVarianceKwargs, required=True)}"}, "bioimageio.spec.model.v0_5.ZeroMeanUnitVarianceDescr.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_5.ZeroMeanUnitVarianceDescr.model_computed_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ZeroMeanUnitVarianceDescr.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_5.ScaleRangeKwargs": {"fullname": "bioimageio.spec.model.v0_5.ScaleRangeKwargs", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ScaleRangeKwargs", "kind": "class", "doc": "
    base class for pre-/postprocessing key word arguments
    \n", "bases": "bioimageio.spec.model.v0_4.ProcessingKwargs"}, "bioimageio.spec.model.v0_5.ScaleRangeKwargs.axes": {"fullname": "bioimageio.spec.model.v0_5.ScaleRangeKwargs.axes", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ScaleRangeKwargs.axes", "kind": "variable", "doc": "
    The subset of axes to normalize jointly, i.e. axes to reduce to compute the min/max percentile value.\nFor example to normalize 'batch', 'x' and 'y' jointly in a tensor ('batch', 'channel', 'y', 'x')\nresulting in a tensor of equal shape normalized per channel, specify axes=('batch', 'x', 'y').\nTo normalize samples indepdencently, leave out the \"batch\" axis.\nDefault: Scale all axes jointly.
    \n", "annotation": ": Annotated[Optional[Sequence[bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]]], FieldInfo(annotation=NoneType, required=True, examples=[('batch', 'x', 'y')])]"}, "bioimageio.spec.model.v0_5.ScaleRangeKwargs.min_percentile": {"fullname": "bioimageio.spec.model.v0_5.ScaleRangeKwargs.min_percentile", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ScaleRangeKwargs.min_percentile", "kind": "variable", "doc": "
    The lower percentile used for normalization.
    \n", "annotation": ": Annotated[float, Interval(gt=None, ge=0, lt=100, le=None)]"}, "bioimageio.spec.model.v0_5.ScaleRangeKwargs.max_percentile": {"fullname": "bioimageio.spec.model.v0_5.ScaleRangeKwargs.max_percentile", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ScaleRangeKwargs.max_percentile", "kind": "variable", "doc": "
    The upper percentile used for normalization\nHas to be bigger than min_percentile.\nThe range is 1 to 100 instead of 0 to 100 to avoid mistakenly\naccepting percentiles specified in the range 0.0 to 1.0.
    \n", "annotation": ": Annotated[float, Interval(gt=1, ge=None, lt=None, le=100)]"}, "bioimageio.spec.model.v0_5.ScaleRangeKwargs.eps": {"fullname": "bioimageio.spec.model.v0_5.ScaleRangeKwargs.eps", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ScaleRangeKwargs.eps", "kind": "variable", "doc": "
    Epsilon for numeric stability.\nout = (tensor - v_lower) / (v_upper - v_lower + eps);\nwith v_lower,v_upper values at the respective percentiles.
    \n", "annotation": ": Annotated[float, Interval(gt=0, ge=None, lt=None, le=0.1)]"}, "bioimageio.spec.model.v0_5.ScaleRangeKwargs.reference_tensor": {"fullname": "bioimageio.spec.model.v0_5.ScaleRangeKwargs.reference_tensor", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ScaleRangeKwargs.reference_tensor", "kind": "variable", "doc": "
    Tensor ID to compute the percentiles from. Default: The tensor itself.\nFor any tensor in inputs only input tensor references are allowed.
    \n", "annotation": ": Optional[bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]]"}, "bioimageio.spec.model.v0_5.ScaleRangeKwargs.min_smaller_max": {"fullname": "bioimageio.spec.model.v0_5.ScaleRangeKwargs.min_smaller_max", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ScaleRangeKwargs.min_smaller_max", "kind": "function", "doc": "
    \n", "signature": "(\tcls,\tvalue: float,\tinfo: pydantic_core.core_schema.ValidationInfo) -> float:", "funcdef": "def"}, "bioimageio.spec.model.v0_5.ScaleRangeKwargs.model_config": {"fullname": "bioimageio.spec.model.v0_5.ScaleRangeKwargs.model_config", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ScaleRangeKwargs.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_5.ScaleRangeKwargs.model_fields": {"fullname": "bioimageio.spec.model.v0_5.ScaleRangeKwargs.model_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ScaleRangeKwargs.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'axes': FieldInfo(annotation=Union[Sequence[ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]], NoneType], required=False, examples=[('batch', 'x', 'y')]), 'min_percentile': FieldInfo(annotation=float, required=False, default=0.0, metadata=[Interval(gt=None, ge=0, lt=100, le=None)]), 'max_percentile': FieldInfo(annotation=float, required=False, default=100.0, metadata=[Interval(gt=1, ge=None, lt=None, le=100)]), 'eps': FieldInfo(annotation=float, required=False, default=1e-06, metadata=[Interval(gt=0, ge=None, lt=None, le=0.1)]), 'reference_tensor': FieldInfo(annotation=Union[ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]], NoneType], required=False)}"}, "bioimageio.spec.model.v0_5.ScaleRangeKwargs.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_5.ScaleRangeKwargs.model_computed_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ScaleRangeKwargs.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_5.ScaleRangeDescr": {"fullname": "bioimageio.spec.model.v0_5.ScaleRangeDescr", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ScaleRangeDescr", "kind": "class", "doc": "
    Scale with percentiles.
    \n", "bases": "ProcessingDescrBase"}, "bioimageio.spec.model.v0_5.ScaleRangeDescr.id": {"fullname": "bioimageio.spec.model.v0_5.ScaleRangeDescr.id", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ScaleRangeDescr.id", "kind": "variable", "doc": "
    \n", "annotation": ": Literal['scale_range']"}, "bioimageio.spec.model.v0_5.ScaleRangeDescr.kwargs": {"fullname": "bioimageio.spec.model.v0_5.ScaleRangeDescr.kwargs", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ScaleRangeDescr.kwargs", "kind": "variable", "doc": "
    \n", "annotation": ": bioimageio.spec.model.v0_5.ScaleRangeKwargs"}, "bioimageio.spec.model.v0_5.ScaleRangeDescr.model_config": {"fullname": "bioimageio.spec.model.v0_5.ScaleRangeDescr.model_config", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ScaleRangeDescr.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_5.ScaleRangeDescr.model_fields": {"fullname": "bioimageio.spec.model.v0_5.ScaleRangeDescr.model_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ScaleRangeDescr.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'id': FieldInfo(annotation=Literal['scale_range'], required=False, default='scale_range'), 'kwargs': FieldInfo(annotation=ScaleRangeKwargs, required=True)}"}, "bioimageio.spec.model.v0_5.ScaleRangeDescr.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_5.ScaleRangeDescr.model_computed_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ScaleRangeDescr.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_5.ScaleMeanVarianceKwargs": {"fullname": "bioimageio.spec.model.v0_5.ScaleMeanVarianceKwargs", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ScaleMeanVarianceKwargs", "kind": "class", "doc": "
    Scale a tensor's data distribution to match another tensor's mean/std.\nout  = (tensor - mean) / (std + eps) * (ref_std + eps) + ref_mean.
    \n", "bases": "bioimageio.spec.model.v0_4.ProcessingKwargs"}, "bioimageio.spec.model.v0_5.ScaleMeanVarianceKwargs.reference_tensor": {"fullname": "bioimageio.spec.model.v0_5.ScaleMeanVarianceKwargs.reference_tensor", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ScaleMeanVarianceKwargs.reference_tensor", "kind": "variable", "doc": "
    Name of tensor to match.
    \n", "annotation": ": bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]"}, "bioimageio.spec.model.v0_5.ScaleMeanVarianceKwargs.axes": {"fullname": "bioimageio.spec.model.v0_5.ScaleMeanVarianceKwargs.axes", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ScaleMeanVarianceKwargs.axes", "kind": "variable", "doc": "
    The subset of axes to normalize jointly, i.e. axes to reduce to compute mean/std.\nFor example to normalize 'batch', 'x' and 'y' jointly in a tensor ('batch', 'channel', 'y', 'x')\nresulting in a tensor of equal shape normalized per channel, specify axes=('batch', 'x', 'y').\nTo normalize samples independently, leave out the 'batch' axis.\nDefault: Scale all axes jointly.
    \n", "annotation": ": Annotated[Optional[Sequence[bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]]], FieldInfo(annotation=NoneType, required=True, examples=[('batch', 'x', 'y')])]"}, "bioimageio.spec.model.v0_5.ScaleMeanVarianceKwargs.eps": {"fullname": "bioimageio.spec.model.v0_5.ScaleMeanVarianceKwargs.eps", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ScaleMeanVarianceKwargs.eps", "kind": "variable", "doc": "
    Epsilon for numeric stability:\nout  = (tensor - mean) / (std + eps) * (ref_std + eps) + ref_mean.
    \n", "annotation": ": Annotated[float, Interval(gt=0, ge=None, lt=None, le=0.1)]"}, "bioimageio.spec.model.v0_5.ScaleMeanVarianceKwargs.model_config": {"fullname": "bioimageio.spec.model.v0_5.ScaleMeanVarianceKwargs.model_config", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ScaleMeanVarianceKwargs.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_5.ScaleMeanVarianceKwargs.model_fields": {"fullname": "bioimageio.spec.model.v0_5.ScaleMeanVarianceKwargs.model_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ScaleMeanVarianceKwargs.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'reference_tensor': FieldInfo(annotation=ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]], required=True), 'axes': FieldInfo(annotation=Union[Sequence[ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]], NoneType], required=False, examples=[('batch', 'x', 'y')]), 'eps': FieldInfo(annotation=float, required=False, default=1e-06, metadata=[Interval(gt=0, ge=None, lt=None, le=0.1)])}"}, "bioimageio.spec.model.v0_5.ScaleMeanVarianceKwargs.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_5.ScaleMeanVarianceKwargs.model_computed_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ScaleMeanVarianceKwargs.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_5.ScaleMeanVarianceDescr": {"fullname": "bioimageio.spec.model.v0_5.ScaleMeanVarianceDescr", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ScaleMeanVarianceDescr", "kind": "class", "doc": "
    Scale the tensor s.t. its mean and variance match a reference tensor.
    \n", "bases": "ProcessingDescrBase"}, "bioimageio.spec.model.v0_5.ScaleMeanVarianceDescr.id": {"fullname": "bioimageio.spec.model.v0_5.ScaleMeanVarianceDescr.id", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ScaleMeanVarianceDescr.id", "kind": "variable", "doc": "
    \n", "annotation": ": Literal['scale_mean_variance']"}, "bioimageio.spec.model.v0_5.ScaleMeanVarianceDescr.kwargs": {"fullname": "bioimageio.spec.model.v0_5.ScaleMeanVarianceDescr.kwargs", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ScaleMeanVarianceDescr.kwargs", "kind": "variable", "doc": "
    \n", "annotation": ": bioimageio.spec.model.v0_5.ScaleMeanVarianceKwargs"}, "bioimageio.spec.model.v0_5.ScaleMeanVarianceDescr.model_config": {"fullname": "bioimageio.spec.model.v0_5.ScaleMeanVarianceDescr.model_config", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ScaleMeanVarianceDescr.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_5.ScaleMeanVarianceDescr.model_fields": {"fullname": "bioimageio.spec.model.v0_5.ScaleMeanVarianceDescr.model_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ScaleMeanVarianceDescr.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'id': FieldInfo(annotation=Literal['scale_mean_variance'], required=False, default='scale_mean_variance'), 'kwargs': FieldInfo(annotation=ScaleMeanVarianceKwargs, required=True)}"}, "bioimageio.spec.model.v0_5.ScaleMeanVarianceDescr.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_5.ScaleMeanVarianceDescr.model_computed_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ScaleMeanVarianceDescr.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_5.PreprocessingDescr": {"fullname": "bioimageio.spec.model.v0_5.PreprocessingDescr", "modulename": "bioimageio.spec.model.v0_5", "qualname": "PreprocessingDescr", "kind": "variable", "doc": "
    \n", "default_value": "typing.Annotated[typing.Union[bioimageio.spec.model.v0_5.BinarizeDescr, bioimageio.spec.model.v0_5.ClipDescr, bioimageio.spec.model.v0_5.EnsureDtypeDescr, bioimageio.spec.model.v0_5.ScaleLinearDescr, bioimageio.spec.model.v0_5.SigmoidDescr, bioimageio.spec.model.v0_5.FixedZeroMeanUnitVarianceDescr, bioimageio.spec.model.v0_5.ZeroMeanUnitVarianceDescr, bioimageio.spec.model.v0_5.ScaleRangeDescr], FieldInfo(annotation=NoneType, required=True, discriminator='id')]"}, "bioimageio.spec.model.v0_5.PostprocessingDescr": {"fullname": "bioimageio.spec.model.v0_5.PostprocessingDescr", "modulename": "bioimageio.spec.model.v0_5", "qualname": "PostprocessingDescr", "kind": "variable", "doc": "
    \n", "default_value": "typing.Annotated[typing.Union[bioimageio.spec.model.v0_5.BinarizeDescr, bioimageio.spec.model.v0_5.ClipDescr, bioimageio.spec.model.v0_5.EnsureDtypeDescr, bioimageio.spec.model.v0_5.ScaleLinearDescr, bioimageio.spec.model.v0_5.SigmoidDescr, bioimageio.spec.model.v0_5.FixedZeroMeanUnitVarianceDescr, bioimageio.spec.model.v0_5.ZeroMeanUnitVarianceDescr, bioimageio.spec.model.v0_5.ScaleRangeDescr, bioimageio.spec.model.v0_5.ScaleMeanVarianceDescr], FieldInfo(annotation=NoneType, required=True, discriminator='id')]"}, "bioimageio.spec.model.v0_5.TensorDescrBase": {"fullname": "bioimageio.spec.model.v0_5.TensorDescrBase", "modulename": "bioimageio.spec.model.v0_5", "qualname": "TensorDescrBase", "kind": "class", "doc": "
    Subpart of a resource description
    \n", "bases": "bioimageio.spec._internal.node.Node, typing.Generic[~IO_AxisT]"}, "bioimageio.spec.model.v0_5.TensorDescrBase.id": {"fullname": "bioimageio.spec.model.v0_5.TensorDescrBase.id", "modulename": "bioimageio.spec.model.v0_5", "qualname": "TensorDescrBase.id", "kind": "variable", "doc": "
    Tensor id. No duplicates are allowed.
    \n", "annotation": ": bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]"}, "bioimageio.spec.model.v0_5.TensorDescrBase.description": {"fullname": "bioimageio.spec.model.v0_5.TensorDescrBase.description", "modulename": "bioimageio.spec.model.v0_5", "qualname": "TensorDescrBase.description", "kind": "variable", "doc": "
    free text description
    \n", "annotation": ": Annotated[str, MaxLen(max_length=128)]"}, "bioimageio.spec.model.v0_5.TensorDescrBase.axes": {"fullname": "bioimageio.spec.model.v0_5.TensorDescrBase.axes", "modulename": "bioimageio.spec.model.v0_5", "qualname": "TensorDescrBase.axes", "kind": "variable", "doc": "
    tensor axes
    \n", "annotation": ": Annotated[Sequence[~IO_AxisT], MinLen(min_length=1)]"}, "bioimageio.spec.model.v0_5.TensorDescrBase.shape": {"fullname": "bioimageio.spec.model.v0_5.TensorDescrBase.shape", "modulename": "bioimageio.spec.model.v0_5", "qualname": "TensorDescrBase.shape", "kind": "variable", "doc": "
    \n"}, "bioimageio.spec.model.v0_5.TensorDescrBase.test_tensor": {"fullname": "bioimageio.spec.model.v0_5.TensorDescrBase.test_tensor", "modulename": "bioimageio.spec.model.v0_5", "qualname": "TensorDescrBase.test_tensor", "kind": "variable", "doc": "
    An example tensor to use for testing.\nUsing the model with the test input tensors is expected to yield the test output tensors.\nEach test tensor has be a an ndarray in the\nnumpy.lib file format.\nThe file extension must be '.npy'.
    \n", "annotation": ": bioimageio.spec._internal.io.FileDescr"}, "bioimageio.spec.model.v0_5.TensorDescrBase.sample_tensor": {"fullname": "bioimageio.spec.model.v0_5.TensorDescrBase.sample_tensor", "modulename": "bioimageio.spec.model.v0_5", "qualname": "TensorDescrBase.sample_tensor", "kind": "variable", "doc": "
    A sample tensor to illustrate a possible input/output for the model,\nThe sample image primarily serves to inform a human user about an example use case\nand is typically stored as .hdf5, .png or .tiff.\nIt has to be readable by the imageio library\n(numpy's .npy format is not supported).\nThe image dimensionality has to match the number of axes specified in this tensor description.
    \n", "annotation": ": Optional[bioimageio.spec._internal.io.FileDescr]"}, "bioimageio.spec.model.v0_5.TensorDescrBase.data": {"fullname": "bioimageio.spec.model.v0_5.TensorDescrBase.data", "modulename": "bioimageio.spec.model.v0_5", "qualname": "TensorDescrBase.data", "kind": "variable", "doc": "
    Description of the tensor's data values, optionally per channel.\nIf specified per channel, the data type needs to match across channels.
    \n", "annotation": ": Union[bioimageio.spec.model.v0_5.NominalOrOrdinalDataDescr, bioimageio.spec.model.v0_5.IntervalOrRatioDataDescr, Annotated[Sequence[Union[bioimageio.spec.model.v0_5.NominalOrOrdinalDataDescr, bioimageio.spec.model.v0_5.IntervalOrRatioDataDescr]], MinLen(min_length=1)]]"}, "bioimageio.spec.model.v0_5.TensorDescrBase.dtype": {"fullname": "bioimageio.spec.model.v0_5.TensorDescrBase.dtype", "modulename": "bioimageio.spec.model.v0_5", "qualname": "TensorDescrBase.dtype", "kind": "variable", "doc": "
    dtype as specified under data.type or data[i].type
    \n", "annotation": ": Literal['float32', 'float64', 'uint8', 'int8', 'uint16', 'int16', 'uint32', 'int32', 'uint64', 'int64', 'bool']"}, "bioimageio.spec.model.v0_5.TensorDescrBase.get_axis_sizes_for_array": {"fullname": "bioimageio.spec.model.v0_5.TensorDescrBase.get_axis_sizes_for_array", "modulename": "bioimageio.spec.model.v0_5", "qualname": "TensorDescrBase.get_axis_sizes_for_array", "kind": "function", "doc": "
    \n", "signature": "(\tself,\tarray: numpy.ndarray[typing.Any, numpy.dtype[typing.Any]]) -> Dict[bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]], int]:", "funcdef": "def"}, "bioimageio.spec.model.v0_5.InputTensorDescr": {"fullname": "bioimageio.spec.model.v0_5.InputTensorDescr", "modulename": "bioimageio.spec.model.v0_5", "qualname": "InputTensorDescr", "kind": "class", "doc": "
    Subpart of a resource description
    \n", "bases": "bioimageio.spec._internal.node.Node, typing.Generic[~IO_AxisT]"}, "bioimageio.spec.model.v0_5.InputTensorDescr.id": {"fullname": "bioimageio.spec.model.v0_5.InputTensorDescr.id", "modulename": "bioimageio.spec.model.v0_5", "qualname": "InputTensorDescr.id", "kind": "variable", "doc": "
    Input tensor id.\nNo duplicates are allowed across all inputs and outputs.
    \n", "annotation": ": bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]"}, "bioimageio.spec.model.v0_5.InputTensorDescr.preprocessing": {"fullname": "bioimageio.spec.model.v0_5.InputTensorDescr.preprocessing", "modulename": "bioimageio.spec.model.v0_5", "qualname": "InputTensorDescr.preprocessing", "kind": "variable", "doc": "
    Description of how this input should be preprocessed.
    \n", "annotation": ": List[Annotated[Union[bioimageio.spec.model.v0_5.BinarizeDescr, bioimageio.spec.model.v0_5.ClipDescr, bioimageio.spec.model.v0_5.EnsureDtypeDescr, bioimageio.spec.model.v0_5.ScaleLinearDescr, bioimageio.spec.model.v0_5.SigmoidDescr, bioimageio.spec.model.v0_5.FixedZeroMeanUnitVarianceDescr, bioimageio.spec.model.v0_5.ZeroMeanUnitVarianceDescr, bioimageio.spec.model.v0_5.ScaleRangeDescr], FieldInfo(annotation=NoneType, required=True, discriminator='id')]]"}, "bioimageio.spec.model.v0_5.convert_axes": {"fullname": "bioimageio.spec.model.v0_5.convert_axes", "modulename": "bioimageio.spec.model.v0_5", "qualname": "convert_axes", "kind": "function", "doc": "
    \n", "signature": "(\taxes: str,\t*,\tshape: Union[Sequence[int], bioimageio.spec.model.v0_4.ParameterizedInputShape, bioimageio.spec.model.v0_4.ImplicitOutputShape],\ttensor_type: Literal['input', 'output'],\thalo: Optional[Sequence[int]],\tsize_refs: Mapping[bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate]]], Mapping[str, int]]):", "funcdef": "def"}, "bioimageio.spec.model.v0_5.OutputTensorDescr": {"fullname": "bioimageio.spec.model.v0_5.OutputTensorDescr", "modulename": "bioimageio.spec.model.v0_5", "qualname": "OutputTensorDescr", "kind": "class", "doc": "
    Subpart of a resource description
    \n", "bases": "bioimageio.spec._internal.node.Node, typing.Generic[~IO_AxisT]"}, "bioimageio.spec.model.v0_5.OutputTensorDescr.id": {"fullname": "bioimageio.spec.model.v0_5.OutputTensorDescr.id", "modulename": "bioimageio.spec.model.v0_5", "qualname": "OutputTensorDescr.id", "kind": "variable", "doc": "
    Output tensor id.\nNo duplicates are allowed across all inputs and outputs.
    \n", "annotation": ": bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]"}, "bioimageio.spec.model.v0_5.OutputTensorDescr.postprocessing": {"fullname": "bioimageio.spec.model.v0_5.OutputTensorDescr.postprocessing", "modulename": "bioimageio.spec.model.v0_5", "qualname": "OutputTensorDescr.postprocessing", "kind": "variable", "doc": "
    Description of how this output should be postprocessed.
    \n", "annotation": ": List[Annotated[Union[bioimageio.spec.model.v0_5.BinarizeDescr, bioimageio.spec.model.v0_5.ClipDescr, bioimageio.spec.model.v0_5.EnsureDtypeDescr, bioimageio.spec.model.v0_5.ScaleLinearDescr, bioimageio.spec.model.v0_5.SigmoidDescr, bioimageio.spec.model.v0_5.FixedZeroMeanUnitVarianceDescr, bioimageio.spec.model.v0_5.ZeroMeanUnitVarianceDescr, bioimageio.spec.model.v0_5.ScaleRangeDescr, bioimageio.spec.model.v0_5.ScaleMeanVarianceDescr], FieldInfo(annotation=NoneType, required=True, discriminator='id')]]"}, "bioimageio.spec.model.v0_5.TensorDescr": {"fullname": "bioimageio.spec.model.v0_5.TensorDescr", "modulename": "bioimageio.spec.model.v0_5", "qualname": "TensorDescr", "kind": "variable", "doc": "
    \n", "default_value": "typing.Union[bioimageio.spec.model.v0_5.InputTensorDescr, bioimageio.spec.model.v0_5.OutputTensorDescr]"}, "bioimageio.spec.model.v0_5.validate_tensors": {"fullname": "bioimageio.spec.model.v0_5.validate_tensors", "modulename": "bioimageio.spec.model.v0_5", "qualname": "validate_tensors", "kind": "function", "doc": "
    \n", "signature": "(\ttensors: Mapping[bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]], Tuple[Union[bioimageio.spec.model.v0_5.InputTensorDescr, bioimageio.spec.model.v0_5.OutputTensorDescr], numpy.ndarray[Any, numpy.dtype[Any]]]],\ttensor_origin: str):", "funcdef": "def"}, "bioimageio.spec.model.v0_5.EnvironmentFileDescr": {"fullname": "bioimageio.spec.model.v0_5.EnvironmentFileDescr", "modulename": "bioimageio.spec.model.v0_5", "qualname": "EnvironmentFileDescr", "kind": "class", "doc": "
    Subpart of a resource description
    \n", "bases": "bioimageio.spec._internal.io.FileDescr"}, "bioimageio.spec.model.v0_5.EnvironmentFileDescr.source": {"fullname": "bioimageio.spec.model.v0_5.EnvironmentFileDescr.source", "modulename": "bioimageio.spec.model.v0_5", "qualname": "EnvironmentFileDescr.source", "kind": "variable", "doc": "
    \u2208\ud83d\udce6 Conda environment file.\nAllows to specify custom dependencies, see conda docs:
    \n\n\n", "annotation": ": Annotated[Union[Annotated[pathlib.Path, PathType(path_type='file')], bioimageio.spec._internal.io.RelativeFilePath, bioimageio.spec._internal.url.HttpUrl, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator(func=<function wo_special_file_name at 0x7f1c21c3ef20>), PlainSerializer(func=<function _package at 0x7f1c21c782c0>, return_type=PydanticUndefined, when_used='unless-none'), WithSuffix(suffix=('.yaml', '.yml'), case_sensitive=True), FieldInfo(annotation=NoneType, required=True, examples=['environment.yaml'])]"}, "bioimageio.spec.model.v0_5.EnvironmentFileDescr.model_config": {"fullname": "bioimageio.spec.model.v0_5.EnvironmentFileDescr.model_config", "modulename": "bioimageio.spec.model.v0_5", "qualname": "EnvironmentFileDescr.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_5.EnvironmentFileDescr.model_fields": {"fullname": "bioimageio.spec.model.v0_5.EnvironmentFileDescr.model_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "EnvironmentFileDescr.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'source': FieldInfo(annotation=Union[Annotated[Path, PathType], RelativeFilePath, HttpUrl, Annotated[Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], required=True, examples=['environment.yaml'], metadata=[AfterValidator(func=<function wo_special_file_name>), PlainSerializer(func=<function _package>, return_type=PydanticUndefined, when_used='unless-none'), WithSuffix(suffix=('.yaml', '.yml'), case_sensitive=True)]), 'sha256': FieldInfo(annotation=Union[Sha256, NoneType], required=False)}"}, "bioimageio.spec.model.v0_5.EnvironmentFileDescr.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_5.EnvironmentFileDescr.model_computed_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "EnvironmentFileDescr.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_5.ArchitectureFromFileDescr": {"fullname": "bioimageio.spec.model.v0_5.ArchitectureFromFileDescr", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ArchitectureFromFileDescr", "kind": "class", "doc": "
    Subpart of a resource description
    \n", "bases": "_ArchitectureCallableDescr, bioimageio.spec._internal.io.FileDescr"}, "bioimageio.spec.model.v0_5.ArchitectureFromFileDescr.model_config": {"fullname": "bioimageio.spec.model.v0_5.ArchitectureFromFileDescr.model_config", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ArchitectureFromFileDescr.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_5.ArchitectureFromFileDescr.model_fields": {"fullname": "bioimageio.spec.model.v0_5.ArchitectureFromFileDescr.model_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ArchitectureFromFileDescr.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'source': FieldInfo(annotation=Union[Annotated[Path, PathType], RelativeFilePath, HttpUrl, Annotated[Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], required=True, metadata=[AfterValidator(func=<function wo_special_file_name>), PlainSerializer(func=<function _package>, return_type=PydanticUndefined, when_used='unless-none')]), 'sha256': FieldInfo(annotation=Union[Sha256, NoneType], required=False), 'callable': FieldInfo(annotation=ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator]], required=True, examples=['MyNetworkClass', 'get_my_model']), 'kwargs': FieldInfo(annotation=Dict[str, Any], required=False, default_factory=dict)}"}, "bioimageio.spec.model.v0_5.ArchitectureFromFileDescr.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_5.ArchitectureFromFileDescr.model_computed_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ArchitectureFromFileDescr.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_5.ArchitectureFromLibraryDescr": {"fullname": "bioimageio.spec.model.v0_5.ArchitectureFromLibraryDescr", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ArchitectureFromLibraryDescr", "kind": "class", "doc": "
    Subpart of a resource description
    \n", "bases": "_ArchitectureCallableDescr"}, "bioimageio.spec.model.v0_5.ArchitectureFromLibraryDescr.import_from": {"fullname": "bioimageio.spec.model.v0_5.ArchitectureFromLibraryDescr.import_from", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ArchitectureFromLibraryDescr.import_from", "kind": "variable", "doc": "
    Where to import the callable from, i.e. from <import_from> import <callable>
    \n", "annotation": ": str"}, "bioimageio.spec.model.v0_5.ArchitectureFromLibraryDescr.model_config": {"fullname": "bioimageio.spec.model.v0_5.ArchitectureFromLibraryDescr.model_config", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ArchitectureFromLibraryDescr.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_5.ArchitectureFromLibraryDescr.model_fields": {"fullname": "bioimageio.spec.model.v0_5.ArchitectureFromLibraryDescr.model_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ArchitectureFromLibraryDescr.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'callable': FieldInfo(annotation=ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator]], required=True, examples=['MyNetworkClass', 'get_my_model']), 'kwargs': FieldInfo(annotation=Dict[str, Any], required=False, default_factory=dict), 'import_from': FieldInfo(annotation=str, required=True)}"}, "bioimageio.spec.model.v0_5.ArchitectureFromLibraryDescr.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_5.ArchitectureFromLibraryDescr.model_computed_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ArchitectureFromLibraryDescr.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_5.ArchitectureDescr": {"fullname": "bioimageio.spec.model.v0_5.ArchitectureDescr", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ArchitectureDescr", "kind": "variable", "doc": "
    \n", "default_value": "typing.Union[bioimageio.spec.model.v0_5.ArchitectureFromFileDescr, bioimageio.spec.model.v0_5.ArchitectureFromLibraryDescr]"}, "bioimageio.spec.model.v0_5.WeightsEntryDescrBase": {"fullname": "bioimageio.spec.model.v0_5.WeightsEntryDescrBase", "modulename": "bioimageio.spec.model.v0_5", "qualname": "WeightsEntryDescrBase", "kind": "class", "doc": "
    Subpart of a resource description
    \n", "bases": "bioimageio.spec._internal.io.FileDescr"}, "bioimageio.spec.model.v0_5.WeightsEntryDescrBase.type": {"fullname": "bioimageio.spec.model.v0_5.WeightsEntryDescrBase.type", "modulename": "bioimageio.spec.model.v0_5", "qualname": "WeightsEntryDescrBase.type", "kind": "variable", "doc": "
    \n", "annotation": ": ClassVar[Literal['keras_hdf5', 'onnx', 'pytorch_state_dict', 'tensorflow_js', 'tensorflow_saved_model_bundle', 'torchscript']]"}, "bioimageio.spec.model.v0_5.WeightsEntryDescrBase.weights_format_name": {"fullname": "bioimageio.spec.model.v0_5.WeightsEntryDescrBase.weights_format_name", "modulename": "bioimageio.spec.model.v0_5", "qualname": "WeightsEntryDescrBase.weights_format_name", "kind": "variable", "doc": "
    \n", "annotation": ": ClassVar[str]"}, "bioimageio.spec.model.v0_5.WeightsEntryDescrBase.source": {"fullname": "bioimageio.spec.model.v0_5.WeightsEntryDescrBase.source", "modulename": "bioimageio.spec.model.v0_5", "qualname": "WeightsEntryDescrBase.source", "kind": "variable", "doc": "
    \u2208\ud83d\udce6 The weights file.
    \n", "annotation": ": Annotated[Union[Annotated[pathlib.Path, PathType(path_type='file')], bioimageio.spec._internal.io.RelativeFilePath, bioimageio.spec._internal.url.HttpUrl, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator(func=<function wo_special_file_name at 0x7f1c21c3ef20>), PlainSerializer(func=<function _package at 0x7f1c21c782c0>, return_type=PydanticUndefined, when_used='unless-none')]"}, "bioimageio.spec.model.v0_5.WeightsEntryDescrBase.authors": {"fullname": "bioimageio.spec.model.v0_5.WeightsEntryDescrBase.authors", "modulename": "bioimageio.spec.model.v0_5", "qualname": "WeightsEntryDescrBase.authors", "kind": "variable", "doc": "
    Authors\nEither the person(s) that have trained this model resulting in the original weights file.\n    (If this is the initial weights entry, i.e. it does not have a parent)\nOr the person(s) who have converted the weights to this weights format.\n    (If this is a child weight, i.e. it has a parent field)
    \n", "annotation": ": Optional[List[bioimageio.spec.generic.v0_3.Author]]"}, "bioimageio.spec.model.v0_5.WeightsEntryDescrBase.parent": {"fullname": "bioimageio.spec.model.v0_5.WeightsEntryDescrBase.parent", "modulename": "bioimageio.spec.model.v0_5", "qualname": "WeightsEntryDescrBase.parent", "kind": "variable", "doc": "
    The source weights these weights were converted from.\nFor example, if a model's weights were converted from the pytorch_state_dict format to torchscript,\nThe pytorch_state_dict weights entry has no parent and is the parent of the torchscript weights.\nAll weight entries except one (the initial set of weights resulting from training the model),\nneed to have this field.
    \n", "annotation": ": Annotated[Optional[Literal['keras_hdf5', 'onnx', 'pytorch_state_dict', 'tensorflow_js', 'tensorflow_saved_model_bundle', 'torchscript']], FieldInfo(annotation=NoneType, required=True, examples=['pytorch_state_dict'])]"}, "bioimageio.spec.model.v0_5.WeightsEntryDescrBase.check_parent_is_not_self": {"fullname": "bioimageio.spec.model.v0_5.WeightsEntryDescrBase.check_parent_is_not_self", "modulename": "bioimageio.spec.model.v0_5", "qualname": "WeightsEntryDescrBase.check_parent_is_not_self", "kind": "function", "doc": "
    \n", "signature": "(self) -> Self:", "funcdef": "def"}, "bioimageio.spec.model.v0_5.WeightsEntryDescrBase.model_config": {"fullname": "bioimageio.spec.model.v0_5.WeightsEntryDescrBase.model_config", "modulename": "bioimageio.spec.model.v0_5", "qualname": "WeightsEntryDescrBase.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_5.WeightsEntryDescrBase.model_fields": {"fullname": "bioimageio.spec.model.v0_5.WeightsEntryDescrBase.model_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "WeightsEntryDescrBase.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'source': FieldInfo(annotation=Union[Annotated[Path, PathType], RelativeFilePath, HttpUrl, Annotated[Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], required=True, metadata=[AfterValidator(func=<function wo_special_file_name>), PlainSerializer(func=<function _package>, return_type=PydanticUndefined, when_used='unless-none')]), 'sha256': FieldInfo(annotation=Union[Sha256, NoneType], required=False), 'authors': FieldInfo(annotation=Union[List[Author], NoneType], required=False), 'parent': FieldInfo(annotation=Union[Literal['keras_hdf5', 'onnx', 'pytorch_state_dict', 'tensorflow_js', 'tensorflow_saved_model_bundle', 'torchscript'], NoneType], required=False, examples=['pytorch_state_dict'])}"}, "bioimageio.spec.model.v0_5.WeightsEntryDescrBase.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_5.WeightsEntryDescrBase.model_computed_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "WeightsEntryDescrBase.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_5.KerasHdf5WeightsDescr": {"fullname": "bioimageio.spec.model.v0_5.KerasHdf5WeightsDescr", "modulename": "bioimageio.spec.model.v0_5", "qualname": "KerasHdf5WeightsDescr", "kind": "class", "doc": "
    Subpart of a resource description
    \n", "bases": "WeightsEntryDescrBase"}, "bioimageio.spec.model.v0_5.KerasHdf5WeightsDescr.type": {"fullname": "bioimageio.spec.model.v0_5.KerasHdf5WeightsDescr.type", "modulename": "bioimageio.spec.model.v0_5", "qualname": "KerasHdf5WeightsDescr.type", "kind": "variable", "doc": "
    \n", "default_value": "'keras_hdf5'"}, "bioimageio.spec.model.v0_5.KerasHdf5WeightsDescr.weights_format_name": {"fullname": "bioimageio.spec.model.v0_5.KerasHdf5WeightsDescr.weights_format_name", "modulename": "bioimageio.spec.model.v0_5", "qualname": "KerasHdf5WeightsDescr.weights_format_name", "kind": "variable", "doc": "
    \n", "annotation": ": ClassVar[str]", "default_value": "'Keras HDF5'"}, "bioimageio.spec.model.v0_5.KerasHdf5WeightsDescr.tensorflow_version": {"fullname": "bioimageio.spec.model.v0_5.KerasHdf5WeightsDescr.tensorflow_version", "modulename": "bioimageio.spec.model.v0_5", "qualname": "KerasHdf5WeightsDescr.tensorflow_version", "kind": "variable", "doc": "
    TensorFlow version used to create these weights.
    \n", "annotation": ": bioimageio.spec._internal.version_type.Version"}, "bioimageio.spec.model.v0_5.KerasHdf5WeightsDescr.model_config": {"fullname": "bioimageio.spec.model.v0_5.KerasHdf5WeightsDescr.model_config", "modulename": "bioimageio.spec.model.v0_5", "qualname": "KerasHdf5WeightsDescr.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_5.KerasHdf5WeightsDescr.model_fields": {"fullname": "bioimageio.spec.model.v0_5.KerasHdf5WeightsDescr.model_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "KerasHdf5WeightsDescr.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'source': FieldInfo(annotation=Union[Annotated[Path, PathType], RelativeFilePath, HttpUrl, Annotated[Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], required=True, metadata=[AfterValidator(func=<function wo_special_file_name>), PlainSerializer(func=<function _package>, return_type=PydanticUndefined, when_used='unless-none')]), 'sha256': FieldInfo(annotation=Union[Sha256, NoneType], required=False), 'authors': FieldInfo(annotation=Union[List[Author], NoneType], required=False), 'parent': FieldInfo(annotation=Union[Literal['keras_hdf5', 'onnx', 'pytorch_state_dict', 'tensorflow_js', 'tensorflow_saved_model_bundle', 'torchscript'], NoneType], required=False, examples=['pytorch_state_dict']), 'tensorflow_version': FieldInfo(annotation=Version, required=True)}"}, "bioimageio.spec.model.v0_5.KerasHdf5WeightsDescr.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_5.KerasHdf5WeightsDescr.model_computed_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "KerasHdf5WeightsDescr.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_5.OnnxWeightsDescr": {"fullname": "bioimageio.spec.model.v0_5.OnnxWeightsDescr", "modulename": "bioimageio.spec.model.v0_5", "qualname": "OnnxWeightsDescr", "kind": "class", "doc": "
    Subpart of a resource description
    \n", "bases": "WeightsEntryDescrBase"}, "bioimageio.spec.model.v0_5.OnnxWeightsDescr.type": {"fullname": "bioimageio.spec.model.v0_5.OnnxWeightsDescr.type", "modulename": "bioimageio.spec.model.v0_5", "qualname": "OnnxWeightsDescr.type", "kind": "variable", "doc": "
    \n", "default_value": "'onnx'"}, "bioimageio.spec.model.v0_5.OnnxWeightsDescr.weights_format_name": {"fullname": "bioimageio.spec.model.v0_5.OnnxWeightsDescr.weights_format_name", "modulename": "bioimageio.spec.model.v0_5", "qualname": "OnnxWeightsDescr.weights_format_name", "kind": "variable", "doc": "
    \n", "annotation": ": ClassVar[str]", "default_value": "'ONNX'"}, "bioimageio.spec.model.v0_5.OnnxWeightsDescr.opset_version": {"fullname": "bioimageio.spec.model.v0_5.OnnxWeightsDescr.opset_version", "modulename": "bioimageio.spec.model.v0_5", "qualname": "OnnxWeightsDescr.opset_version", "kind": "variable", "doc": "
    ONNX opset version
    \n", "annotation": ": Annotated[int, Ge(ge=7)]"}, "bioimageio.spec.model.v0_5.OnnxWeightsDescr.model_config": {"fullname": "bioimageio.spec.model.v0_5.OnnxWeightsDescr.model_config", "modulename": "bioimageio.spec.model.v0_5", "qualname": "OnnxWeightsDescr.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_5.OnnxWeightsDescr.model_fields": {"fullname": "bioimageio.spec.model.v0_5.OnnxWeightsDescr.model_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "OnnxWeightsDescr.model_fields", "kind": "variable", "doc": "
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    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_5.WeightsDescr": {"fullname": "bioimageio.spec.model.v0_5.WeightsDescr", "modulename": "bioimageio.spec.model.v0_5", "qualname": "WeightsDescr", "kind": "class", "doc": "
    Subpart of a resource description
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    \n", "annotation": ": Optional[bioimageio.spec.model.v0_5.TensorflowJsWeightsDescr]"}, "bioimageio.spec.model.v0_5.WeightsDescr.tensorflow_saved_model_bundle": {"fullname": "bioimageio.spec.model.v0_5.WeightsDescr.tensorflow_saved_model_bundle", "modulename": "bioimageio.spec.model.v0_5", "qualname": "WeightsDescr.tensorflow_saved_model_bundle", "kind": "variable", "doc": "
    \n", "annotation": ": Optional[bioimageio.spec.model.v0_5.TensorflowSavedModelBundleWeightsDescr]"}, "bioimageio.spec.model.v0_5.WeightsDescr.torchscript": {"fullname": "bioimageio.spec.model.v0_5.WeightsDescr.torchscript", "modulename": "bioimageio.spec.model.v0_5", "qualname": "WeightsDescr.torchscript", "kind": "variable", "doc": "
    \n", "annotation": ": Optional[bioimageio.spec.model.v0_5.TorchscriptWeightsDescr]"}, "bioimageio.spec.model.v0_5.WeightsDescr.check_entries": {"fullname": "bioimageio.spec.model.v0_5.WeightsDescr.check_entries", "modulename": "bioimageio.spec.model.v0_5", "qualname": "WeightsDescr.check_entries", "kind": "function", "doc": "
    \n", "signature": "(self) -> Self:", "funcdef": "def"}, "bioimageio.spec.model.v0_5.WeightsDescr.model_config": {"fullname": "bioimageio.spec.model.v0_5.WeightsDescr.model_config", "modulename": "bioimageio.spec.model.v0_5", "qualname": "WeightsDescr.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_5.WeightsDescr.model_fields": {"fullname": "bioimageio.spec.model.v0_5.WeightsDescr.model_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "WeightsDescr.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'keras_hdf5': FieldInfo(annotation=Union[KerasHdf5WeightsDescr, NoneType], required=False), 'onnx': FieldInfo(annotation=Union[OnnxWeightsDescr, NoneType], required=False), 'pytorch_state_dict': FieldInfo(annotation=Union[PytorchStateDictWeightsDescr, NoneType], required=False), 'tensorflow_js': FieldInfo(annotation=Union[TensorflowJsWeightsDescr, NoneType], required=False), 'tensorflow_saved_model_bundle': FieldInfo(annotation=Union[TensorflowSavedModelBundleWeightsDescr, NoneType], required=False), 'torchscript': FieldInfo(annotation=Union[TorchscriptWeightsDescr, NoneType], required=False)}"}, "bioimageio.spec.model.v0_5.WeightsDescr.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_5.WeightsDescr.model_computed_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "WeightsDescr.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_5.LinkedModel": {"fullname": "bioimageio.spec.model.v0_5.LinkedModel", "modulename": "bioimageio.spec.model.v0_5", "qualname": "LinkedModel", "kind": "class", "doc": "
    Reference to a bioimage.io model.
    \n", "bases": "bioimageio.spec._internal.node.Node"}, "bioimageio.spec.model.v0_5.LinkedModel.id": {"fullname": "bioimageio.spec.model.v0_5.LinkedModel.id", "modulename": "bioimageio.spec.model.v0_5", "qualname": "LinkedModel.id", "kind": "variable", "doc": "
    A valid model id from the bioimage.io collection.
    \n", "annotation": ": bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]]"}, "bioimageio.spec.model.v0_5.LinkedModel.version_number": {"fullname": "bioimageio.spec.model.v0_5.LinkedModel.version_number", "modulename": "bioimageio.spec.model.v0_5", "qualname": "LinkedModel.version_number", "kind": "variable", "doc": "
    version number (n-th published version, not the semantic version) of linked model
    \n", "annotation": ": int"}, "bioimageio.spec.model.v0_5.LinkedModel.model_config": {"fullname": "bioimageio.spec.model.v0_5.LinkedModel.model_config", "modulename": "bioimageio.spec.model.v0_5", "qualname": "LinkedModel.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_5.LinkedModel.model_fields": {"fullname": "bioimageio.spec.model.v0_5.LinkedModel.model_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "LinkedModel.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'id': FieldInfo(annotation=ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]], required=True), 'version_number': FieldInfo(annotation=int, required=True)}"}, "bioimageio.spec.model.v0_5.LinkedModel.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_5.LinkedModel.model_computed_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "LinkedModel.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_5.ModelDescr": {"fullname": "bioimageio.spec.model.v0_5.ModelDescr", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ModelDescr", "kind": "class", "doc": "
    Specification of the fields used in a bioimage.io-compliant RDF to describe AI models with pretrained weights.\nThese fields are typically stored in a YAML file which we call a model resource description file (model RDF).
    \n", "bases": "bioimageio.spec.generic.v0_3.GenericModelDescrBase"}, "bioimageio.spec.model.v0_5.ModelDescr.format_version": {"fullname": "bioimageio.spec.model.v0_5.ModelDescr.format_version", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ModelDescr.format_version", "kind": "variable", "doc": "
    Version of the bioimage.io model description specification used.\nWhen creating a new model always use the latest micro/patch version described here.\nThe format_version is important for any consumer software to understand how to parse the fields.
    \n", "annotation": ": Literal['0.5.0']"}, "bioimageio.spec.model.v0_5.ModelDescr.type": {"fullname": "bioimageio.spec.model.v0_5.ModelDescr.type", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ModelDescr.type", "kind": "variable", "doc": "
    Specialized resource type 'model'
    \n", "annotation": ": Literal['model']"}, "bioimageio.spec.model.v0_5.ModelDescr.id": {"fullname": "bioimageio.spec.model.v0_5.ModelDescr.id", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ModelDescr.id", "kind": "variable", "doc": "
    Model zoo (bioimage.io) wide, unique identifier (assigned by bioimage.io)
    \n", "annotation": ": Optional[bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]]]"}, "bioimageio.spec.model.v0_5.ModelDescr.authors": {"fullname": "bioimageio.spec.model.v0_5.ModelDescr.authors", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ModelDescr.authors", "kind": "variable", "doc": "
    The authors are the creators of the model RDF and the primary points of contact.
    \n", "annotation": ": Annotated[List[bioimageio.spec.generic.v0_3.Author], MinLen(min_length=1)]"}, "bioimageio.spec.model.v0_5.ModelDescr.documentation": {"fullname": "bioimageio.spec.model.v0_5.ModelDescr.documentation", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ModelDescr.documentation", "kind": "variable", "doc": "
    \u2208\ud83d\udce6 URL or relative path to a markdown file with additional documentation.\nThe recommended documentation file name is README.md. An .md suffix is mandatory.\nThe documentation should include a '#[#] Validation' (sub)section\nwith details on how to quantitatively validate the model on unseen data.
    \n", "annotation": ": Annotated[Union[Annotated[pathlib.Path, PathType(path_type='file'), Predicate(func=<function PurePath.is_absolute at 0x7f1c25245940>)], bioimageio.spec._internal.io.RelativeFilePath, bioimageio.spec._internal.url.HttpUrl], AfterValidator(func=<function _validate_md_suffix at 0x7f1c21d1afc0>), PlainSerializer(func=<function _package at 0x7f1c21c782c0>, return_type=PydanticUndefined, when_used='unless-none'), FieldInfo(annotation=NoneType, required=True, examples=['https://raw.githubusercontent.com/bioimage-io/spec-bioimage-io/main/example_descriptions/models/unet2d_nuclei_broad/README.md', 'README.md'])]"}, "bioimageio.spec.model.v0_5.ModelDescr.inputs": {"fullname": "bioimageio.spec.model.v0_5.ModelDescr.inputs", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ModelDescr.inputs", "kind": "variable", "doc": "
    Describes the input tensors expected by this model.
    \n", "annotation": ": Annotated[Sequence[bioimageio.spec.model.v0_5.InputTensorDescr], MinLen(min_length=1)]"}, "bioimageio.spec.model.v0_5.ModelDescr.name": {"fullname": "bioimageio.spec.model.v0_5.ModelDescr.name", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ModelDescr.name", "kind": "variable", "doc": "
    A human-readable name of this model.\nIt should be no longer than 64 characters\nand may only contain letter, number, underscore, minus or space characters.\nWe recommend to chose a name that refers to the model's task and image modality.
    \n", "annotation": ": Annotated[str, MinLen(min_length=5), AfterWarner(func=<function as_warning.<locals>.wrapper at 0x7f1c138bd300>, severity=20, msg='Name longer than 64 characters.', context={'typ': Annotated[Any, MaxLen(max_length=64)]})]"}, "bioimageio.spec.model.v0_5.ModelDescr.outputs": {"fullname": "bioimageio.spec.model.v0_5.ModelDescr.outputs", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ModelDescr.outputs", "kind": "variable", "doc": "
    Describes the output tensors.
    \n", "annotation": ": Annotated[Sequence[bioimageio.spec.model.v0_5.OutputTensorDescr], MinLen(min_length=1)]"}, "bioimageio.spec.model.v0_5.ModelDescr.packaged_by": {"fullname": "bioimageio.spec.model.v0_5.ModelDescr.packaged_by", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ModelDescr.packaged_by", "kind": "variable", "doc": "
    The persons that have packaged and uploaded this model.\nOnly required if those persons differ from the authors.
    \n", "annotation": ": List[bioimageio.spec.generic.v0_3.Author]"}, "bioimageio.spec.model.v0_5.ModelDescr.parent": {"fullname": "bioimageio.spec.model.v0_5.ModelDescr.parent", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ModelDescr.parent", "kind": "variable", "doc": "
    The model from which this model is derived, e.g. by fine-tuning the weights.
    \n", "annotation": ": Optional[bioimageio.spec.model.v0_5.LinkedModel]"}, "bioimageio.spec.model.v0_5.ModelDescr.run_mode": {"fullname": "bioimageio.spec.model.v0_5.ModelDescr.run_mode", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ModelDescr.run_mode", "kind": "variable", "doc": "
    Custom run mode for this model: for more complex prediction procedures like test time\ndata augmentation that currently cannot be expressed in the specification.\nNo standard run modes are defined yet.
    \n", "annotation": ": Annotated[Optional[bioimageio.spec.model.v0_4.RunMode], AfterWarner(func=<function as_warning.<locals>.wrapper at 0x7f1c1336a0c0>, severity=30, msg="Run mode '{value}' has limited support across consumer softwares.", context={'typ': None})]"}, "bioimageio.spec.model.v0_5.ModelDescr.timestamp": {"fullname": "bioimageio.spec.model.v0_5.ModelDescr.timestamp", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ModelDescr.timestamp", "kind": "variable", "doc": "
    Timestamp in ISO 8601 format\nwith a few restrictions listed here.\n(In Python a datetime object is valid, too).
    \n", "annotation": ": bioimageio.spec._internal.types.Datetime"}, "bioimageio.spec.model.v0_5.ModelDescr.training_data": {"fullname": "bioimageio.spec.model.v0_5.ModelDescr.training_data", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ModelDescr.training_data", "kind": "variable", "doc": "
    The dataset used to train this model
    \n", "annotation": ": Union[bioimageio.spec.dataset.v0_3.LinkedDataset, bioimageio.spec.dataset.v0_3.DatasetDescr, NoneType]"}, "bioimageio.spec.model.v0_5.ModelDescr.weights": {"fullname": "bioimageio.spec.model.v0_5.ModelDescr.weights", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ModelDescr.weights", "kind": "variable", "doc": "
    The weights for this model.\nWeights can be given for different formats, but should otherwise be equivalent.\nThe available weight formats determine which consumers can use this model.
    \n", "annotation": ": bioimageio.spec.model.v0_5.WeightsDescr"}, "bioimageio.spec.model.v0_5.ModelDescr.get_input_test_arrays": {"fullname": "bioimageio.spec.model.v0_5.ModelDescr.get_input_test_arrays", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ModelDescr.get_input_test_arrays", "kind": "function", "doc": "
    \n", "signature": "(self) -> List[numpy.ndarray[Any, numpy.dtype[Any]]]:", "funcdef": "def"}, "bioimageio.spec.model.v0_5.ModelDescr.get_output_test_arrays": {"fullname": "bioimageio.spec.model.v0_5.ModelDescr.get_output_test_arrays", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ModelDescr.get_output_test_arrays", "kind": "function", "doc": "
    \n", "signature": "(self) -> List[numpy.ndarray[Any, numpy.dtype[Any]]]:", "funcdef": "def"}, "bioimageio.spec.model.v0_5.ModelDescr.get_tensor_sizes": {"fullname": "bioimageio.spec.model.v0_5.ModelDescr.get_tensor_sizes", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ModelDescr.get_tensor_sizes", "kind": "function", "doc": "
    \n", "signature": "(\tself,\tn: int,\tbatch_size: int) -> Dict[bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]], Dict[bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]], int]]:", "funcdef": "def"}, "bioimageio.spec.model.v0_5.ModelDescr.implemented_format_version": {"fullname": "bioimageio.spec.model.v0_5.ModelDescr.implemented_format_version", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ModelDescr.implemented_format_version", "kind": "variable", "doc": "
    \n", "annotation": ": ClassVar[str]", "default_value": "'0.5.0'"}, "bioimageio.spec.model.v0_5.ModelDescr.implemented_format_version_tuple": {"fullname": "bioimageio.spec.model.v0_5.ModelDescr.implemented_format_version_tuple", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ModelDescr.implemented_format_version_tuple", "kind": "variable", "doc": "
    \n", "annotation": ": ClassVar[Tuple[int, int, int]]", "default_value": "(0, 5, 0)"}, "bioimageio.spec.model.v0_5.ModelDescr.model_config": {"fullname": "bioimageio.spec.model.v0_5.ModelDescr.model_config", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ModelDescr.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True, 'title': 'bioimage.io model specification'}"}, "bioimageio.spec.model.v0_5.ModelDescr.model_fields": {"fullname": "bioimageio.spec.model.v0_5.ModelDescr.model_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ModelDescr.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'name': FieldInfo(annotation=str, required=True, metadata=[MinLen(min_length=5), AfterWarner(func=<function as_warning.<locals>.wrapper>, severity=20, msg='Name longer than 64 characters.', context={'typ': typing.Annotated[typing.Any, MaxLen(max_length=64)]})]), 'description': FieldInfo(annotation=str, required=True, metadata=[MaxLen(max_length=1024), AfterWarner(func=<function as_warning.<locals>.wrapper>, severity=30, msg='Description longer than 512 characters.', context={'typ': typing.Annotated[typing.Any, MaxLen(max_length=512)]})]), 'covers': FieldInfo(annotation=List[Annotated[Union[HttpUrl, Annotated[Path, PathType, Predicate], RelativeFilePath], WithSuffix, PlainSerializer]], required=False, default_factory=list, description="Cover images. Please use an image smaller than 500KB and an aspect ratio width to height of 2:1 or 1:1.\\nThe supported image formats are: ('.gif', '.jpeg', '.jpg', '.png', '.svg')", examples=[]), 'id_emoji': FieldInfo(annotation=Union[Annotated[str, Len], NoneType], required=False), 'authors': FieldInfo(annotation=List[Author], required=True, metadata=[MinLen(min_length=1)]), 'attachments': FieldInfo(annotation=List[FileDescr], required=False, default_factory=list), 'cite': FieldInfo(annotation=List[CiteEntry], required=True, metadata=[MinLen(min_length=1)]), 'license': FieldInfo(annotation=Union[LicenseId, DeprecatedLicenseId], required=True, examples=['CC-BY-4.0', 'MIT', 'BSD-2-Clause'], metadata=[AfterWarner(func=<function as_warning.<locals>.wrapper>, severity=30, msg='{value} is deprecated, see https://spdx.org/licenses/{value}.html', context={'typ': <class 'bioimageio.spec._internal.license_id.LicenseId'>})]), 'config': FieldInfo(annotation=Dict[str, YamlValue], required=False, default_factory=dict, examples=[{'bioimageio': {'my_custom_key': 3837283, 'another_key': {'nested': 'value'}}, 'imagej': {'macro_dir': 'path/to/macro/file'}}]), 'git_repo': FieldInfo(annotation=Union[HttpUrl, NoneType], required=False, examples=['https://github.com/bioimage-io/spec-bioimage-io/tree/main/example_descriptions/models/unet2d_nuclei_broad']), 'icon': FieldInfo(annotation=Union[Annotated[Union[Annotated[Path, PathType], RelativeFilePath, HttpUrl, Annotated[Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator, PlainSerializer], Annotated[str, Len], NoneType], required=False), 'links': FieldInfo(annotation=List[str], required=False, default_factory=list, examples=[('ilastik/ilastik', 'deepimagej/deepimagej', 'zero/notebook_u-net_3d_zerocostdl4mic')]), 'uploader': FieldInfo(annotation=Union[Uploader, NoneType], required=False), 'maintainers': FieldInfo(annotation=List[Maintainer], required=False, default_factory=list), 'tags': FieldInfo(annotation=List[str], required=False, default_factory=list, examples=[('unet2d', 'pytorch', 'nucleus', 'segmentation', 'dsb2018')]), 'version': FieldInfo(annotation=Union[Version, NoneType], required=False), 'version_number': FieldInfo(annotation=Union[int, NoneType], required=False), 'format_version': FieldInfo(annotation=Literal['0.5.0'], required=False, default='0.5.0'), 'type': FieldInfo(annotation=Literal['model'], required=False, default='model'), 'id': FieldInfo(annotation=Union[ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]], NoneType], required=False), 'documentation': FieldInfo(annotation=Union[Annotated[Path, PathType, Predicate], RelativeFilePath, HttpUrl], required=True, examples=['https://raw.githubusercontent.com/bioimage-io/spec-bioimage-io/main/example_descriptions/models/unet2d_nuclei_broad/README.md', 'README.md'], metadata=[AfterValidator(func=<function _validate_md_suffix>), PlainSerializer(func=<function _package>, return_type=PydanticUndefined, when_used='unless-none')]), 'inputs': FieldInfo(annotation=Sequence[InputTensorDescr], required=True, metadata=[MinLen(min_length=1)]), 'outputs': FieldInfo(annotation=Sequence[OutputTensorDescr], required=True, metadata=[MinLen(min_length=1)]), 'packaged_by': FieldInfo(annotation=List[Author], required=False, default_factory=list), 'parent': FieldInfo(annotation=Union[LinkedModel, NoneType], required=False), 'run_mode': FieldInfo(annotation=Union[RunMode, NoneType], required=False, metadata=[AfterWarner(func=<function as_warning.<locals>.wrapper>, severity=30, msg="Run mode '{value}' has limited support across consumer softwares.", context={'typ': None})]), 'timestamp': FieldInfo(annotation=Datetime, required=False, default=Datetime(root=datetime.datetime(2024, 3, 13, 14, 32, 43, 966760))), 'training_data': FieldInfo(annotation=Union[LinkedDataset, DatasetDescr, NoneType], required=False), 'weights': FieldInfo(annotation=WeightsDescr, required=True)}"}, "bioimageio.spec.model.v0_5.ModelDescr.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_5.ModelDescr.model_computed_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ModelDescr.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_5.generate_covers": {"fullname": "bioimageio.spec.model.v0_5.generate_covers", "modulename": "bioimageio.spec.model.v0_5", "qualname": "generate_covers", "kind": "function", "doc": "
    \n", "signature": "(\tinputs: Sequence[Tuple[bioimageio.spec.model.v0_5.InputTensorDescr, numpy.ndarray[Any, numpy.dtype[Any]]]],\toutputs: Sequence[Tuple[bioimageio.spec.model.v0_5.OutputTensorDescr, numpy.ndarray[Any, numpy.dtype[Any]]]]) -> List[pathlib.Path]:", "funcdef": "def"}, "bioimageio.spec.model.v0_5.TensorDescrBase[Annotated[Union[BatchAxis, ChannelAxis, IndexAxis, TimeInputAxis, SpaceInputAxis], FieldInfo(annotation=NoneType, required=True, discriminator='type')]]": {"fullname": "bioimageio.spec.model.v0_5.TensorDescrBase[Annotated[Union[BatchAxis, ChannelAxis, IndexAxis, TimeInputAxis, SpaceInputAxis], FieldInfo(annotation=NoneType, required=True, discriminator='type')]]", "modulename": "bioimageio.spec.model.v0_5", "qualname": "TensorDescrBase[Annotated[Union[BatchAxis, ChannelAxis, IndexAxis, TimeInputAxis, SpaceInputAxis], FieldInfo(annotation=NoneType, required=True, discriminator='type')]]", "kind": "class", "doc": "
    Subpart of a resource description
    \n", "bases": "bioimageio.spec._internal.node.Node, typing.Generic[~IO_AxisT]"}, "bioimageio.spec.model.v0_5.TensorDescrBase[Annotated[Union[BatchAxis, ChannelAxis, IndexAxis, TimeOutputAxis, SpaceOutputAxis], FieldInfo(annotation=NoneType, required=True, discriminator='type')]]": {"fullname": "bioimageio.spec.model.v0_5.TensorDescrBase[Annotated[Union[BatchAxis, ChannelAxis, IndexAxis, TimeOutputAxis, SpaceOutputAxis], FieldInfo(annotation=NoneType, required=True, discriminator='type')]]", "modulename": "bioimageio.spec.model.v0_5", "qualname": "TensorDescrBase[Annotated[Union[BatchAxis, ChannelAxis, IndexAxis, TimeOutputAxis, SpaceOutputAxis], FieldInfo(annotation=NoneType, required=True, discriminator='type')]]", "kind": "class", "doc": "
    Subpart of a resource description
    \n", "bases": "bioimageio.spec._internal.node.Node, typing.Generic[~IO_AxisT]"}, "bioimageio.spec.notebook": {"fullname": "bioimageio.spec.notebook", "modulename": "bioimageio.spec.notebook", "kind": "module", "doc": "
    implementaions of all released minor versions are available in submodules:
    \n\n\n"}, "bioimageio.spec.notebook.AnyNotebookDescr": {"fullname": "bioimageio.spec.notebook.AnyNotebookDescr", "modulename": "bioimageio.spec.notebook", "qualname": "AnyNotebookDescr", "kind": "variable", "doc": "
    Union of any released notebook desription
    \n", "default_value": "typing.Annotated[typing.Union[bioimageio.spec.notebook.v0_2.NotebookDescr, bioimageio.spec.notebook.v0_3.NotebookDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)]"}, "bioimageio.spec.notebook.v0_2": {"fullname": "bioimageio.spec.notebook.v0_2", "modulename": "bioimageio.spec.notebook.v0_2", "kind": "module", "doc": "
    \n"}, "bioimageio.spec.notebook.v0_2.NotebookSource": {"fullname": "bioimageio.spec.notebook.v0_2.NotebookSource", "modulename": "bioimageio.spec.notebook.v0_2", "qualname": "NotebookSource", "kind": "variable", "doc": "
    \n", "default_value": "typing.Union[typing.Annotated[bioimageio.spec._internal.url.HttpUrl, WithSuffix(suffix='.ipynb', case_sensitive=True)], typing.Annotated[pathlib.Path, PathType(path_type='file'), Predicate(func=<function PurePath.is_absolute>), WithSuffix(suffix='.ipynb', case_sensitive=True)], typing.Annotated[bioimageio.spec._internal.io.RelativeFilePath, WithSuffix(suffix='.ipynb', case_sensitive=True)]]"}, "bioimageio.spec.notebook.v0_2.NotebookDescr": {"fullname": "bioimageio.spec.notebook.v0_2.NotebookDescr", "modulename": "bioimageio.spec.notebook.v0_2", "qualname": "NotebookDescr", "kind": "class", "doc": "
    Bioimage.io description of a Jupyter Notebook.
    \n", "bases": "bioimageio.spec.generic.v0_2.GenericDescrBase"}, "bioimageio.spec.notebook.v0_2.NotebookDescr.type": {"fullname": "bioimageio.spec.notebook.v0_2.NotebookDescr.type", "modulename": "bioimageio.spec.notebook.v0_2", "qualname": "NotebookDescr.type", "kind": "variable", "doc": "
    \n", "annotation": ": Literal['notebook']"}, "bioimageio.spec.notebook.v0_2.NotebookDescr.id": {"fullname": "bioimageio.spec.notebook.v0_2.NotebookDescr.id", "modulename": "bioimageio.spec.notebook.v0_2", "qualname": "NotebookDescr.id", "kind": "variable", "doc": "
    Model zoo (bioimage.io) wide, unique identifier (assigned by bioimage.io)
    \n", "annotation": ": Optional[bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]]]"}, "bioimageio.spec.notebook.v0_2.NotebookDescr.source": {"fullname": "bioimageio.spec.notebook.v0_2.NotebookDescr.source", "modulename": "bioimageio.spec.notebook.v0_2", "qualname": "NotebookDescr.source", "kind": "variable", "doc": "
    The Jupyter notebook
    \n", "annotation": ": Union[Annotated[bioimageio.spec._internal.url.HttpUrl, WithSuffix(suffix='.ipynb', case_sensitive=True)], Annotated[pathlib.Path, PathType(path_type='file'), Predicate(func=<function PurePath.is_absolute at 0x7f1c25245940>), WithSuffix(suffix='.ipynb', case_sensitive=True)], Annotated[bioimageio.spec._internal.io.RelativeFilePath, WithSuffix(suffix='.ipynb', case_sensitive=True)]]"}, "bioimageio.spec.notebook.v0_2.NotebookDescr.implemented_format_version": {"fullname": "bioimageio.spec.notebook.v0_2.NotebookDescr.implemented_format_version", "modulename": "bioimageio.spec.notebook.v0_2", "qualname": "NotebookDescr.implemented_format_version", "kind": "variable", "doc": "
    \n", "annotation": ": ClassVar[str]", "default_value": "'0.2.4'"}, "bioimageio.spec.notebook.v0_2.NotebookDescr.implemented_format_version_tuple": {"fullname": "bioimageio.spec.notebook.v0_2.NotebookDescr.implemented_format_version_tuple", "modulename": "bioimageio.spec.notebook.v0_2", "qualname": "NotebookDescr.implemented_format_version_tuple", "kind": "variable", "doc": "
    \n", "annotation": ": ClassVar[Tuple[int, int, int]]", "default_value": "(0, 2, 4)"}, "bioimageio.spec.notebook.v0_2.NotebookDescr.model_config": {"fullname": "bioimageio.spec.notebook.v0_2.NotebookDescr.model_config", "modulename": "bioimageio.spec.notebook.v0_2", "qualname": "NotebookDescr.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True, 'title': 'bioimage.io notebook specification'}"}, "bioimageio.spec.notebook.v0_2.NotebookDescr.model_fields": {"fullname": "bioimageio.spec.notebook.v0_2.NotebookDescr.model_fields", "modulename": "bioimageio.spec.notebook.v0_2", "qualname": "NotebookDescr.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'name': FieldInfo(annotation=str, required=True, metadata=[MinLen(min_length=1), AfterWarner(func=<function as_warning.<locals>.wrapper>, severity=30, msg='Longer than 128 characters.', context={'typ': typing.Annotated[typing.Any, MaxLen(max_length=128)]})]), 'description': FieldInfo(annotation=str, required=True), 'covers': FieldInfo(annotation=List[Annotated[Union[HttpUrl, Annotated[Path, PathType, Predicate], RelativeFilePath], WithSuffix, PlainSerializer]], required=False, default_factory=list, description="Cover images. Please use an image smaller than 500KB and an aspect ratio width to height of 2:1.\\nThe supported image formats are: ('.gif', '.jpeg', '.jpg', '.png', '.svg')", examples=['cover.png']), 'id_emoji': FieldInfo(annotation=Union[Annotated[str, Len], NoneType], required=False), 'authors': FieldInfo(annotation=List[Author], required=False, default_factory=list), 'attachments': FieldInfo(annotation=Union[AttachmentsDescr, NoneType], required=False), 'cite': FieldInfo(annotation=List[CiteEntry], required=False, default_factory=list), 'config': FieldInfo(annotation=Dict[str, YamlValue], required=False, default_factory=dict, examples=[{'bioimageio': {'my_custom_key': 3837283, 'another_key': {'nested': 'value'}}, 'imagej': {'macro_dir': 'path/to/macro/file'}}]), 'download_url': FieldInfo(annotation=Union[HttpUrl, NoneType], required=False), 'git_repo': FieldInfo(annotation=Union[str, NoneType], required=False, examples=['https://github.com/bioimage-io/spec-bioimage-io/tree/main/example_descriptions/models/unet2d_nuclei_broad']), 'icon': FieldInfo(annotation=Union[Annotated[Union[Annotated[Path, PathType], RelativeFilePath, HttpUrl, Annotated[Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator, PlainSerializer], Annotated[str, Len], NoneType], required=False), 'links': FieldInfo(annotation=List[str], required=False, default_factory=list, examples=[('ilastik/ilastik', 'deepimagej/deepimagej', 'zero/notebook_u-net_3d_zerocostdl4mic')]), 'uploader': FieldInfo(annotation=Union[Uploader, NoneType], required=False), 'maintainers': FieldInfo(annotation=List[Maintainer], required=False, default_factory=list), 'rdf_source': FieldInfo(annotation=Union[Annotated[Path, PathType], RelativeFilePath, HttpUrl, Annotated[Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)], NoneType], required=False), 'tags': FieldInfo(annotation=List[str], required=False, default_factory=list, examples=[('unet2d', 'pytorch', 'nucleus', 'segmentation', 'dsb2018')]), 'version': FieldInfo(annotation=Union[Version, NoneType], required=False), 'version_number': FieldInfo(annotation=Union[int, NoneType], required=False), 'format_version': FieldInfo(annotation=Literal['0.2.4'], required=False, default='0.2.4'), 'badges': FieldInfo(annotation=List[BadgeDescr], required=False, default_factory=list), 'documentation': FieldInfo(annotation=Union[Annotated[Union[Annotated[Path, PathType], RelativeFilePath, HttpUrl, Annotated[Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator, PlainSerializer], NoneType], required=False, examples=['https://raw.githubusercontent.com/bioimage-io/spec-bioimage-io/main/example_descriptions/models/unet2d_nuclei_broad/README.md', 'README.md']), 'license': FieldInfo(annotation=Union[LicenseId, DeprecatedLicenseId, str, NoneType], required=False, examples=['CC-BY-4.0', 'MIT', 'BSD-2-Clause']), 'type': FieldInfo(annotation=Literal['notebook'], required=False, default='notebook'), 'id': FieldInfo(annotation=Union[ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]], NoneType], required=False), 'source': FieldInfo(annotation=Union[Annotated[HttpUrl, WithSuffix], Annotated[Path, PathType, Predicate, WithSuffix], Annotated[RelativeFilePath, WithSuffix]], required=True)}"}, "bioimageio.spec.notebook.v0_2.NotebookDescr.model_computed_fields": {"fullname": "bioimageio.spec.notebook.v0_2.NotebookDescr.model_computed_fields", "modulename": "bioimageio.spec.notebook.v0_2", "qualname": "NotebookDescr.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.notebook.v0_2.LinkedNotebook": {"fullname": "bioimageio.spec.notebook.v0_2.LinkedNotebook", "modulename": "bioimageio.spec.notebook.v0_2", "qualname": "LinkedNotebook", "kind": "class", "doc": "
    Reference to a bioimage.io notebook.
    \n", "bases": "bioimageio.spec._internal.node.Node"}, "bioimageio.spec.notebook.v0_2.LinkedNotebook.id": {"fullname": "bioimageio.spec.notebook.v0_2.LinkedNotebook.id", "modulename": "bioimageio.spec.notebook.v0_2", "qualname": "LinkedNotebook.id", "kind": "variable", "doc": "
    A valid notebook id from the bioimage.io collection.
    \n", "annotation": ": bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]]"}, "bioimageio.spec.notebook.v0_2.LinkedNotebook.version_number": {"fullname": "bioimageio.spec.notebook.v0_2.LinkedNotebook.version_number", "modulename": "bioimageio.spec.notebook.v0_2", "qualname": "LinkedNotebook.version_number", "kind": "variable", "doc": "
    version number (n-th published version, not the semantic version) of linked notebook
    \n", "annotation": ": Optional[int]"}, "bioimageio.spec.notebook.v0_2.LinkedNotebook.model_config": {"fullname": "bioimageio.spec.notebook.v0_2.LinkedNotebook.model_config", "modulename": "bioimageio.spec.notebook.v0_2", "qualname": "LinkedNotebook.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.notebook.v0_2.LinkedNotebook.model_fields": {"fullname": "bioimageio.spec.notebook.v0_2.LinkedNotebook.model_fields", "modulename": "bioimageio.spec.notebook.v0_2", "qualname": "LinkedNotebook.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'id': FieldInfo(annotation=ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]], required=True), 'version_number': FieldInfo(annotation=Union[int, NoneType], required=False)}"}, "bioimageio.spec.notebook.v0_2.LinkedNotebook.model_computed_fields": {"fullname": "bioimageio.spec.notebook.v0_2.LinkedNotebook.model_computed_fields", "modulename": "bioimageio.spec.notebook.v0_2", "qualname": "LinkedNotebook.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.notebook.v0_3": {"fullname": "bioimageio.spec.notebook.v0_3", "modulename": "bioimageio.spec.notebook.v0_3", "kind": "module", "doc": "
    \n"}, "bioimageio.spec.notebook.v0_3.NotebookDescr": {"fullname": "bioimageio.spec.notebook.v0_3.NotebookDescr", "modulename": "bioimageio.spec.notebook.v0_3", "qualname": "NotebookDescr", "kind": "class", "doc": "
    Bioimage.io description of a Jupyter notebook.
    \n", "bases": "bioimageio.spec.generic.v0_3.GenericDescrBase"}, "bioimageio.spec.notebook.v0_3.NotebookDescr.type": {"fullname": "bioimageio.spec.notebook.v0_3.NotebookDescr.type", "modulename": "bioimageio.spec.notebook.v0_3", "qualname": "NotebookDescr.type", "kind": "variable", "doc": "
    \n", "annotation": ": Literal['notebook']"}, "bioimageio.spec.notebook.v0_3.NotebookDescr.id": {"fullname": "bioimageio.spec.notebook.v0_3.NotebookDescr.id", "modulename": "bioimageio.spec.notebook.v0_3", "qualname": "NotebookDescr.id", "kind": "variable", "doc": "
    Model zoo (bioimage.io) wide, unique identifier (assigned by bioimage.io)
    \n", "annotation": ": Optional[bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]]]"}, "bioimageio.spec.notebook.v0_3.NotebookDescr.parent": {"fullname": "bioimageio.spec.notebook.v0_3.NotebookDescr.parent", "modulename": "bioimageio.spec.notebook.v0_3", "qualname": "NotebookDescr.parent", "kind": "variable", "doc": "
    The description from which this one is derived
    \n", "annotation": ": Optional[bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]]]"}, "bioimageio.spec.notebook.v0_3.NotebookDescr.source": {"fullname": "bioimageio.spec.notebook.v0_3.NotebookDescr.source", "modulename": "bioimageio.spec.notebook.v0_3", "qualname": "NotebookDescr.source", "kind": "variable", "doc": "
    The Jupyter notebook
    \n", "annotation": ": Union[Annotated[bioimageio.spec._internal.url.HttpUrl, WithSuffix(suffix='.ipynb', case_sensitive=True)], Annotated[pathlib.Path, PathType(path_type='file'), Predicate(func=<function PurePath.is_absolute at 0x7f1c25245940>), WithSuffix(suffix='.ipynb', case_sensitive=True)], Annotated[bioimageio.spec._internal.io.RelativeFilePath, WithSuffix(suffix='.ipynb', case_sensitive=True)]]"}, "bioimageio.spec.notebook.v0_3.NotebookDescr.implemented_format_version": {"fullname": "bioimageio.spec.notebook.v0_3.NotebookDescr.implemented_format_version", "modulename": "bioimageio.spec.notebook.v0_3", "qualname": "NotebookDescr.implemented_format_version", "kind": "variable", "doc": "
    \n", "annotation": ": ClassVar[str]", "default_value": "'0.3.0'"}, "bioimageio.spec.notebook.v0_3.NotebookDescr.implemented_format_version_tuple": {"fullname": "bioimageio.spec.notebook.v0_3.NotebookDescr.implemented_format_version_tuple", "modulename": "bioimageio.spec.notebook.v0_3", "qualname": "NotebookDescr.implemented_format_version_tuple", "kind": "variable", "doc": "
    \n", "annotation": ": ClassVar[Tuple[int, int, int]]", "default_value": "(0, 3, 0)"}, "bioimageio.spec.notebook.v0_3.NotebookDescr.model_config": {"fullname": "bioimageio.spec.notebook.v0_3.NotebookDescr.model_config", "modulename": "bioimageio.spec.notebook.v0_3", "qualname": "NotebookDescr.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True, 'title': 'bioimage.io notebook specification'}"}, "bioimageio.spec.notebook.v0_3.NotebookDescr.model_fields": {"fullname": "bioimageio.spec.notebook.v0_3.NotebookDescr.model_fields", "modulename": "bioimageio.spec.notebook.v0_3", "qualname": "NotebookDescr.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'name': FieldInfo(annotation=str, required=True, metadata=[MinLen(min_length=1), MaxLen(max_length=128)]), 'description': FieldInfo(annotation=str, required=True, metadata=[MaxLen(max_length=1024), AfterWarner(func=<function as_warning.<locals>.wrapper>, severity=30, msg='Description longer than 512 characters.', context={'typ': typing.Annotated[typing.Any, MaxLen(max_length=512)]})]), 'covers': FieldInfo(annotation=List[Annotated[Union[HttpUrl, Annotated[Path, PathType, Predicate], RelativeFilePath], WithSuffix, PlainSerializer]], required=False, default_factory=list, description="Cover images. Please use an image smaller than 500KB and an aspect ratio width to height of 2:1 or 1:1.\\nThe supported image formats are: ('.gif', '.jpeg', '.jpg', '.png', '.svg')", examples=[]), 'id_emoji': FieldInfo(annotation=Union[Annotated[str, Len], NoneType], required=False), 'authors': FieldInfo(annotation=List[Author], required=True, metadata=[MinLen(min_length=1)]), 'attachments': FieldInfo(annotation=List[FileDescr], required=False, default_factory=list), 'cite': FieldInfo(annotation=List[CiteEntry], required=True, metadata=[MinLen(min_length=1)]), 'license': FieldInfo(annotation=Union[LicenseId, DeprecatedLicenseId], required=True, examples=['CC-BY-4.0', 'MIT', 'BSD-2-Clause'], metadata=[AfterWarner(func=<function as_warning.<locals>.wrapper>, severity=30, msg='{value} is deprecated, see https://spdx.org/licenses/{value}.html', context={'typ': <class 'bioimageio.spec._internal.license_id.LicenseId'>})]), 'config': FieldInfo(annotation=Dict[str, YamlValue], required=False, default_factory=dict, examples=[{'bioimageio': {'my_custom_key': 3837283, 'another_key': {'nested': 'value'}}, 'imagej': {'macro_dir': 'path/to/macro/file'}}]), 'git_repo': FieldInfo(annotation=Union[HttpUrl, NoneType], required=False, examples=['https://github.com/bioimage-io/spec-bioimage-io/tree/main/example_descriptions/models/unet2d_nuclei_broad']), 'icon': FieldInfo(annotation=Union[Annotated[Union[Annotated[Path, PathType], RelativeFilePath, HttpUrl, Annotated[Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator, PlainSerializer], Annotated[str, Len], NoneType], required=False), 'links': FieldInfo(annotation=List[str], required=False, default_factory=list, examples=[('ilastik/ilastik', 'deepimagej/deepimagej', 'zero/notebook_u-net_3d_zerocostdl4mic')]), 'uploader': FieldInfo(annotation=Union[Uploader, NoneType], required=False), 'maintainers': FieldInfo(annotation=List[Maintainer], required=False, default_factory=list), 'tags': FieldInfo(annotation=List[str], required=False, default_factory=list, examples=[('unet2d', 'pytorch', 'nucleus', 'segmentation', 'dsb2018')]), 'version': FieldInfo(annotation=Union[Version, NoneType], required=False), 'version_number': FieldInfo(annotation=Union[int, NoneType], required=False), 'format_version': FieldInfo(annotation=Literal['0.3.0'], required=False, default='0.3.0'), 'documentation': FieldInfo(annotation=Union[Annotated[Union[Annotated[Path, PathType, Predicate], RelativeFilePath, HttpUrl], AfterValidator, PlainSerializer], NoneType], required=False, examples=['https://raw.githubusercontent.com/bioimage-io/spec-bioimage-io/main/example_descriptions/models/unet2d_nuclei_broad/README.md', 'README.md']), 'badges': FieldInfo(annotation=List[BadgeDescr], required=False, default_factory=list), 'type': FieldInfo(annotation=Literal['notebook'], required=False, default='notebook'), 'id': FieldInfo(annotation=Union[ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]], NoneType], required=False), 'parent': FieldInfo(annotation=Union[ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]], NoneType], required=False), 'source': FieldInfo(annotation=Union[Annotated[HttpUrl, WithSuffix], Annotated[Path, PathType, Predicate, WithSuffix], Annotated[RelativeFilePath, WithSuffix]], required=True)}"}, "bioimageio.spec.notebook.v0_3.NotebookDescr.model_computed_fields": {"fullname": "bioimageio.spec.notebook.v0_3.NotebookDescr.model_computed_fields", "modulename": "bioimageio.spec.notebook.v0_3", "qualname": "NotebookDescr.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.notebook.v0_3.LinkedNotebook": {"fullname": "bioimageio.spec.notebook.v0_3.LinkedNotebook", "modulename": "bioimageio.spec.notebook.v0_3", "qualname": "LinkedNotebook", "kind": "class", "doc": "
    Reference to a bioimage.io notebook.
    \n", "bases": "bioimageio.spec._internal.node.Node"}, "bioimageio.spec.notebook.v0_3.LinkedNotebook.id": {"fullname": "bioimageio.spec.notebook.v0_3.LinkedNotebook.id", "modulename": "bioimageio.spec.notebook.v0_3", "qualname": "LinkedNotebook.id", "kind": "variable", "doc": "
    A valid notebook id from the bioimage.io collection.
    \n", "annotation": ": bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]]"}, "bioimageio.spec.notebook.v0_3.LinkedNotebook.version_number": {"fullname": "bioimageio.spec.notebook.v0_3.LinkedNotebook.version_number", "modulename": "bioimageio.spec.notebook.v0_3", "qualname": "LinkedNotebook.version_number", "kind": "variable", "doc": "
    version number (n-th published version, not the semantic version) of linked notebook
    \n", "annotation": ": int"}, "bioimageio.spec.notebook.v0_3.LinkedNotebook.model_config": {"fullname": "bioimageio.spec.notebook.v0_3.LinkedNotebook.model_config", "modulename": "bioimageio.spec.notebook.v0_3", "qualname": "LinkedNotebook.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.notebook.v0_3.LinkedNotebook.model_fields": {"fullname": "bioimageio.spec.notebook.v0_3.LinkedNotebook.model_fields", "modulename": "bioimageio.spec.notebook.v0_3", "qualname": "LinkedNotebook.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'id': FieldInfo(annotation=ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]], required=True), 'version_number': FieldInfo(annotation=int, required=True)}"}, "bioimageio.spec.notebook.v0_3.LinkedNotebook.model_computed_fields": {"fullname": "bioimageio.spec.notebook.v0_3.LinkedNotebook.model_computed_fields", "modulename": "bioimageio.spec.notebook.v0_3", "qualname": "LinkedNotebook.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.partner_utils": {"fullname": "bioimageio.spec.partner_utils", "modulename": "bioimageio.spec.partner_utils", "kind": "module", "doc": "
    bioimageio.spec extensions for bioimage.io community partners
    \n"}, "bioimageio.spec.partner_utils.imjoy": {"fullname": "bioimageio.spec.partner_utils.imjoy", "modulename": "bioimageio.spec.partner_utils.imjoy", "kind": "module", "doc": "
    \n"}, "bioimageio.spec.partner_utils.imjoy.enrich_partial_rdf_with_imjoy_plugin": {"fullname": "bioimageio.spec.partner_utils.imjoy.enrich_partial_rdf_with_imjoy_plugin", "modulename": "bioimageio.spec.partner_utils.imjoy", "qualname": "enrich_partial_rdf_with_imjoy_plugin", "kind": "function", "doc": "
    a (partial) rdf may have 'rdf_source' or 'source' which resolve to rdf data that may be overwritten.\nDue to resolving imjoy plugins this is not done in bioimageio.spec.collection atm
    \n", "signature": "(\tpartial_rdf: Dict[str, Any],\troot: Union[Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)], Annotated[pathlib.Path, PathType(path_type='dir')]],\tresolve_rdf_source: Callable[[Union[Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)], Annotated[pathlib.Path, PathType(path_type='file')], str]], Tuple[Dict[str, Any], str, Union[Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)], Annotated[pathlib.Path, PathType(path_type='dir')]]]]) -> Dict[str, Any]:", "funcdef": "def"}, "bioimageio.spec.partner_utils.imjoy.get_plugin_as_rdf": {"fullname": "bioimageio.spec.partner_utils.imjoy.get_plugin_as_rdf", "modulename": "bioimageio.spec.partner_utils.imjoy", "qualname": "get_plugin_as_rdf", "kind": "function", "doc": "
    Get imjoy plugin config in RDF format.
    \n", "signature": "(source_url: str) -> Dict[Any, Any]:", "funcdef": "def"}, "bioimageio.spec.pretty_validation_errors": {"fullname": "bioimageio.spec.pretty_validation_errors", "modulename": "bioimageio.spec.pretty_validation_errors", "kind": "module", "doc": "
    \n"}, "bioimageio.spec.pretty_validation_errors.PrettyValidationError": {"fullname": "bioimageio.spec.pretty_validation_errors.PrettyValidationError", "modulename": "bioimageio.spec.pretty_validation_errors", "qualname": "PrettyValidationError", "kind": "class", "doc": "
    Wrap a pydantic.ValidationError to custumize formatting.
    \n", "bases": "builtins.ValueError"}, "bioimageio.spec.pretty_validation_errors.PrettyValidationError.__init__": {"fullname": "bioimageio.spec.pretty_validation_errors.PrettyValidationError.__init__", "modulename": "bioimageio.spec.pretty_validation_errors", "qualname": "PrettyValidationError.__init__", "kind": "function", "doc": "
    \n", "signature": "(validation_error: pydantic_core._pydantic_core.ValidationError)"}, "bioimageio.spec.pretty_validation_errors.PrettyValidationError.error": {"fullname": "bioimageio.spec.pretty_validation_errors.PrettyValidationError.error", "modulename": "bioimageio.spec.pretty_validation_errors", "qualname": "PrettyValidationError.error", "kind": "variable", "doc": "
    \n"}, "bioimageio.spec.pretty_validation_errors.enable_pretty_validation_errors_in_ipynb": {"fullname": "bioimageio.spec.pretty_validation_errors.enable_pretty_validation_errors_in_ipynb", "modulename": "bioimageio.spec.pretty_validation_errors", "qualname": "enable_pretty_validation_errors_in_ipynb", "kind": "function", "doc": "
    A modestly hacky way to display prettified validaiton error messages and traceback\nin interactive Python notebooks
    \n", "signature": "():", "funcdef": "def"}, "bioimageio.spec.summary": {"fullname": "bioimageio.spec.summary", "modulename": "bioimageio.spec.summary", "kind": "module", "doc": "
    \n"}, "bioimageio.spec.summary.Loc": {"fullname": "bioimageio.spec.summary.Loc", "modulename": "bioimageio.spec.summary", "qualname": "Loc", "kind": "variable", "doc": "
    location of error/warning in a nested data structure
    \n", "default_value": "typing.Tuple[typing.Union[int, str], ...]"}, "bioimageio.spec.summary.WarningSeverityName": {"fullname": "bioimageio.spec.summary.WarningSeverityName", "modulename": "bioimageio.spec.summary", "qualname": "WarningSeverityName", "kind": "variable", "doc": "
    \n", "default_value": "typing.Literal['info', 'warning', 'alert']"}, "bioimageio.spec.summary.WarningLevelName": {"fullname": "bioimageio.spec.summary.WarningLevelName", "modulename": "bioimageio.spec.summary", "qualname": "WarningLevelName", "kind": "variable", "doc": "
    \n", "default_value": "typing.Literal['info', 'warning', 'alert', 'error']"}, "bioimageio.spec.summary.WARNING_SEVERITY_TO_NAME": {"fullname": "bioimageio.spec.summary.WARNING_SEVERITY_TO_NAME", "modulename": "bioimageio.spec.summary", "qualname": "WARNING_SEVERITY_TO_NAME", "kind": "variable", "doc": "
    \n", "annotation": ": Mapping[Literal[20, 30, 35], Literal['info', 'warning', 'alert']]", "default_value": "mappingproxy({20: 'info', 30: 'warning', 35: 'alert'})"}, "bioimageio.spec.summary.WARNING_LEVEL_TO_NAME": {"fullname": "bioimageio.spec.summary.WARNING_LEVEL_TO_NAME", "modulename": "bioimageio.spec.summary", "qualname": "WARNING_LEVEL_TO_NAME", "kind": "variable", "doc": "
    \n", "annotation": ": Mapping[Literal[20, 30, 35, 50], Literal['info', 'warning', 'alert', 'error']]", "default_value": "mappingproxy({20: 'info', 30: 'warning', 35: 'alert', 50: 'error'})"}, "bioimageio.spec.summary.WARNING_NAME_TO_LEVEL": {"fullname": "bioimageio.spec.summary.WARNING_NAME_TO_LEVEL", "modulename": "bioimageio.spec.summary", "qualname": "WARNING_NAME_TO_LEVEL", "kind": "variable", "doc": "
    \n", "annotation": ": Mapping[Literal['info', 'warning', 'alert', 'error'], Literal[20, 30, 35, 50]]", "default_value": "mappingproxy({'info': 20, 'warning': 30, 'alert': 35, 'error': 50})"}, "bioimageio.spec.summary.ValidationEntry": {"fullname": "bioimageio.spec.summary.ValidationEntry", "modulename": "bioimageio.spec.summary", "qualname": "ValidationEntry", "kind": "class", "doc": "
    Usage docs: https://docs.pydantic.dev/2.6/concepts/models/
    \n\n
    A base class for creating Pydantic models.
    \n\n
    Attributes:\n    __class_vars__: The names of classvars defined on the model.\n    __private_attributes__: Metadata about the private attributes of the model.\n    __signature__: The signature for instantiating the model.
    \n\n
    __pydantic_complete__: Whether model building is completed, or if there are still undefined fields.\n__pydantic_core_schema__: The pydantic-core schema used to build the SchemaValidator and SchemaSerializer.\n__pydantic_custom_init__: Whether the model has a custom `__init__` function.\n__pydantic_decorators__: Metadata containing the decorators defined on the model.\n    This replaces `Model.__validators__` and `Model.__root_validators__` from Pydantic V1.\n__pydantic_generic_metadata__: Metadata for generic models; contains data used for a similar purpose to\n    __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.\n__pydantic_parent_namespace__: Parent namespace of the model, used for automatic rebuilding of models.\n__pydantic_post_init__: The name of the post-init method for the model, if defined.\n__pydantic_root_model__: Whether the model is a `RootModel`.\n__pydantic_serializer__: The pydantic-core SchemaSerializer used to dump instances of the model.\n__pydantic_validator__: The pydantic-core SchemaValidator used to validate instances of the model.\n\n__pydantic_extra__: An instance attribute with the values of extra fields from validation when\n    `model_config['extra'] == 'allow'`.\n__pydantic_fields_set__: An instance attribute with the names of fields explicitly set.\n__pydantic_private__: Instance attribute with the values of private attributes set on the model instance.\n
    \n", "bases": "pydantic.main.BaseModel"}, "bioimageio.spec.summary.ValidationEntry.loc": {"fullname": "bioimageio.spec.summary.ValidationEntry.loc", "modulename": "bioimageio.spec.summary", "qualname": "ValidationEntry.loc", "kind": "variable", "doc": "
    \n", "annotation": ": Tuple[Union[int, str], ...]"}, "bioimageio.spec.summary.ValidationEntry.msg": {"fullname": "bioimageio.spec.summary.ValidationEntry.msg", "modulename": "bioimageio.spec.summary", "qualname": "ValidationEntry.msg", "kind": "variable", "doc": "
    \n", "annotation": ": str"}, "bioimageio.spec.summary.ValidationEntry.type": {"fullname": "bioimageio.spec.summary.ValidationEntry.type", "modulename": "bioimageio.spec.summary", "qualname": "ValidationEntry.type", "kind": "variable", "doc": "
    \n", "annotation": ": Union[Literal['no_such_attribute', 'json_invalid', 'json_type', 'recursion_loop', 'missing', 'frozen_field', 'frozen_instance', 'extra_forbidden', 'invalid_key', 'get_attribute_error', 'model_type', 'model_attributes_type', 'dataclass_type', 'dataclass_exact_type', 'none_required', 'greater_than', 'greater_than_equal', 'less_than', 'less_than_equal', 'multiple_of', 'finite_number', 'too_short', 'too_long', 'iterable_type', 'iteration_error', 'string_type', 'string_sub_type', 'string_unicode', 'string_too_short', 'string_too_long', 'string_pattern_mismatch', 'enum', 'dict_type', 'mapping_type', 'list_type', 'tuple_type', 'set_type', 'bool_type', 'bool_parsing', 'int_type', 'int_parsing', 'int_parsing_size', 'int_from_float', 'float_type', 'float_parsing', 'bytes_type', 'bytes_too_short', 'bytes_too_long', 'value_error', 'assertion_error', 'literal_error', 'date_type', 'date_parsing', 'date_from_datetime_parsing', 'date_from_datetime_inexact', 'date_past', 'date_future', 'time_type', 'time_parsing', 'datetime_type', 'datetime_parsing', 'datetime_object_invalid', 'datetime_from_date_parsing', 'datetime_past', 'datetime_future', 'timezone_naive', 'timezone_aware', 'timezone_offset', 'time_delta_type', 'time_delta_parsing', 'frozen_set_type', 'is_instance_of', 'is_subclass_of', 'callable_type', 'union_tag_invalid', 'union_tag_not_found', 'arguments_type', 'missing_argument', 'unexpected_keyword_argument', 'missing_keyword_only_argument', 'unexpected_positional_argument', 'missing_positional_only_argument', 'multiple_argument_values', 'url_type', 'url_parsing', 'url_syntax_violation', 'url_too_long', 'url_scheme', 'uuid_type', 'uuid_parsing', 'uuid_version', 'decimal_type', 'decimal_parsing', 'decimal_max_digits', 'decimal_max_places', 'decimal_whole_digits'], str]"}, "bioimageio.spec.summary.ValidationEntry.model_config": {"fullname": "bioimageio.spec.summary.ValidationEntry.model_config", "modulename": "bioimageio.spec.summary", "qualname": "ValidationEntry.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.summary.ValidationEntry.model_fields": {"fullname": "bioimageio.spec.summary.ValidationEntry.model_fields", "modulename": "bioimageio.spec.summary", "qualname": "ValidationEntry.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'loc': FieldInfo(annotation=Tuple[Union[int, str], ...], required=True), 'msg': FieldInfo(annotation=str, required=True), 'type': FieldInfo(annotation=Union[Literal['no_such_attribute', 'json_invalid', 'json_type', 'recursion_loop', 'missing', 'frozen_field', 'frozen_instance', 'extra_forbidden', 'invalid_key', 'get_attribute_error', 'model_type', 'model_attributes_type', 'dataclass_type', 'dataclass_exact_type', 'none_required', 'greater_than', 'greater_than_equal', 'less_than', 'less_than_equal', 'multiple_of', 'finite_number', 'too_short', 'too_long', 'iterable_type', 'iteration_error', 'string_type', 'string_sub_type', 'string_unicode', 'string_too_short', 'string_too_long', 'string_pattern_mismatch', 'enum', 'dict_type', 'mapping_type', 'list_type', 'tuple_type', 'set_type', 'bool_type', 'bool_parsing', 'int_type', 'int_parsing', 'int_parsing_size', 'int_from_float', 'float_type', 'float_parsing', 'bytes_type', 'bytes_too_short', 'bytes_too_long', 'value_error', 'assertion_error', 'literal_error', 'date_type', 'date_parsing', 'date_from_datetime_parsing', 'date_from_datetime_inexact', 'date_past', 'date_future', 'time_type', 'time_parsing', 'datetime_type', 'datetime_parsing', 'datetime_object_invalid', 'datetime_from_date_parsing', 'datetime_past', 'datetime_future', 'timezone_naive', 'timezone_aware', 'timezone_offset', 'time_delta_type', 'time_delta_parsing', 'frozen_set_type', 'is_instance_of', 'is_subclass_of', 'callable_type', 'union_tag_invalid', 'union_tag_not_found', 'arguments_type', 'missing_argument', 'unexpected_keyword_argument', 'missing_keyword_only_argument', 'unexpected_positional_argument', 'missing_positional_only_argument', 'multiple_argument_values', 'url_type', 'url_parsing', 'url_syntax_violation', 'url_too_long', 'url_scheme', 'uuid_type', 'uuid_parsing', 'uuid_version', 'decimal_type', 'decimal_parsing', 'decimal_max_digits', 'decimal_max_places', 'decimal_whole_digits'], str], required=True)}"}, "bioimageio.spec.summary.ValidationEntry.model_computed_fields": {"fullname": "bioimageio.spec.summary.ValidationEntry.model_computed_fields", "modulename": "bioimageio.spec.summary", "qualname": "ValidationEntry.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.summary.ErrorEntry": {"fullname": "bioimageio.spec.summary.ErrorEntry", "modulename": "bioimageio.spec.summary", "qualname": "ErrorEntry", "kind": "class", "doc": "
    Usage docs: https://docs.pydantic.dev/2.6/concepts/models/
    \n\n
    A base class for creating Pydantic models.
    \n\n
    Attributes:\n    __class_vars__: The names of classvars defined on the model.\n    __private_attributes__: Metadata about the private attributes of the model.\n    __signature__: The signature for instantiating the model.
    \n\n
    __pydantic_complete__: Whether model building is completed, or if there are still undefined fields.\n__pydantic_core_schema__: The pydantic-core schema used to build the SchemaValidator and SchemaSerializer.\n__pydantic_custom_init__: Whether the model has a custom `__init__` function.\n__pydantic_decorators__: Metadata containing the decorators defined on the model.\n    This replaces `Model.__validators__` and `Model.__root_validators__` from Pydantic V1.\n__pydantic_generic_metadata__: Metadata for generic models; contains data used for a similar purpose to\n    __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.\n__pydantic_parent_namespace__: Parent namespace of the model, used for automatic rebuilding of models.\n__pydantic_post_init__: The name of the post-init method for the model, if defined.\n__pydantic_root_model__: Whether the model is a `RootModel`.\n__pydantic_serializer__: The pydantic-core SchemaSerializer used to dump instances of the model.\n__pydantic_validator__: The pydantic-core SchemaValidator used to validate instances of the model.\n\n__pydantic_extra__: An instance attribute with the values of extra fields from validation when\n    `model_config['extra'] == 'allow'`.\n__pydantic_fields_set__: An instance attribute with the names of fields explicitly set.\n__pydantic_private__: Instance attribute with the values of private attributes set on the model instance.\n
    \n", "bases": "ValidationEntry"}, "bioimageio.spec.summary.ErrorEntry.traceback": {"fullname": "bioimageio.spec.summary.ErrorEntry.traceback", "modulename": "bioimageio.spec.summary", "qualname": "ErrorEntry.traceback", "kind": "variable", "doc": "
    \n", "annotation": ": List[str]"}, "bioimageio.spec.summary.ErrorEntry.model_config": {"fullname": "bioimageio.spec.summary.ErrorEntry.model_config", "modulename": "bioimageio.spec.summary", "qualname": "ErrorEntry.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.summary.ErrorEntry.model_fields": {"fullname": "bioimageio.spec.summary.ErrorEntry.model_fields", "modulename": "bioimageio.spec.summary", "qualname": "ErrorEntry.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'loc': FieldInfo(annotation=Tuple[Union[int, str], ...], required=True), 'msg': FieldInfo(annotation=str, required=True), 'type': FieldInfo(annotation=Union[Literal['no_such_attribute', 'json_invalid', 'json_type', 'recursion_loop', 'missing', 'frozen_field', 'frozen_instance', 'extra_forbidden', 'invalid_key', 'get_attribute_error', 'model_type', 'model_attributes_type', 'dataclass_type', 'dataclass_exact_type', 'none_required', 'greater_than', 'greater_than_equal', 'less_than', 'less_than_equal', 'multiple_of', 'finite_number', 'too_short', 'too_long', 'iterable_type', 'iteration_error', 'string_type', 'string_sub_type', 'string_unicode', 'string_too_short', 'string_too_long', 'string_pattern_mismatch', 'enum', 'dict_type', 'mapping_type', 'list_type', 'tuple_type', 'set_type', 'bool_type', 'bool_parsing', 'int_type', 'int_parsing', 'int_parsing_size', 'int_from_float', 'float_type', 'float_parsing', 'bytes_type', 'bytes_too_short', 'bytes_too_long', 'value_error', 'assertion_error', 'literal_error', 'date_type', 'date_parsing', 'date_from_datetime_parsing', 'date_from_datetime_inexact', 'date_past', 'date_future', 'time_type', 'time_parsing', 'datetime_type', 'datetime_parsing', 'datetime_object_invalid', 'datetime_from_date_parsing', 'datetime_past', 'datetime_future', 'timezone_naive', 'timezone_aware', 'timezone_offset', 'time_delta_type', 'time_delta_parsing', 'frozen_set_type', 'is_instance_of', 'is_subclass_of', 'callable_type', 'union_tag_invalid', 'union_tag_not_found', 'arguments_type', 'missing_argument', 'unexpected_keyword_argument', 'missing_keyword_only_argument', 'unexpected_positional_argument', 'missing_positional_only_argument', 'multiple_argument_values', 'url_type', 'url_parsing', 'url_syntax_violation', 'url_too_long', 'url_scheme', 'uuid_type', 'uuid_parsing', 'uuid_version', 'decimal_type', 'decimal_parsing', 'decimal_max_digits', 'decimal_max_places', 'decimal_whole_digits'], str], required=True), 'traceback': FieldInfo(annotation=List[str], required=False, default_factory=list)}"}, "bioimageio.spec.summary.ErrorEntry.model_computed_fields": {"fullname": "bioimageio.spec.summary.ErrorEntry.model_computed_fields", "modulename": "bioimageio.spec.summary", "qualname": "ErrorEntry.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.summary.WarningEntry": {"fullname": "bioimageio.spec.summary.WarningEntry", "modulename": "bioimageio.spec.summary", "qualname": "WarningEntry", "kind": "class", "doc": "
    Usage docs: https://docs.pydantic.dev/2.6/concepts/models/
    \n\n
    A base class for creating Pydantic models.
    \n\n
    Attributes:\n    __class_vars__: The names of classvars defined on the model.\n    __private_attributes__: Metadata about the private attributes of the model.\n    __signature__: The signature for instantiating the model.
    \n\n
    __pydantic_complete__: Whether model building is completed, or if there are still undefined fields.\n__pydantic_core_schema__: The pydantic-core schema used to build the SchemaValidator and SchemaSerializer.\n__pydantic_custom_init__: Whether the model has a custom `__init__` function.\n__pydantic_decorators__: Metadata containing the decorators defined on the model.\n    This replaces `Model.__validators__` and `Model.__root_validators__` from Pydantic V1.\n__pydantic_generic_metadata__: Metadata for generic models; contains data used for a similar purpose to\n    __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.\n__pydantic_parent_namespace__: Parent namespace of the model, used for automatic rebuilding of models.\n__pydantic_post_init__: The name of the post-init method for the model, if defined.\n__pydantic_root_model__: Whether the model is a `RootModel`.\n__pydantic_serializer__: The pydantic-core SchemaSerializer used to dump instances of the model.\n__pydantic_validator__: The pydantic-core SchemaValidator used to validate instances of the model.\n\n__pydantic_extra__: An instance attribute with the values of extra fields from validation when\n    `model_config['extra'] == 'allow'`.\n__pydantic_fields_set__: An instance attribute with the names of fields explicitly set.\n__pydantic_private__: Instance attribute with the values of private attributes set on the model instance.\n
    \n", "bases": "ValidationEntry"}, "bioimageio.spec.summary.WarningEntry.severity": {"fullname": "bioimageio.spec.summary.WarningEntry.severity", "modulename": "bioimageio.spec.summary", "qualname": "WarningEntry.severity", "kind": "variable", "doc": "
    \n", "annotation": ": Literal[20, 30, 35]"}, "bioimageio.spec.summary.WarningEntry.severity_name": {"fullname": "bioimageio.spec.summary.WarningEntry.severity_name", "modulename": "bioimageio.spec.summary", "qualname": "WarningEntry.severity_name", "kind": "variable", "doc": "
    \n", "annotation": ": Literal['info', 'warning', 'alert']"}, "bioimageio.spec.summary.WarningEntry.sync_severity_with_severity_name": {"fullname": "bioimageio.spec.summary.WarningEntry.sync_severity_with_severity_name", "modulename": "bioimageio.spec.summary", "qualname": "WarningEntry.sync_severity_with_severity_name", "kind": "function", "doc": "
    \n", "signature": "(cls, data: Union[Mapping[Any, Any], Any]) -> Any:", "funcdef": "def"}, "bioimageio.spec.summary.WarningEntry.model_config": {"fullname": "bioimageio.spec.summary.WarningEntry.model_config", "modulename": "bioimageio.spec.summary", "qualname": "WarningEntry.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.summary.WarningEntry.model_fields": {"fullname": "bioimageio.spec.summary.WarningEntry.model_fields", "modulename": "bioimageio.spec.summary", "qualname": "WarningEntry.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'loc': FieldInfo(annotation=Tuple[Union[int, str], ...], required=True), 'msg': FieldInfo(annotation=str, required=True), 'type': FieldInfo(annotation=Union[Literal['no_such_attribute', 'json_invalid', 'json_type', 'recursion_loop', 'missing', 'frozen_field', 'frozen_instance', 'extra_forbidden', 'invalid_key', 'get_attribute_error', 'model_type', 'model_attributes_type', 'dataclass_type', 'dataclass_exact_type', 'none_required', 'greater_than', 'greater_than_equal', 'less_than', 'less_than_equal', 'multiple_of', 'finite_number', 'too_short', 'too_long', 'iterable_type', 'iteration_error', 'string_type', 'string_sub_type', 'string_unicode', 'string_too_short', 'string_too_long', 'string_pattern_mismatch', 'enum', 'dict_type', 'mapping_type', 'list_type', 'tuple_type', 'set_type', 'bool_type', 'bool_parsing', 'int_type', 'int_parsing', 'int_parsing_size', 'int_from_float', 'float_type', 'float_parsing', 'bytes_type', 'bytes_too_short', 'bytes_too_long', 'value_error', 'assertion_error', 'literal_error', 'date_type', 'date_parsing', 'date_from_datetime_parsing', 'date_from_datetime_inexact', 'date_past', 'date_future', 'time_type', 'time_parsing', 'datetime_type', 'datetime_parsing', 'datetime_object_invalid', 'datetime_from_date_parsing', 'datetime_past', 'datetime_future', 'timezone_naive', 'timezone_aware', 'timezone_offset', 'time_delta_type', 'time_delta_parsing', 'frozen_set_type', 'is_instance_of', 'is_subclass_of', 'callable_type', 'union_tag_invalid', 'union_tag_not_found', 'arguments_type', 'missing_argument', 'unexpected_keyword_argument', 'missing_keyword_only_argument', 'unexpected_positional_argument', 'missing_positional_only_argument', 'multiple_argument_values', 'url_type', 'url_parsing', 'url_syntax_violation', 'url_too_long', 'url_scheme', 'uuid_type', 'uuid_parsing', 'uuid_version', 'decimal_type', 'decimal_parsing', 'decimal_max_digits', 'decimal_max_places', 'decimal_whole_digits'], str], required=True), 'severity': FieldInfo(annotation=Literal[20, 30, 35], required=False, default=30), 'severity_name': FieldInfo(annotation=Literal['info', 'warning', 'alert'], required=False, default='warning')}"}, "bioimageio.spec.summary.WarningEntry.model_computed_fields": {"fullname": "bioimageio.spec.summary.WarningEntry.model_computed_fields", "modulename": "bioimageio.spec.summary", "qualname": "WarningEntry.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.summary.format_loc": {"fullname": "bioimageio.spec.summary.format_loc", "modulename": "bioimageio.spec.summary", "qualname": "format_loc", "kind": "function", "doc": "
    \n", "signature": "(loc: Tuple[Union[int, str], ...]) -> str:", "funcdef": "def"}, "bioimageio.spec.summary.InstalledPackage": {"fullname": "bioimageio.spec.summary.InstalledPackage", "modulename": "bioimageio.spec.summary", "qualname": "InstalledPackage", "kind": "class", "doc": "
    \n", "bases": "typing_extensions.TypedDict"}, "bioimageio.spec.summary.InstalledPackage.name": {"fullname": "bioimageio.spec.summary.InstalledPackage.name", "modulename": "bioimageio.spec.summary", "qualname": "InstalledPackage.name", "kind": "variable", "doc": "
    \n", "annotation": ": str"}, "bioimageio.spec.summary.InstalledPackage.version": {"fullname": "bioimageio.spec.summary.InstalledPackage.version", "modulename": "bioimageio.spec.summary", "qualname": "InstalledPackage.version", "kind": "variable", "doc": "
    \n", "annotation": ": str"}, "bioimageio.spec.summary.ValidationDetail": {"fullname": "bioimageio.spec.summary.ValidationDetail", "modulename": "bioimageio.spec.summary", "qualname": "ValidationDetail", "kind": "class", "doc": "
    Usage docs: https://docs.pydantic.dev/2.6/concepts/models/
    \n\n
    A base class for creating Pydantic models.
    \n\n
    Attributes:\n    __class_vars__: The names of classvars defined on the model.\n    __private_attributes__: Metadata about the private attributes of the model.\n    __signature__: The signature for instantiating the model.
    \n\n
    __pydantic_complete__: Whether model building is completed, or if there are still undefined fields.\n__pydantic_core_schema__: The pydantic-core schema used to build the SchemaValidator and SchemaSerializer.\n__pydantic_custom_init__: Whether the model has a custom `__init__` function.\n__pydantic_decorators__: Metadata containing the decorators defined on the model.\n    This replaces `Model.__validators__` and `Model.__root_validators__` from Pydantic V1.\n__pydantic_generic_metadata__: Metadata for generic models; contains data used for a similar purpose to\n    __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.\n__pydantic_parent_namespace__: Parent namespace of the model, used for automatic rebuilding of models.\n__pydantic_post_init__: The name of the post-init method for the model, if defined.\n__pydantic_root_model__: Whether the model is a `RootModel`.\n__pydantic_serializer__: The pydantic-core SchemaSerializer used to dump instances of the model.\n__pydantic_validator__: The pydantic-core SchemaValidator used to validate instances of the model.\n\n__pydantic_extra__: An instance attribute with the values of extra fields from validation when\n    `model_config['extra'] == 'allow'`.\n__pydantic_fields_set__: An instance attribute with the names of fields explicitly set.\n__pydantic_private__: Instance attribute with the values of private attributes set on the model instance.\n
    \n", "bases": "pydantic.main.BaseModel"}, "bioimageio.spec.summary.ValidationDetail.name": {"fullname": "bioimageio.spec.summary.ValidationDetail.name", "modulename": "bioimageio.spec.summary", "qualname": "ValidationDetail.name", "kind": "variable", "doc": "
    \n", "annotation": ": str"}, "bioimageio.spec.summary.ValidationDetail.status": {"fullname": "bioimageio.spec.summary.ValidationDetail.status", "modulename": "bioimageio.spec.summary", "qualname": "ValidationDetail.status", "kind": "variable", "doc": "
    \n", "annotation": ": Literal['passed', 'failed']"}, "bioimageio.spec.summary.ValidationDetail.errors": {"fullname": "bioimageio.spec.summary.ValidationDetail.errors", "modulename": "bioimageio.spec.summary", "qualname": "ValidationDetail.errors", "kind": "variable", "doc": "
    \n", "annotation": ": List[bioimageio.spec.summary.ErrorEntry]"}, "bioimageio.spec.summary.ValidationDetail.warnings": {"fullname": "bioimageio.spec.summary.ValidationDetail.warnings", "modulename": "bioimageio.spec.summary", "qualname": "ValidationDetail.warnings", "kind": "variable", "doc": "
    \n", "annotation": ": List[bioimageio.spec.summary.WarningEntry]"}, "bioimageio.spec.summary.ValidationDetail.status_icon": {"fullname": "bioimageio.spec.summary.ValidationDetail.status_icon", "modulename": "bioimageio.spec.summary", "qualname": "ValidationDetail.status_icon", "kind": "variable", "doc": "
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'Linux-man-pages-copyleft-2-para', 'Linux-man-pages-copyleft-var', 'Linux-OpenIB', 'LOOP', 'LPL-1.0', 'LPL-1.02', 'LPPL-1.0', 'LPPL-1.1', 'LPPL-1.2', 'LPPL-1.3a', 'LPPL-1.3c', 'LZMA-SDK-9.11-to-9.20', 'LZMA-SDK-9.22', 'MakeIndex', 'Martin-Birgmeier', 'metamail', 'Minpack', 'MirOS', 'MIT', 'MIT-0', 'MIT-advertising', 'MIT-CMU', 'MIT-enna', 'MIT-feh', 'MIT-Festival', 'MIT-Modern-Variant', 'MIT-open-group', 'MIT-Wu', 'MITNFA', 'Motosoto', 'mpi-permissive', 'mpich2', 'MPL-1.0', 'MPL-1.1', 'MPL-2.0', 'MPL-2.0-no-copyleft-exception', 'mplus', 'MS-LPL', 'MS-PL', 'MS-RL', 'MTLL', 'MulanPSL-1.0', 'MulanPSL-2.0', 'Multics', 'Mup', 'NAIST-2003', 'NASA-1.3', 'Naumen', 'NBPL-1.0', 'NCGL-UK-2.0', 'NCSA', 'Net-SNMP', 'NetCDF', 'Newsletr', 'NGPL', 'NICTA-1.0', 'NIST-PD', 'NIST-PD-fallback', 'NIST-Software', 'NLOD-1.0', 'NLOD-2.0', 'NLPL', 'Nokia', 'NOSL', 'Noweb', 'NPL-1.0', 'NPL-1.1', 'NPOSL-3.0', 'NRL', 'NTP', 'NTP-0', 'O-UDA-1.0', 'OCCT-PL', 'OCLC-2.0', 'ODbL-1.0', 'ODC-By-1.0', 'OFFIS', 'OFL-1.0', 'OFL-1.0-no-RFN', 'OFL-1.0-RFN', 'OFL-1.1', 'OFL-1.1-no-RFN', 'OFL-1.1-RFN', 'OGC-1.0', 'OGDL-Taiwan-1.0', 'OGL-Canada-2.0', 'OGL-UK-1.0', 'OGL-UK-2.0', 'OGL-UK-3.0', 'OGTSL', 'OLDAP-1.1', 'OLDAP-1.2', 'OLDAP-1.3', 'OLDAP-1.4', 'OLDAP-2.0', 'OLDAP-2.0.1', 'OLDAP-2.1', 'OLDAP-2.2', 'OLDAP-2.2.1', 'OLDAP-2.2.2', 'OLDAP-2.3', 'OLDAP-2.4', 'OLDAP-2.5', 'OLDAP-2.6', 'OLDAP-2.7', 'OLDAP-2.8', 'OLFL-1.3', 'OML', 'OpenPBS-2.3', 'OpenSSL', 'OPL-1.0', 'OPL-UK-3.0', 'OPUBL-1.0', 'OSET-PL-2.1', 'OSL-1.0', 'OSL-1.1', 'OSL-2.0', 'OSL-2.1', 'OSL-3.0', 'Parity-6.0.0', 'Parity-7.0.0', 'PDDL-1.0', 'PHP-3.0', 'PHP-3.01', 'Plexus', 'PolyForm-Noncommercial-1.0.0', 'PolyForm-Small-Business-1.0.0', 'PostgreSQL', 'PSF-2.0', 'psfrag', 'psutils', 'Python-2.0', 'Python-2.0.1', 'Qhull', 'QPL-1.0', 'QPL-1.0-INRIA-2004', 'Rdisc', 'RHeCos-1.1', 'RPL-1.1', 'RPL-1.5', 'RPSL-1.0', 'RSA-MD', 'RSCPL', 'Ruby', 'SAX-PD', 'Saxpath', 'SCEA', 'SchemeReport', 'Sendmail', 'Sendmail-8.23', 'SGI-B-1.0', 'SGI-B-1.1', 'SGI-B-2.0', 'SGP4', 'SHL-0.5', 'SHL-0.51', 'SimPL-2.0', 'SISSL', 'SISSL-1.2', 'Sleepycat', 'SMLNJ', 'SMPPL', 'SNIA', 'snprintf', 'Spencer-86', 'Spencer-94', 'Spencer-99', 'SPL-1.0', 'SSH-OpenSSH', 'SSH-short', 'SSPL-1.0', 'SugarCRM-1.1.3', 'SunPro', 'SWL', 'Symlinks', 'TAPR-OHL-1.0', 'TCL', 'TCP-wrappers', 'TermReadKey', 'TMate', 'TORQUE-1.1', 'TOSL', 'TPDL', 'TPL-1.0', 'TTWL', 'TU-Berlin-1.0', 'TU-Berlin-2.0', 'UCAR', 'UCL-1.0', 'Unicode-DFS-2015', 'Unicode-DFS-2016', 'Unicode-TOU', 'UnixCrypt', 'Unlicense', 'UPL-1.0', 'Vim', 'VOSTROM', 'VSL-1.0', 'W3C', 'W3C-19980720', 'W3C-20150513', 'w3m', 'Watcom-1.0', 'Widget-Workshop', 'Wsuipa', 'WTFPL', 'X11', 'X11-distribute-modifications-variant', 'Xdebug-1.03', 'Xerox', 'Xfig', 'XFree86-1.1', 'xinetd', 'xlock', 'Xnet', 'xpp', 'XSkat', 'YPL-1.0', 'YPL-1.1', 'Zed', 'Zend-2.0', 'Zimbra-1.3', 'Zimbra-1.4', 'Zlib', 'zlib-acknowledgement', 'ZPL-1.1', 'ZPL-2.0', 'ZPL-2.1']]": {"tf": 1}, "bioimageio.spec._internal.validated_string.ValidatedString": {"tf": 1}, 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+    /** pdoc search index */const docs = {"version": "0.9.5", "fields": ["qualname", "fullname", "annotation", "default_value", "signature", "bases", "doc"], "ref": "fullname", "documentStore": {"docs": {"bioimageio.spec": {"fullname": "bioimageio.spec", "modulename": "bioimageio.spec", "kind": "module", "doc": "
    \"License\"\n\"PyPI\"\n\"conda-version\"
    \n\n
    Specifications for bioimage.io
    \n\n
    This repository contains specifications defined by the bioimage.io community. These specifications are used for defining fields in YAML 1.2 files which should be named rdf.yaml. Such a rdf.yaml --- along with files referenced in it --- can be downloaded from or uploaded to the bioimage.io website and may be produced or consumed by bioimage.io-compatible consumers (e.g. image analysis software like ilastik).
    \n\n
    bioimage.io-compatible resources must fulfill the following rules:
    \n\n
    Note that the Python package PyYAML does not support YAML 1.2 .\nWe therefore use and recommend ruyaml.\nFor differences see https://ruamelyaml.readthedocs.io/en/latest/pyyaml.
    \n\n
    Please also note that the best way to check whether your rdf.yaml file is bioimage.io-compliant is to call bioimageio.core.validate from the bioimageio.core Python package.\nThe bioimageio.core Python package also provides the bioimageio command line interface (CLI) with the validate command:
    \n\n
    bioimageio validate path/to/your/rdf.yaml\n
    \n\n
    Format version overview
    \n\n
    All bioimage.io description formats are defined as Pydantic models.
    \n\n\n\n\n  \n  \n  \n\n\n\n\n  \n  \n  \n\n\n  \n  \n  \n\n\n  \n  \n  \n\n\n  \n  \n  \n\n\n  \n  \n  \n\n\n  \n  \n  \n\n\n
    typeformat versiondocumentation
    model0.5 
     0.4    		model_descr_v0-5.md 
     model_descr_v0-4.md
    dataset0.3 
     0.2    		dataset_descr_v0-3.md 
     dataset_descr_v0-2.md
    notebook0.3 
     0.2    		notebook_descr_v0-3.md 
     notebook_descr_v0-2.md
    application0.3 
     0.2    		application_descr_v0-3.md 
     application_descr_v0-2.md
    collection0.3 
     0.2    		collection_descr_v0-3.md 
     collection_descr_v0-2.md
    generic0.3 
     0.2    		generic_descr_v0-3.md 
     generic_descr_v0-2.md
    \n\n
    JSON schema
    \n\n
    Simplified descriptions are available as JSON schema:
    \n\n\n\n\n  \n  \n\n\n\n\n  \n  \n\n\n  \n  \n\n\n
    bioimageio.spec versionJSON schema
    latestbioimageio_schema_latest.json
    0.5bioimageio_schema_v0-5.json
    \n\n
    These are primarily intended for syntax highlighting and form generation.
    \n\n
    Examples
    \n\n
    We provide some examples for using rdf.yaml files to describe models, applications, notebooks and datasets.
    \n\n
    \ud83d\udc81 Recommendations
    \n\n
      \n
    • Due to the limitations of storage services such as Zenodo, which does not support subfolders, it is recommended to place other files in the same directory level of the rdf.yaml file and try to avoid using subdirectories.
      • \n
    • Use the bioimageio.core Python package to validate your rdf.yaml file.
      • \n
    • bioimageio.spec keeps evolving. Try to use and upgrade to the most current format version!
      • \n
    \n\n
    \u2328 bioimageio command-line interface (CLI)
    \n\n
    The bioimageio CLI has moved entirely to bioimageio.core.
    \n\n
    \ud83d\udda5 Installation
    \n\n
    bioimageio.spec can be installed with either conda or pip, we recommend to install bioimageio.core instead:
    \n\n
    \n
    conda install -c conda-forge bioimageio.core\n
    \n
    \n\n
    or
    \n\n
    \n
    pip install -U bioimageio.core\n
    \n
    \n\n
    \ud83e\udd1d How to contribute
    \n\n
    \u2665 Contributors
    \n\n
    \n  \"bioimageio.spec\n
    \n\n
    Made with contrib.rocks.
    \n\n
    \u0394 Changelog
    \n\n
    bioimageio.spec Python package
    \n\n
    bioimageio.spec 0.5.0post2
    \n\n
      \n
    • don't fail if CI env var is a string
      • \n
    \n\n
    bioimageio.spec 0.5.0post1
    \n\n
      \n
    • fix _internal.io_utils.identify_bioimageio_yaml_file()
      • \n
    \n\n
    bioimageio.spec 0.5.0
    \n\n
      \n
    • new description formats: generic 0.3, application 0.3, collection 0.3, dataset 0.3, notebook 0.3 and model 0.5.
      • \n
    • various API changes, most important functions:\n
        \n
      • bioimageio.spec.load_description (replaces load_raw_resource_description, interface changed)
        • \n
      • bioimageio.spec.validate_format (new)
        • \n
      • bioimageio.spec.dump_description (replaces serialize_raw_resource_description_to_dict, interface changed)
        • \n
      • bioimageio.spec.update_format (interface changed)
        • \n
      • \n
    • switch from Marshmallow to Pydantic\n
        \n
      • extended validation
        • \n
      • one joint, more precise JSON schema
        • \n
      • \n
    \n\n
    bioimageio.spec 0.4.9
    \n\n
      \n
    • small bugixes
      • \n
    • better type hints
      • \n
    • improved tests
      • \n
    \n\n
    bioimageio.spec 0.4.8post1
    \n\n
      \n
    • add axes and eps to scale_mean_var
      • \n
    \n\n
    bioimageio.spec 0.4.7post1
    \n\n
      \n
    • add simple forward compatibility by treating future format versions as latest known (for the respective resource type)
      • \n
    \n\n
    bioimageio.spec 0.4.6post3
    \n\n
      \n
    • Make CLI output more readable
      • \n
    • find redirected URLs when checking for URL availability
      • \n
    \n\n
    bioimageio.spec 0.4.6post2
    \n\n
      \n
    • Improve error message for non-existing RDF file path given as string
      • \n
    • Improve documentation for model description's documentation field
      • \n
    \n\n
    bioimageio.spec 0.4.6post1
    \n\n\n\n
    bioimageio.spec 0.4.5post16
    \n\n
      \n
    • fix rdf_update of entries in resolve_collection_entries()
      • \n
    \n\n
    bioimageio.spec 0.4.5post15
    \n\n
      \n
    • pass root to enrich_partial_rdf arg of resolve_collection_entries()
      • \n
    \n\n
    bioimageio.spec 0.4.5post14
    \n\n
      \n
    • keep ResourceDescrption.root_path as URI for remote resources. This fixes the collection description as the collection entries are resolved after the collection description has been loaded.
      • \n
    \n\n
    bioimageio.spec 0.4.5post13
    \n\n
      \n
    • new bioimageio.spec.partner module adding validate-partner-collection command if optional 'lxml' dependency is available
      • \n
    \n\n
    bioimageio.spec 0.4.5post12
    \n\n
      \n
    • new env var BIOIMAGEIO_CACHE_WARNINGS_LIMIT (default: 3) to avoid spam from cache hit warnings
      • \n
    • more robust conversion of ImportableSourceFile for absolute paths to relative paths (don't fail on non-path source file)
      • \n
    \n\n
    bioimageio.spec 0.4.5post11
    \n\n
      \n
    • resolve symlinks when transforming absolute to relative paths during serialization; see #438
      • \n
    \n\n
    bioimageio.spec 0.4.5post10
    \n\n
      \n
    • fix loading of collection description with id (id used to be ignored)
      • \n
    \n\n
    bioimageio.spec 0.4.5post9
    \n\n
      \n
    • support loading bioimageio resources by their animal nickname (currently only models have nicknames).
      • \n
    \n\n
    bioimageio.spec 0.4.5post8
    \n\n
      \n
    • any field previously expecting a local relative path is now also accepting an absolute path
      • \n
    • load_raw_resource_description returns a raw resource description which has no relative paths (any relative paths are converted to absolute paths).
      • \n
    \n\n
    bioimageio.spec 0.4.4post7
    \n\n
      \n
    • add command commands.update_rdf()/update-rdf(cli)
      • \n
    \n\n
    bioimageio.spec 0.4.4post2
    \n\n
      \n
    • fix unresolved ImportableSourceFile
      • \n
    \n\n
    bioimageio.spec 0.4.4post1
    \n\n
      \n
    • fix collection description conversion for type field
      • \n
    \n\n
    bioimageio.spec 0.4.3post1
    \n\n
      \n
    • fix to shape validation for model description 0.4: output shape now needs to be bigger than halo
      • \n
    • moved objects from bioimageio.spec.shared.utils to bioimageio.spec.shared[.node_transformer]
      • \n
    • additional keys to validation summary: bioimageio_spec_version, status
      • \n
    \n\n
    bioimageio.spec 0.4.2post4
    \n\n
      \n
    • fixes to generic description:\n
        \n
      • ignore value of field root_path if present in yaml. This field is used internally and always present in RDF nodes.
        • \n
      • \n
    \n\n
    bioimageio.spec 0.4.1.post5
    \n\n
      \n
    • fixes to collection description:\n
        \n
      • RDFs specified directly in collection description are validated correctly even if their source field does not point to an RDF.
        • \n
      • nesting of collection description allowed
        • \n
      • \n
    \n\n
    bioimageio.spec 0.4.1.post4
    \n\n
      \n
    • fixed missing field icon in generic description's raw node
      • \n
    • fixes to collection description:
      \n\n
        \n
      • RDFs specified directly in collection description are validated correctly
        • \n
      • no nesting of collection description allowed for now
        • \n
      • links is no longer an explicit collection entry field (\"moved\" to unknown)
        • \n
      • \n
    \n\n
    bioimageio.spec 0.4.1.post0
    \n\n
      \n
    • new model spec 0.3.5 and 0.4.1
      • \n
    \n\n
    bioimageio.spec 0.4.0.post3
    \n\n
      \n
    • load_raw_resource_description no longer accepts update_to_current_format kwarg (use update_to_format instead)
      • \n
    \n\n
    bioimageio.spec 0.4.0.post2
    \n\n
      \n
    • load_raw_resource_description accepts update_to_format kwarg
      • \n
    \n\n
    Resource Description Format Versions
    \n\n
    generic 0.3.0 / application 0.3.0 / collection 0.3.0 / dataset 0.3.0 / notebook 0.3.0
    \n\n
      \n
    • Breaking canges that are fully auto-convertible\n
        \n
      • dropped download_url
        • \n
      • dropped non-file attachments
        • \n
      • attachments.files moved to attachments.i.source
        • \n
      • \n
    • Non-breaking changes\n
        \n
      • added optional parent field
        • \n
      • \n
    \n\n
    model 0.5.0
    \n\n
    all generic 0.3.0 changes (except models already have the parent field) plus:
    \n\n
      \n
    • Breaking changes that are partially auto-convertible\n
        \n
      • inputs.i.axes are now defined in more detail (same for outputs.i.axes)
        • \n
      • inputs.i.shape moved per axes to inputs.i.axes.size (same for outputs.i.shape)
        • \n
      • new pre-/postprocessing 'fixed_zero_mean_unit_variance' separated from 'zero_mean_unit_variance', where mode=fixed is no longer valid.\n(for scalar values this is auto-convertible.)
        • \n
      • \n
    • Breaking changes that are fully auto-convertible\n
        \n
      • changes in weights.pytorch_state_dict.architecture\n
          \n
        • renamed weights.pytorch_state_dict.architecture.source_file to ...architecture.source
          • \n
        • \n
      • changes in weights.pytorch_state_dict.dependencies\n
          \n
        • only conda environment allowed and specified by weights.pytorch_state_dict.dependencies.source
          • \n
        • new optional field weights.pytorch_state_dict.dependencies.sha256
          • \n
        • \n
      • changes in weights.tensorflow_model_bundle.dependencies\n
          \n
        • same as changes in weights.pytorch_state_dict.dependencies
          • \n
        • \n
      • moved test_inputs to inputs.i.test_tensor
        • \n
      • moved test_outputs to outputs.i.test_tensor
        • \n
      • moved sample_inputs to inputs.i.sample_tensor
        • \n
      • moved sample_outputs to outputs.i.sample_tensor
        • \n
      • renamed inputs.i.name to inputs.i.id
        • \n
      • renamed outputs.i.name to outputs.i.id
        • \n
      • renamed inputs.i.preprocessing.name to inputs.i.preprocessing.id
        • \n
      • renamed outputs.i.postprocessing.name to outputs.i.postprocessing.id
        • \n
      • \n
    • Non-breaking changes:\n
        \n
      • new pre-/postprocessing: id='ensure_dtype' with kwarg dtype
        • \n
      • \n
    \n\n
    generic 0.2.4 and model 0.4.10
    \n\n
      \n
    • Breaking changes that are fully auto-convertible\n
        \n
      • id overwritten with value from config.bioimageio.nickname if available
        • \n
      • \n
    • Non-breaking changes\n
        \n
      • version_number is a new, optional field indicating that an RDF is the nth published version with a given id
        • \n
      • id_emoji is a new, optional field (set from config.bioimageio.nickname_icon if available)
        • \n
      • uploader is a new, optional field with email and an optional name subfields
        • \n
      • \n
    \n\n
    model 0.4.9
    \n\n
      \n
    • Non-breaking changes\n
        \n
      • make pre-/postprocessing kwargs mode and axes always optional for model description 0.3 and 0.4
        • \n
      • \n
    \n\n
    model 0.4.8
    \n\n
      \n
    • Non-breaking changes\n
        \n
      • cite field is now optional
        • \n
      • \n
    \n\n
    generic 0.2.2 and model 0.4.7
    \n\n
      \n
    • Breaking changes that are fully auto-convertible\n
        \n
      • name field may not include '/' or '\\' (conversion removes these)
        • \n
      • \n
    \n\n
    model 0.4.6
    \n\n
      \n
    • Non-breaking changes\n
        \n
      • Implicit output shape can be expanded by inserting null into shape:scale and indicating length of new dimension D in the offset field. Keep in mind that D=2*'offset'.
        • \n
      • \n
    \n\n
    model 0.4.5
    \n\n
      \n
    • Breaking changes that are fully auto-convertible\n
        \n
      • parent field changed to hold a string that is a bioimage.io ID, a URL or a local relative path (and not subfields uri and sha256)
        • \n
      • \n
    \n\n
    model 0.4.4
    \n\n
      \n
    • Non-breaking changes\n
        \n
      • new optional field training_data
        • \n
      • \n
    \n\n
    dataset 0.2.2
    \n\n
      \n
    • Non-breaking changes\n
        \n
      • explicitly define and document dataset description (for now, clone of generic description with type=\"dataset\")
        • \n
      • \n
    \n\n
    model 0.4.3
    \n\n
      \n
    • Non-breaking changes\n
        \n
      • add optional field download_url
        • \n
      • add optional field dependencies to all weight formats (not only pytorch_state_dict)
        • \n
      • add optional pytorch_version to the pytorch_state_dict and torchscript weight formats
        • \n
      • \n
    \n\n
    model 0.4.2
    \n\n
      \n
    • Bug fixes:\n
        \n
      • in a pytorch_state_dict weight entry architecture is no longer optional.
        • \n
      • \n
    \n\n
    collection 0.2.2
    \n\n
      \n
    • Non-breaking changes
      \n\n
        \n
      • make authors, cite, documentation and tags optional
        • \n
      • \n
    • Breaking changes that are fully auto-convertible
      \n\n
        \n
      • Simplifies collection description 0.2.1 by merging resource type fields together to a collection field,\nholindg a list of all resources in the specified collection.
        • \n
      • \n
    \n\n
    generic 0.2.2 / model 0.3.6 / model 0.4.2
    \n\n
      \n
    • Non-breaking changes\n
        \n
      • rdf_source new optional field
        • \n
      • id new optional field
        • \n
      • \n
    \n\n
    collection 0.2.1
    \n\n
      \n
    • First official release, extends generic description with fields application, model, dataset, notebook and (nested)\ncollection, which hold lists linking to respective resources.
      • \n
    \n\n
    generic 0.2.1
    \n\n
      \n
    • Non-breaking changes\n
        \n
      • add optional email and github_user fields to entries in authors
        • \n
      • add optional maintainers field (entries like in authors but  github_user is required (and name is not))
        • \n
      • \n
    \n\n
    model 0.4.1
    \n\n
      \n
    • Breaking changes that are fully auto-convertible
      \n\n
        \n
      • moved field dependencies to weights:pytorch_state_dict:dependencies
        • \n
      • \n
    • Non-breaking changes
      \n\n
        \n
      • documentation field accepts URLs as well
        • \n
      • \n
    \n\n
    model 0.3.5
    \n\n
      \n
    • Non-breaking changes\n
        \n
      • documentation field accepts URLs as well
        • \n
      • \n
    \n\n
    model 0.4.0
    \n\n
      \n
    • Breaking changes
      \n\n
        \n
      • model inputs and outputs may not use duplicated names.
        • \n
      • model field sha256 is required if pytorch_state_dict weights are defined.\nand is now moved to the pytroch_state_dict entry as architecture_sha256.
        • \n
      • \n
    • Breaking changes that are fully auto-convertible
      \n\n
        \n
      • model fields language and framework are removed.
        • \n
      • model field source is renamed architecture and is moved together with kwargs to the pytorch_state_dict\nweights entry (if it exists, otherwise they are removed).
        • \n
      • the weight format pytorch_script was renamed to torchscript.
        • \n
      • \n
    • Other changes\n
        \n
      • model inputs (like outputs) may be defined by scaleing and offseting a reference_tensor
        • \n
      • a maintainers field was added to the model description.
        • \n
      • the entries in the authors field may now additionally contain email or github_user.
        • \n
      • the summary returned by the validate command now also contains a list of warnings.
        • \n
      • an update_format command was added to aid with updating older RDFs by applying auto-conversion.
        • \n
      • \n
    \n\n
    model 0.3.4
    \n\n
      \n
    • Non-breaking changes\n
        \n
      • Add optional parameter eps to scale_range postprocessing.
        • \n
      • \n
    \n\n
    model 0.3.3
    \n\n
      \n
    • Breaking changes that are fully auto-convertible\n
        \n
      • reference_input for implicit output tensor shape was renamed to reference_tensor
        • \n
      • \n
    \n\n
    model 0.3.2
    \n\n
      \n
    • Breaking changes
      \n\n
        \n
      • The RDF file name in a package should be rdf.yaml for all the RDF (not model.yaml);
        • \n
      • Change authors and packaged_by fields from List[str] to List[Author] with Author consisting of a dictionary {name: '<Full name>', affiliation: '<Affiliation>', orcid: 'optional orcid id'};
        • \n
      • Add a mandatory type field to comply with the generic description. Only valid value is 'model' for model description;
        • \n
      • Only allow license identifier from the SPDX license list;
        • \n
      • \n
    • Non-breaking changes
      \n\n
        \n
      • Add optional version field (default 0.1.0) to keep track of model changes;
        • \n
      • Allow the values in the attachments list to be any values besides URI;
        • \n
      • \n
    \n"}, "bioimageio.spec._internal.common_nodes": {"fullname": "bioimageio.spec._internal.common_nodes", "modulename": "bioimageio.spec._internal.common_nodes", "kind": "module", "doc": "
    \n"}, "bioimageio.spec._internal.common_nodes.StringNode": {"fullname": "bioimageio.spec._internal.common_nodes.StringNode", "modulename": "bioimageio.spec._internal.common_nodes", "qualname": "StringNode", "kind": "class", "doc": "
    deprecated! don't use for new spec fields!
    \n", "bases": "collections.UserString, abc.ABC"}, "bioimageio.spec._internal.common_nodes.StringNode.__init__": {"fullname": "bioimageio.spec._internal.common_nodes.StringNode.__init__", "modulename": "bioimageio.spec._internal.common_nodes", "qualname": "StringNode.__init__", "kind": "function", "doc": "
    \n", "signature": "(seq: object)"}, "bioimageio.spec._internal.common_nodes.StringNode.model_fields": {"fullname": "bioimageio.spec._internal.common_nodes.StringNode.model_fields", "modulename": "bioimageio.spec._internal.common_nodes", "qualname": "StringNode.model_fields", "kind": "variable", "doc": "
    \n"}, "bioimageio.spec._internal.common_nodes.CArgs": {"fullname": "bioimageio.spec._internal.common_nodes.CArgs", "modulename": "bioimageio.spec._internal.common_nodes", "qualname": "CArgs", "kind": "variable", "doc": "
    \n", "default_value": "CArgs"}, "bioimageio.spec._internal.common_nodes.Converter": {"fullname": "bioimageio.spec._internal.common_nodes.Converter", "modulename": "bioimageio.spec._internal.common_nodes", "qualname": "Converter", "kind": "class", "doc": "
    Abstract base class for generic types.
    \n\n
    On Python 3.12 and newer, generic classes implicitly inherit from\nGeneric when they declare a parameter list after the class's name::
    \n\n
    class Mapping[KT, VT]:\n    def __getitem__(self, key: KT) -> VT:\n        ...\n    # Etc.\n
    \n\n
    On older versions of Python, however, generic classes have to\nexplicitly inherit from Generic.
    \n\n
    After a class has been declared to be generic, it can then be used as\nfollows::
    \n\n
    def lookup_name[KT, VT](mapping: Mapping[KT, VT], key: KT, default: VT) -> VT:\n    try:\n        return mapping[key]\n    except KeyError:\n        return default\n
    \n", "bases": "typing.Generic[~SRC, ~TGT, typing.Unpack[CArgs]], abc.ABC"}, "bioimageio.spec._internal.common_nodes.Converter.src": {"fullname": "bioimageio.spec._internal.common_nodes.Converter.src", "modulename": "bioimageio.spec._internal.common_nodes", "qualname": "Converter.src", "kind": "variable", "doc": "
    \n", "annotation": ": Final[Type[~SRC]]"}, "bioimageio.spec._internal.common_nodes.Converter.tgt": {"fullname": "bioimageio.spec._internal.common_nodes.Converter.tgt", "modulename": "bioimageio.spec._internal.common_nodes", "qualname": "Converter.tgt", "kind": "variable", "doc": "
    \n", "annotation": ": Final[Type[~TGT]]"}, "bioimageio.spec._internal.common_nodes.Converter.convert": {"fullname": "bioimageio.spec._internal.common_nodes.Converter.convert", "modulename": "bioimageio.spec._internal.common_nodes", "qualname": "Converter.convert", "kind": "function", "doc": "
    convert source node
    \n\n
    Args:\n    source: A bioimageio description node
    \n\n
    Raises:\n    ValidationError: conversion failed
    \n", "signature": "(self, source: ~SRC, /, *args: Unpack[CArgs]) -> ~TGT:", "funcdef": "def"}, "bioimageio.spec._internal.common_nodes.Converter.convert_as_dict": {"fullname": "bioimageio.spec._internal.common_nodes.Converter.convert_as_dict", "modulename": "bioimageio.spec._internal.common_nodes", "qualname": "Converter.convert_as_dict", "kind": "function", "doc": "
    \n", "signature": "(self, source: ~SRC, /, *args: Unpack[CArgs]) -> Dict[str, Any]:", "funcdef": "def"}, "bioimageio.spec._internal.common_nodes.NodeWithExplicitlySetFields": {"fullname": "bioimageio.spec._internal.common_nodes.NodeWithExplicitlySetFields", "modulename": "bioimageio.spec._internal.common_nodes", "qualname": "NodeWithExplicitlySetFields", "kind": "class", "doc": "
    Subpart of a resource description
    \n", "bases": "bioimageio.spec._internal.node.Node"}, "bioimageio.spec._internal.common_nodes.NodeWithExplicitlySetFields.fields_to_set_explicitly": {"fullname": "bioimageio.spec._internal.common_nodes.NodeWithExplicitlySetFields.fields_to_set_explicitly", "modulename": "bioimageio.spec._internal.common_nodes", "qualname": "NodeWithExplicitlySetFields.fields_to_set_explicitly", "kind": "variable", "doc": "
    set set these fields explicitly with their default value if they are not set,\nsuch that they are always included even when dumping with 'exlude_unset'
    \n", "annotation": ": ClassVar[FrozenSet[LiteralString]]", "default_value": "frozenset()"}, "bioimageio.spec._internal.common_nodes.NodeWithExplicitlySetFields.set_fields_explicitly": {"fullname": "bioimageio.spec._internal.common_nodes.NodeWithExplicitlySetFields.set_fields_explicitly", "modulename": "bioimageio.spec._internal.common_nodes", "qualname": "NodeWithExplicitlySetFields.set_fields_explicitly", "kind": "function", "doc": "
    \n", "signature": "(cls, data: Union[Any, Dict[str, Any]]) -> Union[Any, Dict[str, Any]]:", "funcdef": "def"}, "bioimageio.spec._internal.common_nodes.NodeWithExplicitlySetFields.model_config": {"fullname": "bioimageio.spec._internal.common_nodes.NodeWithExplicitlySetFields.model_config", "modulename": "bioimageio.spec._internal.common_nodes", "qualname": "NodeWithExplicitlySetFields.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec._internal.common_nodes.NodeWithExplicitlySetFields.model_fields": {"fullname": "bioimageio.spec._internal.common_nodes.NodeWithExplicitlySetFields.model_fields", "modulename": "bioimageio.spec._internal.common_nodes", "qualname": "NodeWithExplicitlySetFields.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec._internal.common_nodes.NodeWithExplicitlySetFields.model_computed_fields": {"fullname": "bioimageio.spec._internal.common_nodes.NodeWithExplicitlySetFields.model_computed_fields", "modulename": "bioimageio.spec._internal.common_nodes", "qualname": "NodeWithExplicitlySetFields.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec._internal.common_nodes.ResourceDescrBase": {"fullname": "bioimageio.spec._internal.common_nodes.ResourceDescrBase", "modulename": "bioimageio.spec._internal.common_nodes", "qualname": "ResourceDescrBase", "kind": "class", "doc": "
    base class for all resource descriptions
    \n", "bases": "NodeWithExplicitlySetFields, abc.ABC, _ResourceDescrBaseAbstractFieldsProtocol"}, "bioimageio.spec._internal.common_nodes.ResourceDescrBase.fields_to_set_explicitly": {"fullname": "bioimageio.spec._internal.common_nodes.ResourceDescrBase.fields_to_set_explicitly", "modulename": "bioimageio.spec._internal.common_nodes", "qualname": "ResourceDescrBase.fields_to_set_explicitly", "kind": "variable", "doc": "
    set set these fields explicitly with their default value if they are not set,\nsuch that they are always included even when dumping with 'exlude_unset'
    \n", "annotation": ": ClassVar[FrozenSet[LiteralString]]", "default_value": "frozenset({'format_version', 'type'})"}, "bioimageio.spec._internal.common_nodes.ResourceDescrBase.implemented_format_version": {"fullname": "bioimageio.spec._internal.common_nodes.ResourceDescrBase.implemented_format_version", "modulename": "bioimageio.spec._internal.common_nodes", "qualname": "ResourceDescrBase.implemented_format_version", "kind": "variable", "doc": "
    \n", "annotation": ": ClassVar[str]"}, "bioimageio.spec._internal.common_nodes.ResourceDescrBase.implemented_format_version_tuple": {"fullname": "bioimageio.spec._internal.common_nodes.ResourceDescrBase.implemented_format_version_tuple", "modulename": "bioimageio.spec._internal.common_nodes", "qualname": "ResourceDescrBase.implemented_format_version_tuple", "kind": "variable", "doc": "
    \n", "annotation": ": ClassVar[Tuple[int, int, int]]"}, "bioimageio.spec._internal.common_nodes.ResourceDescrBase.validation_summary": {"fullname": "bioimageio.spec._internal.common_nodes.ResourceDescrBase.validation_summary", "modulename": "bioimageio.spec._internal.common_nodes", "qualname": "ResourceDescrBase.validation_summary", "kind": "variable", "doc": "
    \n", "annotation": ": bioimageio.spec.summary.ValidationSummary"}, "bioimageio.spec._internal.common_nodes.ResourceDescrBase.root": {"fullname": "bioimageio.spec._internal.common_nodes.ResourceDescrBase.root", "modulename": "bioimageio.spec._internal.common_nodes", "qualname": "ResourceDescrBase.root", "kind": "variable", "doc": "
    \n", "annotation": ": Union[bioimageio.spec._internal.url.HttpUrl, Annotated[pathlib.Path, PathType(path_type='dir')]]"}, "bioimageio.spec._internal.common_nodes.ResourceDescrBase.load": {"fullname": "bioimageio.spec._internal.common_nodes.ResourceDescrBase.load", "modulename": "bioimageio.spec._internal.common_nodes", "qualname": "ResourceDescrBase.load", "kind": "function", "doc": "
    \n", "signature": "(\tcls,\tdata: Dict[str, YamlValue],\tcontext: Optional[bioimageio.spec._internal.validation_context.ValidationContext] = None) -> Union[Self, bioimageio.spec._internal.common_nodes.InvalidDescr]:", "funcdef": "def"}, "bioimageio.spec._internal.common_nodes.ResourceDescrBase.model_config": {"fullname": "bioimageio.spec._internal.common_nodes.ResourceDescrBase.model_config", "modulename": "bioimageio.spec._internal.common_nodes", "qualname": "ResourceDescrBase.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec._internal.common_nodes.ResourceDescrBase.model_post_init": {"fullname": "bioimageio.spec._internal.common_nodes.ResourceDescrBase.model_post_init", "modulename": "bioimageio.spec._internal.common_nodes", "qualname": "ResourceDescrBase.model_post_init", "kind": "function", "doc": "
    This function is meant to behave like a BaseModel method to initialise private attributes.
    \n\n
    It takes context as an argument since that's what pydantic-core passes when calling it.
    \n\n
    Args:\n    self: The BaseModel instance.\n    __context: The context.
    \n", "signature": "(self: pydantic.main.BaseModel, __context: Any) -> None:", "funcdef": "def"}, "bioimageio.spec._internal.common_nodes.ResourceDescrBase.model_fields": {"fullname": "bioimageio.spec._internal.common_nodes.ResourceDescrBase.model_fields", "modulename": "bioimageio.spec._internal.common_nodes", "qualname": "ResourceDescrBase.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec._internal.common_nodes.ResourceDescrBase.model_computed_fields": {"fullname": "bioimageio.spec._internal.common_nodes.ResourceDescrBase.model_computed_fields", "modulename": "bioimageio.spec._internal.common_nodes", "qualname": "ResourceDescrBase.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec._internal.common_nodes.InvalidDescr": {"fullname": "bioimageio.spec._internal.common_nodes.InvalidDescr", "modulename": "bioimageio.spec._internal.common_nodes", "qualname": "InvalidDescr", "kind": "class", "doc": "
    base class for all resource descriptions
    \n", "bases": "ResourceDescrBase"}, "bioimageio.spec._internal.common_nodes.InvalidDescr.type": {"fullname": "bioimageio.spec._internal.common_nodes.InvalidDescr.type", "modulename": "bioimageio.spec._internal.common_nodes", "qualname": "InvalidDescr.type", "kind": "variable", "doc": "
    \n", "annotation": ": Any"}, "bioimageio.spec._internal.common_nodes.InvalidDescr.format_version": {"fullname": "bioimageio.spec._internal.common_nodes.InvalidDescr.format_version", "modulename": "bioimageio.spec._internal.common_nodes", "qualname": "InvalidDescr.format_version", "kind": "variable", "doc": "
    \n", "annotation": ": Any"}, "bioimageio.spec._internal.common_nodes.InvalidDescr.fields_to_set_explicitly": {"fullname": "bioimageio.spec._internal.common_nodes.InvalidDescr.fields_to_set_explicitly", "modulename": "bioimageio.spec._internal.common_nodes", "qualname": "InvalidDescr.fields_to_set_explicitly", "kind": "variable", "doc": "
    set set these fields explicitly with their default value if they are not set,\nsuch that they are always included even when dumping with 'exlude_unset'
    \n", "annotation": ": ClassVar[FrozenSet[LiteralString]]", "default_value": "frozenset()"}, "bioimageio.spec._internal.common_nodes.InvalidDescr.implemented_format_version": {"fullname": "bioimageio.spec._internal.common_nodes.InvalidDescr.implemented_format_version", "modulename": "bioimageio.spec._internal.common_nodes", "qualname": "InvalidDescr.implemented_format_version", "kind": "variable", "doc": "
    \n", "annotation": ": ClassVar[str]", "default_value": "'unknown'"}, "bioimageio.spec._internal.common_nodes.InvalidDescr.implemented_format_version_tuple": {"fullname": "bioimageio.spec._internal.common_nodes.InvalidDescr.implemented_format_version_tuple", "modulename": "bioimageio.spec._internal.common_nodes", "qualname": "InvalidDescr.implemented_format_version_tuple", "kind": "variable", "doc": "
    \n", "annotation": ": ClassVar[Tuple[int, int, int]]", "default_value": "(0, 0, 0)"}, "bioimageio.spec._internal.common_nodes.InvalidDescr.model_config": {"fullname": "bioimageio.spec._internal.common_nodes.InvalidDescr.model_config", "modulename": "bioimageio.spec._internal.common_nodes", "qualname": "InvalidDescr.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'allow', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True, 'title': 'An invalid resource description'}"}, "bioimageio.spec._internal.common_nodes.InvalidDescr.model_fields": {"fullname": "bioimageio.spec._internal.common_nodes.InvalidDescr.model_fields", "modulename": "bioimageio.spec._internal.common_nodes", "qualname": "InvalidDescr.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'type': FieldInfo(annotation=Any, required=False, default='unknown'), 'format_version': FieldInfo(annotation=Any, required=False, default='unknown')}"}, "bioimageio.spec._internal.common_nodes.InvalidDescr.model_computed_fields": {"fullname": "bioimageio.spec._internal.common_nodes.InvalidDescr.model_computed_fields", "modulename": "bioimageio.spec._internal.common_nodes", "qualname": "InvalidDescr.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec._internal.common_nodes.KwargsNode": {"fullname": "bioimageio.spec._internal.common_nodes.KwargsNode", "modulename": "bioimageio.spec._internal.common_nodes", "qualname": "KwargsNode", "kind": "class", "doc": "
    Subpart of a resource description
    \n", "bases": "bioimageio.spec._internal.node.Node"}, "bioimageio.spec._internal.common_nodes.KwargsNode.get": {"fullname": "bioimageio.spec._internal.common_nodes.KwargsNode.get", "modulename": "bioimageio.spec._internal.common_nodes", "qualname": "KwargsNode.get", "kind": "function", "doc": "
    \n", "signature": "(self, item: str, default: Any = None) -> Any:", "funcdef": "def"}, "bioimageio.spec._internal.common_nodes.KwargsNode.model_config": {"fullname": "bioimageio.spec._internal.common_nodes.KwargsNode.model_config", "modulename": "bioimageio.spec._internal.common_nodes", "qualname": "KwargsNode.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec._internal.common_nodes.KwargsNode.model_fields": {"fullname": "bioimageio.spec._internal.common_nodes.KwargsNode.model_fields", "modulename": "bioimageio.spec._internal.common_nodes", "qualname": "KwargsNode.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec._internal.common_nodes.KwargsNode.model_computed_fields": {"fullname": "bioimageio.spec._internal.common_nodes.KwargsNode.model_computed_fields", "modulename": "bioimageio.spec._internal.common_nodes", "qualname": "KwargsNode.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec._internal.constants": {"fullname": "bioimageio.spec._internal.constants", "modulename": "bioimageio.spec._internal.constants", "kind": "module", "doc": "
    \n"}, "bioimageio.spec._internal.constants.DOI_REGEX": {"fullname": "bioimageio.spec._internal.constants.DOI_REGEX", "modulename": "bioimageio.spec._internal.constants", "qualname": "DOI_REGEX", "kind": "variable", "doc": "
    \n", "default_value": "'^10\\\\.[0-9]{4}.+$'"}, "bioimageio.spec._internal.constants.IN_PACKAGE_MESSAGE": {"fullname": "bioimageio.spec._internal.constants.IN_PACKAGE_MESSAGE", "modulename": "bioimageio.spec._internal.constants", "qualname": "IN_PACKAGE_MESSAGE", "kind": "variable", "doc": "
    DEPRECATED, use ImportantFileSource to indicate that a file source should be included in a package
    \n", "default_value": "'\u2208\ud83d\udce6 '"}, "bioimageio.spec._internal.constants.SHA256_HINT": {"fullname": "bioimageio.spec._internal.constants.SHA256_HINT", "modulename": "bioimageio.spec._internal.constants", "qualname": "SHA256_HINT", "kind": "variable", "doc": "
    \n", "default_value": ""You can drag and drop your file to this\\n[online tool](http://emn178.github.io/online-tools/sha256_checksum.html) to generate a SHA256 in your browser.\\nOr you can generate a SHA256 checksum with Python's `hashlib`,\\n[here is a codesnippet](https://gist.github.com/FynnBe/e64460463df89439cff218bbf59c1100).""}, "bioimageio.spec._internal.constants.SI_UNIT_REGEX": {"fullname": "bioimageio.spec._internal.constants.SI_UNIT_REGEX", "modulename": "bioimageio.spec._internal.constants", "qualname": "SI_UNIT_REGEX", "kind": "variable", "doc": "
    \n", "default_value": "'^(Q|R|Y|Z|E|P|T|G|M|k|h|da|d|c|m|\u00b5|n|p|f|a|z|y|r|q)?(m|g|s|A|K|mol|cd|Hz|N|Pa|J|W|C|V|F|\u03a9|S|Wb|T|H|lm|lx|Bq|Gy|Sv|kat|l|L)(\\\\^[+-]?[1-9]\\\\d*)?((\u00b7(Q|R|Y|Z|E|P|T|G|M|k|h|da|d|c|m|\u00b5|n|p|f|a|z|y|r|q)?(m|g|s|A|K|mol|cd|Hz|N|Pa|J|W|C|V|F|\u03a9|S|Wb|T|H|lm|lx|Bq|Gy|Sv|kat|l|L)(\\\\^[+-]?[1-9]\\\\d*)?)|(/(Q|R|Y|Z|E|P|T|G|M|k|h|da|d|c|m|\u00b5|n|p|f|a|z|y|r|q)?(m|g|s|A|K|mol|cd|Hz|N|Pa|J|W|C|V|F|\u03a9|S|Wb|T|H|lm|lx|Bq|Gy|Sv|kat|l|L)(\\\\^+?[1-9]\\\\d*)?))*$'"}, "bioimageio.spec._internal.constants.MinMax": {"fullname": "bioimageio.spec._internal.constants.MinMax", "modulename": "bioimageio.spec._internal.constants", "qualname": "MinMax", "kind": "class", "doc": "
    MinMax(min, max)
    \n", "bases": "typing.NamedTuple"}, "bioimageio.spec._internal.constants.MinMax.__init__": {"fullname": "bioimageio.spec._internal.constants.MinMax.__init__", "modulename": "bioimageio.spec._internal.constants", "qualname": "MinMax.__init__", "kind": "function", "doc": "
    Create new instance of MinMax(min, max)
    \n", "signature": "(\tmin: ForwardRef('Union[int, float]'),\tmax: ForwardRef('Union[int, float]'))"}, "bioimageio.spec._internal.constants.MinMax.min": {"fullname": "bioimageio.spec._internal.constants.MinMax.min", "modulename": "bioimageio.spec._internal.constants", "qualname": "MinMax.min", "kind": "variable", "doc": "
    Alias for field number 0
    \n", "annotation": ": Union[int, float]"}, "bioimageio.spec._internal.constants.MinMax.max": {"fullname": "bioimageio.spec._internal.constants.MinMax.max", "modulename": "bioimageio.spec._internal.constants", "qualname": "MinMax.max", "kind": "variable", "doc": "
    Alias for field number 1
    \n", "annotation": ": Union[int, float]"}, "bioimageio.spec._internal.constants.DTYPE_LIMITS": {"fullname": "bioimageio.spec._internal.constants.DTYPE_LIMITS", "modulename": "bioimageio.spec._internal.constants", "qualname": "DTYPE_LIMITS", "kind": "variable", "doc": "
    \n", "default_value": "mappingproxy({'float32': MinMax(min=-3.4028235e+38, max=3.4028235e+38), 'float64': MinMax(min=-1.7976931348623157e+308, max=1.7976931348623157e+308), 'uint8': MinMax(min=0, max=255), 'int8': MinMax(min=-128, max=127), 'uint16': MinMax(min=0, max=65535), 'int16': MinMax(min=-32768, max=32767), 'uint32': MinMax(min=0, max=4294967295), 'int32': MinMax(min=-2147483648, max=2147483647), 'uint64': MinMax(min=0, max=18446744073709551615), 'int64': MinMax(min=-9223372036854775808, max=9223372036854775807)})"}, "bioimageio.spec._internal.constants.KNOWN_GH_USERS": {"fullname": "bioimageio.spec._internal.constants.KNOWN_GH_USERS", "modulename": "bioimageio.spec._internal.constants", "qualname": "KNOWN_GH_USERS", "kind": "variable", "doc": "
    \n", "annotation": ": Set[str]", "default_value": "{'lenkaback', 'k-dominik', 'constantinpape', 'aaitorg', 'danifranco', 'bioimageiobot', 'ctr26', 'iarganda', 'donglaiw', 'esgomezm', 'fynnbe', 'jansanrom', 'clementcaporal', 'githubuser2', 'ivanhcenalmor', 'pedgomgal1', 'cfusterbarcelo', 'oeway', 'carlosuc3m'}"}, "bioimageio.spec._internal.constants.N_KNOWN_GH_USERS": {"fullname": "bioimageio.spec._internal.constants.N_KNOWN_GH_USERS", "modulename": "bioimageio.spec._internal.constants", "qualname": "N_KNOWN_GH_USERS", "kind": "variable", "doc": "
    \n", "default_value": "19"}, "bioimageio.spec._internal.constants.KNOWN_INVALID_GH_USERS": {"fullname": "bioimageio.spec._internal.constants.KNOWN_INVALID_GH_USERS", "modulename": "bioimageio.spec._internal.constants", "qualname": "KNOWN_INVALID_GH_USERS", "kind": "variable", "doc": "
    \n", "annotation": ": Set[str]", "default_value": "{'arratemunoz', 'lmescu'}"}, "bioimageio.spec._internal.constants.N_KNOWN_INVALID_GH_USERS": {"fullname": "bioimageio.spec._internal.constants.N_KNOWN_INVALID_GH_USERS", "modulename": "bioimageio.spec._internal.constants", "qualname": "N_KNOWN_INVALID_GH_USERS", "kind": "variable", "doc": "
    \n", "default_value": "2"}, "bioimageio.spec._internal.constants.VERSION": {"fullname": "bioimageio.spec._internal.constants.VERSION", "modulename": "bioimageio.spec._internal.constants", "qualname": "VERSION", "kind": "variable", "doc": "
    \n", "annotation": ": str", "default_value": "'0.5.0post2'"}, "bioimageio.spec._internal.constants.TAG_CATEGORIES": {"fullname": "bioimageio.spec._internal.constants.TAG_CATEGORIES", "modulename": "bioimageio.spec._internal.constants", "qualname": "TAG_CATEGORIES", "kind": "variable", "doc": "
    \n", "annotation": ": Mapping[str, Mapping[str, Sequence[str]]]", "default_value": "{'model': {'modality': ['electron-microscopy', 'cryo-electron-microscopy', 'fluorescence-light-microscopy', 'transmission-light-microscopy', 'super-resolution-microscopy', 'x-ray-microscopy', 'force-microscopy', 'high-content-imaging', 'whole-slide-imaging', 'other'], 'dims': ['2d', '3d', '2d-t', '3d-t'], 'content': ['cells', 'nuclei', 'extracellular-vesicles', 'tissue', 'plant', 'mitochondria', 'vasculature', 'cell-membrane', 'brain', 'whole-organism'], 'framework': ['tensorflow', 'pytorch', 'tensorflow.js'], 'software': ['ilastik', 'imagej', 'fiji', 'imjoy', 'deepimagej', 'n2v'], 'network': ['unet', 'densenet', 'resnet', 'inception', 'shufflenet'], 'task': ['semantic-segmentation', 'instance-segmentation', 'object-detection', 'image-classification', 'denoising', 'image-restoration', 'image-reconstruction', 'in-silico-labeling']}}"}, "bioimageio.spec._internal.docs_utils": {"fullname": "bioimageio.spec._internal.docs_utils", "modulename": "bioimageio.spec._internal.docs_utils", "kind": "module", "doc": "
    \n"}, "bioimageio.spec._internal.docs_utils.get_ref_url": {"fullname": "bioimageio.spec._internal.docs_utils.get_ref_url", "modulename": "bioimageio.spec._internal.docs_utils", "qualname": "get_ref_url", "kind": "function", "doc": "
    get github url with line range fragment to reference implementation from non-raw github file url
    \n\n
    example:
    \n\n
    \n
    >>> get_ref_url(\n...     "class",\n...     "Binarize",\n...     "https://github.com/bioimage-io/core-bioimage-io-python/blob/main/bioimageio/core/prediction_pipeline/_processing.py"\n... )\n'https://github.com/bioimage-io/core-bioimage-io-python/blob/main/bioimageio/core/prediction_pipeline/_processing.py#L120-L127'\n
    \n
    \n", "signature": "(\ttype_: Literal['class', 'function'],\tname: str,\tgithub_file_url: str) -> str:", "funcdef": "def"}, "bioimageio.spec._internal.field_validation": {"fullname": "bioimageio.spec._internal.field_validation", "modulename": "bioimageio.spec._internal.field_validation", "kind": "module", "doc": "
    \n"}, "bioimageio.spec._internal.field_validation.is_valid_yaml_leaf_value": {"fullname": "bioimageio.spec._internal.field_validation.is_valid_yaml_leaf_value", "modulename": "bioimageio.spec._internal.field_validation", "qualname": "is_valid_yaml_leaf_value", "kind": "function", "doc": "
    \n", "signature": "(value: Any) -> bool:", "funcdef": "def"}, "bioimageio.spec._internal.field_validation.is_valid_yaml_key": {"fullname": "bioimageio.spec._internal.field_validation.is_valid_yaml_key", "modulename": "bioimageio.spec._internal.field_validation", "qualname": "is_valid_yaml_key", "kind": "function", "doc": "
    \n", "signature": "(value: Union[Any, Sequence[Any]]) -> bool:", "funcdef": "def"}, "bioimageio.spec._internal.field_validation.is_valid_yaml_mapping": {"fullname": "bioimageio.spec._internal.field_validation.is_valid_yaml_mapping", "modulename": "bioimageio.spec._internal.field_validation", "qualname": "is_valid_yaml_mapping", "kind": "function", "doc": "
    \n", "signature": "(value: Union[Any, Mapping[Any, Any]]) -> bool:", "funcdef": "def"}, "bioimageio.spec._internal.field_validation.is_valid_yaml_sequence": {"fullname": "bioimageio.spec._internal.field_validation.is_valid_yaml_sequence", "modulename": "bioimageio.spec._internal.field_validation", "qualname": "is_valid_yaml_sequence", "kind": "function", "doc": "
    \n", "signature": "(value: Union[Any, Sequence[Any]]) -> bool:", "funcdef": "def"}, "bioimageio.spec._internal.field_validation.is_valid_yaml_value": {"fullname": "bioimageio.spec._internal.field_validation.is_valid_yaml_value", "modulename": "bioimageio.spec._internal.field_validation", "qualname": "is_valid_yaml_value", "kind": "function", "doc": "
    \n", "signature": "(value: Any) -> bool:", "funcdef": "def"}, "bioimageio.spec._internal.field_validation.validate_unique_entries": {"fullname": "bioimageio.spec._internal.field_validation.validate_unique_entries", "modulename": "bioimageio.spec._internal.field_validation", "qualname": "validate_unique_entries", "kind": "function", "doc": "
    \n", "signature": "(seq: Sequence[Hashable]):", "funcdef": "def"}, "bioimageio.spec._internal.field_validation.validate_gh_user": {"fullname": "bioimageio.spec._internal.field_validation.validate_gh_user", "modulename": "bioimageio.spec._internal.field_validation", "qualname": "validate_gh_user", "kind": "function", "doc": "
    \n", "signature": "(username: str, hotfix_known_errorenous_names: bool = True) -> str:", "funcdef": "def"}, "bioimageio.spec._internal.field_warning": {"fullname": "bioimageio.spec._internal.field_warning", "modulename": "bioimageio.spec._internal.field_warning", "kind": "module", "doc": "
    \n"}, "bioimageio.spec._internal.field_warning.ValidatorFunction": {"fullname": "bioimageio.spec._internal.field_warning.ValidatorFunction", "modulename": "bioimageio.spec._internal.field_warning", "qualname": "ValidatorFunction", "kind": "variable", "doc": "
    \n", "default_value": "typing.Union[typing.Callable[[typing.Any], typing.Any], typing.Callable[[typing.Any, pydantic_core.core_schema.ValidationInfo], typing.Any]]"}, "bioimageio.spec._internal.field_warning.AnnotationMetaData": {"fullname": "bioimageio.spec._internal.field_warning.AnnotationMetaData", "modulename": "bioimageio.spec._internal.field_warning", "qualname": "AnnotationMetaData", "kind": "variable", "doc": "
    \n", "default_value": "typing.Union[annotated_types.BaseMetadata, annotated_types.GroupedMetadata]"}, "bioimageio.spec._internal.field_warning.warn": {"fullname": "bioimageio.spec._internal.field_warning.warn", "modulename": "bioimageio.spec._internal.field_warning", "qualname": "warn", "kind": "function", "doc": "
    treat a type or its annotation metadata as a warning condition
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    \n", "signature": "(\tfunc: Union[pydantic.functional_validators._V2ValidatorClsMethod, Callable[[Any, pydantic_core.core_schema.ValidationInfo], Any], pydantic.functional_validators._OnlyValueValidatorClsMethod, Callable[[Any], Any]],\tmode: Literal['after', 'before', 'plain', 'wrap'],\tvalue: Any,\tinfo: pydantic_core.core_schema.ValidationInfo) -> Any:", "funcdef": "def"}, "bioimageio.spec._internal.field_warning.as_warning": {"fullname": "bioimageio.spec._internal.field_warning.as_warning", "modulename": "bioimageio.spec._internal.field_warning", "qualname": "as_warning", "kind": "function", "doc": "
    turn validation function into a no-op, based on warning level
    \n", "signature": "(\tfunc: Union[pydantic.functional_validators._V2ValidatorClsMethod, Callable[[Any, pydantic_core.core_schema.ValidationInfo], Any], pydantic.functional_validators._OnlyValueValidatorClsMethod, Callable[[Any], Any]],\t*,\tmode: Literal['after', 'before', 'plain', 'wrap'] = 'after',\tseverity: Literal[20, 30, 35] = 30,\tmsg: Optional[LiteralString] = None,\tmsg_context: Optional[Dict[str, Any]] = None) -> Union[Callable[[Any], Any], Callable[[Any, pydantic_core.core_schema.ValidationInfo], Any]]:", "funcdef": "def"}, "bioimageio.spec._internal.field_warning.AfterWarner": {"fullname": "bioimageio.spec._internal.field_warning.AfterWarner", "modulename": "bioimageio.spec._internal.field_warning", "qualname": "AfterWarner", "kind": "class", "doc": "
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    \n", "bases": "pydantic.functional_validators.AfterValidator"}, "bioimageio.spec._internal.field_warning.AfterWarner.__init__": {"fullname": "bioimageio.spec._internal.field_warning.AfterWarner.__init__", "modulename": "bioimageio.spec._internal.field_warning", "qualname": "AfterWarner.__init__", "kind": "function", "doc": "
    \n", "signature": "(\tfunc: 'core_schema.NoInfoValidatorFunction | core_schema.WithInfoValidatorFunction',\tseverity: Literal[20, 30, 35] = 30,\tmsg: Optional[LiteralString] = None,\tcontext: Optional[Dict[str, Any]] = None)"}, "bioimageio.spec._internal.field_warning.AfterWarner.severity": {"fullname": "bioimageio.spec._internal.field_warning.AfterWarner.severity", "modulename": "bioimageio.spec._internal.field_warning", "qualname": "AfterWarner.severity", "kind": "variable", "doc": "
    \n", "annotation": ": Literal[20, 30, 35]"}, "bioimageio.spec._internal.field_warning.AfterWarner.msg": {"fullname": "bioimageio.spec._internal.field_warning.AfterWarner.msg", "modulename": "bioimageio.spec._internal.field_warning", "qualname": "AfterWarner.msg", "kind": "variable", "doc": "
    \n", "annotation": ": Optional[LiteralString]"}, "bioimageio.spec._internal.field_warning.AfterWarner.context": {"fullname": "bioimageio.spec._internal.field_warning.AfterWarner.context", "modulename": "bioimageio.spec._internal.field_warning", "qualname": "AfterWarner.context", "kind": "variable", "doc": "
    \n", "annotation": ": Optional[Dict[str, Any]]"}, "bioimageio.spec._internal.field_warning.BeforeWarner": {"fullname": "bioimageio.spec._internal.field_warning.BeforeWarner", "modulename": "bioimageio.spec._internal.field_warning", "qualname": "BeforeWarner", "kind": "class", "doc": "
    Like BeforeValidator, but wraps validation func as_warning
    \n", "bases": "pydantic.functional_validators.BeforeValidator"}, "bioimageio.spec._internal.field_warning.BeforeWarner.__init__": {"fullname": "bioimageio.spec._internal.field_warning.BeforeWarner.__init__", "modulename": "bioimageio.spec._internal.field_warning", "qualname": "BeforeWarner.__init__", "kind": "function", "doc": "
    \n", "signature": "(\tfunc: 'core_schema.NoInfoValidatorFunction | core_schema.WithInfoValidatorFunction',\tseverity: Literal[20, 30, 35] = 30,\tmsg: Optional[LiteralString] = None,\tcontext: Optional[Dict[str, Any]] = None)"}, "bioimageio.spec._internal.field_warning.BeforeWarner.severity": {"fullname": "bioimageio.spec._internal.field_warning.BeforeWarner.severity", "modulename": "bioimageio.spec._internal.field_warning", "qualname": "BeforeWarner.severity", "kind": "variable", "doc": "
    \n", "annotation": ": Literal[20, 30, 35]"}, "bioimageio.spec._internal.field_warning.BeforeWarner.msg": {"fullname": "bioimageio.spec._internal.field_warning.BeforeWarner.msg", "modulename": "bioimageio.spec._internal.field_warning", "qualname": "BeforeWarner.msg", "kind": "variable", "doc": "
    \n", "annotation": ": Optional[LiteralString]"}, "bioimageio.spec._internal.field_warning.BeforeWarner.context": {"fullname": "bioimageio.spec._internal.field_warning.BeforeWarner.context", "modulename": "bioimageio.spec._internal.field_warning", "qualname": "BeforeWarner.context", "kind": "variable", "doc": "
    \n", "annotation": ": Optional[Dict[str, Any]]"}, "bioimageio.spec._internal.field_warning.issue_warning": {"fullname": "bioimageio.spec._internal.field_warning.issue_warning", "modulename": "bioimageio.spec._internal.field_warning", "qualname": "issue_warning", "kind": "function", "doc": "
    \n", "signature": "(\tmsg: LiteralString,\t*,\tvalue: Any,\tseverity: Literal[20, 30, 35] = 30,\tmsg_context: Optional[Dict[str, Any]] = None):", "funcdef": "def"}, "bioimageio.spec._internal.io": {"fullname": "bioimageio.spec._internal.io", "modulename": "bioimageio.spec._internal.io", "kind": "module", "doc": "
    \n"}, "bioimageio.spec._internal.io.Sha256": {"fullname": "bioimageio.spec._internal.io.Sha256", "modulename": "bioimageio.spec._internal.io", "qualname": "Sha256", "kind": "class", "doc": "
    SHA-256 hash value
    \n", "bases": "pydantic.main.BaseModel, typing.Generic[~RootModelRootType]"}, "bioimageio.spec._internal.io.RelativePathBase": {"fullname": "bioimageio.spec._internal.io.RelativePathBase", "modulename": "bioimageio.spec._internal.io", "qualname": "RelativePathBase", "kind": "class", "doc": "
    Usage docs: https://docs.pydantic.dev/2.6/concepts/models/#rootmodel-and-custom-root-types
    \n\n
    A Pydantic BaseModel for the root object of the model.
    \n\n
    Attributes:\n    root: The root object of the model.\n    __pydantic_root_model__: Whether the model is a RootModel.\n    __pydantic_private__: Private fields in the model.\n    __pydantic_extra__: Extra fields in the model.
    \n", "bases": "pydantic.root_model.RootModel[PurePath], typing.Generic[~AbsolutePathT]"}, "bioimageio.spec._internal.io.RelativePathBase.path": {"fullname": "bioimageio.spec._internal.io.RelativePathBase.path", "modulename": "bioimageio.spec._internal.io", "qualname": "RelativePathBase.path", "kind": "variable", "doc": "
    \n", "annotation": ": pathlib.PurePath"}, "bioimageio.spec._internal.io.RelativePathBase.absolute": {"fullname": "bioimageio.spec._internal.io.RelativePathBase.absolute", "modulename": "bioimageio.spec._internal.io", "qualname": "RelativePathBase.absolute", "kind": "variable", "doc": "
    the absolute path/url (resolved at time of initialization with the root of the ValidationContext)
    \n", "annotation": ": ~AbsolutePathT"}, "bioimageio.spec._internal.io.RelativePathBase.model_post_init": {"fullname": "bioimageio.spec._internal.io.RelativePathBase.model_post_init", "modulename": "bioimageio.spec._internal.io", "qualname": "RelativePathBase.model_post_init", "kind": "function", "doc": "
    We need to both initialize private attributes and call the user-defined model_post_init\nmethod.
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    \n", "signature": "(\tself,\troot: Union[bioimageio.spec._internal.root_url.RootHttpUrl, Annotated[pathlib.Path, PathType(path_type='dir'), Predicate(func=<function PurePath.is_absolute>)], pydantic_core._pydantic_core.Url]) -> ~AbsolutePathT:", "funcdef": "def"}, "bioimageio.spec._internal.io.RelativePath": {"fullname": "bioimageio.spec._internal.io.RelativePath", "modulename": "bioimageio.spec._internal.io", "qualname": "RelativePath", "kind": "class", "doc": "
    Usage docs: https://docs.pydantic.dev/2.6/concepts/models/#rootmodel-and-custom-root-types
    \n\n
    A Pydantic BaseModel for the root object of the model.
    \n\n
    Attributes:\n    root: The root object of the model.\n    __pydantic_root_model__: Whether the model is a RootModel.\n    __pydantic_private__: Private fields in the model.\n    __pydantic_extra__: Extra fields in the model.
    \n", "bases": "pydantic.root_model.RootModel[PurePath], typing.Generic[~AbsolutePathT]"}, "bioimageio.spec._internal.io.RelativePath.get_absolute": {"fullname": "bioimageio.spec._internal.io.RelativePath.get_absolute", "modulename": "bioimageio.spec._internal.io", "qualname": "RelativePath.get_absolute", "kind": "function", "doc": "
    \n", "signature": "(\tself,\troot: bioimageio.spec._internal.root_url.RootHttpUrl | pathlib.Path | pydantic_core._pydantic_core.Url) -> Union[Annotated[pathlib.Path, PathType(path_type='file'), Predicate(func=<function PurePath.is_absolute at 0x7afca4145940>)], Annotated[pathlib.Path, PathType(path_type='dir'), Predicate(func=<function PurePath.is_absolute at 0x7afca4145940>)], bioimageio.spec._internal.url.HttpUrl]:", "funcdef": "def"}, "bioimageio.spec._internal.io.RelativeFilePath": {"fullname": "bioimageio.spec._internal.io.RelativeFilePath", "modulename": "bioimageio.spec._internal.io", "qualname": "RelativeFilePath", "kind": "class", "doc": "
    Usage docs: https://docs.pydantic.dev/2.6/concepts/models/#rootmodel-and-custom-root-types
    \n\n
    A Pydantic BaseModel for the root object of the model.
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    Attributes:\n    root: The root object of the model.\n    __pydantic_root_model__: Whether the model is a RootModel.\n    __pydantic_private__: Private fields in the model.\n    __pydantic_extra__: Extra fields in the model.
    \n", "bases": "pydantic.root_model.RootModel[PurePath], typing.Generic[~AbsolutePathT]"}, "bioimageio.spec._internal.io.RelativeFilePath.get_absolute": {"fullname": "bioimageio.spec._internal.io.RelativeFilePath.get_absolute", "modulename": "bioimageio.spec._internal.io", "qualname": "RelativeFilePath.get_absolute", "kind": "function", "doc": "
    \n", "signature": "(\tself,\troot: bioimageio.spec._internal.root_url.RootHttpUrl | pathlib.Path | pydantic_core._pydantic_core.Url) -> Union[Annotated[pathlib.Path, PathType(path_type='file'), Predicate(func=<function PurePath.is_absolute at 0x7afca4145940>)], bioimageio.spec._internal.url.HttpUrl]:", "funcdef": "def"}, "bioimageio.spec._internal.io.RelativeDirectory": {"fullname": "bioimageio.spec._internal.io.RelativeDirectory", "modulename": "bioimageio.spec._internal.io", "qualname": "RelativeDirectory", "kind": "class", "doc": "
    Usage docs: https://docs.pydantic.dev/2.6/concepts/models/#rootmodel-and-custom-root-types
    \n\n
    A Pydantic BaseModel for the root object of the model.
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    Attributes:\n    root: The root object of the model.\n    __pydantic_root_model__: Whether the model is a RootModel.\n    __pydantic_private__: Private fields in the model.\n    __pydantic_extra__: Extra fields in the model.
    \n", "bases": "pydantic.root_model.RootModel[PurePath], typing.Generic[~AbsolutePathT]"}, "bioimageio.spec._internal.io.RelativeDirectory.get_absolute": {"fullname": "bioimageio.spec._internal.io.RelativeDirectory.get_absolute", "modulename": "bioimageio.spec._internal.io", "qualname": "RelativeDirectory.get_absolute", "kind": "function", "doc": "
    \n", "signature": "(\tself,\troot: bioimageio.spec._internal.root_url.RootHttpUrl | pathlib.Path | pydantic_core._pydantic_core.Url) -> Union[Annotated[pathlib.Path, PathType(path_type='dir'), Predicate(func=<function PurePath.is_absolute at 0x7afca4145940>)], bioimageio.spec._internal.url.HttpUrl]:", "funcdef": "def"}, "bioimageio.spec._internal.io.FileSource": {"fullname": "bioimageio.spec._internal.io.FileSource", "modulename": "bioimageio.spec._internal.io", "qualname": "FileSource", "kind": "variable", "doc": "
    \n", "default_value": "typing.Union[typing.Annotated[pathlib.Path, PathType(path_type='file')], bioimageio.spec._internal.io.RelativeFilePath, bioimageio.spec._internal.url.HttpUrl, typing.Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]]"}, "bioimageio.spec._internal.io.PermissiveFileSource": {"fullname": "bioimageio.spec._internal.io.PermissiveFileSource", "modulename": "bioimageio.spec._internal.io", "qualname": "PermissiveFileSource", "kind": "variable", "doc": "
    \n", "default_value": "typing.Union[typing.Annotated[pathlib.Path, PathType(path_type='file')], bioimageio.spec._internal.io.RelativeFilePath, bioimageio.spec._internal.url.HttpUrl, typing.Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)], str]"}, "bioimageio.spec._internal.io.path_or_url_adapter": {"fullname": "bioimageio.spec._internal.io.path_or_url_adapter", "modulename": "bioimageio.spec._internal.io", "qualname": "path_or_url_adapter", "kind": "variable", "doc": "
    \n", "default_value": "<pydantic.type_adapter.TypeAdapter object>"}, "bioimageio.spec._internal.io.validate_suffix": {"fullname": "bioimageio.spec._internal.io.validate_suffix", "modulename": "bioimageio.spec._internal.io", "qualname": "validate_suffix", "kind": "function", "doc": "
    check final suffix
    \n", "signature": "(\tvalue: ~V_suffix,\tsuffix: Union[str, Sequence[str]],\tcase_sensitive: bool) -> ~V_suffix:", "funcdef": "def"}, "bioimageio.spec._internal.io.WithSuffix": {"fullname": "bioimageio.spec._internal.io.WithSuffix", "modulename": "bioimageio.spec._internal.io", "qualname": "WithSuffix", "kind": "class", "doc": "
    \n"}, "bioimageio.spec._internal.io.WithSuffix.__init__": {"fullname": "bioimageio.spec._internal.io.WithSuffix.__init__", "modulename": "bioimageio.spec._internal.io", "qualname": "WithSuffix.__init__", "kind": "function", "doc": "
    \n", "signature": "(\tsuffix: Union[LiteralString, Tuple[LiteralString, ...]],\tcase_sensitive: bool)"}, "bioimageio.spec._internal.io.WithSuffix.suffix": {"fullname": "bioimageio.spec._internal.io.WithSuffix.suffix", "modulename": "bioimageio.spec._internal.io", "qualname": "WithSuffix.suffix", "kind": "variable", "doc": "
    \n", "annotation": ": Union[LiteralString, Tuple[LiteralString, ...]]"}, "bioimageio.spec._internal.io.WithSuffix.case_sensitive": {"fullname": "bioimageio.spec._internal.io.WithSuffix.case_sensitive", "modulename": "bioimageio.spec._internal.io", "qualname": "WithSuffix.case_sensitive", "kind": "variable", "doc": "
    \n", "annotation": ": bool"}, "bioimageio.spec._internal.io.WithSuffix.validate": {"fullname": "bioimageio.spec._internal.io.WithSuffix.validate", "modulename": "bioimageio.spec._internal.io", "qualname": "WithSuffix.validate", "kind": "function", "doc": "
    \n", "signature": "(\tself,\tvalue: Union[Annotated[pathlib.Path, PathType(path_type='file')], bioimageio.spec._internal.io.RelativeFilePath, bioimageio.spec._internal.url.HttpUrl, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]]) -> Union[Annotated[pathlib.Path, PathType(path_type='file')], bioimageio.spec._internal.io.RelativeFilePath, bioimageio.spec._internal.url.HttpUrl, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]]:", "funcdef": "def"}, "bioimageio.spec._internal.io.wo_special_file_name": {"fullname": "bioimageio.spec._internal.io.wo_special_file_name", "modulename": "bioimageio.spec._internal.io", "qualname": "wo_special_file_name", "kind": "function", "doc": "
    \n", "signature": "(\tsrc: Union[Annotated[pathlib.Path, PathType(path_type='file')], bioimageio.spec._internal.io.RelativeFilePath, bioimageio.spec._internal.url.HttpUrl, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]]) -> Union[Annotated[pathlib.Path, PathType(path_type='file')], bioimageio.spec._internal.io.RelativeFilePath, bioimageio.spec._internal.url.HttpUrl, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]]:", "funcdef": "def"}, "bioimageio.spec._internal.io.include_in_package_serializer": {"fullname": "bioimageio.spec._internal.io.include_in_package_serializer", "modulename": "bioimageio.spec._internal.io", "qualname": "include_in_package_serializer", "kind": "variable", "doc": "
    \n", "default_value": "PlainSerializer(func=<function _package>, return_type=PydanticUndefined, when_used='unless-none')"}, "bioimageio.spec._internal.io.ImportantFileSource": {"fullname": "bioimageio.spec._internal.io.ImportantFileSource", "modulename": "bioimageio.spec._internal.io", "qualname": "ImportantFileSource", "kind": "variable", "doc": "
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    \n", "signature": "(file_name: str) -> bool:", "funcdef": "def"}, "bioimageio.spec._internal.io.ensure_has_valid_rdf_name": {"fullname": "bioimageio.spec._internal.io.ensure_has_valid_rdf_name", "modulename": "bioimageio.spec._internal.io", "qualname": "ensure_has_valid_rdf_name", "kind": "function", "doc": "
    \n", "signature": "(\tsrc: Union[Annotated[pathlib.Path, PathType(path_type='file')], bioimageio.spec._internal.io.RelativeFilePath, bioimageio.spec._internal.url.HttpUrl, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]]) -> Union[Annotated[pathlib.Path, PathType(path_type='file')], bioimageio.spec._internal.io.RelativeFilePath, bioimageio.spec._internal.url.HttpUrl, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]]:", "funcdef": "def"}, "bioimageio.spec._internal.io.ensure_is_valid_rdf_name": {"fullname": "bioimageio.spec._internal.io.ensure_is_valid_rdf_name", "modulename": "bioimageio.spec._internal.io", "qualname": "ensure_is_valid_rdf_name", "kind": "function", "doc": "
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    \n", "default_value": "typing.Dict[str, YamlValue]"}, "bioimageio.spec._internal.io.BioimageioYamlSource": {"fullname": "bioimageio.spec._internal.io.BioimageioYamlSource", "modulename": "bioimageio.spec._internal.io", "qualname": "BioimageioYamlSource", "kind": "variable", "doc": "
    \n", "default_value": "typing.Union[typing.Annotated[pathlib.Path, PathType(path_type='file')], bioimageio.spec._internal.io.RelativeFilePath, bioimageio.spec._internal.url.HttpUrl, typing.Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)], str, typing.Dict[str, YamlValue]]"}, "bioimageio.spec._internal.io.OpenedBioimageioYaml": {"fullname": "bioimageio.spec._internal.io.OpenedBioimageioYaml", "modulename": "bioimageio.spec._internal.io", "qualname": "OpenedBioimageioYaml", "kind": "class", "doc": "
    \n"}, "bioimageio.spec._internal.io.OpenedBioimageioYaml.__init__": {"fullname": "bioimageio.spec._internal.io.OpenedBioimageioYaml.__init__", "modulename": "bioimageio.spec._internal.io", "qualname": "OpenedBioimageioYaml.__init__", "kind": "function", "doc": "
    \n", "signature": "(\tcontent: Dict[str, YamlValue],\toriginal_root: Union[Annotated[pathlib.Path, PathType(path_type='dir'), Predicate(func=<function PurePath.is_absolute>)], bioimageio.spec._internal.root_url.RootHttpUrl],\toriginal_file_name: str)"}, "bioimageio.spec._internal.io.OpenedBioimageioYaml.content": {"fullname": "bioimageio.spec._internal.io.OpenedBioimageioYaml.content", "modulename": "bioimageio.spec._internal.io", "qualname": "OpenedBioimageioYaml.content", "kind": "variable", "doc": "
    \n", "annotation": ": Dict[str, YamlValue]"}, "bioimageio.spec._internal.io.OpenedBioimageioYaml.original_root": {"fullname": "bioimageio.spec._internal.io.OpenedBioimageioYaml.original_root", "modulename": "bioimageio.spec._internal.io", "qualname": "OpenedBioimageioYaml.original_root", "kind": "variable", "doc": "
    \n", "annotation": ": Union[Annotated[pathlib.Path, PathType(path_type='dir'), Predicate(func=<function PurePath.is_absolute at 0x7afca4145940>)], bioimageio.spec._internal.root_url.RootHttpUrl]"}, "bioimageio.spec._internal.io.OpenedBioimageioYaml.original_file_name": {"fullname": "bioimageio.spec._internal.io.OpenedBioimageioYaml.original_file_name", "modulename": "bioimageio.spec._internal.io", "qualname": "OpenedBioimageioYaml.original_file_name", "kind": "variable", "doc": "
    \n", "annotation": ": str"}, "bioimageio.spec._internal.io.DownloadedFile": {"fullname": "bioimageio.spec._internal.io.DownloadedFile", "modulename": "bioimageio.spec._internal.io", "qualname": "DownloadedFile", "kind": "class", "doc": "
    \n"}, "bioimageio.spec._internal.io.DownloadedFile.__init__": {"fullname": "bioimageio.spec._internal.io.DownloadedFile.__init__", "modulename": "bioimageio.spec._internal.io", "qualname": "DownloadedFile.__init__", "kind": "function", "doc": "
    \n", "signature": "(\tpath: Annotated[pathlib.Path, PathType(path_type='file')],\toriginal_root: Union[Annotated[pathlib.Path, PathType(path_type='dir'), Predicate(func=<function PurePath.is_absolute>)], bioimageio.spec._internal.root_url.RootHttpUrl],\toriginal_file_name: str)"}, "bioimageio.spec._internal.io.DownloadedFile.path": {"fullname": "bioimageio.spec._internal.io.DownloadedFile.path", "modulename": "bioimageio.spec._internal.io", "qualname": "DownloadedFile.path", "kind": "variable", "doc": "
    \n", "annotation": ": Annotated[pathlib.Path, PathType(path_type='file')]"}, "bioimageio.spec._internal.io.DownloadedFile.original_root": {"fullname": "bioimageio.spec._internal.io.DownloadedFile.original_root", "modulename": "bioimageio.spec._internal.io", "qualname": "DownloadedFile.original_root", "kind": "variable", "doc": "
    \n", "annotation": ": Union[Annotated[pathlib.Path, PathType(path_type='dir'), Predicate(func=<function PurePath.is_absolute at 0x7afca4145940>)], bioimageio.spec._internal.root_url.RootHttpUrl]"}, "bioimageio.spec._internal.io.DownloadedFile.original_file_name": {"fullname": "bioimageio.spec._internal.io.DownloadedFile.original_file_name", "modulename": "bioimageio.spec._internal.io", "qualname": "DownloadedFile.original_file_name", "kind": "variable", "doc": "
    \n", "annotation": ": str"}, "bioimageio.spec._internal.io.HashKwargs": {"fullname": "bioimageio.spec._internal.io.HashKwargs", "modulename": "bioimageio.spec._internal.io", "qualname": "HashKwargs", "kind": "class", "doc": "
    \n", "bases": "typing.TypedDict"}, "bioimageio.spec._internal.io.HashKwargs.sha256": {"fullname": "bioimageio.spec._internal.io.HashKwargs.sha256", "modulename": "bioimageio.spec._internal.io", "qualname": "HashKwargs.sha256", "kind": "variable", "doc": "
    \n", "annotation": ": NotRequired[Optional[bioimageio.spec._internal.io.Sha256]]"}, "bioimageio.spec._internal.io.StrictFileSource": {"fullname": "bioimageio.spec._internal.io.StrictFileSource", "modulename": "bioimageio.spec._internal.io", "qualname": "StrictFileSource", "kind": "variable", "doc": "
    \n", "default_value": "typing.Union[bioimageio.spec._internal.url.HttpUrl, typing.Annotated[pathlib.Path, PathType(path_type='file')], bioimageio.spec._internal.io.RelativeFilePath]"}, "bioimageio.spec._internal.io.interprete_file_source": {"fullname": "bioimageio.spec._internal.io.interprete_file_source", "modulename": "bioimageio.spec._internal.io", "qualname": "interprete_file_source", "kind": "function", "doc": "
    \n", "signature": "(\tfile_source: Union[Annotated[pathlib.Path, PathType(path_type='file')], bioimageio.spec._internal.io.RelativeFilePath, bioimageio.spec._internal.url.HttpUrl, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)], str]) -> Union[bioimageio.spec._internal.url.HttpUrl, Annotated[pathlib.Path, PathType(path_type='file')], bioimageio.spec._internal.io.RelativeFilePath]:", "funcdef": "def"}, "bioimageio.spec._internal.io.download": {"fullname": "bioimageio.spec._internal.io.download", "modulename": "bioimageio.spec._internal.io", "qualname": "download", "kind": "function", "doc": "
    \n", "signature": "(\tsource: Union[Annotated[pathlib.Path, PathType(path_type='file')], bioimageio.spec._internal.io.RelativeFilePath, bioimageio.spec._internal.url.HttpUrl, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)], str, bioimageio.spec._internal.io.FileDescr],\t/,\t**kwargs: Unpack[bioimageio.spec._internal.io.HashKwargs]) -> bioimageio.spec._internal.io.DownloadedFile:", "funcdef": "def"}, "bioimageio.spec._internal.io.FileDescr": {"fullname": "bioimageio.spec._internal.io.FileDescr", "modulename": "bioimageio.spec._internal.io", "qualname": "FileDescr", "kind": "class", "doc": "
    Subpart of a resource description
    \n", "bases": "bioimageio.spec._internal.node.Node"}, "bioimageio.spec._internal.io.FileDescr.source": {"fullname": "bioimageio.spec._internal.io.FileDescr.source", "modulename": "bioimageio.spec._internal.io", "qualname": "FileDescr.source", "kind": "variable", "doc": "
    \u2208\ud83d\udce6 file source
    \n", "annotation": ": Annotated[Union[Annotated[pathlib.Path, PathType(path_type='file')], bioimageio.spec._internal.io.RelativeFilePath, bioimageio.spec._internal.url.HttpUrl, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator(func=<function wo_special_file_name at 0x7afca0d90540>), PlainSerializer(func=<function _package at 0x7afca0d91760>, return_type=PydanticUndefined, when_used='unless-none')]"}, "bioimageio.spec._internal.io.FileDescr.sha256": {"fullname": "bioimageio.spec._internal.io.FileDescr.sha256", "modulename": "bioimageio.spec._internal.io", "qualname": "FileDescr.sha256", "kind": "variable", "doc": "
    SHA256 checksum of the source file
    \n", "annotation": ": Optional[bioimageio.spec._internal.io.Sha256]"}, "bioimageio.spec._internal.io.FileDescr.validate_sha256": {"fullname": "bioimageio.spec._internal.io.FileDescr.validate_sha256", "modulename": "bioimageio.spec._internal.io", "qualname": "FileDescr.validate_sha256", "kind": "function", "doc": "
    \n", "signature": "(self) -> Self:", "funcdef": "def"}, "bioimageio.spec._internal.io.FileDescr.download": {"fullname": "bioimageio.spec._internal.io.FileDescr.download", "modulename": "bioimageio.spec._internal.io", "qualname": "FileDescr.download", "kind": "function", "doc": "
    \n", "signature": "(self):", "funcdef": "def"}, "bioimageio.spec._internal.io.FileDescr.model_config": {"fullname": "bioimageio.spec._internal.io.FileDescr.model_config", "modulename": "bioimageio.spec._internal.io", "qualname": "FileDescr.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec._internal.io.FileDescr.model_fields": {"fullname": "bioimageio.spec._internal.io.FileDescr.model_fields", "modulename": "bioimageio.spec._internal.io", "qualname": "FileDescr.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'source': FieldInfo(annotation=Union[Annotated[Path, PathType], RelativeFilePath, HttpUrl, Annotated[Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], required=True, metadata=[AfterValidator(func=<function wo_special_file_name>), PlainSerializer(func=<function _package>, return_type=PydanticUndefined, when_used='unless-none')]), 'sha256': FieldInfo(annotation=Union[Sha256, NoneType], required=False)}"}, "bioimageio.spec._internal.io.FileDescr.model_computed_fields": {"fullname": "bioimageio.spec._internal.io.FileDescr.model_computed_fields", "modulename": "bioimageio.spec._internal.io", "qualname": "FileDescr.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec._internal.io.extract_file_name": {"fullname": "bioimageio.spec._internal.io.extract_file_name", "modulename": "bioimageio.spec._internal.io", "qualname": "extract_file_name", "kind": "function", "doc": "
    \n", "signature": "(\tsrc: Union[Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)], bioimageio.spec._internal.url.HttpUrl, pathlib.PurePath, bioimageio.spec._internal.io.RelativeFilePath]) -> str:", "funcdef": "def"}, "bioimageio.spec._internal.io.get_sha256": {"fullname": "bioimageio.spec._internal.io.get_sha256", "modulename": "bioimageio.spec._internal.io", "qualname": "get_sha256", "kind": "function", "doc": "
    from https://stackoverflow.com/a/44873382
    \n", "signature": "(path: pathlib.Path) -> bioimageio.spec._internal.io.Sha256:", "funcdef": "def"}, "bioimageio.spec._internal.io.RelativePathBase[Union[Annotated[Path, PathType, Predicate], Annotated[Path, PathType, Predicate], HttpUrl]]": {"fullname": "bioimageio.spec._internal.io.RelativePathBase[Union[Annotated[Path, PathType, Predicate], Annotated[Path, PathType, Predicate], HttpUrl]]", "modulename": "bioimageio.spec._internal.io", "qualname": "RelativePathBase[Union[Annotated[Path, PathType, Predicate], Annotated[Path, PathType, Predicate], HttpUrl]]", "kind": "class", "doc": "
    Usage docs: https://docs.pydantic.dev/2.6/concepts/models/#rootmodel-and-custom-root-types
    \n\n
    A Pydantic BaseModel for the root object of the model.
    \n\n
    Attributes:\n    root: The root object of the model.\n    __pydantic_root_model__: Whether the model is a RootModel.\n    __pydantic_private__: Private fields in the model.\n    __pydantic_extra__: Extra fields in the model.
    \n", "bases": "pydantic.root_model.RootModel[PurePath], typing.Generic[~AbsolutePathT]"}, "bioimageio.spec._internal.io.RelativePathBase[Union[Annotated[Path, PathType, Predicate], HttpUrl]]": {"fullname": "bioimageio.spec._internal.io.RelativePathBase[Union[Annotated[Path, PathType, Predicate], HttpUrl]]", "modulename": "bioimageio.spec._internal.io", "qualname": "RelativePathBase[Union[Annotated[Path, PathType, Predicate], HttpUrl]]", "kind": "class", "doc": "
    Usage docs: https://docs.pydantic.dev/2.6/concepts/models/#rootmodel-and-custom-root-types
    \n\n
    A Pydantic BaseModel for the root object of the model.
    \n\n
    Attributes:\n    root: The root object of the model.\n    __pydantic_root_model__: Whether the model is a RootModel.\n    __pydantic_private__: Private fields in the model.\n    __pydantic_extra__: Extra fields in the model.
    \n", "bases": "pydantic.root_model.RootModel[PurePath], typing.Generic[~AbsolutePathT]"}, "bioimageio.spec._internal.io.RelativePathBase[Union[Annotated[Path, PathType, Predicate], HttpUrl]]_": {"fullname": "bioimageio.spec._internal.io.RelativePathBase[Union[Annotated[Path, PathType, Predicate], HttpUrl]]_", "modulename": "bioimageio.spec._internal.io", "qualname": "RelativePathBase[Union[Annotated[Path, PathType, Predicate], HttpUrl]]_", "kind": "variable", "doc": "
    \n", "default_value": "<class 'bioimageio.spec._internal.io.RelativePathBase[Union[Annotated[Path, PathType, Predicate], HttpUrl]]'>"}, "bioimageio.spec._internal.io_basics": {"fullname": "bioimageio.spec._internal.io_basics", "modulename": "bioimageio.spec._internal.io_basics", "kind": "module", "doc": "
    \n"}, "bioimageio.spec._internal.io_basics.FileName": {"fullname": "bioimageio.spec._internal.io_basics.FileName", "modulename": "bioimageio.spec._internal.io_basics", "qualname": "FileName", "kind": "variable", "doc": "
    \n", "default_value": "<class 'str'>"}, "bioimageio.spec._internal.io_basics.AbsoluteDirectory": {"fullname": "bioimageio.spec._internal.io_basics.AbsoluteDirectory", "modulename": "bioimageio.spec._internal.io_basics", "qualname": "AbsoluteDirectory", "kind": "variable", "doc": "
    \n", "default_value": "typing.Annotated[pathlib.Path, PathType(path_type='dir'), Predicate(func=<function PurePath.is_absolute>)]"}, "bioimageio.spec._internal.io_basics.AbsoluteFilePath": {"fullname": "bioimageio.spec._internal.io_basics.AbsoluteFilePath", "modulename": "bioimageio.spec._internal.io_basics", "qualname": "AbsoluteFilePath", "kind": "variable", "doc": "
    \n", "default_value": "typing.Annotated[pathlib.Path, PathType(path_type='file'), Predicate(func=<function PurePath.is_absolute>)]"}, "bioimageio.spec._internal.io_basics.BIOIMAGEIO_YAML": {"fullname": "bioimageio.spec._internal.io_basics.BIOIMAGEIO_YAML", "modulename": "bioimageio.spec._internal.io_basics", "qualname": "BIOIMAGEIO_YAML", "kind": "variable", "doc": "
    \n", "default_value": "'rdf.yaml'"}, "bioimageio.spec._internal.io_basics.ALTERNATIVE_BIOIMAGEIO_YAML_NAMES": {"fullname": "bioimageio.spec._internal.io_basics.ALTERNATIVE_BIOIMAGEIO_YAML_NAMES", "modulename": "bioimageio.spec._internal.io_basics", "qualname": "ALTERNATIVE_BIOIMAGEIO_YAML_NAMES", "kind": "variable", "doc": "
    \n", "default_value": "('bioimageio.yaml', 'model.yaml')"}, "bioimageio.spec._internal.io_basics.ALL_BIOIMAGEIO_YAML_NAMES": {"fullname": "bioimageio.spec._internal.io_basics.ALL_BIOIMAGEIO_YAML_NAMES", "modulename": "bioimageio.spec._internal.io_basics", "qualname": "ALL_BIOIMAGEIO_YAML_NAMES", "kind": "variable", "doc": "
    \n", "default_value": "('rdf.yaml', 'bioimageio.yaml', 'model.yaml')"}, "bioimageio.spec._internal.io_utils": {"fullname": "bioimageio.spec._internal.io_utils", "modulename": "bioimageio.spec._internal.io_utils", "kind": "module", "doc": "
    \n"}, "bioimageio.spec._internal.io_utils.yaml": {"fullname": "bioimageio.spec._internal.io_utils.yaml", "modulename": "bioimageio.spec._internal.io_utils", "qualname": "yaml", "kind": "variable", "doc": "
    \n", "default_value": "<ruyaml.main.YAML object>"}, "bioimageio.spec._internal.io_utils.read_yaml": {"fullname": "bioimageio.spec._internal.io_utils.read_yaml", "modulename": "bioimageio.spec._internal.io_utils", "qualname": "read_yaml", "kind": "function", "doc": "
    \n", "signature": "(\tfile: Union[Annotated[pathlib.Path, PathType(path_type='file')], TextIO]) -> YamlValue:", "funcdef": "def"}, "bioimageio.spec._internal.io_utils.write_yaml": {"fullname": "bioimageio.spec._internal.io_utils.write_yaml", "modulename": "bioimageio.spec._internal.io_utils", "qualname": "write_yaml", "kind": "function", "doc": "
    \n", "signature": "(\tcontent: YamlValue,\t/,\tfile: Union[Annotated[pathlib.Path, PathType(path_type='new')], Annotated[pathlib.Path, PathType(path_type='file')], TextIO]):", "funcdef": "def"}, "bioimageio.spec._internal.io_utils.open_bioimageio_yaml": {"fullname": "bioimageio.spec._internal.io_utils.open_bioimageio_yaml", "modulename": "bioimageio.spec._internal.io_utils", "qualname": "open_bioimageio_yaml", "kind": "function", "doc": "
    \n", "signature": "(\tsource: Union[Annotated[pathlib.Path, PathType(path_type='file')], bioimageio.spec._internal.io.RelativeFilePath, bioimageio.spec._internal.url.HttpUrl, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)], str],\t/,\t**kwargs: Unpack[bioimageio.spec._internal.io.HashKwargs]) -> bioimageio.spec._internal.io.OpenedBioimageioYaml:", "funcdef": "def"}, "bioimageio.spec._internal.io_utils.identify_bioimageio_yaml_file_name": {"fullname": "bioimageio.spec._internal.io_utils.identify_bioimageio_yaml_file_name", "modulename": "bioimageio.spec._internal.io_utils", "qualname": "identify_bioimageio_yaml_file_name", "kind": "function", "doc": "
    \n", "signature": "(file_names: Iterable[str]) -> str:", "funcdef": "def"}, "bioimageio.spec._internal.io_utils.find_bioimageio_yaml_file_name": {"fullname": "bioimageio.spec._internal.io_utils.find_bioimageio_yaml_file_name", "modulename": "bioimageio.spec._internal.io_utils", "qualname": "find_bioimageio_yaml_file_name", "kind": "function", "doc": "
    \n", "signature": "(path: pathlib.Path) -> str:", "funcdef": "def"}, "bioimageio.spec._internal.io_utils.unzip": {"fullname": "bioimageio.spec._internal.io_utils.unzip", "modulename": "bioimageio.spec._internal.io_utils", "qualname": "unzip", "kind": "function", "doc": "
    \n", "signature": "(\tzip_file: Union[Annotated[pathlib.Path, PathType(path_type='file')], zipfile.ZipFile],\tout_path: Optional[Annotated[pathlib.Path, PathType(path_type='dir')]] = None,\toverwrite: bool = False) -> Annotated[pathlib.Path, PathType(path_type='dir')]:", "funcdef": "def"}, "bioimageio.spec._internal.io_utils.write_zip": {"fullname": "bioimageio.spec._internal.io_utils.write_zip", "modulename": "bioimageio.spec._internal.io_utils", "qualname": "write_zip", "kind": "function", "doc": "
    Write a zip archive.
    \n\n
    Args:\n    path: output path to write to.\n    content: dict mapping archive names to local file paths, strings (for text files), or dict (for yaml files).\n    compression: The numeric constant of compression method.\n    compression_level: Compression level to use when writing files to the archive.\n                       See https://docs.python.org/3/library/zipfile.html#zipfile.ZipFile
    \n", "signature": "(\tpath: Annotated[pathlib.Path, PathType(path_type='file')],\tcontent: Mapping[str, Union[str, Annotated[pathlib.Path, PathType(path_type='file')], Dict[Any, Any]]],\t*,\tcompression: int,\tcompression_level: int) -> None:", "funcdef": "def"}, "bioimageio.spec._internal.io_utils.load_array": {"fullname": "bioimageio.spec._internal.io_utils.load_array", "modulename": "bioimageio.spec._internal.io_utils", "qualname": "load_array", "kind": "function", "doc": "
    \n", "signature": "(\tsource: Union[Annotated[pathlib.Path, PathType(path_type='file')], bioimageio.spec._internal.io.RelativeFilePath, bioimageio.spec._internal.url.HttpUrl, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)], bioimageio.spec._internal.io.FileDescr]) -> numpy.ndarray[typing.Any, numpy.dtype[typing.Any]]:", "funcdef": "def"}, "bioimageio.spec._internal.io_utils.save_array": {"fullname": "bioimageio.spec._internal.io_utils.save_array", "modulename": "bioimageio.spec._internal.io_utils", "qualname": "save_array", "kind": "function", "doc": "
    \n", "signature": "(\tpath: pathlib.Path,\tarray: numpy.ndarray[typing.Any, numpy.dtype[typing.Any]]) -> None:", "funcdef": "def"}, "bioimageio.spec._internal.license_id": {"fullname": "bioimageio.spec._internal.license_id", "modulename": "bioimageio.spec._internal.license_id", "kind": "module", "doc": "
    \n"}, "bioimageio.spec._internal.license_id.DeprecatedLicenseId": {"fullname": "bioimageio.spec._internal.license_id.DeprecatedLicenseId", "modulename": "bioimageio.spec._internal.license_id", "qualname": "DeprecatedLicenseId", "kind": "class", "doc": "
    Usage docs: https://docs.pydantic.dev/2.6/concepts/models/#rootmodel-and-custom-root-types
    \n\n
    A Pydantic BaseModel for the root object of the model.
    \n\n
    Attributes:\n    root: The root object of the model.\n    __pydantic_root_model__: Whether the model is a RootModel.\n    __pydantic_private__: Private fields in the model.\n    __pydantic_extra__: Extra fields in the model.
    \n", "bases": "pydantic.main.BaseModel, typing.Generic[~RootModelRootType]"}, "bioimageio.spec._internal.license_id.LicenseId": {"fullname": "bioimageio.spec._internal.license_id.LicenseId", "modulename": "bioimageio.spec._internal.license_id", "qualname": "LicenseId", "kind": "class", "doc": "
    Usage docs: https://docs.pydantic.dev/2.6/concepts/models/#rootmodel-and-custom-root-types
    \n\n
    A Pydantic BaseModel for the root object of the model.
    \n\n
    Attributes:\n    root: The root object of the model.\n    __pydantic_root_model__: Whether the model is a RootModel.\n    __pydantic_private__: Private fields in the model.\n    __pydantic_extra__: Extra fields in the model.
    \n", "bases": "pydantic.main.BaseModel, typing.Generic[~RootModelRootType]"}, "bioimageio.spec._internal.license_id._LicenseId[Literal['AGPL-1.0', 'AGPL-3.0', 'BSD-2-Clause-FreeBSD', 'BSD-2-Clause-NetBSD', 'bzip2-1.0.5', 'eCos-2.0', 'GFDL-1.1', 'GFDL-1.2', 'GFDL-1.3', 'GPL-1.0', 'GPL-1.0+', 'GPL-2.0', 'GPL-2.0+', 'GPL-2.0-with-autoconf-exception', 'GPL-2.0-with-bison-exception', 'GPL-2.0-with-classpath-exception', 'GPL-2.0-with-font-exception', 'GPL-2.0-with-GCC-exception', 'GPL-3.0', 'GPL-3.0+', 'GPL-3.0-with-autoconf-exception', 'GPL-3.0-with-GCC-exception', 'LGPL-2.0', 'LGPL-2.0+', 'LGPL-2.1', 'LGPL-2.1+', 'LGPL-3.0', 'LGPL-3.0+', 'Nunit', 'StandardML-NJ', 'wxWindows']]": {"fullname": "bioimageio.spec._internal.license_id._LicenseId[Literal['AGPL-1.0', 'AGPL-3.0', 'BSD-2-Clause-FreeBSD', 'BSD-2-Clause-NetBSD', 'bzip2-1.0.5', 'eCos-2.0', 'GFDL-1.1', 'GFDL-1.2', 'GFDL-1.3', 'GPL-1.0', 'GPL-1.0+', 'GPL-2.0', 'GPL-2.0+', 'GPL-2.0-with-autoconf-exception', 'GPL-2.0-with-bison-exception', 'GPL-2.0-with-classpath-exception', 'GPL-2.0-with-font-exception', 'GPL-2.0-with-GCC-exception', 'GPL-3.0', 'GPL-3.0+', 'GPL-3.0-with-autoconf-exception', 'GPL-3.0-with-GCC-exception', 'LGPL-2.0', 'LGPL-2.0+', 'LGPL-2.1', 'LGPL-2.1+', 'LGPL-3.0', 'LGPL-3.0+', 'Nunit', 'StandardML-NJ', 'wxWindows']]", "modulename": "bioimageio.spec._internal.license_id", "qualname": "_LicenseId[Literal['AGPL-1.0', 'AGPL-3.0', 'BSD-2-Clause-FreeBSD', 'BSD-2-Clause-NetBSD', 'bzip2-1.0.5', 'eCos-2.0', 'GFDL-1.1', 'GFDL-1.2', 'GFDL-1.3', 'GPL-1.0', 'GPL-1.0+', 'GPL-2.0', 'GPL-2.0+', 'GPL-2.0-with-autoconf-exception', 'GPL-2.0-with-bison-exception', 'GPL-2.0-with-classpath-exception', 'GPL-2.0-with-font-exception', 'GPL-2.0-with-GCC-exception', 'GPL-3.0', 'GPL-3.0+', 'GPL-3.0-with-autoconf-exception', 'GPL-3.0-with-GCC-exception', 'LGPL-2.0', 'LGPL-2.0+', 'LGPL-2.1', 'LGPL-2.1+', 'LGPL-3.0', 'LGPL-3.0+', 'Nunit', 'StandardML-NJ', 'wxWindows']]", "kind": "class", "doc": "
    Usage docs: https://docs.pydantic.dev/2.6/concepts/models/#rootmodel-and-custom-root-types
    \n\n
    A Pydantic BaseModel for the root object of the model.
    \n\n
    Attributes:\n    root: The root object of the model.\n    __pydantic_root_model__: Whether the model is a RootModel.\n    __pydantic_private__: Private fields in the model.\n    __pydantic_extra__: Extra fields in the model.
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'OGL-UK-1.0', 'OGL-UK-2.0', 'OGL-UK-3.0', 'OGTSL', 'OLDAP-1.1', 'OLDAP-1.2', 'OLDAP-1.3', 'OLDAP-1.4', 'OLDAP-2.0', 'OLDAP-2.0.1', 'OLDAP-2.1', 'OLDAP-2.2', 'OLDAP-2.2.1', 'OLDAP-2.2.2', 'OLDAP-2.3', 'OLDAP-2.4', 'OLDAP-2.5', 'OLDAP-2.6', 'OLDAP-2.7', 'OLDAP-2.8', 'OLFL-1.3', 'OML', 'OpenPBS-2.3', 'OpenSSL', 'OPL-1.0', 'OPL-UK-3.0', 'OPUBL-1.0', 'OSET-PL-2.1', 'OSL-1.0', 'OSL-1.1', 'OSL-2.0', 'OSL-2.1', 'OSL-3.0', 'Parity-6.0.0', 'Parity-7.0.0', 'PDDL-1.0', 'PHP-3.0', 'PHP-3.01', 'Plexus', 'PolyForm-Noncommercial-1.0.0', 'PolyForm-Small-Business-1.0.0', 'PostgreSQL', 'PSF-2.0', 'psfrag', 'psutils', 'Python-2.0', 'Python-2.0.1', 'Qhull', 'QPL-1.0', 'QPL-1.0-INRIA-2004', 'Rdisc', 'RHeCos-1.1', 'RPL-1.1', 'RPL-1.5', 'RPSL-1.0', 'RSA-MD', 'RSCPL', 'Ruby', 'SAX-PD', 'Saxpath', 'SCEA', 'SchemeReport', 'Sendmail', 'Sendmail-8.23', 'SGI-B-1.0', 'SGI-B-1.1', 'SGI-B-2.0', 'SGP4', 'SHL-0.5', 'SHL-0.51', 'SimPL-2.0', 'SISSL', 'SISSL-1.2', 'Sleepycat', 'SMLNJ', 'SMPPL', 'SNIA', 'snprintf', 'Spencer-86', 'Spencer-94', 'Spencer-99', 'SPL-1.0', 'SSH-OpenSSH', 'SSH-short', 'SSPL-1.0', 'SugarCRM-1.1.3', 'SunPro', 'SWL', 'Symlinks', 'TAPR-OHL-1.0', 'TCL', 'TCP-wrappers', 'TermReadKey', 'TMate', 'TORQUE-1.1', 'TOSL', 'TPDL', 'TPL-1.0', 'TTWL', 'TU-Berlin-1.0', 'TU-Berlin-2.0', 'UCAR', 'UCL-1.0', 'Unicode-DFS-2015', 'Unicode-DFS-2016', 'Unicode-TOU', 'UnixCrypt', 'Unlicense', 'UPL-1.0', 'Vim', 'VOSTROM', 'VSL-1.0', 'W3C', 'W3C-19980720', 'W3C-20150513', 'w3m', 'Watcom-1.0', 'Widget-Workshop', 'Wsuipa', 'WTFPL', 'X11', 'X11-distribute-modifications-variant', 'Xdebug-1.03', 'Xerox', 'Xfig', 'XFree86-1.1', 'xinetd', 'xlock', 'Xnet', 'xpp', 'XSkat', 'YPL-1.0', 'YPL-1.1', 'Zed', 'Zend-2.0', 'Zimbra-1.3', 'Zimbra-1.4', 'Zlib', 'zlib-acknowledgement', 'ZPL-1.1', 'ZPL-2.0', 'ZPL-2.1']]", "kind": "class", "doc": "
    Usage docs: https://docs.pydantic.dev/2.6/concepts/models/#rootmodel-and-custom-root-types
    \n\n
    A Pydantic BaseModel for the root object of the model.
    \n\n
    Attributes:\n    root: The root object of the model.\n    __pydantic_root_model__: Whether the model is a RootModel.\n    __pydantic_private__: Private fields in the model.\n    __pydantic_extra__: Extra fields in the model.
    \n", "bases": "pydantic.main.BaseModel, typing.Generic[~RootModelRootType]"}, "bioimageio.spec._internal.node": {"fullname": "bioimageio.spec._internal.node", "modulename": "bioimageio.spec._internal.node", "kind": "module", "doc": "
    \n"}, "bioimageio.spec._internal.node.Node": {"fullname": "bioimageio.spec._internal.node.Node", "modulename": "bioimageio.spec._internal.node", "qualname": "Node", "kind": "class", "doc": "
    Subpart of a resource description
    \n", "bases": "pydantic.main.BaseModel"}, "bioimageio.spec._internal.node.Node.model_validate": {"fullname": "bioimageio.spec._internal.node.Node.model_validate", "modulename": "bioimageio.spec._internal.node", "qualname": "Node.model_validate", "kind": "function", "doc": "
    Validate a pydantic model instance.
    \n\n
    Args:\n    obj: The object to validate.\n    strict: Whether to raise an exception on invalid fields.\n    from_attributes: Whether to extract data from object attributes.\n    context: Additional context to pass to the validator.
    \n\n
    Raises:\n    ValidationError: If the object failed validation.
    \n\n
    Returns:\n    The validated description instance.
    \n", "signature": "(\tcls,\tobj: Union[Any, Dict[str, Any]],\t*,\tstrict: Optional[bool] = None,\tfrom_attributes: Optional[bool] = None,\tcontext: Union[bioimageio.spec._internal.validation_context.ValidationContext, Dict[str, Any], NoneType] = None) -> Self:", "funcdef": "def"}, "bioimageio.spec._internal.node.Node.model_config": {"fullname": "bioimageio.spec._internal.node.Node.model_config", "modulename": "bioimageio.spec._internal.node", "qualname": "Node.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec._internal.node.Node.model_fields": {"fullname": "bioimageio.spec._internal.node.Node.model_fields", "modulename": "bioimageio.spec._internal.node", "qualname": "Node.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec._internal.node.Node.model_computed_fields": {"fullname": "bioimageio.spec._internal.node.Node.model_computed_fields", "modulename": "bioimageio.spec._internal.node", "qualname": "Node.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec._internal.packaging_context": {"fullname": "bioimageio.spec._internal.packaging_context", "modulename": "bioimageio.spec._internal.packaging_context", "kind": "module", "doc": "
    \n"}, "bioimageio.spec._internal.packaging_context.PackagingContext": {"fullname": "bioimageio.spec._internal.packaging_context.PackagingContext", "modulename": "bioimageio.spec._internal.packaging_context", "qualname": "PackagingContext", "kind": "class", "doc": "
    \n"}, "bioimageio.spec._internal.packaging_context.PackagingContext.__init__": {"fullname": "bioimageio.spec._internal.packaging_context.PackagingContext.__init__", "modulename": "bioimageio.spec._internal.packaging_context", "qualname": "PackagingContext.__init__", "kind": "function", "doc": "
    \n", "signature": "(\tbioimageio_yaml_file_name: str,\tfile_sources: Dict[str, Union[Annotated[pathlib.Path, PathType(path_type='file'), Predicate(func=<function PurePath.is_absolute>)], bioimageio.spec._internal.url.HttpUrl]] = <factory>)"}, "bioimageio.spec._internal.packaging_context.PackagingContext.bioimageio_yaml_file_name": {"fullname": "bioimageio.spec._internal.packaging_context.PackagingContext.bioimageio_yaml_file_name", "modulename": "bioimageio.spec._internal.packaging_context", "qualname": "PackagingContext.bioimageio_yaml_file_name", "kind": "variable", "doc": "
    \n", "annotation": ": str"}, "bioimageio.spec._internal.packaging_context.PackagingContext.file_sources": {"fullname": "bioimageio.spec._internal.packaging_context.PackagingContext.file_sources", "modulename": "bioimageio.spec._internal.packaging_context", "qualname": "PackagingContext.file_sources", "kind": "variable", "doc": "
    File sources to include in the packaged resource
    \n", "annotation": ": Dict[str, Union[Annotated[pathlib.Path, PathType(path_type='file'), Predicate(func=<function PurePath.is_absolute at 0x7afca4145940>)], bioimageio.spec._internal.url.HttpUrl]]"}, "bioimageio.spec._internal.packaging_context.PackagingContext.replace": {"fullname": "bioimageio.spec._internal.packaging_context.PackagingContext.replace", "modulename": "bioimageio.spec._internal.packaging_context", "qualname": "PackagingContext.replace", "kind": "function", "doc": "
    return a modiefied copy
    \n", "signature": "(\tself,\t*,\tbioimageio_yaml_file_name: Optional[str] = None,\tfile_sources: Optional[Dict[str, Union[Annotated[pathlib.Path, PathType(path_type='file'), Predicate(func=<function PurePath.is_absolute>)], bioimageio.spec._internal.url.HttpUrl]]] = None) -> bioimageio.spec._internal.packaging_context.PackagingContext:", "funcdef": "def"}, "bioimageio.spec._internal.packaging_context.packaging_context_var": {"fullname": "bioimageio.spec._internal.packaging_context.packaging_context_var", "modulename": "bioimageio.spec._internal.packaging_context", "qualname": "packaging_context_var", "kind": "variable", "doc": "
    \n", "annotation": ": _contextvars.ContextVar[typing.Optional[bioimageio.spec._internal.packaging_context.PackagingContext]]", "default_value": "<ContextVar name='packaging_context_var' default=None>"}, "bioimageio.spec._internal.root_url": {"fullname": "bioimageio.spec._internal.root_url", "modulename": "bioimageio.spec._internal.root_url", "kind": "module", "doc": "
    \n"}, "bioimageio.spec._internal.root_url.RootHttpUrl": {"fullname": "bioimageio.spec._internal.root_url.RootHttpUrl", "modulename": "bioimageio.spec._internal.root_url", "qualname": "RootHttpUrl", "kind": "class", "doc": "
    A 'URL folder', possibly an invalid http URL
    \n", "bases": "pydantic.main.BaseModel, typing.Generic[~RootModelRootType]"}, "bioimageio.spec._internal.root_url.RootHttpUrl.scheme": {"fullname": "bioimageio.spec._internal.root_url.RootHttpUrl.scheme", "modulename": "bioimageio.spec._internal.root_url", "qualname": "RootHttpUrl.scheme", "kind": "variable", "doc": "
    \n", "annotation": ": str"}, "bioimageio.spec._internal.root_url.RootHttpUrl.host": {"fullname": "bioimageio.spec._internal.root_url.RootHttpUrl.host", "modulename": "bioimageio.spec._internal.root_url", "qualname": "RootHttpUrl.host", "kind": "variable", "doc": "
    \n", "annotation": ": Optional[str]"}, "bioimageio.spec._internal.root_url.RootHttpUrl.path": {"fullname": "bioimageio.spec._internal.root_url.RootHttpUrl.path", "modulename": "bioimageio.spec._internal.root_url", "qualname": "RootHttpUrl.path", "kind": "variable", "doc": "
    \n", "annotation": ": Optional[str]"}, "bioimageio.spec._internal.root_url.RootHttpUrl.parent": {"fullname": "bioimageio.spec._internal.root_url.RootHttpUrl.parent", "modulename": "bioimageio.spec._internal.root_url", "qualname": "RootHttpUrl.parent", "kind": "variable", "doc": "
    \n", "annotation": ": bioimageio.spec._internal.root_url.RootHttpUrl"}, "bioimageio.spec._internal.types": {"fullname": "bioimageio.spec._internal.types", "modulename": "bioimageio.spec._internal.types", "kind": "module", "doc": "
    \n"}, "bioimageio.spec._internal.types.NotEmpty": {"fullname": "bioimageio.spec._internal.types.NotEmpty", "modulename": "bioimageio.spec._internal.types", "qualname": "NotEmpty", "kind": "variable", "doc": "
    \n", "default_value": "typing.Annotated[~S, MinLen(min_length=1)]"}, "bioimageio.spec._internal.types.Datetime": {"fullname": "bioimageio.spec._internal.types.Datetime", "modulename": "bioimageio.spec._internal.types", "qualname": "Datetime", "kind": "class", "doc": "
    Timestamp in ISO 8601 format\nwith a few restrictions listed here.
    \n", "bases": "pydantic.main.BaseModel, typing.Generic[~RootModelRootType]"}, "bioimageio.spec._internal.types.Doi": {"fullname": "bioimageio.spec._internal.types.Doi", "modulename": "bioimageio.spec._internal.types", "qualname": "Doi", "kind": "variable", "doc": "
    \n", "default_value": "<class 'bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, StringConstraints]]'>"}, "bioimageio.spec._internal.types.FormatVersionPlaceholder": {"fullname": "bioimageio.spec._internal.types.FormatVersionPlaceholder", "modulename": "bioimageio.spec._internal.types", "qualname": "FormatVersionPlaceholder", "kind": "variable", "doc": "
    \n", "default_value": "typing.Literal['latest', 'discover']"}, "bioimageio.spec._internal.types.IdentifierAnno": {"fullname": "bioimageio.spec._internal.types.IdentifierAnno", "modulename": "bioimageio.spec._internal.types", "qualname": "IdentifierAnno", "kind": "variable", "doc": "
    \n", "default_value": "typing.Annotated[str, MinLen(min_length=1), AfterValidator(func=<function _validate_identifier>), AfterValidator(func=<function _validate_is_not_keyword>)]"}, "bioimageio.spec._internal.types.Identifier": {"fullname": "bioimageio.spec._internal.types.Identifier", "modulename": "bioimageio.spec._internal.types", "qualname": "Identifier", "kind": "variable", "doc": "
    \n", "default_value": "<class 'bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator]]'>"}, "bioimageio.spec._internal.types.LowerCaseIdentifierAnno": {"fullname": "bioimageio.spec._internal.types.LowerCaseIdentifierAnno", "modulename": "bioimageio.spec._internal.types", "qualname": "LowerCaseIdentifierAnno", "kind": "variable", "doc": "
    \n", "default_value": "typing.Annotated[str, MinLen(min_length=1), AfterValidator(func=<function _validate_identifier>), AfterValidator(func=<function _validate_is_not_keyword>), typing.Annotated[~_StrType, Predicate(func=<method 'islower' of 'str' objects>)]]"}, "bioimageio.spec._internal.types.LowerCaseIdentifier": {"fullname": "bioimageio.spec._internal.types.LowerCaseIdentifier", "modulename": "bioimageio.spec._internal.types", "qualname": "LowerCaseIdentifier", "kind": "variable", "doc": "
    \n", "default_value": "<class 'bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate]]]'>"}, "bioimageio.spec._internal.types.OrcidId": {"fullname": "bioimageio.spec._internal.types.OrcidId", "modulename": "bioimageio.spec._internal.types", "qualname": "OrcidId", "kind": "variable", "doc": "
    \n", "default_value": "<class 'bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, AfterValidator]]'>"}, "bioimageio.spec._internal.types.SiUnit": {"fullname": "bioimageio.spec._internal.types.SiUnit", "modulename": "bioimageio.spec._internal.types", "qualname": "SiUnit", "kind": "variable", "doc": "
    \n", "default_value": "<class 'bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, StringConstraints, BeforeValidator]]'>"}, "bioimageio.spec._internal.types.ResourceId": {"fullname": "bioimageio.spec._internal.types.ResourceId", "modulename": "bioimageio.spec._internal.types", "qualname": "ResourceId", "kind": "variable", "doc": "
    \n", "default_value": "<class 'bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]]'>"}, "bioimageio.spec._internal.types.ApplicationId": {"fullname": "bioimageio.spec._internal.types.ApplicationId", "modulename": "bioimageio.spec._internal.types", "qualname": "ApplicationId", "kind": "variable", "doc": "
    \n", "default_value": "<class 'bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]]'>"}, "bioimageio.spec._internal.types.CollectionId": {"fullname": "bioimageio.spec._internal.types.CollectionId", "modulename": "bioimageio.spec._internal.types", "qualname": "CollectionId", "kind": "variable", "doc": "
    \n", "default_value": "<class 'bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]]'>"}, "bioimageio.spec._internal.types.DatasetId": {"fullname": "bioimageio.spec._internal.types.DatasetId", "modulename": "bioimageio.spec._internal.types", "qualname": "DatasetId", "kind": "variable", "doc": "
    \n", "default_value": "<class 'bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]]'>"}, "bioimageio.spec._internal.types.ModelId": {"fullname": "bioimageio.spec._internal.types.ModelId", "modulename": "bioimageio.spec._internal.types", "qualname": "ModelId", "kind": "variable", "doc": "
    \n", "default_value": "<class 'bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]]'>"}, "bioimageio.spec._internal.types.NotebookId": {"fullname": "bioimageio.spec._internal.types.NotebookId", "modulename": "bioimageio.spec._internal.types", "qualname": "NotebookId", "kind": "variable", "doc": "
    \n", "default_value": "<class 'bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]]'>"}, "bioimageio.spec._internal.url": {"fullname": "bioimageio.spec._internal.url", "modulename": "bioimageio.spec._internal.url", "kind": "module", "doc": "
    \n"}, "bioimageio.spec._internal.url.check_url": {"fullname": "bioimageio.spec._internal.url.check_url", "modulename": "bioimageio.spec._internal.url", "qualname": "check_url", "kind": "function", "doc": "
    \n", "signature": "(url: str) -> None:", "funcdef": "def"}, "bioimageio.spec._internal.url.HttpUrl": {"fullname": "bioimageio.spec._internal.url.HttpUrl", "modulename": "bioimageio.spec._internal.url", "qualname": "HttpUrl", "kind": "class", "doc": "
    A 'URL folder', possibly an invalid http URL
    \n", "bases": "pydantic.main.BaseModel, typing.Generic[~RootModelRootType]"}, "bioimageio.spec._internal.utils": {"fullname": "bioimageio.spec._internal.utils", "modulename": "bioimageio.spec._internal.utils", "kind": "module", "doc": "
    \n"}, "bioimageio.spec._internal.utils.NestedDict": {"fullname": "bioimageio.spec._internal.utils.NestedDict", "modulename": "bioimageio.spec._internal.utils", "qualname": "NestedDict", "kind": "variable", "doc": "
    \n", "default_value": "typing.Dict[~K, ForwardRef('NestedDict[K, V] | V')]"}, "bioimageio.spec._internal.utils.nest_dict": {"fullname": "bioimageio.spec._internal.utils.nest_dict", "modulename": "bioimageio.spec._internal.utils", "qualname": "nest_dict", "kind": "function", "doc": "
    \n", "signature": "(flat_dict: Dict[Tuple[~K, ...], ~V]) -> 'NestedDict[K, V]':", "funcdef": "def"}, "bioimageio.spec._internal.utils.nest_dict_with_narrow_first_key": {"fullname": "bioimageio.spec._internal.utils.nest_dict_with_narrow_first_key", "modulename": "bioimageio.spec._internal.utils", "qualname": "nest_dict_with_narrow_first_key", "kind": "function", "doc": "
    convenience function to annotate a special version of a NestedDict.\nRoot level keys are of a narrower type than the nested keys. If not a ValueError is raisd.
    \n", "signature": "(\tflat_dict: Dict[Tuple[~K, ...], ~V],\tfirst_k: Type[~FirstK]) -> "Dict[FirstK, 'NestedDict[K, V] | V']":", "funcdef": "def"}, "bioimageio.spec._internal.utils.unindent": {"fullname": "bioimageio.spec._internal.utils.unindent", "modulename": "bioimageio.spec._internal.utils", "qualname": "unindent", "kind": "function", "doc": "
    remove minimum count of spaces at beginning of each line.
    \n\n
    Args:\n    text: indented text\n    ignore_first_line: allows to correctly unindent doc strings
    \n", "signature": "(text: str, ignore_first_line: bool = False):", "funcdef": "def"}, "bioimageio.spec._internal.utils.P": {"fullname": "bioimageio.spec._internal.utils.P", "modulename": "bioimageio.spec._internal.utils", "qualname": "P", "kind": "variable", "doc": "
    \n", "default_value": "~P"}, "bioimageio.spec._internal.utils.assert_all_params_set_explicitly": {"fullname": "bioimageio.spec._internal.utils.assert_all_params_set_explicitly", "modulename": "bioimageio.spec._internal.utils", "qualname": "assert_all_params_set_explicitly", "kind": "function", "doc": "
    \n", "signature": "(fn: Callable[~P, ~T]) -> Callable[~P, ~T]:", "funcdef": "def"}, "bioimageio.spec._internal.validated_string": {"fullname": "bioimageio.spec._internal.validated_string", "modulename": "bioimageio.spec._internal.validated_string", "kind": "module", "doc": "
    \n"}, "bioimageio.spec._internal.validated_string.ValidatedString": {"fullname": "bioimageio.spec._internal.validated_string.ValidatedString", "modulename": "bioimageio.spec._internal.validated_string", "qualname": "ValidatedString", "kind": "class", "doc": "
    Usage docs: https://docs.pydantic.dev/2.6/concepts/models/#rootmodel-and-custom-root-types
    \n\n
    A Pydantic BaseModel for the root object of the model.
    \n\n
    Attributes:\n    root: The root object of the model.\n    __pydantic_root_model__: Whether the model is a RootModel.\n    __pydantic_private__: Private fields in the model.\n    __pydantic_extra__: Extra fields in the model.
    \n", "bases": "pydantic.main.BaseModel, typing.Generic[~RootModelRootType]"}, "bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, AfterValidator]]": {"fullname": "bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, AfterValidator]]", "modulename": "bioimageio.spec._internal.validated_string", "qualname": "ValidatedString[Annotated[str, AfterValidator]]", "kind": "class", "doc": "
    Usage docs: https://docs.pydantic.dev/2.6/concepts/models/#rootmodel-and-custom-root-types
    \n\n
    A Pydantic BaseModel for the root object of the model.
    \n\n
    Attributes:\n    root: The root object of the model.\n    __pydantic_root_model__: Whether the model is a RootModel.\n    __pydantic_private__: Private fields in the model.\n    __pydantic_extra__: Extra fields in the model.
    \n", "bases": "pydantic.main.BaseModel, typing.Generic[~RootModelRootType]"}, "bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, StringConstraints]]": {"fullname": "bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, StringConstraints]]", "modulename": "bioimageio.spec._internal.validated_string", "qualname": "ValidatedString[Annotated[str, StringConstraints]]", "kind": "class", "doc": "
    Usage docs: https://docs.pydantic.dev/2.6/concepts/models/#rootmodel-and-custom-root-types
    \n\n
    A Pydantic BaseModel for the root object of the model.
    \n\n
    Attributes:\n    root: The root object of the model.\n    __pydantic_root_model__: Whether the model is a RootModel.\n    __pydantic_private__: Private fields in the model.\n    __pydantic_extra__: Extra fields in the model.
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    Usage docs: https://docs.pydantic.dev/2.6/concepts/models/#rootmodel-and-custom-root-types
    \n\n
    A Pydantic BaseModel for the root object of the model.
    \n\n
    Attributes:\n    root: The root object of the model.\n    __pydantic_root_model__: Whether the model is a RootModel.\n    __pydantic_private__: Private fields in the model.\n    __pydantic_extra__: Extra fields in the model.
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    \n", "default_value": "<class 'bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, StringConstraints]]'>"}, "bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator]]": {"fullname": "bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator]]", "modulename": "bioimageio.spec._internal.validated_string", "qualname": "ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator]]", "kind": "class", "doc": "
    Usage docs: https://docs.pydantic.dev/2.6/concepts/models/#rootmodel-and-custom-root-types
    \n\n
    A Pydantic BaseModel for the root object of the model.
    \n\n
    Attributes:\n    root: The root object of the model.\n    __pydantic_root_model__: Whether the model is a RootModel.\n    __pydantic_private__: Private fields in the model.\n    __pydantic_extra__: Extra fields in the model.
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    Usage docs: https://docs.pydantic.dev/2.6/concepts/models/#rootmodel-and-custom-root-types
    \n\n
    A Pydantic BaseModel for the root object of the model.
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    Attributes:\n    root: The root object of the model.\n    __pydantic_root_model__: Whether the model is a RootModel.\n    __pydantic_private__: Private fields in the model.\n    __pydantic_extra__: Extra fields in the model.
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    \n", "default_value": "<class 'bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, AfterValidator]]'>"}, "bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, StringConstraints, BeforeValidator]]": {"fullname": "bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, StringConstraints, BeforeValidator]]", "modulename": "bioimageio.spec._internal.validated_string", "qualname": "ValidatedString[Annotated[str, StringConstraints, BeforeValidator]]", "kind": "class", "doc": "
    Usage docs: https://docs.pydantic.dev/2.6/concepts/models/#rootmodel-and-custom-root-types
    \n\n
    A Pydantic BaseModel for the root object of the model.
    \n\n
    Attributes:\n    root: The root object of the model.\n    __pydantic_root_model__: Whether the model is a RootModel.\n    __pydantic_private__: Private fields in the model.\n    __pydantic_extra__: Extra fields in the model.
    \n", "bases": "pydantic.main.BaseModel, typing.Generic[~RootModelRootType]"}, "bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]]": {"fullname": "bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]]", "modulename": "bioimageio.spec._internal.validated_string", "qualname": "ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]]", "kind": "class", "doc": "
    Usage docs: https://docs.pydantic.dev/2.6/concepts/models/#rootmodel-and-custom-root-types
    \n\n
    A Pydantic BaseModel for the root object of the model.
    \n\n
    Attributes:\n    root: The root object of the model.\n    __pydantic_root_model__: Whether the model is a RootModel.\n    __pydantic_private__: Private fields in the model.\n    __pydantic_extra__: Extra fields in the model.
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    Usage docs: https://docs.pydantic.dev/2.6/concepts/models/#rootmodel-and-custom-root-types
    \n\n
    A Pydantic BaseModel for the root object of the model.
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    Attributes:\n    root: The root object of the model.\n    __pydantic_root_model__: Whether the model is a RootModel.\n    __pydantic_private__: Private fields in the model.\n    __pydantic_extra__: Extra fields in the model.
    \n", "bases": "pydantic.main.BaseModel, typing.Generic[~RootModelRootType]"}, "bioimageio.spec._internal.validation_context": {"fullname": "bioimageio.spec._internal.validation_context", "modulename": "bioimageio.spec._internal.validation_context", "kind": "module", "doc": "
    \n"}, "bioimageio.spec._internal.validation_context.ValidationContext": {"fullname": "bioimageio.spec._internal.validation_context.ValidationContext", "modulename": "bioimageio.spec._internal.validation_context", "qualname": "ValidationContext", "kind": "class", "doc": "
    \n"}, "bioimageio.spec._internal.validation_context.ValidationContext.__init__": {"fullname": "bioimageio.spec._internal.validation_context.ValidationContext.__init__", "modulename": "bioimageio.spec._internal.validation_context", "qualname": "ValidationContext.__init__", "kind": "function", "doc": "
    \n", "signature": "(\troot: Union[bioimageio.spec._internal.root_url.RootHttpUrl, Annotated[pathlib.Path, PathType(path_type='dir'), Predicate(func=<function PurePath.is_absolute>)]] = PosixPath('.'),\twarning_level: Literal[20, 30, 35, 50] = 50,\tlog_warnings: bool = True,\tfile_name: Optional[str] = None,\tperform_io_checks: bool = True)"}, "bioimageio.spec._internal.validation_context.ValidationContext.root": {"fullname": "bioimageio.spec._internal.validation_context.ValidationContext.root", "modulename": "bioimageio.spec._internal.validation_context", "qualname": "ValidationContext.root", "kind": "variable", "doc": "
    url/directory serving as base to resolve any relative file paths
    \n", "annotation": ": Union[bioimageio.spec._internal.root_url.RootHttpUrl, Annotated[pathlib.Path, PathType(path_type='dir'), Predicate(func=<function PurePath.is_absolute at 0x7afca4145940>)]]", "default_value": "PosixPath('.')"}, "bioimageio.spec._internal.validation_context.ValidationContext.warning_level": {"fullname": "bioimageio.spec._internal.validation_context.ValidationContext.warning_level", "modulename": "bioimageio.spec._internal.validation_context", "qualname": "ValidationContext.warning_level", "kind": "variable", "doc": "
    raise warnings of severity s as validation errors if s >= warning_level
    \n", "annotation": ": Literal[20, 30, 35, 50]", "default_value": "50"}, "bioimageio.spec._internal.validation_context.ValidationContext.log_warnings": {"fullname": "bioimageio.spec._internal.validation_context.ValidationContext.log_warnings", "modulename": "bioimageio.spec._internal.validation_context", "qualname": "ValidationContext.log_warnings", "kind": "variable", "doc": "
    if True log warnings that are not raised to the console
    \n", "annotation": ": bool", "default_value": "True"}, "bioimageio.spec._internal.validation_context.ValidationContext.file_name": {"fullname": "bioimageio.spec._internal.validation_context.ValidationContext.file_name", "modulename": "bioimageio.spec._internal.validation_context", "qualname": "ValidationContext.file_name", "kind": "variable", "doc": "
    file name of the bioimageio Yaml file
    \n", "annotation": ": Optional[str]", "default_value": "None"}, "bioimageio.spec._internal.validation_context.ValidationContext.perform_io_checks": {"fullname": "bioimageio.spec._internal.validation_context.ValidationContext.perform_io_checks", "modulename": "bioimageio.spec._internal.validation_context", "qualname": "ValidationContext.perform_io_checks", "kind": "variable", "doc": "
    wether or not to perform validation that requires file io,\ne.g. downloading a remote files.
    \n\n
    Existence of local absolute file paths is still being checked.
    \n", "annotation": ": bool", "default_value": "True"}, "bioimageio.spec._internal.validation_context.ValidationContext.replace": {"fullname": "bioimageio.spec._internal.validation_context.ValidationContext.replace", "modulename": "bioimageio.spec._internal.validation_context", "qualname": "ValidationContext.replace", "kind": "function", "doc": "
    \n", "signature": "(\tself,\troot: Union[bioimageio.spec._internal.root_url.RootHttpUrl, Annotated[pathlib.Path, PathType(path_type='dir')], NoneType] = None,\twarning_level: Optional[Literal[20, 30, 35, 50]] = None,\tlog_warnings: Optional[bool] = None,\tfile_name: Optional[str] = None,\tperform_io_checks: Optional[bool] = None) -> bioimageio.spec._internal.validation_context.ValidationContext:", "funcdef": "def"}, "bioimageio.spec._internal.validation_context.ValidationContext.source_name": {"fullname": "bioimageio.spec._internal.validation_context.ValidationContext.source_name", "modulename": "bioimageio.spec._internal.validation_context", "qualname": "ValidationContext.source_name", "kind": "variable", "doc": "
    \n", "annotation": ": str"}, "bioimageio.spec._internal.validation_context.validation_context_var": {"fullname": "bioimageio.spec._internal.validation_context.validation_context_var", "modulename": "bioimageio.spec._internal.validation_context", "qualname": "validation_context_var", "kind": "variable", "doc": "
    \n", "annotation": ": _contextvars.ContextVar[bioimageio.spec._internal.validation_context.ValidationContext]", "default_value": "<ContextVar name='validation_context_var' default=ValidationContext(_context_tokens=[], root=PosixPath('.'), warning_level=50, log_warnings=True, file_name=None, perform_io_checks=True)>"}, "bioimageio.spec._internal.validator_annotations": {"fullname": "bioimageio.spec._internal.validator_annotations", "modulename": "bioimageio.spec._internal.validator_annotations", "kind": "module", "doc": "
    \n"}, "bioimageio.spec._internal.validator_annotations.AfterValidator": {"fullname": "bioimageio.spec._internal.validator_annotations.AfterValidator", "modulename": "bioimageio.spec._internal.validator_annotations", "qualname": "AfterValidator", "kind": "class", "doc": "
    \n", "bases": "pydantic.functional_validators.AfterValidator"}, "bioimageio.spec._internal.validator_annotations.AfterValidator.__init__": {"fullname": "bioimageio.spec._internal.validator_annotations.AfterValidator.__init__", "modulename": "bioimageio.spec._internal.validator_annotations", "qualname": "AfterValidator.__init__", "kind": "function", "doc": "
    \n", "signature": "(\tfunc: 'core_schema.NoInfoValidatorFunction | core_schema.WithInfoValidatorFunction')"}, "bioimageio.spec._internal.validator_annotations.BeforeValidator": {"fullname": "bioimageio.spec._internal.validator_annotations.BeforeValidator", "modulename": "bioimageio.spec._internal.validator_annotations", "qualname": "BeforeValidator", "kind": "class", "doc": "
    \n", "bases": "pydantic.functional_validators.BeforeValidator"}, "bioimageio.spec._internal.validator_annotations.BeforeValidator.__init__": {"fullname": "bioimageio.spec._internal.validator_annotations.BeforeValidator.__init__", "modulename": "bioimageio.spec._internal.validator_annotations", "qualname": "BeforeValidator.__init__", "kind": "function", "doc": "
    \n", "signature": "(\tfunc: 'core_schema.NoInfoValidatorFunction | core_schema.WithInfoValidatorFunction')"}, "bioimageio.spec._internal.validator_annotations.Predicate": {"fullname": "bioimageio.spec._internal.validator_annotations.Predicate", "modulename": "bioimageio.spec._internal.validator_annotations", "qualname": "Predicate", "kind": "class", "doc": "
    \n", "bases": "annotated_types.Predicate"}, "bioimageio.spec._internal.validator_annotations.Predicate.__init__": {"fullname": "bioimageio.spec._internal.validator_annotations.Predicate.__init__", "modulename": "bioimageio.spec._internal.validator_annotations", "qualname": "Predicate.__init__", "kind": "function", "doc": "
    \n", "signature": "(func: Callable[[Any], bool])"}, "bioimageio.spec._internal.validator_annotations.RestrictCharacters": {"fullname": "bioimageio.spec._internal.validator_annotations.RestrictCharacters", "modulename": "bioimageio.spec._internal.validator_annotations", "qualname": "RestrictCharacters", "kind": "class", "doc": "
    \n"}, "bioimageio.spec._internal.validator_annotations.RestrictCharacters.__init__": {"fullname": "bioimageio.spec._internal.validator_annotations.RestrictCharacters.__init__", "modulename": "bioimageio.spec._internal.validator_annotations", "qualname": "RestrictCharacters.__init__", "kind": "function", "doc": "
    \n", "signature": "(alphabet: str)"}, "bioimageio.spec._internal.validator_annotations.RestrictCharacters.alphabet": {"fullname": "bioimageio.spec._internal.validator_annotations.RestrictCharacters.alphabet", "modulename": "bioimageio.spec._internal.validator_annotations", "qualname": "RestrictCharacters.alphabet", "kind": "variable", "doc": "
    \n", "annotation": ": str"}, "bioimageio.spec._internal.validator_annotations.RestrictCharacters.validate": {"fullname": "bioimageio.spec._internal.validator_annotations.RestrictCharacters.validate", "modulename": "bioimageio.spec._internal.validator_annotations", "qualname": "RestrictCharacters.validate", "kind": "function", "doc": "
    \n", "signature": "(self, value: str) -> str:", "funcdef": "def"}, "bioimageio.spec._internal.version_type": {"fullname": "bioimageio.spec._internal.version_type", "modulename": "bioimageio.spec._internal.version_type", "kind": "module", "doc": "
    \n"}, "bioimageio.spec._internal.version_type.Version": {"fullname": "bioimageio.spec._internal.version_type.Version", "modulename": "bioimageio.spec._internal.version_type", "qualname": "Version", "kind": "class", "doc": "
    wraps a packaging.version.Version instance for validation in pydantic models
    \n", "bases": "pydantic.main.BaseModel, typing.Generic[~RootModelRootType]"}, "bioimageio.spec._internal.version_type.Version.epoch": {"fullname": "bioimageio.spec._internal.version_type.Version.epoch", "modulename": "bioimageio.spec._internal.version_type", "qualname": "Version.epoch", "kind": "variable", "doc": "
    The epoch of the version.
    \n\n
    \n
    >>> Version("2.0.0").epoch\n0\n>>> Version("1!2.0.0").epoch\n1\n
    \n
    \n", "annotation": ": int"}, "bioimageio.spec._internal.version_type.Version.release": {"fullname": "bioimageio.spec._internal.version_type.Version.release", "modulename": "bioimageio.spec._internal.version_type", "qualname": "Version.release", "kind": "variable", "doc": "
    The components of the \"release\" segment of the version.
    \n\n
    \n
    >>> Version("1.2.3").release\n(1, 2, 3)\n>>> Version("2.0.0").release\n(2, 0, 0)\n>>> Version("1!2.0.0.post0").release\n(2, 0, 0)\n
    \n
    \n\n
    Includes trailing zeroes but not the epoch or any pre-release / development /\npost-release suffixes.
    \n", "annotation": ": Tuple[int, ...]"}, "bioimageio.spec._internal.version_type.Version.pre": {"fullname": "bioimageio.spec._internal.version_type.Version.pre", "modulename": "bioimageio.spec._internal.version_type", "qualname": "Version.pre", "kind": "variable", "doc": "
    The pre-release segment of the version.
    \n\n
    \n
    >>> print(Version("1.2.3").pre)\nNone\n>>> Version("1.2.3a1").pre\n('a', 1)\n>>> Version("1.2.3b1").pre\n('b', 1)\n>>> Version("1.2.3rc1").pre\n('rc', 1)\n
    \n
    \n", "annotation": ": Optional[Tuple[str, int]]"}, "bioimageio.spec._internal.version_type.Version.post": {"fullname": "bioimageio.spec._internal.version_type.Version.post", "modulename": "bioimageio.spec._internal.version_type", "qualname": "Version.post", "kind": "variable", "doc": "
    The post-release number of the version.
    \n\n
    \n
    >>> print(Version("1.2.3").post)\nNone\n>>> Version("1.2.3.post1").post\n1\n
    \n
    \n", "annotation": ": Optional[int]"}, "bioimageio.spec._internal.version_type.Version.dev": {"fullname": "bioimageio.spec._internal.version_type.Version.dev", "modulename": "bioimageio.spec._internal.version_type", "qualname": "Version.dev", "kind": "variable", "doc": "
    The development number of the version.
    \n\n
    \n
    >>> print(Version("1.2.3").dev)\nNone\n>>> Version("1.2.3.dev1").dev\n1\n
    \n
    \n", "annotation": ": Optional[int]"}, "bioimageio.spec._internal.version_type.Version.local": {"fullname": "bioimageio.spec._internal.version_type.Version.local", "modulename": "bioimageio.spec._internal.version_type", "qualname": "Version.local", "kind": "variable", "doc": "
    The local version segment of the version.
    \n\n
    \n
    >>> print(Version("1.2.3").local)\nNone\n>>> Version("1.2.3+abc").local\n'abc'\n
    \n
    \n", "annotation": ": Optional[str]"}, "bioimageio.spec._internal.version_type.Version.public": {"fullname": "bioimageio.spec._internal.version_type.Version.public", "modulename": "bioimageio.spec._internal.version_type", "qualname": "Version.public", "kind": "variable", "doc": "
    The public portion of the version.
    \n\n
    \n
    >>> Version("1.2.3").public\n'1.2.3'\n>>> Version("1.2.3+abc").public\n'1.2.3'\n>>> Version("1.2.3+abc.dev1").public\n'1.2.3'\n
    \n
    \n", "annotation": ": str"}, "bioimageio.spec._internal.version_type.Version.base_version": {"fullname": "bioimageio.spec._internal.version_type.Version.base_version", "modulename": "bioimageio.spec._internal.version_type", "qualname": "Version.base_version", "kind": "variable", "doc": "
    The \"base version\" of the version.
    \n\n
    \n
    >>> Version("1.2.3").base_version\n'1.2.3'\n>>> Version("1.2.3+abc").base_version\n'1.2.3'\n>>> Version("1!1.2.3+abc.dev1").base_version\n'1!1.2.3'\n
    \n
    \n\n
    The \"base version\" is the public version of the project without any pre or post\nrelease markers.
    \n", "annotation": ": str"}, "bioimageio.spec._internal.version_type.Version.is_prerelease": {"fullname": "bioimageio.spec._internal.version_type.Version.is_prerelease", "modulename": "bioimageio.spec._internal.version_type", "qualname": "Version.is_prerelease", "kind": "variable", "doc": "
    Whether this version is a pre-release.
    \n\n
    \n
    >>> Version("1.2.3").is_prerelease\nFalse\n>>> Version("1.2.3a1").is_prerelease\nTrue\n>>> Version("1.2.3b1").is_prerelease\nTrue\n>>> Version("1.2.3rc1").is_prerelease\nTrue\n>>> Version("1.2.3dev1").is_prerelease\nTrue\n
    \n
    \n", "annotation": ": bool"}, "bioimageio.spec._internal.version_type.Version.is_postrelease": {"fullname": "bioimageio.spec._internal.version_type.Version.is_postrelease", "modulename": "bioimageio.spec._internal.version_type", "qualname": "Version.is_postrelease", "kind": "variable", "doc": "
    Whether this version is a post-release.
    \n\n
    \n
    >>> Version("1.2.3").is_postrelease\nFalse\n>>> Version("1.2.3.post1").is_postrelease\nTrue\n
    \n
    \n", "annotation": ": bool"}, "bioimageio.spec._internal.version_type.Version.is_devrelease": {"fullname": "bioimageio.spec._internal.version_type.Version.is_devrelease", "modulename": "bioimageio.spec._internal.version_type", "qualname": "Version.is_devrelease", "kind": "variable", "doc": "
    Whether this version is a development release.
    \n\n
    \n
    >>> Version("1.2.3").is_devrelease\nFalse\n>>> Version("1.2.3.dev1").is_devrelease\nTrue\n
    \n
    \n", "annotation": ": bool"}, "bioimageio.spec._internal.version_type.Version.major": {"fullname": "bioimageio.spec._internal.version_type.Version.major", "modulename": "bioimageio.spec._internal.version_type", "qualname": "Version.major", "kind": "variable", "doc": "
    The first item of release or 0 if unavailable.
    \n\n
    \n
    >>> Version("1.2.3").major\n1\n
    \n
    \n", "annotation": ": int"}, "bioimageio.spec._internal.version_type.Version.minor": {"fullname": "bioimageio.spec._internal.version_type.Version.minor", "modulename": "bioimageio.spec._internal.version_type", "qualname": "Version.minor", "kind": "variable", "doc": "
    The second item of release or 0 if unavailable.
    \n\n
    \n
    >>> Version("1.2.3").minor\n2\n>>> Version("1").minor\n0\n
    \n
    \n", "annotation": ": int"}, "bioimageio.spec._internal.version_type.Version.micro": {"fullname": "bioimageio.spec._internal.version_type.Version.micro", "modulename": "bioimageio.spec._internal.version_type", "qualname": "Version.micro", "kind": "variable", "doc": "
    The third item of release or 0 if unavailable.
    \n\n
    \n
    >>> Version("1.2.3").micro\n3\n>>> Version("1").micro\n0\n
    \n
    \n", "annotation": ": int"}, "bioimageio.spec._internal.warning_levels": {"fullname": "bioimageio.spec._internal.warning_levels", "modulename": "bioimageio.spec._internal.warning_levels", "kind": "module", "doc": "
    \n"}, "bioimageio.spec._internal.warning_levels.WarningSeverity": {"fullname": "bioimageio.spec._internal.warning_levels.WarningSeverity", "modulename": "bioimageio.spec._internal.warning_levels", "qualname": "WarningSeverity", "kind": "variable", "doc": "
    \n", "default_value": "typing.Literal[20, 30, 35]"}, "bioimageio.spec._internal.warning_levels.WarningLevel": {"fullname": "bioimageio.spec._internal.warning_levels.WarningLevel", "modulename": "bioimageio.spec._internal.warning_levels", "qualname": "WarningLevel", "kind": "variable", "doc": "
    With warning level x validation warnings of severity >=x are raised.\nHighest warning level 50/error does not raise any validaiton warnings (only validation errors).
    \n", "default_value": "typing.Literal[20, 30, 35, 50]"}, "bioimageio.spec.application": {"fullname": "bioimageio.spec.application", "modulename": "bioimageio.spec.application", "kind": "module", "doc": "
    implementaions of all released minor versions are available in submodules:
    \n\n\n"}, "bioimageio.spec.application.AnyApplicationDescr": {"fullname": "bioimageio.spec.application.AnyApplicationDescr", "modulename": "bioimageio.spec.application", "qualname": "AnyApplicationDescr", "kind": "variable", "doc": "
    Union of any released application desription
    \n", "default_value": "typing.Annotated[typing.Union[bioimageio.spec.application.v0_2.ApplicationDescr, bioimageio.spec.application.v0_3.ApplicationDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)]"}, "bioimageio.spec.application.v0_2": {"fullname": "bioimageio.spec.application.v0_2", "modulename": "bioimageio.spec.application.v0_2", "kind": "module", "doc": "
    \n"}, "bioimageio.spec.application.v0_2.ApplicationDescr": {"fullname": "bioimageio.spec.application.v0_2.ApplicationDescr", "modulename": "bioimageio.spec.application.v0_2", "qualname": "ApplicationDescr", "kind": "class", "doc": "
    Bioimage.io description of an application.
    \n", "bases": "bioimageio.spec.generic.v0_2.GenericDescrBase"}, "bioimageio.spec.application.v0_2.ApplicationDescr.type": {"fullname": "bioimageio.spec.application.v0_2.ApplicationDescr.type", "modulename": "bioimageio.spec.application.v0_2", "qualname": "ApplicationDescr.type", "kind": "variable", "doc": "
    \n", "annotation": ": Literal['application']"}, "bioimageio.spec.application.v0_2.ApplicationDescr.id": {"fullname": "bioimageio.spec.application.v0_2.ApplicationDescr.id", "modulename": "bioimageio.spec.application.v0_2", "qualname": "ApplicationDescr.id", "kind": "variable", "doc": "
    Model zoo (bioimage.io) wide, unique identifier (assigned by bioimage.io)
    \n", "annotation": ": Optional[bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]]]"}, "bioimageio.spec.application.v0_2.ApplicationDescr.source": {"fullname": "bioimageio.spec.application.v0_2.ApplicationDescr.source", "modulename": "bioimageio.spec.application.v0_2", "qualname": "ApplicationDescr.source", "kind": "variable", "doc": "
    The primary source of the application
    \n", "annotation": ": Annotated[Optional[Annotated[Union[Annotated[pathlib.Path, PathType(path_type='file')], bioimageio.spec._internal.io.RelativeFilePath, bioimageio.spec._internal.url.HttpUrl, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator(func=<function wo_special_file_name at 0x7afca0d90540>), PlainSerializer(func=<function _package at 0x7afca0d91760>, return_type=PydanticUndefined, when_used='unless-none')]], FieldInfo(annotation=NoneType, required=True, description='URL or path to the source of the application')]"}, "bioimageio.spec.application.v0_2.ApplicationDescr.implemented_format_version": {"fullname": "bioimageio.spec.application.v0_2.ApplicationDescr.implemented_format_version", "modulename": "bioimageio.spec.application.v0_2", "qualname": "ApplicationDescr.implemented_format_version", "kind": "variable", "doc": "
    \n", "annotation": ": ClassVar[str]", "default_value": "'0.2.4'"}, "bioimageio.spec.application.v0_2.ApplicationDescr.implemented_format_version_tuple": {"fullname": "bioimageio.spec.application.v0_2.ApplicationDescr.implemented_format_version_tuple", "modulename": "bioimageio.spec.application.v0_2", "qualname": "ApplicationDescr.implemented_format_version_tuple", "kind": "variable", "doc": "
    \n", "annotation": ": ClassVar[Tuple[int, int, int]]", "default_value": "(0, 2, 4)"}, "bioimageio.spec.application.v0_2.ApplicationDescr.model_config": {"fullname": "bioimageio.spec.application.v0_2.ApplicationDescr.model_config", "modulename": "bioimageio.spec.application.v0_2", "qualname": "ApplicationDescr.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True, 'title': 'bioimage.io application specification'}"}, "bioimageio.spec.application.v0_2.ApplicationDescr.model_fields": {"fullname": "bioimageio.spec.application.v0_2.ApplicationDescr.model_fields", "modulename": "bioimageio.spec.application.v0_2", "qualname": "ApplicationDescr.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'name': FieldInfo(annotation=str, required=True, metadata=[MinLen(min_length=1), AfterWarner(func=<function as_warning.<locals>.wrapper>, severity=30, msg='Longer than 128 characters.', context={'typ': typing.Annotated[typing.Any, MaxLen(max_length=128)]})]), 'description': FieldInfo(annotation=str, required=True), 'covers': FieldInfo(annotation=List[Annotated[Union[HttpUrl, Annotated[Path, PathType, Predicate], RelativeFilePath], WithSuffix, PlainSerializer]], required=False, default_factory=list, description="Cover images. Please use an image smaller than 500KB and an aspect ratio width to height of 2:1.\\nThe supported image formats are: ('.gif', '.jpeg', '.jpg', '.png', '.svg')", examples=['cover.png']), 'id_emoji': FieldInfo(annotation=Union[Annotated[str, Len], NoneType], required=False), 'authors': FieldInfo(annotation=List[Author], required=False, default_factory=list), 'attachments': FieldInfo(annotation=Union[AttachmentsDescr, NoneType], required=False), 'cite': FieldInfo(annotation=List[CiteEntry], required=False, default_factory=list), 'config': FieldInfo(annotation=Dict[str, YamlValue], required=False, default_factory=dict, examples=[{'bioimageio': {'my_custom_key': 3837283, 'another_key': {'nested': 'value'}}, 'imagej': {'macro_dir': 'path/to/macro/file'}}]), 'download_url': FieldInfo(annotation=Union[HttpUrl, NoneType], required=False), 'git_repo': FieldInfo(annotation=Union[str, NoneType], required=False, examples=['https://github.com/bioimage-io/spec-bioimage-io/tree/main/example_descriptions/models/unet2d_nuclei_broad']), 'icon': FieldInfo(annotation=Union[Annotated[Union[Annotated[Path, PathType], RelativeFilePath, HttpUrl, Annotated[Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator, PlainSerializer], Annotated[str, Len], NoneType], required=False), 'links': FieldInfo(annotation=List[str], required=False, default_factory=list, examples=[('ilastik/ilastik', 'deepimagej/deepimagej', 'zero/notebook_u-net_3d_zerocostdl4mic')]), 'uploader': FieldInfo(annotation=Union[Uploader, NoneType], required=False), 'maintainers': FieldInfo(annotation=List[Maintainer], required=False, default_factory=list), 'rdf_source': FieldInfo(annotation=Union[Annotated[Path, PathType], RelativeFilePath, HttpUrl, Annotated[Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)], NoneType], required=False), 'tags': FieldInfo(annotation=List[str], required=False, default_factory=list, examples=[('unet2d', 'pytorch', 'nucleus', 'segmentation', 'dsb2018')]), 'version': FieldInfo(annotation=Union[Version, NoneType], required=False), 'version_number': FieldInfo(annotation=Union[int, NoneType], required=False), 'format_version': FieldInfo(annotation=Literal['0.2.4'], required=False, default='0.2.4'), 'badges': FieldInfo(annotation=List[BadgeDescr], required=False, default_factory=list), 'documentation': FieldInfo(annotation=Union[Annotated[Union[Annotated[Path, PathType], RelativeFilePath, HttpUrl, Annotated[Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator, PlainSerializer], NoneType], required=False, examples=['https://raw.githubusercontent.com/bioimage-io/spec-bioimage-io/main/example_descriptions/models/unet2d_nuclei_broad/README.md', 'README.md']), 'license': FieldInfo(annotation=Union[LicenseId, DeprecatedLicenseId, str, NoneType], required=False, examples=['CC-BY-4.0', 'MIT', 'BSD-2-Clause']), 'type': FieldInfo(annotation=Literal['application'], required=False, default='application'), 'id': FieldInfo(annotation=Union[ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]], NoneType], required=False), 'source': FieldInfo(annotation=Union[Annotated[Union[Annotated[Path, PathType], RelativeFilePath, HttpUrl, Annotated[Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator, PlainSerializer], NoneType], required=False, description='URL or path to the source of the application')}"}, "bioimageio.spec.application.v0_2.ApplicationDescr.model_computed_fields": {"fullname": "bioimageio.spec.application.v0_2.ApplicationDescr.model_computed_fields", "modulename": "bioimageio.spec.application.v0_2", "qualname": "ApplicationDescr.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.application.v0_2.LinkedApplication": {"fullname": "bioimageio.spec.application.v0_2.LinkedApplication", "modulename": "bioimageio.spec.application.v0_2", "qualname": "LinkedApplication", "kind": "class", "doc": "
    Reference to a bioimage.io application.
    \n", "bases": "bioimageio.spec._internal.node.Node"}, "bioimageio.spec.application.v0_2.LinkedApplication.id": {"fullname": "bioimageio.spec.application.v0_2.LinkedApplication.id", "modulename": "bioimageio.spec.application.v0_2", "qualname": "LinkedApplication.id", "kind": "variable", "doc": "
    A valid application id from the bioimage.io collection.
    \n", "annotation": ": bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]]"}, "bioimageio.spec.application.v0_2.LinkedApplication.version_number": {"fullname": "bioimageio.spec.application.v0_2.LinkedApplication.version_number", "modulename": "bioimageio.spec.application.v0_2", "qualname": "LinkedApplication.version_number", "kind": "variable", "doc": "
    version number (n-th published version, not the semantic version) of linked application
    \n", "annotation": ": Optional[int]"}, "bioimageio.spec.application.v0_2.LinkedApplication.model_config": {"fullname": "bioimageio.spec.application.v0_2.LinkedApplication.model_config", "modulename": "bioimageio.spec.application.v0_2", "qualname": "LinkedApplication.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.application.v0_2.LinkedApplication.model_fields": {"fullname": "bioimageio.spec.application.v0_2.LinkedApplication.model_fields", "modulename": "bioimageio.spec.application.v0_2", "qualname": "LinkedApplication.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'id': FieldInfo(annotation=ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]], required=True), 'version_number': FieldInfo(annotation=Union[int, NoneType], required=False)}"}, "bioimageio.spec.application.v0_2.LinkedApplication.model_computed_fields": {"fullname": "bioimageio.spec.application.v0_2.LinkedApplication.model_computed_fields", "modulename": "bioimageio.spec.application.v0_2", "qualname": "LinkedApplication.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.application.v0_3": {"fullname": "bioimageio.spec.application.v0_3", "modulename": "bioimageio.spec.application.v0_3", "kind": "module", "doc": "
    \n"}, "bioimageio.spec.application.v0_3.ApplicationDescr": {"fullname": "bioimageio.spec.application.v0_3.ApplicationDescr", "modulename": "bioimageio.spec.application.v0_3", "qualname": "ApplicationDescr", "kind": "class", "doc": "
    Bioimage.io description of an application.
    \n", "bases": "bioimageio.spec.generic.v0_3.GenericDescrBase"}, "bioimageio.spec.application.v0_3.ApplicationDescr.type": {"fullname": "bioimageio.spec.application.v0_3.ApplicationDescr.type", "modulename": "bioimageio.spec.application.v0_3", "qualname": "ApplicationDescr.type", "kind": "variable", "doc": "
    \n", "annotation": ": Literal['application']"}, "bioimageio.spec.application.v0_3.ApplicationDescr.id": {"fullname": "bioimageio.spec.application.v0_3.ApplicationDescr.id", "modulename": "bioimageio.spec.application.v0_3", "qualname": "ApplicationDescr.id", "kind": "variable", "doc": "
    Model zoo (bioimage.io) wide, unique identifier (assigned by bioimage.io)
    \n", "annotation": ": Optional[bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]]]"}, "bioimageio.spec.application.v0_3.ApplicationDescr.parent": {"fullname": "bioimageio.spec.application.v0_3.ApplicationDescr.parent", "modulename": "bioimageio.spec.application.v0_3", "qualname": "ApplicationDescr.parent", "kind": "variable", "doc": "
    The description from which this one is derived
    \n", "annotation": ": Optional[bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]]]"}, "bioimageio.spec.application.v0_3.ApplicationDescr.source": {"fullname": "bioimageio.spec.application.v0_3.ApplicationDescr.source", "modulename": "bioimageio.spec.application.v0_3", "qualname": "ApplicationDescr.source", "kind": "variable", "doc": "
    The primary source of the application
    \n", "annotation": ": Annotated[Optional[Annotated[Union[Annotated[pathlib.Path, PathType(path_type='file')], bioimageio.spec._internal.io.RelativeFilePath, bioimageio.spec._internal.url.HttpUrl, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator(func=<function wo_special_file_name at 0x7afca0d90540>), PlainSerializer(func=<function _package at 0x7afca0d91760>, return_type=PydanticUndefined, when_used='unless-none')]], FieldInfo(annotation=NoneType, required=True, description='URL or path to the source of the application')]"}, "bioimageio.spec.application.v0_3.ApplicationDescr.implemented_format_version": {"fullname": "bioimageio.spec.application.v0_3.ApplicationDescr.implemented_format_version", "modulename": "bioimageio.spec.application.v0_3", "qualname": "ApplicationDescr.implemented_format_version", "kind": "variable", "doc": "
    \n", "annotation": ": ClassVar[str]", "default_value": "'0.3.0'"}, "bioimageio.spec.application.v0_3.ApplicationDescr.implemented_format_version_tuple": {"fullname": "bioimageio.spec.application.v0_3.ApplicationDescr.implemented_format_version_tuple", "modulename": "bioimageio.spec.application.v0_3", "qualname": "ApplicationDescr.implemented_format_version_tuple", "kind": "variable", "doc": "
    \n", "annotation": ": ClassVar[Tuple[int, int, int]]", "default_value": "(0, 3, 0)"}, "bioimageio.spec.application.v0_3.ApplicationDescr.model_config": {"fullname": "bioimageio.spec.application.v0_3.ApplicationDescr.model_config", "modulename": "bioimageio.spec.application.v0_3", "qualname": "ApplicationDescr.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True, 'title': 'bioimage.io application specification'}"}, "bioimageio.spec.application.v0_3.ApplicationDescr.model_fields": {"fullname": "bioimageio.spec.application.v0_3.ApplicationDescr.model_fields", "modulename": "bioimageio.spec.application.v0_3", "qualname": "ApplicationDescr.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'name': FieldInfo(annotation=str, required=True, metadata=[MinLen(min_length=1), MaxLen(max_length=128)]), 'description': FieldInfo(annotation=str, required=True, metadata=[MaxLen(max_length=1024), AfterWarner(func=<function as_warning.<locals>.wrapper>, severity=30, msg='Description longer than 512 characters.', context={'typ': typing.Annotated[typing.Any, MaxLen(max_length=512)]})]), 'covers': FieldInfo(annotation=List[Annotated[Union[HttpUrl, Annotated[Path, PathType, Predicate], RelativeFilePath], WithSuffix, PlainSerializer]], required=False, default_factory=list, description="Cover images. Please use an image smaller than 500KB and an aspect ratio width to height of 2:1 or 1:1.\\nThe supported image formats are: ('.gif', '.jpeg', '.jpg', '.png', '.svg')", examples=[]), 'id_emoji': FieldInfo(annotation=Union[Annotated[str, Len], NoneType], required=False), 'authors': FieldInfo(annotation=List[Author], required=True, metadata=[MinLen(min_length=1)]), 'attachments': FieldInfo(annotation=List[FileDescr], required=False, default_factory=list), 'cite': FieldInfo(annotation=List[CiteEntry], required=True, metadata=[MinLen(min_length=1)]), 'license': FieldInfo(annotation=Union[LicenseId, DeprecatedLicenseId], required=True, examples=['CC-BY-4.0', 'MIT', 'BSD-2-Clause'], metadata=[AfterWarner(func=<function as_warning.<locals>.wrapper>, severity=30, msg='{value} is deprecated, see https://spdx.org/licenses/{value}.html', context={'typ': <class 'bioimageio.spec._internal.license_id.LicenseId'>})]), 'config': FieldInfo(annotation=Dict[str, YamlValue], required=False, default_factory=dict, examples=[{'bioimageio': {'my_custom_key': 3837283, 'another_key': {'nested': 'value'}}, 'imagej': {'macro_dir': 'path/to/macro/file'}}]), 'git_repo': FieldInfo(annotation=Union[HttpUrl, NoneType], required=False, examples=['https://github.com/bioimage-io/spec-bioimage-io/tree/main/example_descriptions/models/unet2d_nuclei_broad']), 'icon': FieldInfo(annotation=Union[Annotated[Union[Annotated[Path, PathType], RelativeFilePath, HttpUrl, Annotated[Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator, PlainSerializer], Annotated[str, Len], NoneType], required=False), 'links': FieldInfo(annotation=List[str], required=False, default_factory=list, examples=[('ilastik/ilastik', 'deepimagej/deepimagej', 'zero/notebook_u-net_3d_zerocostdl4mic')]), 'uploader': FieldInfo(annotation=Union[Uploader, NoneType], required=False), 'maintainers': FieldInfo(annotation=List[Maintainer], required=False, default_factory=list), 'tags': FieldInfo(annotation=List[str], required=False, default_factory=list, examples=[('unet2d', 'pytorch', 'nucleus', 'segmentation', 'dsb2018')]), 'version': FieldInfo(annotation=Union[Version, NoneType], required=False), 'version_number': FieldInfo(annotation=Union[int, NoneType], required=False), 'format_version': FieldInfo(annotation=Literal['0.3.0'], required=False, default='0.3.0'), 'documentation': FieldInfo(annotation=Union[Annotated[Union[Annotated[Path, PathType, Predicate], RelativeFilePath, HttpUrl], AfterValidator, PlainSerializer], NoneType], required=False, examples=['https://raw.githubusercontent.com/bioimage-io/spec-bioimage-io/main/example_descriptions/models/unet2d_nuclei_broad/README.md', 'README.md']), 'badges': FieldInfo(annotation=List[BadgeDescr], required=False, default_factory=list), 'type': FieldInfo(annotation=Literal['application'], required=False, default='application'), 'id': FieldInfo(annotation=Union[ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]], NoneType], required=False), 'parent': FieldInfo(annotation=Union[ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]], NoneType], required=False), 'source': FieldInfo(annotation=Union[Annotated[Union[Annotated[Path, PathType], RelativeFilePath, HttpUrl, Annotated[Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator, PlainSerializer], NoneType], required=False, description='URL or path to the source of the application')}"}, "bioimageio.spec.application.v0_3.ApplicationDescr.model_computed_fields": {"fullname": "bioimageio.spec.application.v0_3.ApplicationDescr.model_computed_fields", "modulename": "bioimageio.spec.application.v0_3", "qualname": "ApplicationDescr.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.application.v0_3.LinkedApplication": {"fullname": "bioimageio.spec.application.v0_3.LinkedApplication", "modulename": "bioimageio.spec.application.v0_3", "qualname": "LinkedApplication", "kind": "class", "doc": "
    Reference to a bioimage.io application.
    \n", "bases": "bioimageio.spec._internal.node.Node"}, "bioimageio.spec.application.v0_3.LinkedApplication.id": {"fullname": "bioimageio.spec.application.v0_3.LinkedApplication.id", "modulename": "bioimageio.spec.application.v0_3", "qualname": "LinkedApplication.id", "kind": "variable", "doc": "
    A valid application id from the bioimage.io collection.
    \n", "annotation": ": bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]]"}, "bioimageio.spec.application.v0_3.LinkedApplication.version_number": {"fullname": "bioimageio.spec.application.v0_3.LinkedApplication.version_number", "modulename": "bioimageio.spec.application.v0_3", "qualname": "LinkedApplication.version_number", "kind": "variable", "doc": "
    version number (n-th published version, not the semantic version) of linked application
    \n", "annotation": ": int"}, "bioimageio.spec.application.v0_3.LinkedApplication.model_config": {"fullname": "bioimageio.spec.application.v0_3.LinkedApplication.model_config", "modulename": "bioimageio.spec.application.v0_3", "qualname": "LinkedApplication.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.application.v0_3.LinkedApplication.model_fields": {"fullname": "bioimageio.spec.application.v0_3.LinkedApplication.model_fields", "modulename": "bioimageio.spec.application.v0_3", "qualname": "LinkedApplication.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'id': FieldInfo(annotation=ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]], required=True), 'version_number': FieldInfo(annotation=int, required=True)}"}, "bioimageio.spec.application.v0_3.LinkedApplication.model_computed_fields": {"fullname": "bioimageio.spec.application.v0_3.LinkedApplication.model_computed_fields", "modulename": "bioimageio.spec.application.v0_3", "qualname": "LinkedApplication.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.collection": {"fullname": "bioimageio.spec.collection", "modulename": "bioimageio.spec.collection", "kind": "module", "doc": "
    implementaions of all released minor versions are available in submodules:
    \n\n\n"}, "bioimageio.spec.collection.AnyCollectionDescr": {"fullname": "bioimageio.spec.collection.AnyCollectionDescr", "modulename": "bioimageio.spec.collection", "qualname": "AnyCollectionDescr", "kind": "variable", "doc": "
    Union of any released collection desription
    \n", "default_value": "typing.Annotated[typing.Union[bioimageio.spec.collection.v0_2.CollectionDescr, bioimageio.spec.collection.v0_3.CollectionDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)]"}, "bioimageio.spec.collection.v0_2": {"fullname": "bioimageio.spec.collection.v0_2", "modulename": "bioimageio.spec.collection.v0_2", "kind": "module", "doc": "
    \n"}, "bioimageio.spec.collection.v0_2.EntryDescr": {"fullname": "bioimageio.spec.collection.v0_2.EntryDescr", "modulename": "bioimageio.spec.collection.v0_2", "qualname": "EntryDescr", "kind": "variable", "doc": "
    \n", "default_value": "typing.Union[bioimageio.spec.application.v0_2.ApplicationDescr, bioimageio.spec.dataset.v0_2.DatasetDescr, bioimageio.spec.generic.v0_2.GenericDescr, bioimageio.spec.model.v0_4.ModelDescr, bioimageio.spec.notebook.v0_2.NotebookDescr]"}, "bioimageio.spec.collection.v0_2.CollectionEntry": {"fullname": "bioimageio.spec.collection.v0_2.CollectionEntry", "modulename": "bioimageio.spec.collection.v0_2", "qualname": "CollectionEntry", "kind": "class", "doc": "
    A valid resource description (RD).\nThe entry RD is based on the collection description itself.\nFields are added/overwritten by the content of rdf_source if rdf_source is specified,\nand finally added/overwritten by any fields specified directly in the entry.\nExcept for the id field, fields are overwritten entirely, their content is not merged!\nThe final id for each collection entry is composed of the collection's id\nand the entry's 'sub-'id, specified remotely as part of rdf_source or superseeded in-place,\nsuch that the final_entry_id = <collection_id>/<entry_id>
    \n", "bases": "bioimageio.spec._internal.node.Node"}, "bioimageio.spec.collection.v0_2.CollectionEntry.rdf_source": {"fullname": "bioimageio.spec.collection.v0_2.CollectionEntry.rdf_source", "modulename": "bioimageio.spec.collection.v0_2", "qualname": "CollectionEntry.rdf_source", "kind": "variable", "doc": "
    resource description file (RDF) source to load entry from
    \n", "annotation": ": Union[Annotated[pathlib.Path, PathType(path_type='file')], bioimageio.spec._internal.io.RelativeFilePath, bioimageio.spec._internal.url.HttpUrl, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)], NoneType]"}, "bioimageio.spec.collection.v0_2.CollectionEntry.id": {"fullname": "bioimageio.spec.collection.v0_2.CollectionEntry.id", "modulename": "bioimageio.spec.collection.v0_2", "qualname": "CollectionEntry.id", "kind": "variable", "doc": "
    Collection entry sub id overwriting rdf_source.id.\nThe full collection entry's id is the collection's base id, followed by this sub id and separated by a slash '/'.
    \n", "annotation": ": Optional[bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]]]"}, "bioimageio.spec.collection.v0_2.CollectionEntry.rdf_update": {"fullname": "bioimageio.spec.collection.v0_2.CollectionEntry.rdf_update", "modulename": "bioimageio.spec.collection.v0_2", "qualname": "CollectionEntry.rdf_update", "kind": "variable", "doc": "
    \n", "annotation": ": Dict[str, YamlValue]"}, "bioimageio.spec.collection.v0_2.CollectionEntry.descr": {"fullname": "bioimageio.spec.collection.v0_2.CollectionEntry.descr", "modulename": "bioimageio.spec.collection.v0_2", "qualname": "CollectionEntry.descr", "kind": "variable", "doc": "
    \n", "annotation": ": Union[bioimageio.spec.application.v0_2.ApplicationDescr, bioimageio.spec.dataset.v0_2.DatasetDescr, bioimageio.spec.generic.v0_2.GenericDescr, bioimageio.spec.model.v0_4.ModelDescr, bioimageio.spec.notebook.v0_2.NotebookDescr, NoneType]"}, "bioimageio.spec.collection.v0_2.CollectionEntry.model_config": {"fullname": "bioimageio.spec.collection.v0_2.CollectionEntry.model_config", "modulename": "bioimageio.spec.collection.v0_2", "qualname": "CollectionEntry.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'allow', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.collection.v0_2.CollectionEntry.model_post_init": {"fullname": "bioimageio.spec.collection.v0_2.CollectionEntry.model_post_init", "modulename": "bioimageio.spec.collection.v0_2", "qualname": "CollectionEntry.model_post_init", "kind": "function", "doc": "
    This function is meant to behave like a BaseModel method to initialise private attributes.
    \n\n
    It takes context as an argument since that's what pydantic-core passes when calling it.
    \n\n
    Args:\n    self: The BaseModel instance.\n    __context: The context.
    \n", "signature": "(self: pydantic.main.BaseModel, __context: Any) -> None:", "funcdef": "def"}, "bioimageio.spec.collection.v0_2.CollectionEntry.model_fields": {"fullname": "bioimageio.spec.collection.v0_2.CollectionEntry.model_fields", "modulename": "bioimageio.spec.collection.v0_2", "qualname": "CollectionEntry.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'rdf_source': FieldInfo(annotation=Union[Annotated[Path, PathType], RelativeFilePath, HttpUrl, Annotated[Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)], NoneType], required=False), 'id': FieldInfo(annotation=Union[ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]], NoneType], required=False)}"}, "bioimageio.spec.collection.v0_2.CollectionEntry.model_computed_fields": {"fullname": "bioimageio.spec.collection.v0_2.CollectionEntry.model_computed_fields", "modulename": "bioimageio.spec.collection.v0_2", "qualname": "CollectionEntry.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.collection.v0_2.CollectionDescr": {"fullname": "bioimageio.spec.collection.v0_2.CollectionDescr", "modulename": "bioimageio.spec.collection.v0_2", "qualname": "CollectionDescr", "kind": "class", "doc": "
    A bioimage.io collection describes several other bioimage.io resources.\nNote that collections cannot be nested; resources listed under collection may not be collections themselves.
    \n", "bases": "bioimageio.spec.generic.v0_2.GenericDescrBase"}, "bioimageio.spec.collection.v0_2.CollectionDescr.type": {"fullname": "bioimageio.spec.collection.v0_2.CollectionDescr.type", "modulename": "bioimageio.spec.collection.v0_2", "qualname": "CollectionDescr.type", "kind": "variable", "doc": "
    \n", "annotation": ": Literal['collection']"}, "bioimageio.spec.collection.v0_2.CollectionDescr.id": {"fullname": "bioimageio.spec.collection.v0_2.CollectionDescr.id", "modulename": "bioimageio.spec.collection.v0_2", "qualname": "CollectionDescr.id", "kind": "variable", "doc": "
    Model zoo (bioimage.io) wide, unique identifier (assigned by bioimage.io)
    \n", "annotation": ": Optional[bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]]]"}, "bioimageio.spec.collection.v0_2.CollectionDescr.collection": {"fullname": "bioimageio.spec.collection.v0_2.CollectionDescr.collection", "modulename": "bioimageio.spec.collection.v0_2", "qualname": "CollectionDescr.collection", "kind": "variable", "doc": "
    Collection entries
    \n", "annotation": ": Annotated[List[bioimageio.spec.collection.v0_2.CollectionEntry], MinLen(min_length=1)]"}, "bioimageio.spec.collection.v0_2.CollectionDescr.finalize_entries": {"fullname": "bioimageio.spec.collection.v0_2.CollectionDescr.finalize_entries", "modulename": "bioimageio.spec.collection.v0_2", "qualname": "CollectionDescr.finalize_entries", "kind": "function", "doc": "
    \n", "signature": "(self) -> Self:", "funcdef": "def"}, "bioimageio.spec.collection.v0_2.CollectionDescr.move_groups_to_collection_field": {"fullname": "bioimageio.spec.collection.v0_2.CollectionDescr.move_groups_to_collection_field", "modulename": "bioimageio.spec.collection.v0_2", "qualname": "CollectionDescr.move_groups_to_collection_field", "kind": "function", "doc": "
    \n", "signature": "(cls, data: Dict[str, YamlValue]) -> Dict[str, YamlValue]:", "funcdef": "def"}, "bioimageio.spec.collection.v0_2.CollectionDescr.implemented_format_version": {"fullname": "bioimageio.spec.collection.v0_2.CollectionDescr.implemented_format_version", "modulename": "bioimageio.spec.collection.v0_2", "qualname": "CollectionDescr.implemented_format_version", "kind": "variable", "doc": "
    \n", "annotation": ": ClassVar[str]", "default_value": "'0.2.4'"}, "bioimageio.spec.collection.v0_2.CollectionDescr.implemented_format_version_tuple": {"fullname": "bioimageio.spec.collection.v0_2.CollectionDescr.implemented_format_version_tuple", "modulename": "bioimageio.spec.collection.v0_2", "qualname": "CollectionDescr.implemented_format_version_tuple", "kind": "variable", "doc": "
    \n", "annotation": ": ClassVar[Tuple[int, int, int]]", "default_value": "(0, 2, 4)"}, "bioimageio.spec.collection.v0_2.CollectionDescr.model_config": {"fullname": "bioimageio.spec.collection.v0_2.CollectionDescr.model_config", "modulename": "bioimageio.spec.collection.v0_2", "qualname": "CollectionDescr.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'allow', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True, 'title': 'bioimage.io collection specification'}"}, "bioimageio.spec.collection.v0_2.CollectionDescr.model_fields": {"fullname": "bioimageio.spec.collection.v0_2.CollectionDescr.model_fields", "modulename": "bioimageio.spec.collection.v0_2", "qualname": "CollectionDescr.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'name': FieldInfo(annotation=str, required=True, metadata=[MinLen(min_length=1), AfterWarner(func=<function as_warning.<locals>.wrapper>, severity=30, msg='Longer than 128 characters.', context={'typ': typing.Annotated[typing.Any, MaxLen(max_length=128)]})]), 'description': FieldInfo(annotation=str, required=True), 'covers': FieldInfo(annotation=List[Annotated[Union[HttpUrl, Annotated[Path, PathType, Predicate], RelativeFilePath], WithSuffix, PlainSerializer]], required=False, default_factory=list, description="Cover images. Please use an image smaller than 500KB and an aspect ratio width to height of 2:1.\\nThe supported image formats are: ('.gif', '.jpeg', '.jpg', '.png', '.svg')", examples=['cover.png']), 'id_emoji': FieldInfo(annotation=Union[Annotated[str, Len], NoneType], required=False), 'authors': FieldInfo(annotation=List[Author], required=False, default_factory=list), 'attachments': FieldInfo(annotation=Union[AttachmentsDescr, NoneType], required=False), 'cite': FieldInfo(annotation=List[CiteEntry], required=False, default_factory=list), 'config': FieldInfo(annotation=Dict[str, YamlValue], required=False, default_factory=dict, examples=[{'bioimageio': {'my_custom_key': 3837283, 'another_key': {'nested': 'value'}}, 'imagej': {'macro_dir': 'path/to/macro/file'}}]), 'download_url': FieldInfo(annotation=Union[HttpUrl, NoneType], required=False), 'git_repo': FieldInfo(annotation=Union[str, NoneType], required=False, examples=['https://github.com/bioimage-io/spec-bioimage-io/tree/main/example_descriptions/models/unet2d_nuclei_broad']), 'icon': FieldInfo(annotation=Union[Annotated[Union[Annotated[Path, PathType], RelativeFilePath, HttpUrl, Annotated[Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator, PlainSerializer], Annotated[str, Len], NoneType], required=False), 'links': FieldInfo(annotation=List[str], required=False, default_factory=list, examples=[('ilastik/ilastik', 'deepimagej/deepimagej', 'zero/notebook_u-net_3d_zerocostdl4mic')]), 'uploader': FieldInfo(annotation=Union[Uploader, NoneType], required=False), 'maintainers': FieldInfo(annotation=List[Maintainer], required=False, default_factory=list), 'rdf_source': FieldInfo(annotation=Union[Annotated[Path, PathType], RelativeFilePath, HttpUrl, Annotated[Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)], NoneType], required=False), 'tags': FieldInfo(annotation=List[str], required=False, default_factory=list, examples=[('unet2d', 'pytorch', 'nucleus', 'segmentation', 'dsb2018')]), 'version': FieldInfo(annotation=Union[Version, NoneType], required=False), 'version_number': FieldInfo(annotation=Union[int, NoneType], required=False), 'format_version': FieldInfo(annotation=Literal['0.2.4'], required=False, default='0.2.4'), 'badges': FieldInfo(annotation=List[BadgeDescr], required=False, default_factory=list), 'documentation': FieldInfo(annotation=Union[Annotated[Union[Annotated[Path, PathType], RelativeFilePath, HttpUrl, Annotated[Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator, PlainSerializer], NoneType], required=False, examples=['https://raw.githubusercontent.com/bioimage-io/spec-bioimage-io/main/example_descriptions/models/unet2d_nuclei_broad/README.md', 'README.md']), 'license': FieldInfo(annotation=Union[LicenseId, DeprecatedLicenseId, str, NoneType], required=False, examples=['CC-BY-4.0', 'MIT', 'BSD-2-Clause']), 'type': FieldInfo(annotation=Literal['collection'], required=False, default='collection'), 'id': FieldInfo(annotation=Union[ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]], NoneType], required=False), 'collection': FieldInfo(annotation=List[CollectionEntry], required=True, metadata=[MinLen(min_length=1)])}"}, "bioimageio.spec.collection.v0_2.CollectionDescr.model_computed_fields": {"fullname": "bioimageio.spec.collection.v0_2.CollectionDescr.model_computed_fields", "modulename": "bioimageio.spec.collection.v0_2", "qualname": "CollectionDescr.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.collection.v0_2.LinkedCollection": {"fullname": "bioimageio.spec.collection.v0_2.LinkedCollection", "modulename": "bioimageio.spec.collection.v0_2", "qualname": "LinkedCollection", "kind": "class", "doc": "
    Reference to a bioimage.io collection.
    \n", "bases": "bioimageio.spec._internal.node.Node"}, "bioimageio.spec.collection.v0_2.LinkedCollection.id": {"fullname": "bioimageio.spec.collection.v0_2.LinkedCollection.id", "modulename": "bioimageio.spec.collection.v0_2", "qualname": "LinkedCollection.id", "kind": "variable", "doc": "
    A valid collection id from the bioimage.io collection.
    \n", "annotation": ": bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]]"}, "bioimageio.spec.collection.v0_2.LinkedCollection.version_number": {"fullname": "bioimageio.spec.collection.v0_2.LinkedCollection.version_number", "modulename": "bioimageio.spec.collection.v0_2", "qualname": "LinkedCollection.version_number", "kind": "variable", "doc": "
    version number (n-th published version, not the semantic version) of linked collection
    \n", "annotation": ": Optional[int]"}, "bioimageio.spec.collection.v0_2.LinkedCollection.model_config": {"fullname": "bioimageio.spec.collection.v0_2.LinkedCollection.model_config", "modulename": "bioimageio.spec.collection.v0_2", "qualname": "LinkedCollection.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.collection.v0_2.LinkedCollection.model_fields": {"fullname": "bioimageio.spec.collection.v0_2.LinkedCollection.model_fields", "modulename": "bioimageio.spec.collection.v0_2", "qualname": "LinkedCollection.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'id': FieldInfo(annotation=ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]], required=True), 'version_number': FieldInfo(annotation=Union[int, NoneType], required=False)}"}, "bioimageio.spec.collection.v0_2.LinkedCollection.model_computed_fields": {"fullname": "bioimageio.spec.collection.v0_2.LinkedCollection.model_computed_fields", "modulename": "bioimageio.spec.collection.v0_2", "qualname": "LinkedCollection.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.collection.v0_3": {"fullname": "bioimageio.spec.collection.v0_3", "modulename": "bioimageio.spec.collection.v0_3", "kind": "module", "doc": "
    \n"}, "bioimageio.spec.collection.v0_3.EntryDescr": {"fullname": "bioimageio.spec.collection.v0_3.EntryDescr", "modulename": "bioimageio.spec.collection.v0_3", "qualname": "EntryDescr", "kind": "variable", "doc": "
    \n", "default_value": "typing.Union[bioimageio.spec.application.v0_2.ApplicationDescr, bioimageio.spec.application.v0_3.ApplicationDescr, bioimageio.spec.dataset.v0_2.DatasetDescr, bioimageio.spec.dataset.v0_3.DatasetDescr, bioimageio.spec.model.v0_4.ModelDescr, bioimageio.spec.model.v0_5.ModelDescr, bioimageio.spec.notebook.v0_2.NotebookDescr, bioimageio.spec.notebook.v0_3.NotebookDescr, bioimageio.spec.generic.v0_2.GenericDescr, bioimageio.spec.generic.v0_3.GenericDescr]"}, "bioimageio.spec.collection.v0_3.CollectionEntry": {"fullname": "bioimageio.spec.collection.v0_3.CollectionEntry", "modulename": "bioimageio.spec.collection.v0_3", "qualname": "CollectionEntry", "kind": "class", "doc": "
    A collection entry description is based on the collection description itself.\nFields are added/overwritten by the content of descr_source if descr_source is set,\nand finally added/overwritten by any fields specified directly in the entry.\nExcept for the id field, fields are overwritten entirely, their content is not merged!\nThe final id for each collection entry is composed of the collection's id\nand the entry's 'sub-'id, specified externally in descr_source or superseeded in-place,\nsuch that the final_entry_id = <collection_id>/<entry_id>
    \n", "bases": "bioimageio.spec._internal.node.Node"}, "bioimageio.spec.collection.v0_3.CollectionEntry.entry_source": {"fullname": "bioimageio.spec.collection.v0_3.CollectionEntry.entry_source", "modulename": "bioimageio.spec.collection.v0_3", "qualname": "CollectionEntry.entry_source", "kind": "variable", "doc": "
    an external source this entry description is based on
    \n", "annotation": ": Union[Annotated[pathlib.Path, PathType(path_type='file')], bioimageio.spec._internal.io.RelativeFilePath, bioimageio.spec._internal.url.HttpUrl, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)], NoneType]"}, "bioimageio.spec.collection.v0_3.CollectionEntry.id": {"fullname": "bioimageio.spec.collection.v0_3.CollectionEntry.id", "modulename": "bioimageio.spec.collection.v0_3", "qualname": "CollectionEntry.id", "kind": "variable", "doc": "
    Collection entry sub id overwriting rdf_source.id.\nThe full collection entry's id is the collection's base id, followed by this sub id and separated by a slash '/'.
    \n", "annotation": ": Optional[bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]]]"}, "bioimageio.spec.collection.v0_3.CollectionEntry.entry_update": {"fullname": "bioimageio.spec.collection.v0_3.CollectionEntry.entry_update", "modulename": "bioimageio.spec.collection.v0_3", "qualname": "CollectionEntry.entry_update", "kind": "variable", "doc": "
    \n", "annotation": ": Dict[str, YamlValue]"}, "bioimageio.spec.collection.v0_3.CollectionEntry.descr": {"fullname": "bioimageio.spec.collection.v0_3.CollectionEntry.descr", "modulename": "bioimageio.spec.collection.v0_3", "qualname": "CollectionEntry.descr", "kind": "variable", "doc": "
    \n", "annotation": ": Union[bioimageio.spec.application.v0_2.ApplicationDescr, bioimageio.spec.application.v0_3.ApplicationDescr, bioimageio.spec.dataset.v0_2.DatasetDescr, bioimageio.spec.dataset.v0_3.DatasetDescr, bioimageio.spec.model.v0_4.ModelDescr, bioimageio.spec.model.v0_5.ModelDescr, bioimageio.spec.notebook.v0_2.NotebookDescr, bioimageio.spec.notebook.v0_3.NotebookDescr, bioimageio.spec.generic.v0_2.GenericDescr, bioimageio.spec.generic.v0_3.GenericDescr, NoneType]"}, "bioimageio.spec.collection.v0_3.CollectionEntry.model_config": {"fullname": "bioimageio.spec.collection.v0_3.CollectionEntry.model_config", "modulename": "bioimageio.spec.collection.v0_3", "qualname": "CollectionEntry.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'allow', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.collection.v0_3.CollectionEntry.model_post_init": {"fullname": "bioimageio.spec.collection.v0_3.CollectionEntry.model_post_init", "modulename": "bioimageio.spec.collection.v0_3", "qualname": "CollectionEntry.model_post_init", "kind": "function", "doc": "
    This function is meant to behave like a BaseModel method to initialise private attributes.
    \n\n
    It takes context as an argument since that's what pydantic-core passes when calling it.
    \n\n
    Args:\n    self: The BaseModel instance.\n    __context: The context.
    \n", "signature": "(self: pydantic.main.BaseModel, __context: Any) -> None:", "funcdef": "def"}, "bioimageio.spec.collection.v0_3.CollectionEntry.model_fields": {"fullname": "bioimageio.spec.collection.v0_3.CollectionEntry.model_fields", "modulename": "bioimageio.spec.collection.v0_3", "qualname": "CollectionEntry.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'entry_source': FieldInfo(annotation=Union[Annotated[Path, PathType], RelativeFilePath, HttpUrl, Annotated[Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)], NoneType], required=False), 'id': FieldInfo(annotation=Union[ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]], NoneType], required=False)}"}, "bioimageio.spec.collection.v0_3.CollectionEntry.model_computed_fields": {"fullname": "bioimageio.spec.collection.v0_3.CollectionEntry.model_computed_fields", "modulename": "bioimageio.spec.collection.v0_3", "qualname": "CollectionEntry.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.collection.v0_3.CollectionDescr": {"fullname": "bioimageio.spec.collection.v0_3.CollectionDescr", "modulename": "bioimageio.spec.collection.v0_3", "qualname": "CollectionDescr", "kind": "class", "doc": "
    A bioimage.io collection resource description file (collection RDF) describes a collection of bioimage.io\nresources.\nThe resources listed in a collection RDF have types other than 'collection'; collections cannot be nested.
    \n", "bases": "bioimageio.spec.generic.v0_3.GenericDescrBase"}, "bioimageio.spec.collection.v0_3.CollectionDescr.type": {"fullname": "bioimageio.spec.collection.v0_3.CollectionDescr.type", "modulename": "bioimageio.spec.collection.v0_3", "qualname": "CollectionDescr.type", "kind": "variable", "doc": "
    \n", "annotation": ": Literal['collection']"}, "bioimageio.spec.collection.v0_3.CollectionDescr.id": {"fullname": "bioimageio.spec.collection.v0_3.CollectionDescr.id", "modulename": "bioimageio.spec.collection.v0_3", "qualname": "CollectionDescr.id", "kind": "variable", "doc": "
    Model zoo (bioimage.io) wide, unique identifier (assigned by bioimage.io)
    \n", "annotation": ": Optional[bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]]]"}, "bioimageio.spec.collection.v0_3.CollectionDescr.parent": {"fullname": "bioimageio.spec.collection.v0_3.CollectionDescr.parent", "modulename": "bioimageio.spec.collection.v0_3", "qualname": "CollectionDescr.parent", "kind": "variable", "doc": "
    The description from which this one is derived
    \n", "annotation": ": Optional[bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]]]"}, "bioimageio.spec.collection.v0_3.CollectionDescr.collection": {"fullname": "bioimageio.spec.collection.v0_3.CollectionDescr.collection", "modulename": "bioimageio.spec.collection.v0_3", "qualname": "CollectionDescr.collection", "kind": "variable", "doc": "
    Collection entries
    \n", "annotation": ": Annotated[List[bioimageio.spec.collection.v0_3.CollectionEntry], MinLen(min_length=1)]"}, "bioimageio.spec.collection.v0_3.CollectionDescr.finalize_entries": {"fullname": "bioimageio.spec.collection.v0_3.CollectionDescr.finalize_entries", "modulename": "bioimageio.spec.collection.v0_3", "qualname": "CollectionDescr.finalize_entries", "kind": "function", "doc": "
    \n", "signature": "(self) -> Self:", "funcdef": "def"}, "bioimageio.spec.collection.v0_3.CollectionDescr.implemented_format_version": {"fullname": "bioimageio.spec.collection.v0_3.CollectionDescr.implemented_format_version", "modulename": "bioimageio.spec.collection.v0_3", "qualname": "CollectionDescr.implemented_format_version", "kind": "variable", "doc": "
    \n", "annotation": ": ClassVar[str]", "default_value": "'0.3.0'"}, "bioimageio.spec.collection.v0_3.CollectionDescr.implemented_format_version_tuple": {"fullname": "bioimageio.spec.collection.v0_3.CollectionDescr.implemented_format_version_tuple", "modulename": "bioimageio.spec.collection.v0_3", "qualname": "CollectionDescr.implemented_format_version_tuple", "kind": "variable", "doc": "
    \n", "annotation": ": ClassVar[Tuple[int, int, int]]", "default_value": "(0, 3, 0)"}, "bioimageio.spec.collection.v0_3.CollectionDescr.model_config": {"fullname": "bioimageio.spec.collection.v0_3.CollectionDescr.model_config", "modulename": "bioimageio.spec.collection.v0_3", "qualname": "CollectionDescr.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'allow', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True, 'title': 'bioimage.io collection specification'}"}, "bioimageio.spec.collection.v0_3.CollectionDescr.model_fields": {"fullname": "bioimageio.spec.collection.v0_3.CollectionDescr.model_fields", "modulename": "bioimageio.spec.collection.v0_3", "qualname": "CollectionDescr.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'name': FieldInfo(annotation=str, required=True, metadata=[MinLen(min_length=1), MaxLen(max_length=128)]), 'description': FieldInfo(annotation=str, required=True, metadata=[MaxLen(max_length=1024), AfterWarner(func=<function as_warning.<locals>.wrapper>, severity=30, msg='Description longer than 512 characters.', context={'typ': typing.Annotated[typing.Any, MaxLen(max_length=512)]})]), 'covers': FieldInfo(annotation=List[Annotated[Union[HttpUrl, Annotated[Path, PathType, Predicate], RelativeFilePath], WithSuffix, PlainSerializer]], required=False, default_factory=list, description="Cover images. Please use an image smaller than 500KB and an aspect ratio width to height of 2:1 or 1:1.\\nThe supported image formats are: ('.gif', '.jpeg', '.jpg', '.png', '.svg')", examples=[]), 'id_emoji': FieldInfo(annotation=Union[Annotated[str, Len], NoneType], required=False), 'authors': FieldInfo(annotation=List[Author], required=True, metadata=[MinLen(min_length=1)]), 'attachments': FieldInfo(annotation=List[FileDescr], required=False, default_factory=list), 'cite': FieldInfo(annotation=List[CiteEntry], required=True, metadata=[MinLen(min_length=1)]), 'license': FieldInfo(annotation=Union[LicenseId, DeprecatedLicenseId], required=True, examples=['CC-BY-4.0', 'MIT', 'BSD-2-Clause'], metadata=[AfterWarner(func=<function as_warning.<locals>.wrapper>, severity=30, msg='{value} is deprecated, see https://spdx.org/licenses/{value}.html', context={'typ': <class 'bioimageio.spec._internal.license_id.LicenseId'>})]), 'config': FieldInfo(annotation=Dict[str, YamlValue], required=False, default_factory=dict, examples=[{'bioimageio': {'my_custom_key': 3837283, 'another_key': {'nested': 'value'}}, 'imagej': {'macro_dir': 'path/to/macro/file'}}]), 'git_repo': FieldInfo(annotation=Union[HttpUrl, NoneType], required=False, examples=['https://github.com/bioimage-io/spec-bioimage-io/tree/main/example_descriptions/models/unet2d_nuclei_broad']), 'icon': FieldInfo(annotation=Union[Annotated[Union[Annotated[Path, PathType], RelativeFilePath, HttpUrl, Annotated[Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator, PlainSerializer], Annotated[str, Len], NoneType], required=False), 'links': FieldInfo(annotation=List[str], required=False, default_factory=list, examples=[('ilastik/ilastik', 'deepimagej/deepimagej', 'zero/notebook_u-net_3d_zerocostdl4mic')]), 'uploader': FieldInfo(annotation=Union[Uploader, NoneType], required=False), 'maintainers': FieldInfo(annotation=List[Maintainer], required=False, default_factory=list), 'tags': FieldInfo(annotation=List[str], required=False, default_factory=list, examples=[('unet2d', 'pytorch', 'nucleus', 'segmentation', 'dsb2018')]), 'version': FieldInfo(annotation=Union[Version, NoneType], required=False), 'version_number': FieldInfo(annotation=Union[int, NoneType], required=False), 'format_version': FieldInfo(annotation=Literal['0.3.0'], required=False, default='0.3.0'), 'documentation': FieldInfo(annotation=Union[Annotated[Union[Annotated[Path, PathType, Predicate], RelativeFilePath, HttpUrl], AfterValidator, PlainSerializer], NoneType], required=False, examples=['https://raw.githubusercontent.com/bioimage-io/spec-bioimage-io/main/example_descriptions/models/unet2d_nuclei_broad/README.md', 'README.md']), 'badges': FieldInfo(annotation=List[BadgeDescr], required=False, default_factory=list), 'type': FieldInfo(annotation=Literal['collection'], required=False, default='collection'), 'id': FieldInfo(annotation=Union[ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]], NoneType], required=False), 'parent': FieldInfo(annotation=Union[ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]], NoneType], required=False), 'collection': FieldInfo(annotation=List[CollectionEntry], required=True, metadata=[MinLen(min_length=1)])}"}, "bioimageio.spec.collection.v0_3.CollectionDescr.model_computed_fields": {"fullname": "bioimageio.spec.collection.v0_3.CollectionDescr.model_computed_fields", "modulename": "bioimageio.spec.collection.v0_3", "qualname": "CollectionDescr.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.collection.v0_3.LinkedCollection": {"fullname": "bioimageio.spec.collection.v0_3.LinkedCollection", "modulename": "bioimageio.spec.collection.v0_3", "qualname": "LinkedCollection", "kind": "class", "doc": "
    Reference to a bioimage.io collection.
    \n", "bases": "bioimageio.spec._internal.node.Node"}, "bioimageio.spec.collection.v0_3.LinkedCollection.id": {"fullname": "bioimageio.spec.collection.v0_3.LinkedCollection.id", "modulename": "bioimageio.spec.collection.v0_3", "qualname": "LinkedCollection.id", "kind": "variable", "doc": "
    A valid collection id from the bioimage.io collection.
    \n", "annotation": ": bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]]"}, "bioimageio.spec.collection.v0_3.LinkedCollection.version_number": {"fullname": "bioimageio.spec.collection.v0_3.LinkedCollection.version_number", "modulename": "bioimageio.spec.collection.v0_3", "qualname": "LinkedCollection.version_number", "kind": "variable", "doc": "
    version number (n-th published version, not the semantic version) of linked collection
    \n", "annotation": ": int"}, "bioimageio.spec.collection.v0_3.LinkedCollection.model_config": {"fullname": "bioimageio.spec.collection.v0_3.LinkedCollection.model_config", "modulename": "bioimageio.spec.collection.v0_3", "qualname": "LinkedCollection.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.collection.v0_3.LinkedCollection.model_fields": {"fullname": "bioimageio.spec.collection.v0_3.LinkedCollection.model_fields", "modulename": "bioimageio.spec.collection.v0_3", "qualname": "LinkedCollection.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'id': FieldInfo(annotation=ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]], required=True), 'version_number': FieldInfo(annotation=int, required=True)}"}, "bioimageio.spec.collection.v0_3.LinkedCollection.model_computed_fields": {"fullname": "bioimageio.spec.collection.v0_3.LinkedCollection.model_computed_fields", "modulename": "bioimageio.spec.collection.v0_3", "qualname": "LinkedCollection.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.common": {"fullname": "bioimageio.spec.common", "modulename": "bioimageio.spec.common", "kind": "module", "doc": "
    \n"}, "bioimageio.spec.dataset": {"fullname": "bioimageio.spec.dataset", "modulename": "bioimageio.spec.dataset", "kind": "module", "doc": "
    implementaions of all released minor versions are available in submodules:
    \n\n\n"}, "bioimageio.spec.dataset.AnyDatasetDescr": {"fullname": "bioimageio.spec.dataset.AnyDatasetDescr", "modulename": "bioimageio.spec.dataset", "qualname": "AnyDatasetDescr", "kind": "variable", "doc": "
    Union of any released dataset desription
    \n", "default_value": "typing.Annotated[typing.Union[bioimageio.spec.dataset.v0_2.DatasetDescr, bioimageio.spec.dataset.v0_3.DatasetDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)]"}, "bioimageio.spec.dataset.v0_2": {"fullname": "bioimageio.spec.dataset.v0_2", "modulename": "bioimageio.spec.dataset.v0_2", "kind": "module", "doc": "
    \n"}, "bioimageio.spec.dataset.v0_2.DatasetDescr": {"fullname": "bioimageio.spec.dataset.v0_2.DatasetDescr", "modulename": "bioimageio.spec.dataset.v0_2", "qualname": "DatasetDescr", "kind": "class", "doc": "
    A bioimage.io dataset resource description file (dataset RDF) describes a dataset relevant to bioimage\nprocessing.
    \n", "bases": "bioimageio.spec.generic.v0_2.GenericDescrBase"}, "bioimageio.spec.dataset.v0_2.DatasetDescr.type": {"fullname": "bioimageio.spec.dataset.v0_2.DatasetDescr.type", "modulename": "bioimageio.spec.dataset.v0_2", "qualname": "DatasetDescr.type", "kind": "variable", "doc": "
    \n", "annotation": ": Literal['dataset']"}, "bioimageio.spec.dataset.v0_2.DatasetDescr.id": {"fullname": "bioimageio.spec.dataset.v0_2.DatasetDescr.id", "modulename": "bioimageio.spec.dataset.v0_2", "qualname": "DatasetDescr.id", "kind": "variable", "doc": "
    Model zoo (bioimage.io) wide, unique identifier (assigned by bioimage.io)
    \n", "annotation": ": Optional[bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]]]"}, "bioimageio.spec.dataset.v0_2.DatasetDescr.source": {"fullname": "bioimageio.spec.dataset.v0_2.DatasetDescr.source", "modulename": "bioimageio.spec.dataset.v0_2", "qualname": "DatasetDescr.source", "kind": "variable", "doc": "
    \"URL to the source of the dataset.
    \n", "annotation": ": Optional[bioimageio.spec._internal.url.HttpUrl]"}, "bioimageio.spec.dataset.v0_2.DatasetDescr.implemented_format_version": {"fullname": "bioimageio.spec.dataset.v0_2.DatasetDescr.implemented_format_version", "modulename": "bioimageio.spec.dataset.v0_2", "qualname": "DatasetDescr.implemented_format_version", "kind": "variable", "doc": "
    \n", "annotation": ": ClassVar[str]", "default_value": "'0.2.4'"}, "bioimageio.spec.dataset.v0_2.DatasetDescr.implemented_format_version_tuple": {"fullname": "bioimageio.spec.dataset.v0_2.DatasetDescr.implemented_format_version_tuple", "modulename": "bioimageio.spec.dataset.v0_2", "qualname": "DatasetDescr.implemented_format_version_tuple", "kind": "variable", "doc": "
    \n", "annotation": ": ClassVar[Tuple[int, int, int]]", "default_value": "(0, 2, 4)"}, "bioimageio.spec.dataset.v0_2.DatasetDescr.model_config": {"fullname": "bioimageio.spec.dataset.v0_2.DatasetDescr.model_config", "modulename": "bioimageio.spec.dataset.v0_2", "qualname": "DatasetDescr.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True, 'title': 'bioimage.io dataset specification'}"}, "bioimageio.spec.dataset.v0_2.DatasetDescr.model_fields": {"fullname": "bioimageio.spec.dataset.v0_2.DatasetDescr.model_fields", "modulename": "bioimageio.spec.dataset.v0_2", "qualname": "DatasetDescr.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'name': FieldInfo(annotation=str, required=True, metadata=[MinLen(min_length=1), AfterWarner(func=<function as_warning.<locals>.wrapper>, severity=30, msg='Longer than 128 characters.', context={'typ': typing.Annotated[typing.Any, MaxLen(max_length=128)]})]), 'description': FieldInfo(annotation=str, required=True), 'covers': FieldInfo(annotation=List[Annotated[Union[HttpUrl, Annotated[Path, PathType, Predicate], RelativeFilePath], WithSuffix, PlainSerializer]], required=False, default_factory=list, description="Cover images. Please use an image smaller than 500KB and an aspect ratio width to height of 2:1.\\nThe supported image formats are: ('.gif', '.jpeg', '.jpg', '.png', '.svg')", examples=['cover.png']), 'id_emoji': FieldInfo(annotation=Union[Annotated[str, Len], NoneType], required=False), 'authors': FieldInfo(annotation=List[Author], required=False, default_factory=list), 'attachments': FieldInfo(annotation=Union[AttachmentsDescr, NoneType], required=False), 'cite': FieldInfo(annotation=List[CiteEntry], required=False, default_factory=list), 'config': FieldInfo(annotation=Dict[str, YamlValue], required=False, default_factory=dict, examples=[{'bioimageio': {'my_custom_key': 3837283, 'another_key': {'nested': 'value'}}, 'imagej': {'macro_dir': 'path/to/macro/file'}}]), 'download_url': FieldInfo(annotation=Union[HttpUrl, NoneType], required=False), 'git_repo': FieldInfo(annotation=Union[str, NoneType], required=False, examples=['https://github.com/bioimage-io/spec-bioimage-io/tree/main/example_descriptions/models/unet2d_nuclei_broad']), 'icon': FieldInfo(annotation=Union[Annotated[Union[Annotated[Path, PathType], RelativeFilePath, HttpUrl, Annotated[Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator, PlainSerializer], Annotated[str, Len], NoneType], required=False), 'links': FieldInfo(annotation=List[str], required=False, default_factory=list, examples=[('ilastik/ilastik', 'deepimagej/deepimagej', 'zero/notebook_u-net_3d_zerocostdl4mic')]), 'uploader': FieldInfo(annotation=Union[Uploader, NoneType], required=False), 'maintainers': FieldInfo(annotation=List[Maintainer], required=False, default_factory=list), 'rdf_source': FieldInfo(annotation=Union[Annotated[Path, PathType], RelativeFilePath, HttpUrl, Annotated[Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)], NoneType], required=False), 'tags': FieldInfo(annotation=List[str], required=False, default_factory=list, examples=[('unet2d', 'pytorch', 'nucleus', 'segmentation', 'dsb2018')]), 'version': FieldInfo(annotation=Union[Version, NoneType], required=False), 'version_number': FieldInfo(annotation=Union[int, NoneType], required=False), 'format_version': FieldInfo(annotation=Literal['0.2.4'], required=False, default='0.2.4'), 'badges': FieldInfo(annotation=List[BadgeDescr], required=False, default_factory=list), 'documentation': FieldInfo(annotation=Union[Annotated[Union[Annotated[Path, PathType], RelativeFilePath, HttpUrl, Annotated[Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator, PlainSerializer], NoneType], required=False, examples=['https://raw.githubusercontent.com/bioimage-io/spec-bioimage-io/main/example_descriptions/models/unet2d_nuclei_broad/README.md', 'README.md']), 'license': FieldInfo(annotation=Union[LicenseId, DeprecatedLicenseId, str, NoneType], required=False, examples=['CC-BY-4.0', 'MIT', 'BSD-2-Clause']), 'type': FieldInfo(annotation=Literal['dataset'], required=False, default='dataset'), 'id': FieldInfo(annotation=Union[ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]], NoneType], required=False), 'source': FieldInfo(annotation=Union[HttpUrl, NoneType], required=False)}"}, "bioimageio.spec.dataset.v0_2.DatasetDescr.model_computed_fields": {"fullname": "bioimageio.spec.dataset.v0_2.DatasetDescr.model_computed_fields", "modulename": "bioimageio.spec.dataset.v0_2", "qualname": "DatasetDescr.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.dataset.v0_2.LinkedDataset": {"fullname": "bioimageio.spec.dataset.v0_2.LinkedDataset", "modulename": "bioimageio.spec.dataset.v0_2", "qualname": "LinkedDataset", "kind": "class", "doc": "
    Reference to a bioimage.io dataset.
    \n", "bases": "bioimageio.spec._internal.node.Node"}, "bioimageio.spec.dataset.v0_2.LinkedDataset.id": {"fullname": "bioimageio.spec.dataset.v0_2.LinkedDataset.id", "modulename": "bioimageio.spec.dataset.v0_2", "qualname": "LinkedDataset.id", "kind": "variable", "doc": "
    A valid dataset id from the bioimage.io collection.
    \n", "annotation": ": bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]]"}, "bioimageio.spec.dataset.v0_2.LinkedDataset.version_number": {"fullname": "bioimageio.spec.dataset.v0_2.LinkedDataset.version_number", "modulename": "bioimageio.spec.dataset.v0_2", "qualname": "LinkedDataset.version_number", "kind": "variable", "doc": "
    version number (n-th published version, not the semantic version) of linked dataset
    \n", "annotation": ": Optional[int]"}, "bioimageio.spec.dataset.v0_2.LinkedDataset.model_config": {"fullname": "bioimageio.spec.dataset.v0_2.LinkedDataset.model_config", "modulename": "bioimageio.spec.dataset.v0_2", "qualname": "LinkedDataset.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.dataset.v0_2.LinkedDataset.model_fields": {"fullname": "bioimageio.spec.dataset.v0_2.LinkedDataset.model_fields", "modulename": "bioimageio.spec.dataset.v0_2", "qualname": "LinkedDataset.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'id': FieldInfo(annotation=ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]], required=True), 'version_number': FieldInfo(annotation=Union[int, NoneType], required=False)}"}, "bioimageio.spec.dataset.v0_2.LinkedDataset.model_computed_fields": {"fullname": "bioimageio.spec.dataset.v0_2.LinkedDataset.model_computed_fields", "modulename": "bioimageio.spec.dataset.v0_2", "qualname": "LinkedDataset.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.dataset.v0_3": {"fullname": "bioimageio.spec.dataset.v0_3", "modulename": "bioimageio.spec.dataset.v0_3", "kind": "module", "doc": "
    \n"}, "bioimageio.spec.dataset.v0_3.DatasetDescr": {"fullname": "bioimageio.spec.dataset.v0_3.DatasetDescr", "modulename": "bioimageio.spec.dataset.v0_3", "qualname": "DatasetDescr", "kind": "class", "doc": "
    A bioimage.io dataset resource description file (dataset RDF) describes a dataset relevant to bioimage\nprocessing.
    \n", "bases": "bioimageio.spec.generic.v0_3.GenericDescrBase"}, "bioimageio.spec.dataset.v0_3.DatasetDescr.type": {"fullname": "bioimageio.spec.dataset.v0_3.DatasetDescr.type", "modulename": "bioimageio.spec.dataset.v0_3", "qualname": "DatasetDescr.type", "kind": "variable", "doc": "
    \n", "annotation": ": Literal['dataset']"}, "bioimageio.spec.dataset.v0_3.DatasetDescr.id": {"fullname": "bioimageio.spec.dataset.v0_3.DatasetDescr.id", "modulename": "bioimageio.spec.dataset.v0_3", "qualname": "DatasetDescr.id", "kind": "variable", "doc": "
    Model zoo (bioimage.io) wide, unique identifier (assigned by bioimage.io)
    \n", "annotation": ": Optional[bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]]]"}, "bioimageio.spec.dataset.v0_3.DatasetDescr.parent": {"fullname": "bioimageio.spec.dataset.v0_3.DatasetDescr.parent", "modulename": "bioimageio.spec.dataset.v0_3", "qualname": "DatasetDescr.parent", "kind": "variable", "doc": "
    The description from which this one is derived
    \n", "annotation": ": Optional[bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]]]"}, "bioimageio.spec.dataset.v0_3.DatasetDescr.source": {"fullname": "bioimageio.spec.dataset.v0_3.DatasetDescr.source", "modulename": "bioimageio.spec.dataset.v0_3", "qualname": "DatasetDescr.source", "kind": "variable", "doc": "
    \"URL to the source of the dataset.
    \n", "annotation": ": Optional[bioimageio.spec._internal.url.HttpUrl]"}, "bioimageio.spec.dataset.v0_3.DatasetDescr.implemented_format_version": {"fullname": "bioimageio.spec.dataset.v0_3.DatasetDescr.implemented_format_version", "modulename": "bioimageio.spec.dataset.v0_3", "qualname": "DatasetDescr.implemented_format_version", "kind": "variable", "doc": "
    \n", "annotation": ": ClassVar[str]", "default_value": "'0.3.0'"}, "bioimageio.spec.dataset.v0_3.DatasetDescr.implemented_format_version_tuple": {"fullname": "bioimageio.spec.dataset.v0_3.DatasetDescr.implemented_format_version_tuple", "modulename": "bioimageio.spec.dataset.v0_3", "qualname": "DatasetDescr.implemented_format_version_tuple", "kind": "variable", "doc": "
    \n", "annotation": ": ClassVar[Tuple[int, int, int]]", "default_value": "(0, 3, 0)"}, "bioimageio.spec.dataset.v0_3.DatasetDescr.model_config": {"fullname": "bioimageio.spec.dataset.v0_3.DatasetDescr.model_config", "modulename": "bioimageio.spec.dataset.v0_3", "qualname": "DatasetDescr.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True, 'title': 'bioimage.io dataset specification'}"}, "bioimageio.spec.dataset.v0_3.DatasetDescr.model_fields": {"fullname": "bioimageio.spec.dataset.v0_3.DatasetDescr.model_fields", "modulename": "bioimageio.spec.dataset.v0_3", "qualname": "DatasetDescr.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'name': FieldInfo(annotation=str, required=True, metadata=[MinLen(min_length=1), MaxLen(max_length=128)]), 'description': FieldInfo(annotation=str, required=True, metadata=[MaxLen(max_length=1024), AfterWarner(func=<function as_warning.<locals>.wrapper>, severity=30, msg='Description longer than 512 characters.', context={'typ': typing.Annotated[typing.Any, MaxLen(max_length=512)]})]), 'covers': FieldInfo(annotation=List[Annotated[Union[HttpUrl, Annotated[Path, PathType, Predicate], RelativeFilePath], WithSuffix, PlainSerializer]], required=False, default_factory=list, description="Cover images. Please use an image smaller than 500KB and an aspect ratio width to height of 2:1 or 1:1.\\nThe supported image formats are: ('.gif', '.jpeg', '.jpg', '.png', '.svg')", examples=[]), 'id_emoji': FieldInfo(annotation=Union[Annotated[str, Len], NoneType], required=False), 'authors': FieldInfo(annotation=List[Author], required=True, metadata=[MinLen(min_length=1)]), 'attachments': FieldInfo(annotation=List[FileDescr], required=False, default_factory=list), 'cite': FieldInfo(annotation=List[CiteEntry], required=True, metadata=[MinLen(min_length=1)]), 'license': FieldInfo(annotation=Union[LicenseId, DeprecatedLicenseId], required=True, examples=['CC-BY-4.0', 'MIT', 'BSD-2-Clause'], metadata=[AfterWarner(func=<function as_warning.<locals>.wrapper>, severity=30, msg='{value} is deprecated, see https://spdx.org/licenses/{value}.html', context={'typ': <class 'bioimageio.spec._internal.license_id.LicenseId'>})]), 'config': FieldInfo(annotation=Dict[str, YamlValue], required=False, default_factory=dict, examples=[{'bioimageio': {'my_custom_key': 3837283, 'another_key': {'nested': 'value'}}, 'imagej': {'macro_dir': 'path/to/macro/file'}}]), 'git_repo': FieldInfo(annotation=Union[HttpUrl, NoneType], required=False, examples=['https://github.com/bioimage-io/spec-bioimage-io/tree/main/example_descriptions/models/unet2d_nuclei_broad']), 'icon': FieldInfo(annotation=Union[Annotated[Union[Annotated[Path, PathType], RelativeFilePath, HttpUrl, Annotated[Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator, PlainSerializer], Annotated[str, Len], NoneType], required=False), 'links': FieldInfo(annotation=List[str], required=False, default_factory=list, examples=[('ilastik/ilastik', 'deepimagej/deepimagej', 'zero/notebook_u-net_3d_zerocostdl4mic')]), 'uploader': FieldInfo(annotation=Union[Uploader, NoneType], required=False), 'maintainers': FieldInfo(annotation=List[Maintainer], required=False, default_factory=list), 'tags': FieldInfo(annotation=List[str], required=False, default_factory=list, examples=[('unet2d', 'pytorch', 'nucleus', 'segmentation', 'dsb2018')]), 'version': FieldInfo(annotation=Union[Version, NoneType], required=False), 'version_number': FieldInfo(annotation=Union[int, NoneType], required=False), 'format_version': FieldInfo(annotation=Literal['0.3.0'], required=False, default='0.3.0'), 'documentation': FieldInfo(annotation=Union[Annotated[Union[Annotated[Path, PathType, Predicate], RelativeFilePath, HttpUrl], AfterValidator, PlainSerializer], NoneType], required=False, examples=['https://raw.githubusercontent.com/bioimage-io/spec-bioimage-io/main/example_descriptions/models/unet2d_nuclei_broad/README.md', 'README.md']), 'badges': FieldInfo(annotation=List[BadgeDescr], required=False, default_factory=list), 'type': FieldInfo(annotation=Literal['dataset'], required=False, default='dataset'), 'id': FieldInfo(annotation=Union[ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]], NoneType], required=False), 'parent': FieldInfo(annotation=Union[ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]], NoneType], required=False), 'source': FieldInfo(annotation=Union[HttpUrl, NoneType], required=False)}"}, "bioimageio.spec.dataset.v0_3.DatasetDescr.model_computed_fields": {"fullname": "bioimageio.spec.dataset.v0_3.DatasetDescr.model_computed_fields", "modulename": "bioimageio.spec.dataset.v0_3", "qualname": "DatasetDescr.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.dataset.v0_3.LinkedDataset": {"fullname": "bioimageio.spec.dataset.v0_3.LinkedDataset", "modulename": "bioimageio.spec.dataset.v0_3", "qualname": "LinkedDataset", "kind": "class", "doc": "
    Reference to a bioimage.io dataset.
    \n", "bases": "bioimageio.spec._internal.node.Node"}, "bioimageio.spec.dataset.v0_3.LinkedDataset.id": {"fullname": "bioimageio.spec.dataset.v0_3.LinkedDataset.id", "modulename": "bioimageio.spec.dataset.v0_3", "qualname": "LinkedDataset.id", "kind": "variable", "doc": "
    A valid dataset id from the bioimage.io collection.
    \n", "annotation": ": bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]]"}, "bioimageio.spec.dataset.v0_3.LinkedDataset.version_number": {"fullname": "bioimageio.spec.dataset.v0_3.LinkedDataset.version_number", "modulename": "bioimageio.spec.dataset.v0_3", "qualname": "LinkedDataset.version_number", "kind": "variable", "doc": "
    version number (n-th published version, not the semantic version) of linked dataset
    \n", "annotation": ": int"}, "bioimageio.spec.dataset.v0_3.LinkedDataset.model_config": {"fullname": "bioimageio.spec.dataset.v0_3.LinkedDataset.model_config", "modulename": "bioimageio.spec.dataset.v0_3", "qualname": "LinkedDataset.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.dataset.v0_3.LinkedDataset.model_fields": {"fullname": "bioimageio.spec.dataset.v0_3.LinkedDataset.model_fields", "modulename": "bioimageio.spec.dataset.v0_3", "qualname": "LinkedDataset.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'id': FieldInfo(annotation=ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]], required=True), 'version_number': FieldInfo(annotation=int, required=True)}"}, "bioimageio.spec.dataset.v0_3.LinkedDataset.model_computed_fields": {"fullname": "bioimageio.spec.dataset.v0_3.LinkedDataset.model_computed_fields", "modulename": "bioimageio.spec.dataset.v0_3", "qualname": "LinkedDataset.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.generic": {"fullname": "bioimageio.spec.generic", "modulename": "bioimageio.spec.generic", "kind": "module", "doc": "
    implementaions of all released minor versions are available in submodules:
    \n\n\n"}, "bioimageio.spec.generic.AnyGenericDescr": {"fullname": "bioimageio.spec.generic.AnyGenericDescr", "modulename": "bioimageio.spec.generic", "qualname": "AnyGenericDescr", "kind": "variable", "doc": "
    Union of any released generic desription
    \n", "default_value": "typing.Annotated[typing.Union[bioimageio.spec.generic.v0_2.GenericDescr, bioimageio.spec.generic.v0_3.GenericDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)]"}, "bioimageio.spec.generic.v0_2": {"fullname": "bioimageio.spec.generic.v0_2", "modulename": "bioimageio.spec.generic.v0_2", "kind": "module", "doc": "
    \n"}, "bioimageio.spec.generic.v0_2.KNOWN_SPECIFIC_RESOURCE_TYPES": {"fullname": "bioimageio.spec.generic.v0_2.KNOWN_SPECIFIC_RESOURCE_TYPES", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "KNOWN_SPECIFIC_RESOURCE_TYPES", "kind": "variable", "doc": "
    \n", "default_value": "('application', 'collection', 'dataset', 'model', 'notebook')"}, "bioimageio.spec.generic.v0_2.VALID_COVER_IMAGE_EXTENSIONS": {"fullname": "bioimageio.spec.generic.v0_2.VALID_COVER_IMAGE_EXTENSIONS", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "VALID_COVER_IMAGE_EXTENSIONS", "kind": "variable", "doc": "
    \n", "default_value": "('.gif', '.jpeg', '.jpg', '.png', '.svg')"}, "bioimageio.spec.generic.v0_2.CoverImageSource": {"fullname": "bioimageio.spec.generic.v0_2.CoverImageSource", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "CoverImageSource", "kind": "variable", "doc": "
    \n", "default_value": "typing.Annotated[typing.Union[bioimageio.spec._internal.url.HttpUrl, typing.Annotated[pathlib.Path, PathType(path_type='file'), Predicate(func=<function PurePath.is_absolute>)], bioimageio.spec._internal.io.RelativeFilePath], WithSuffix(suffix=('.gif', '.jpeg', '.jpg', '.png', '.svg'), case_sensitive=False), PlainSerializer(func=<function _package>, return_type=PydanticUndefined, when_used='unless-none')]"}, "bioimageio.spec.generic.v0_2.AttachmentsDescr": {"fullname": "bioimageio.spec.generic.v0_2.AttachmentsDescr", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "AttachmentsDescr", "kind": "class", "doc": "
    Subpart of a resource description
    \n", "bases": "bioimageio.spec._internal.node.Node"}, "bioimageio.spec.generic.v0_2.AttachmentsDescr.model_config": {"fullname": "bioimageio.spec.generic.v0_2.AttachmentsDescr.model_config", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "AttachmentsDescr.model_config", "kind": "variable", "doc": "
    update pydantic model config to allow additional unknown keys
    \n", "default_value": "{'extra': 'allow', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.generic.v0_2.AttachmentsDescr.files": {"fullname": "bioimageio.spec.generic.v0_2.AttachmentsDescr.files", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "AttachmentsDescr.files", "kind": "variable", "doc": "
    \u2208\ud83d\udce6 File attachments
    \n", "annotation": ": List[Annotated[Union[Annotated[pathlib.Path, PathType(path_type='file')], bioimageio.spec._internal.io.RelativeFilePath, bioimageio.spec._internal.url.HttpUrl, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator(func=<function wo_special_file_name at 0x7afca0d90540>), PlainSerializer(func=<function _package at 0x7afca0d91760>, return_type=PydanticUndefined, when_used='unless-none')]]"}, "bioimageio.spec.generic.v0_2.AttachmentsDescr.model_fields": {"fullname": "bioimageio.spec.generic.v0_2.AttachmentsDescr.model_fields", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "AttachmentsDescr.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'files': FieldInfo(annotation=List[Annotated[Union[Annotated[Path, PathType], RelativeFilePath, HttpUrl, Annotated[Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator, PlainSerializer]], required=False, default_factory=list)}"}, "bioimageio.spec.generic.v0_2.AttachmentsDescr.model_computed_fields": {"fullname": "bioimageio.spec.generic.v0_2.AttachmentsDescr.model_computed_fields", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "AttachmentsDescr.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.generic.v0_2.Uploader": {"fullname": "bioimageio.spec.generic.v0_2.Uploader", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "Uploader", "kind": "class", "doc": "
    Subpart of a resource description
    \n", "bases": "bioimageio.spec._internal.node.Node"}, "bioimageio.spec.generic.v0_2.Uploader.email": {"fullname": "bioimageio.spec.generic.v0_2.Uploader.email", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "Uploader.email", "kind": "variable", "doc": "
    Email
    \n", "annotation": ": pydantic.networks.EmailStr"}, "bioimageio.spec.generic.v0_2.Uploader.name": {"fullname": "bioimageio.spec.generic.v0_2.Uploader.name", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "Uploader.name", "kind": "variable", "doc": "
    name
    \n", "annotation": ": Optional[Annotated[str, AfterValidator(func=<function _remove_slashes at 0x7afca0ba67a0>)]]"}, "bioimageio.spec.generic.v0_2.Uploader.model_config": {"fullname": "bioimageio.spec.generic.v0_2.Uploader.model_config", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "Uploader.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.generic.v0_2.Uploader.model_fields": {"fullname": "bioimageio.spec.generic.v0_2.Uploader.model_fields", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "Uploader.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'email': FieldInfo(annotation=EmailStr, required=True), 'name': FieldInfo(annotation=Union[Annotated[str, AfterValidator], NoneType], required=False)}"}, "bioimageio.spec.generic.v0_2.Uploader.model_computed_fields": {"fullname": "bioimageio.spec.generic.v0_2.Uploader.model_computed_fields", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "Uploader.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.generic.v0_2.Author": {"fullname": "bioimageio.spec.generic.v0_2.Author", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "Author", "kind": "class", "doc": "
    Subpart of a resource description
    \n", "bases": "_Person"}, "bioimageio.spec.generic.v0_2.Author.name": {"fullname": "bioimageio.spec.generic.v0_2.Author.name", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "Author.name", "kind": "variable", "doc": "
    \n", "annotation": ": Annotated[str, AfterValidator(func=<function _remove_slashes at 0x7afca0ba67a0>)]"}, "bioimageio.spec.generic.v0_2.Author.github_user": {"fullname": "bioimageio.spec.generic.v0_2.Author.github_user", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "Author.github_user", "kind": "variable", "doc": "
    \n", "annotation": ": Optional[str]"}, "bioimageio.spec.generic.v0_2.Author.model_config": {"fullname": "bioimageio.spec.generic.v0_2.Author.model_config", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "Author.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.generic.v0_2.Author.model_fields": {"fullname": "bioimageio.spec.generic.v0_2.Author.model_fields", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "Author.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'affiliation': FieldInfo(annotation=Union[str, NoneType], required=False), 'email': FieldInfo(annotation=Union[EmailStr, NoneType], required=False), 'orcid': FieldInfo(annotation=Union[ValidatedString[Annotated[str, AfterValidator]], NoneType], required=False, examples=['0000-0001-2345-6789']), 'name': FieldInfo(annotation=str, required=True, metadata=[AfterValidator(func=<function _remove_slashes>)]), 'github_user': FieldInfo(annotation=Union[str, NoneType], required=False)}"}, "bioimageio.spec.generic.v0_2.Author.model_computed_fields": {"fullname": "bioimageio.spec.generic.v0_2.Author.model_computed_fields", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "Author.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.generic.v0_2.Maintainer": {"fullname": "bioimageio.spec.generic.v0_2.Maintainer", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "Maintainer", "kind": "class", "doc": "
    Subpart of a resource description
    \n", "bases": "_Person"}, "bioimageio.spec.generic.v0_2.Maintainer.name": {"fullname": "bioimageio.spec.generic.v0_2.Maintainer.name", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "Maintainer.name", "kind": "variable", "doc": "
    \n", "annotation": ": Optional[Annotated[str, AfterValidator(func=<function _remove_slashes at 0x7afca0ba67a0>)]]"}, "bioimageio.spec.generic.v0_2.Maintainer.github_user": {"fullname": "bioimageio.spec.generic.v0_2.Maintainer.github_user", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "Maintainer.github_user", "kind": "variable", "doc": "
    \n", "annotation": ": str"}, "bioimageio.spec.generic.v0_2.Maintainer.model_config": {"fullname": "bioimageio.spec.generic.v0_2.Maintainer.model_config", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "Maintainer.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.generic.v0_2.Maintainer.model_fields": {"fullname": "bioimageio.spec.generic.v0_2.Maintainer.model_fields", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "Maintainer.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'affiliation': FieldInfo(annotation=Union[str, NoneType], required=False), 'email': FieldInfo(annotation=Union[EmailStr, NoneType], required=False), 'orcid': FieldInfo(annotation=Union[ValidatedString[Annotated[str, AfterValidator]], NoneType], required=False, examples=['0000-0001-2345-6789']), 'name': FieldInfo(annotation=Union[Annotated[str, AfterValidator], NoneType], required=False), 'github_user': FieldInfo(annotation=str, required=True)}"}, "bioimageio.spec.generic.v0_2.Maintainer.model_computed_fields": {"fullname": "bioimageio.spec.generic.v0_2.Maintainer.model_computed_fields", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "Maintainer.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.generic.v0_2.BadgeDescr": {"fullname": "bioimageio.spec.generic.v0_2.BadgeDescr", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "BadgeDescr", "kind": "class", "doc": "
    A custom badge
    \n", "bases": "bioimageio.spec._internal.node.Node"}, "bioimageio.spec.generic.v0_2.BadgeDescr.label": {"fullname": "bioimageio.spec.generic.v0_2.BadgeDescr.label", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "BadgeDescr.label", "kind": "variable", "doc": "
    badge label to display on hover
    \n", "annotation": ": Annotated[str, FieldInfo(annotation=NoneType, required=True, examples=['Open in Colab'])]"}, "bioimageio.spec.generic.v0_2.BadgeDescr.icon": {"fullname": "bioimageio.spec.generic.v0_2.BadgeDescr.icon", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "BadgeDescr.icon", "kind": "variable", "doc": "
    badge icon
    \n", "annotation": ": Annotated[Optional[bioimageio.spec._internal.url.HttpUrl], FieldInfo(annotation=NoneType, required=True, examples=['https://colab.research.google.com/assets/colab-badge.svg'])]"}, "bioimageio.spec.generic.v0_2.BadgeDescr.url": {"fullname": "bioimageio.spec.generic.v0_2.BadgeDescr.url", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "BadgeDescr.url", "kind": "variable", "doc": "
    target URL
    \n", "annotation": ": Annotated[bioimageio.spec._internal.url.HttpUrl, FieldInfo(annotation=NoneType, required=True, examples=['https://colab.research.google.com/github/HenriquesLab/ZeroCostDL4Mic/blob/master/Colab_notebooks/U-net_2D_ZeroCostDL4Mic.ipynb'])]"}, "bioimageio.spec.generic.v0_2.BadgeDescr.model_config": {"fullname": "bioimageio.spec.generic.v0_2.BadgeDescr.model_config", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "BadgeDescr.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True, 'title': 'Custom badge'}"}, "bioimageio.spec.generic.v0_2.BadgeDescr.model_fields": {"fullname": "bioimageio.spec.generic.v0_2.BadgeDescr.model_fields", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "BadgeDescr.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'label': FieldInfo(annotation=str, required=True, examples=['Open in Colab']), 'icon': FieldInfo(annotation=Union[HttpUrl, NoneType], required=False, examples=['https://colab.research.google.com/assets/colab-badge.svg']), 'url': FieldInfo(annotation=HttpUrl, required=True, examples=['https://colab.research.google.com/github/HenriquesLab/ZeroCostDL4Mic/blob/master/Colab_notebooks/U-net_2D_ZeroCostDL4Mic.ipynb'])}"}, "bioimageio.spec.generic.v0_2.BadgeDescr.model_computed_fields": {"fullname": "bioimageio.spec.generic.v0_2.BadgeDescr.model_computed_fields", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "BadgeDescr.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.generic.v0_2.CiteEntry": {"fullname": "bioimageio.spec.generic.v0_2.CiteEntry", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "CiteEntry", "kind": "class", "doc": "
    Subpart of a resource description
    \n", "bases": "bioimageio.spec._internal.node.Node"}, "bioimageio.spec.generic.v0_2.CiteEntry.text": {"fullname": "bioimageio.spec.generic.v0_2.CiteEntry.text", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "CiteEntry.text", "kind": "variable", "doc": "
    free text description
    \n", "annotation": ": str"}, "bioimageio.spec.generic.v0_2.CiteEntry.doi": {"fullname": "bioimageio.spec.generic.v0_2.CiteEntry.doi", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "CiteEntry.doi", "kind": "variable", "doc": "
    A digital object identifier (DOI) is the prefered citation reference.\nSee https://www.doi.org/ for details. (alternatively specify url)
    \n", "annotation": ": Optional[bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, StringConstraints]]]"}, "bioimageio.spec.generic.v0_2.CiteEntry.accept_prefixed_doi": {"fullname": "bioimageio.spec.generic.v0_2.CiteEntry.accept_prefixed_doi", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "CiteEntry.accept_prefixed_doi", "kind": "function", "doc": "
    \n", "signature": "(cls, doi: Any) -> Any:", "funcdef": "def"}, "bioimageio.spec.generic.v0_2.CiteEntry.url": {"fullname": "bioimageio.spec.generic.v0_2.CiteEntry.url", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "CiteEntry.url", "kind": "variable", "doc": "
    URL to cite (preferably specify a doi instead)
    \n", "annotation": ": Optional[str]"}, "bioimageio.spec.generic.v0_2.CiteEntry.model_config": {"fullname": "bioimageio.spec.generic.v0_2.CiteEntry.model_config", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "CiteEntry.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.generic.v0_2.CiteEntry.model_fields": {"fullname": "bioimageio.spec.generic.v0_2.CiteEntry.model_fields", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "CiteEntry.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'text': FieldInfo(annotation=str, required=True), 'doi': FieldInfo(annotation=Union[ValidatedString[Annotated[str, StringConstraints]], NoneType], required=False), 'url': FieldInfo(annotation=Union[str, NoneType], required=False)}"}, "bioimageio.spec.generic.v0_2.CiteEntry.model_computed_fields": {"fullname": "bioimageio.spec.generic.v0_2.CiteEntry.model_computed_fields", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "CiteEntry.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.generic.v0_2.LinkedResource": {"fullname": "bioimageio.spec.generic.v0_2.LinkedResource", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "LinkedResource", "kind": "class", "doc": "
    Reference to a bioimage.io resource
    \n", "bases": "bioimageio.spec._internal.node.Node"}, "bioimageio.spec.generic.v0_2.LinkedResource.id": {"fullname": "bioimageio.spec.generic.v0_2.LinkedResource.id", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "LinkedResource.id", "kind": "variable", "doc": "
    A valid resource id from the bioimage.io collection.
    \n", "annotation": ": bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]]"}, "bioimageio.spec.generic.v0_2.LinkedResource.version_number": {"fullname": "bioimageio.spec.generic.v0_2.LinkedResource.version_number", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "LinkedResource.version_number", "kind": "variable", "doc": "
    version number (n-th published version, not the semantic version) of linked resource
    \n", "annotation": ": Optional[int]"}, "bioimageio.spec.generic.v0_2.LinkedResource.model_config": {"fullname": "bioimageio.spec.generic.v0_2.LinkedResource.model_config", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "LinkedResource.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.generic.v0_2.LinkedResource.model_fields": {"fullname": "bioimageio.spec.generic.v0_2.LinkedResource.model_fields", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "LinkedResource.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'id': FieldInfo(annotation=ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]], required=True), 'version_number': FieldInfo(annotation=Union[int, NoneType], required=False)}"}, "bioimageio.spec.generic.v0_2.LinkedResource.model_computed_fields": {"fullname": "bioimageio.spec.generic.v0_2.LinkedResource.model_computed_fields", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "LinkedResource.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.generic.v0_2.GenericModelDescrBase": {"fullname": "bioimageio.spec.generic.v0_2.GenericModelDescrBase", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "GenericModelDescrBase", "kind": "class", "doc": "
    Base for all resource descriptions including of model descriptions
    \n", "bases": "bioimageio.spec._internal.common_nodes.ResourceDescrBase"}, "bioimageio.spec.generic.v0_2.GenericModelDescrBase.name": {"fullname": "bioimageio.spec.generic.v0_2.GenericModelDescrBase.name", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "GenericModelDescrBase.name", "kind": "variable", "doc": "
    A human-friendly name of the resource description
    \n", "annotation": ": Annotated[str, MinLen(min_length=1), AfterWarner(func=<function as_warning.<locals>.wrapper at 0x7afca0c05080>, severity=30, msg='Longer than 128 characters.', context={'typ': Annotated[Any, MaxLen(max_length=128)]})]"}, "bioimageio.spec.generic.v0_2.GenericModelDescrBase.description": {"fullname": "bioimageio.spec.generic.v0_2.GenericModelDescrBase.description", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "GenericModelDescrBase.description", "kind": "variable", "doc": "
    \n", "annotation": ": str"}, "bioimageio.spec.generic.v0_2.GenericModelDescrBase.covers": {"fullname": "bioimageio.spec.generic.v0_2.GenericModelDescrBase.covers", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "GenericModelDescrBase.covers", "kind": "variable", "doc": "
    \u2208\ud83d\udce6 Cover images. Please use an image smaller than 500KB and an aspect ratio width to height of 2:1.
    \n", "annotation": ": Annotated[List[Annotated[Union[bioimageio.spec._internal.url.HttpUrl, Annotated[pathlib.Path, PathType(path_type='file'), Predicate(func=<function PurePath.is_absolute at 0x7afca4145940>)], bioimageio.spec._internal.io.RelativeFilePath], WithSuffix(suffix=('.gif', '.jpeg', '.jpg', '.png', '.svg'), case_sensitive=False), PlainSerializer(func=<function _package at 0x7afca0d91760>, return_type=PydanticUndefined, when_used='unless-none')]], FieldInfo(annotation=NoneType, required=True, description="Cover images. Please use an image smaller than 500KB and an aspect ratio width to height of 2:1.\\nThe supported image formats are: ('.gif', '.jpeg', '.jpg', '.png', '.svg')", examples=['cover.png'])]"}, "bioimageio.spec.generic.v0_2.GenericModelDescrBase.id_emoji": {"fullname": "bioimageio.spec.generic.v0_2.GenericModelDescrBase.id_emoji", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "GenericModelDescrBase.id_emoji", "kind": "variable", "doc": "
    UTF-8 emoji for display alongside the id.
    \n", "annotation": ": Optional[Annotated[str, Len(min_length=1, max_length=1)]]"}, "bioimageio.spec.generic.v0_2.GenericModelDescrBase.authors": {"fullname": "bioimageio.spec.generic.v0_2.GenericModelDescrBase.authors", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "GenericModelDescrBase.authors", "kind": "variable", "doc": "
    The authors are the creators of the RDF and the primary points of contact.
    \n", "annotation": ": List[bioimageio.spec.generic.v0_2.Author]"}, "bioimageio.spec.generic.v0_2.GenericModelDescrBase.accept_author_strings": {"fullname": "bioimageio.spec.generic.v0_2.GenericModelDescrBase.accept_author_strings", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "GenericModelDescrBase.accept_author_strings", "kind": "function", "doc": "
    we unofficially accept strings as author entries
    \n", "signature": "(cls, authors: Union[Any, Sequence[Any]]) -> Any:", "funcdef": "def"}, "bioimageio.spec.generic.v0_2.GenericModelDescrBase.attachments": {"fullname": "bioimageio.spec.generic.v0_2.GenericModelDescrBase.attachments", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "GenericModelDescrBase.attachments", "kind": "variable", "doc": "
    file and other attachments
    \n", "annotation": ": Optional[bioimageio.spec.generic.v0_2.AttachmentsDescr]"}, "bioimageio.spec.generic.v0_2.GenericModelDescrBase.cite": {"fullname": "bioimageio.spec.generic.v0_2.GenericModelDescrBase.cite", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "GenericModelDescrBase.cite", "kind": "variable", "doc": "
    citations
    \n", "annotation": ": List[bioimageio.spec.generic.v0_2.CiteEntry]"}, "bioimageio.spec.generic.v0_2.GenericModelDescrBase.config": {"fullname": "bioimageio.spec.generic.v0_2.GenericModelDescrBase.config", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "GenericModelDescrBase.config", "kind": "variable", "doc": "
    A field for custom configuration that can contain any keys not present in the RDF spec.\nThis means you should not store, for example, a github repo URL in config since we already have the\ngit_repo field defined in the spec.\nKeys in config may be very specific to a tool or consumer software. To avoid conflicting definitions,\nit is recommended to wrap added configuration into a sub-field named with the specific domain or tool name,\nfor example:
    \n\n
    \n
    config:\n    bioimageio:  # here is the domain name\n        my_custom_key: 3837283\n        another_key:\n            nested: value\n    imagej:       # config specific to ImageJ\n        macro_dir: path/to/macro/file\n
    \n
    \n\n
    If possible, please use snake_case for keys in config.\nYou may want to list linked files additionally under attachments to include them when packaging a resource\n(packaging a resource means downloading/copying important linked files and creating a ZIP archive that contains\nan altered rdf.yaml file with local references to the downloaded files)
    \n", "annotation": ": Annotated[Dict[str, YamlValue], FieldInfo(annotation=NoneType, required=True, examples=[{'bioimageio': {'my_custom_key': 3837283, 'another_key': {'nested': 'value'}}, 'imagej': {'macro_dir': 'path/to/macro/file'}}])]"}, "bioimageio.spec.generic.v0_2.GenericModelDescrBase.download_url": {"fullname": "bioimageio.spec.generic.v0_2.GenericModelDescrBase.download_url", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "GenericModelDescrBase.download_url", "kind": "variable", "doc": "
    URL to download the resource from (deprecated)
    \n", "annotation": ": Optional[bioimageio.spec._internal.url.HttpUrl]"}, "bioimageio.spec.generic.v0_2.GenericModelDescrBase.git_repo": {"fullname": "bioimageio.spec.generic.v0_2.GenericModelDescrBase.git_repo", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "GenericModelDescrBase.git_repo", "kind": "variable", "doc": "
    A URL to the Git repository where the resource is being developed.
    \n", "annotation": ": Annotated[Optional[str], FieldInfo(annotation=NoneType, required=True, examples=['https://github.com/bioimage-io/spec-bioimage-io/tree/main/example_descriptions/models/unet2d_nuclei_broad'])]"}, "bioimageio.spec.generic.v0_2.GenericModelDescrBase.icon": {"fullname": "bioimageio.spec.generic.v0_2.GenericModelDescrBase.icon", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "GenericModelDescrBase.icon", "kind": "variable", "doc": "
    An icon for illustration
    \n", "annotation": ": Union[Annotated[Union[Annotated[pathlib.Path, PathType(path_type='file')], bioimageio.spec._internal.io.RelativeFilePath, bioimageio.spec._internal.url.HttpUrl, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator(func=<function wo_special_file_name at 0x7afca0d90540>), PlainSerializer(func=<function _package at 0x7afca0d91760>, return_type=PydanticUndefined, when_used='unless-none')], Annotated[str, Len(min_length=1, max_length=2)], NoneType]"}, "bioimageio.spec.generic.v0_2.GenericModelDescrBase.links": {"fullname": "bioimageio.spec.generic.v0_2.GenericModelDescrBase.links", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "GenericModelDescrBase.links", "kind": "variable", "doc": "
    IDs of other bioimage.io resources
    \n", "annotation": ": Annotated[List[str], FieldInfo(annotation=NoneType, required=True, examples=[('ilastik/ilastik', 'deepimagej/deepimagej', 'zero/notebook_u-net_3d_zerocostdl4mic')])]"}, "bioimageio.spec.generic.v0_2.GenericModelDescrBase.uploader": {"fullname": "bioimageio.spec.generic.v0_2.GenericModelDescrBase.uploader", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "GenericModelDescrBase.uploader", "kind": "variable", "doc": "
    The person who uploaded the model (e.g. to bioimage.io)
    \n", "annotation": ": Optional[bioimageio.spec.generic.v0_2.Uploader]"}, "bioimageio.spec.generic.v0_2.GenericModelDescrBase.maintainers": {"fullname": "bioimageio.spec.generic.v0_2.GenericModelDescrBase.maintainers", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "GenericModelDescrBase.maintainers", "kind": "variable", "doc": "
    Maintainers of this resource.\nIf not specified authors are maintainers and at least some of them should specify their github_user name
    \n", "annotation": ": List[bioimageio.spec.generic.v0_2.Maintainer]"}, "bioimageio.spec.generic.v0_2.GenericModelDescrBase.rdf_source": {"fullname": "bioimageio.spec.generic.v0_2.GenericModelDescrBase.rdf_source", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "GenericModelDescrBase.rdf_source", "kind": "variable", "doc": "
    Resource description file (RDF) source; used to keep track of where an rdf.yaml was loaded from.\nDo not set this field in a YAML file.
    \n", "annotation": ": Union[Annotated[pathlib.Path, PathType(path_type='file')], bioimageio.spec._internal.io.RelativeFilePath, bioimageio.spec._internal.url.HttpUrl, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)], NoneType]"}, "bioimageio.spec.generic.v0_2.GenericModelDescrBase.tags": {"fullname": "bioimageio.spec.generic.v0_2.GenericModelDescrBase.tags", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "GenericModelDescrBase.tags", "kind": "variable", "doc": "
    Associated tags
    \n", "annotation": ": Annotated[List[str], FieldInfo(annotation=NoneType, required=True, examples=[('unet2d', 'pytorch', 'nucleus', 'segmentation', 'dsb2018')])]"}, "bioimageio.spec.generic.v0_2.GenericModelDescrBase.warn_about_tag_categories": {"fullname": "bioimageio.spec.generic.v0_2.GenericModelDescrBase.warn_about_tag_categories", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "GenericModelDescrBase.warn_about_tag_categories", "kind": "function", "doc": "
    \n", "signature": "(value: Any, info: pydantic_core.core_schema.ValidationInfo) -> Any:", "funcdef": "def"}, "bioimageio.spec.generic.v0_2.GenericModelDescrBase.version": {"fullname": "bioimageio.spec.generic.v0_2.GenericModelDescrBase.version", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "GenericModelDescrBase.version", "kind": "variable", "doc": "
    The version of the resource following SemVer 2.0.
    \n", "annotation": ": Optional[bioimageio.spec._internal.version_type.Version]"}, "bioimageio.spec.generic.v0_2.GenericModelDescrBase.version_number": {"fullname": "bioimageio.spec.generic.v0_2.GenericModelDescrBase.version_number", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "GenericModelDescrBase.version_number", "kind": "variable", "doc": "
    version number (n-th published version, not the semantic version)
    \n", "annotation": ": Optional[int]"}, "bioimageio.spec.generic.v0_2.GenericModelDescrBase.model_config": {"fullname": "bioimageio.spec.generic.v0_2.GenericModelDescrBase.model_config", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "GenericModelDescrBase.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.generic.v0_2.GenericModelDescrBase.model_fields": {"fullname": "bioimageio.spec.generic.v0_2.GenericModelDescrBase.model_fields", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "GenericModelDescrBase.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'name': FieldInfo(annotation=str, required=True, metadata=[MinLen(min_length=1), AfterWarner(func=<function as_warning.<locals>.wrapper>, severity=30, msg='Longer than 128 characters.', context={'typ': typing.Annotated[typing.Any, MaxLen(max_length=128)]})]), 'description': FieldInfo(annotation=str, required=True), 'covers': FieldInfo(annotation=List[Annotated[Union[HttpUrl, Annotated[Path, PathType, Predicate], RelativeFilePath], WithSuffix, PlainSerializer]], required=False, default_factory=list, description="Cover images. Please use an image smaller than 500KB and an aspect ratio width to height of 2:1.\\nThe supported image formats are: ('.gif', '.jpeg', '.jpg', '.png', '.svg')", examples=['cover.png']), 'id_emoji': FieldInfo(annotation=Union[Annotated[str, Len], NoneType], required=False), 'authors': FieldInfo(annotation=List[Author], required=False, default_factory=list), 'attachments': FieldInfo(annotation=Union[AttachmentsDescr, NoneType], required=False), 'cite': FieldInfo(annotation=List[CiteEntry], required=False, default_factory=list), 'config': FieldInfo(annotation=Dict[str, YamlValue], required=False, default_factory=dict, examples=[{'bioimageio': {'my_custom_key': 3837283, 'another_key': {'nested': 'value'}}, 'imagej': {'macro_dir': 'path/to/macro/file'}}]), 'download_url': FieldInfo(annotation=Union[HttpUrl, NoneType], required=False), 'git_repo': FieldInfo(annotation=Union[str, NoneType], required=False, examples=['https://github.com/bioimage-io/spec-bioimage-io/tree/main/example_descriptions/models/unet2d_nuclei_broad']), 'icon': FieldInfo(annotation=Union[Annotated[Union[Annotated[Path, PathType], RelativeFilePath, HttpUrl, Annotated[Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator, PlainSerializer], Annotated[str, Len], NoneType], required=False), 'links': FieldInfo(annotation=List[str], required=False, default_factory=list, examples=[('ilastik/ilastik', 'deepimagej/deepimagej', 'zero/notebook_u-net_3d_zerocostdl4mic')]), 'uploader': FieldInfo(annotation=Union[Uploader, NoneType], required=False), 'maintainers': FieldInfo(annotation=List[Maintainer], required=False, default_factory=list), 'rdf_source': FieldInfo(annotation=Union[Annotated[Path, PathType], RelativeFilePath, HttpUrl, Annotated[Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)], NoneType], required=False), 'tags': FieldInfo(annotation=List[str], required=False, default_factory=list, examples=[('unet2d', 'pytorch', 'nucleus', 'segmentation', 'dsb2018')]), 'version': FieldInfo(annotation=Union[Version, NoneType], required=False), 'version_number': FieldInfo(annotation=Union[int, NoneType], required=False)}"}, "bioimageio.spec.generic.v0_2.GenericModelDescrBase.model_computed_fields": {"fullname": "bioimageio.spec.generic.v0_2.GenericModelDescrBase.model_computed_fields", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "GenericModelDescrBase.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.generic.v0_2.GenericDescrBase": {"fullname": "bioimageio.spec.generic.v0_2.GenericDescrBase", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "GenericDescrBase", "kind": "class", "doc": "
    Base for all resource descriptions except for the model descriptions
    \n", "bases": "GenericModelDescrBase"}, "bioimageio.spec.generic.v0_2.GenericDescrBase.format_version": {"fullname": "bioimageio.spec.generic.v0_2.GenericDescrBase.format_version", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "GenericDescrBase.format_version", "kind": "variable", "doc": "
    The format version of this resource specification\n(not the version of the resource description)\nWhen creating a new resource always use the latest micro/patch version described here.\nThe format_version is important for any consumer software to understand how to parse the fields.
    \n", "annotation": ": Literal['0.2.4']"}, "bioimageio.spec.generic.v0_2.GenericDescrBase.badges": {"fullname": "bioimageio.spec.generic.v0_2.GenericDescrBase.badges", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "GenericDescrBase.badges", "kind": "variable", "doc": "
    badges associated with this resource
    \n", "annotation": ": List[bioimageio.spec.generic.v0_2.BadgeDescr]"}, "bioimageio.spec.generic.v0_2.GenericDescrBase.documentation": {"fullname": "bioimageio.spec.generic.v0_2.GenericDescrBase.documentation", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "GenericDescrBase.documentation", "kind": "variable", "doc": "
    \u2208\ud83d\udce6 URL or relative path to a markdown file with additional documentation.\nThe recommended documentation file name is README.md. An .md suffix is mandatory.
    \n", "annotation": ": Annotated[Optional[Annotated[Union[Annotated[pathlib.Path, PathType(path_type='file')], bioimageio.spec._internal.io.RelativeFilePath, bioimageio.spec._internal.url.HttpUrl, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator(func=<function wo_special_file_name at 0x7afca0d90540>), PlainSerializer(func=<function _package at 0x7afca0d91760>, return_type=PydanticUndefined, when_used='unless-none')]], FieldInfo(annotation=NoneType, required=True, examples=['https://raw.githubusercontent.com/bioimage-io/spec-bioimage-io/main/example_descriptions/models/unet2d_nuclei_broad/README.md', 'README.md'])]"}, "bioimageio.spec.generic.v0_2.GenericDescrBase.license": {"fullname": "bioimageio.spec.generic.v0_2.GenericDescrBase.license", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "GenericDescrBase.license", "kind": "variable", "doc": "
    A SPDX license identifier.\nWe do not support custom license beyond the SPDX license list, if you need that please\nopen a GitHub issue to discuss your intentions with the community.
    \n", "annotation": ": Annotated[Union[bioimageio.spec._internal.license_id.LicenseId, bioimageio.spec._internal.license_id.DeprecatedLicenseId, str, NoneType], FieldInfo(annotation=NoneType, required=True, examples=['CC-BY-4.0', 'MIT', 'BSD-2-Clause'])]"}, "bioimageio.spec.generic.v0_2.GenericDescrBase.deprecated_spdx_license": {"fullname": "bioimageio.spec.generic.v0_2.GenericDescrBase.deprecated_spdx_license", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "GenericDescrBase.deprecated_spdx_license", "kind": "function", "doc": "
    \n", "signature": "(\tcls,\tvalue: Union[bioimageio.spec._internal.license_id.LicenseId, bioimageio.spec._internal.license_id.DeprecatedLicenseId, str, NoneType]):", "funcdef": "def"}, "bioimageio.spec.generic.v0_2.GenericDescrBase.implemented_format_version": {"fullname": "bioimageio.spec.generic.v0_2.GenericDescrBase.implemented_format_version", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "GenericDescrBase.implemented_format_version", "kind": "variable", "doc": "
    \n", "annotation": ": ClassVar[str]", "default_value": "'0.2.4'"}, "bioimageio.spec.generic.v0_2.GenericDescrBase.implemented_format_version_tuple": {"fullname": "bioimageio.spec.generic.v0_2.GenericDescrBase.implemented_format_version_tuple", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "GenericDescrBase.implemented_format_version_tuple", "kind": "variable", "doc": "
    \n", "annotation": ": ClassVar[Tuple[int, int, int]]", "default_value": "(0, 2, 4)"}, "bioimageio.spec.generic.v0_2.GenericDescrBase.model_config": {"fullname": "bioimageio.spec.generic.v0_2.GenericDescrBase.model_config", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "GenericDescrBase.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.generic.v0_2.GenericDescrBase.model_fields": {"fullname": "bioimageio.spec.generic.v0_2.GenericDescrBase.model_fields", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "GenericDescrBase.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'name': FieldInfo(annotation=str, required=True, metadata=[MinLen(min_length=1), AfterWarner(func=<function as_warning.<locals>.wrapper>, severity=30, msg='Longer than 128 characters.', context={'typ': typing.Annotated[typing.Any, MaxLen(max_length=128)]})]), 'description': FieldInfo(annotation=str, required=True), 'covers': FieldInfo(annotation=List[Annotated[Union[HttpUrl, Annotated[Path, PathType, Predicate], RelativeFilePath], WithSuffix, PlainSerializer]], required=False, default_factory=list, description="Cover images. Please use an image smaller than 500KB and an aspect ratio width to height of 2:1.\\nThe supported image formats are: ('.gif', '.jpeg', '.jpg', '.png', '.svg')", examples=['cover.png']), 'id_emoji': FieldInfo(annotation=Union[Annotated[str, Len], NoneType], required=False), 'authors': FieldInfo(annotation=List[Author], required=False, default_factory=list), 'attachments': FieldInfo(annotation=Union[AttachmentsDescr, NoneType], required=False), 'cite': FieldInfo(annotation=List[CiteEntry], required=False, default_factory=list), 'config': FieldInfo(annotation=Dict[str, YamlValue], required=False, default_factory=dict, examples=[{'bioimageio': {'my_custom_key': 3837283, 'another_key': {'nested': 'value'}}, 'imagej': {'macro_dir': 'path/to/macro/file'}}]), 'download_url': FieldInfo(annotation=Union[HttpUrl, NoneType], required=False), 'git_repo': FieldInfo(annotation=Union[str, NoneType], required=False, examples=['https://github.com/bioimage-io/spec-bioimage-io/tree/main/example_descriptions/models/unet2d_nuclei_broad']), 'icon': FieldInfo(annotation=Union[Annotated[Union[Annotated[Path, PathType], RelativeFilePath, HttpUrl, Annotated[Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator, PlainSerializer], Annotated[str, Len], NoneType], required=False), 'links': FieldInfo(annotation=List[str], required=False, default_factory=list, examples=[('ilastik/ilastik', 'deepimagej/deepimagej', 'zero/notebook_u-net_3d_zerocostdl4mic')]), 'uploader': FieldInfo(annotation=Union[Uploader, NoneType], required=False), 'maintainers': FieldInfo(annotation=List[Maintainer], required=False, default_factory=list), 'rdf_source': FieldInfo(annotation=Union[Annotated[Path, PathType], RelativeFilePath, HttpUrl, Annotated[Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)], NoneType], required=False), 'tags': FieldInfo(annotation=List[str], required=False, default_factory=list, examples=[('unet2d', 'pytorch', 'nucleus', 'segmentation', 'dsb2018')]), 'version': FieldInfo(annotation=Union[Version, NoneType], required=False), 'version_number': FieldInfo(annotation=Union[int, NoneType], required=False), 'format_version': FieldInfo(annotation=Literal['0.2.4'], required=False, default='0.2.4'), 'badges': FieldInfo(annotation=List[BadgeDescr], required=False, default_factory=list), 'documentation': FieldInfo(annotation=Union[Annotated[Union[Annotated[Path, PathType], RelativeFilePath, HttpUrl, Annotated[Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator, PlainSerializer], NoneType], required=False, examples=['https://raw.githubusercontent.com/bioimage-io/spec-bioimage-io/main/example_descriptions/models/unet2d_nuclei_broad/README.md', 'README.md']), 'license': FieldInfo(annotation=Union[LicenseId, DeprecatedLicenseId, str, NoneType], required=False, examples=['CC-BY-4.0', 'MIT', 'BSD-2-Clause'])}"}, "bioimageio.spec.generic.v0_2.GenericDescrBase.model_computed_fields": {"fullname": "bioimageio.spec.generic.v0_2.GenericDescrBase.model_computed_fields", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "GenericDescrBase.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.generic.v0_2.GenericDescr": {"fullname": "bioimageio.spec.generic.v0_2.GenericDescr", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "GenericDescr", "kind": "class", "doc": "
    Specification of the fields used in a generic bioimage.io-compliant resource description file (RDF).
    \n\n
    An RDF is a YAML file that describes a resource such as a model, a dataset, or a notebook.\nNote that those resources are described with a type-specific RDF.\nUse this generic resource description, if none of the known specific types matches your resource.
    \n", "bases": "GenericDescrBase"}, "bioimageio.spec.generic.v0_2.GenericDescr.type": {"fullname": "bioimageio.spec.generic.v0_2.GenericDescr.type", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "GenericDescr.type", "kind": "variable", "doc": "
    The resource type assigns a broad category to the resource.
    \n", "annotation": ": Annotated[str, Annotated[~_StrType, Predicate(func=<method 'islower' of 'str' objects>)], FieldInfo(annotation=NoneType, required=True, frozen=True)]"}, "bioimageio.spec.generic.v0_2.GenericDescr.id": {"fullname": "bioimageio.spec.generic.v0_2.GenericDescr.id", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "GenericDescr.id", "kind": "variable", "doc": "
    Model zoo (bioimage.io) wide, unique identifier (assigned by bioimage.io)
    \n", "annotation": ": Optional[bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]]]"}, "bioimageio.spec.generic.v0_2.GenericDescr.source": {"fullname": "bioimageio.spec.generic.v0_2.GenericDescr.source", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "GenericDescr.source", "kind": "variable", "doc": "
    The primary source of the resource
    \n", "annotation": ": Optional[bioimageio.spec._internal.url.HttpUrl]"}, "bioimageio.spec.generic.v0_2.GenericDescr.check_specific_types": {"fullname": "bioimageio.spec.generic.v0_2.GenericDescr.check_specific_types", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "GenericDescr.check_specific_types", "kind": "function", "doc": "
    \n", "signature": "(cls, value: str) -> str:", "funcdef": "def"}, "bioimageio.spec.generic.v0_2.GenericDescr.implemented_format_version": {"fullname": "bioimageio.spec.generic.v0_2.GenericDescr.implemented_format_version", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "GenericDescr.implemented_format_version", "kind": "variable", "doc": "
    \n", "annotation": ": ClassVar[str]", "default_value": "'0.2.4'"}, "bioimageio.spec.generic.v0_2.GenericDescr.implemented_format_version_tuple": {"fullname": "bioimageio.spec.generic.v0_2.GenericDescr.implemented_format_version_tuple", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "GenericDescr.implemented_format_version_tuple", "kind": "variable", "doc": "
    \n", "annotation": ": ClassVar[Tuple[int, int, int]]", "default_value": "(0, 2, 4)"}, "bioimageio.spec.generic.v0_2.GenericDescr.model_config": {"fullname": "bioimageio.spec.generic.v0_2.GenericDescr.model_config", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "GenericDescr.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'ignore', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True, 'title': 'bioimage.io generic specification'}"}, "bioimageio.spec.generic.v0_2.GenericDescr.model_fields": {"fullname": "bioimageio.spec.generic.v0_2.GenericDescr.model_fields", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "GenericDescr.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'name': FieldInfo(annotation=str, required=True, metadata=[MinLen(min_length=1), AfterWarner(func=<function as_warning.<locals>.wrapper>, severity=30, msg='Longer than 128 characters.', context={'typ': typing.Annotated[typing.Any, MaxLen(max_length=128)]})]), 'description': FieldInfo(annotation=str, required=True), 'covers': FieldInfo(annotation=List[Annotated[Union[HttpUrl, Annotated[Path, PathType, Predicate], RelativeFilePath], WithSuffix, PlainSerializer]], required=False, default_factory=list, description="Cover images. Please use an image smaller than 500KB and an aspect ratio width to height of 2:1.\\nThe supported image formats are: ('.gif', '.jpeg', '.jpg', '.png', '.svg')", examples=['cover.png']), 'id_emoji': FieldInfo(annotation=Union[Annotated[str, Len], NoneType], required=False), 'authors': FieldInfo(annotation=List[Author], required=False, default_factory=list), 'attachments': FieldInfo(annotation=Union[AttachmentsDescr, NoneType], required=False), 'cite': FieldInfo(annotation=List[CiteEntry], required=False, default_factory=list), 'config': FieldInfo(annotation=Dict[str, YamlValue], required=False, default_factory=dict, examples=[{'bioimageio': {'my_custom_key': 3837283, 'another_key': {'nested': 'value'}}, 'imagej': {'macro_dir': 'path/to/macro/file'}}]), 'download_url': FieldInfo(annotation=Union[HttpUrl, NoneType], required=False), 'git_repo': FieldInfo(annotation=Union[str, NoneType], required=False, examples=['https://github.com/bioimage-io/spec-bioimage-io/tree/main/example_descriptions/models/unet2d_nuclei_broad']), 'icon': FieldInfo(annotation=Union[Annotated[Union[Annotated[Path, PathType], RelativeFilePath, HttpUrl, Annotated[Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator, PlainSerializer], Annotated[str, Len], NoneType], required=False), 'links': FieldInfo(annotation=List[str], required=False, default_factory=list, examples=[('ilastik/ilastik', 'deepimagej/deepimagej', 'zero/notebook_u-net_3d_zerocostdl4mic')]), 'uploader': FieldInfo(annotation=Union[Uploader, NoneType], required=False), 'maintainers': FieldInfo(annotation=List[Maintainer], required=False, default_factory=list), 'rdf_source': FieldInfo(annotation=Union[Annotated[Path, PathType], RelativeFilePath, HttpUrl, Annotated[Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)], NoneType], required=False), 'tags': FieldInfo(annotation=List[str], required=False, default_factory=list, examples=[('unet2d', 'pytorch', 'nucleus', 'segmentation', 'dsb2018')]), 'version': FieldInfo(annotation=Union[Version, NoneType], required=False), 'version_number': FieldInfo(annotation=Union[int, NoneType], required=False), 'format_version': FieldInfo(annotation=Literal['0.2.4'], required=False, default='0.2.4'), 'badges': FieldInfo(annotation=List[BadgeDescr], required=False, default_factory=list), 'documentation': FieldInfo(annotation=Union[Annotated[Union[Annotated[Path, PathType], RelativeFilePath, HttpUrl, Annotated[Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator, PlainSerializer], NoneType], required=False, examples=['https://raw.githubusercontent.com/bioimage-io/spec-bioimage-io/main/example_descriptions/models/unet2d_nuclei_broad/README.md', 'README.md']), 'license': FieldInfo(annotation=Union[LicenseId, DeprecatedLicenseId, str, NoneType], required=False, examples=['CC-BY-4.0', 'MIT', 'BSD-2-Clause']), 'type': FieldInfo(annotation=str, required=False, default='generic', frozen=True, metadata=[typing.Annotated[~_StrType, Predicate(func=<method 'islower' of 'str' objects>)]]), 'id': FieldInfo(annotation=Union[ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]], NoneType], required=False), 'source': FieldInfo(annotation=Union[HttpUrl, NoneType], required=False)}"}, "bioimageio.spec.generic.v0_2.GenericDescr.model_computed_fields": {"fullname": "bioimageio.spec.generic.v0_2.GenericDescr.model_computed_fields", "modulename": "bioimageio.spec.generic.v0_2", "qualname": "GenericDescr.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.generic.v0_3": {"fullname": "bioimageio.spec.generic.v0_3", "modulename": "bioimageio.spec.generic.v0_3", "kind": "module", "doc": "
    \n"}, "bioimageio.spec.generic.v0_3.KNOWN_SPECIFIC_RESOURCE_TYPES": {"fullname": "bioimageio.spec.generic.v0_3.KNOWN_SPECIFIC_RESOURCE_TYPES", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "KNOWN_SPECIFIC_RESOURCE_TYPES", "kind": "variable", "doc": "
    \n", "default_value": "('application', 'collection', 'dataset', 'model', 'notebook')"}, "bioimageio.spec.generic.v0_3.DocumentationSource": {"fullname": "bioimageio.spec.generic.v0_3.DocumentationSource", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "DocumentationSource", "kind": "variable", "doc": "
    \n", "default_value": "typing.Annotated[typing.Union[typing.Annotated[pathlib.Path, PathType(path_type='file'), Predicate(func=<function PurePath.is_absolute>)], bioimageio.spec._internal.io.RelativeFilePath, bioimageio.spec._internal.url.HttpUrl], AfterValidator(func=<function _validate_md_suffix>), PlainSerializer(func=<function _package>, return_type=PydanticUndefined, when_used='unless-none')]"}, "bioimageio.spec.generic.v0_3.Author": {"fullname": "bioimageio.spec.generic.v0_3.Author", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "Author", "kind": "class", "doc": "
    Subpart of a resource description
    \n", "bases": "bioimageio.spec.generic.v0_2.Author"}, "bioimageio.spec.generic.v0_3.Author.name": {"fullname": "bioimageio.spec.generic.v0_3.Author.name", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "Author.name", "kind": "variable", "doc": "
    \n", "annotation": ": Annotated[str, Predicate(func=<function _has_no_slash at 0x7afca0a94cc0>)]"}, "bioimageio.spec.generic.v0_3.Author.github_user": {"fullname": "bioimageio.spec.generic.v0_3.Author.github_user", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "Author.github_user", "kind": "variable", "doc": "
    \n", "annotation": ": Optional[str]"}, "bioimageio.spec.generic.v0_3.Author.model_config": {"fullname": "bioimageio.spec.generic.v0_3.Author.model_config", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "Author.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.generic.v0_3.Author.model_fields": {"fullname": "bioimageio.spec.generic.v0_3.Author.model_fields", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "Author.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'affiliation': FieldInfo(annotation=Union[str, NoneType], required=False), 'email': FieldInfo(annotation=Union[EmailStr, NoneType], required=False), 'orcid': FieldInfo(annotation=Union[ValidatedString[Annotated[str, AfterValidator]], NoneType], required=False, examples=['0000-0001-2345-6789']), 'name': FieldInfo(annotation=str, required=True, metadata=[Predicate(func=<function _has_no_slash>)]), 'github_user': FieldInfo(annotation=Union[str, NoneType], required=False)}"}, "bioimageio.spec.generic.v0_3.Author.model_computed_fields": {"fullname": "bioimageio.spec.generic.v0_3.Author.model_computed_fields", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "Author.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.generic.v0_3.Maintainer": {"fullname": "bioimageio.spec.generic.v0_3.Maintainer", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "Maintainer", "kind": "class", "doc": "
    Subpart of a resource description
    \n", "bases": "bioimageio.spec.generic.v0_2.Maintainer"}, "bioimageio.spec.generic.v0_3.Maintainer.name": {"fullname": "bioimageio.spec.generic.v0_3.Maintainer.name", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "Maintainer.name", "kind": "variable", "doc": "
    \n", "annotation": ": Optional[Annotated[str, Predicate(func=<function _has_no_slash at 0x7afca0a94cc0>)]]"}, "bioimageio.spec.generic.v0_3.Maintainer.github_user": {"fullname": "bioimageio.spec.generic.v0_3.Maintainer.github_user", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "Maintainer.github_user", "kind": "variable", "doc": "
    \n", "annotation": ": str"}, "bioimageio.spec.generic.v0_3.Maintainer.validate_gh_user": {"fullname": "bioimageio.spec.generic.v0_3.Maintainer.validate_gh_user", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "Maintainer.validate_gh_user", "kind": "function", "doc": "
    \n", "signature": "(cls, value: str):", "funcdef": "def"}, "bioimageio.spec.generic.v0_3.Maintainer.model_config": {"fullname": "bioimageio.spec.generic.v0_3.Maintainer.model_config", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "Maintainer.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.generic.v0_3.Maintainer.model_fields": {"fullname": "bioimageio.spec.generic.v0_3.Maintainer.model_fields", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "Maintainer.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'affiliation': FieldInfo(annotation=Union[str, NoneType], required=False), 'email': FieldInfo(annotation=Union[EmailStr, NoneType], required=False), 'orcid': FieldInfo(annotation=Union[ValidatedString[Annotated[str, AfterValidator]], NoneType], required=False, examples=['0000-0001-2345-6789']), 'name': FieldInfo(annotation=Union[Annotated[str, Predicate], NoneType], required=False), 'github_user': FieldInfo(annotation=str, required=True)}"}, "bioimageio.spec.generic.v0_3.Maintainer.model_computed_fields": {"fullname": "bioimageio.spec.generic.v0_3.Maintainer.model_computed_fields", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "Maintainer.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.generic.v0_3.CiteEntry": {"fullname": "bioimageio.spec.generic.v0_3.CiteEntry", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "CiteEntry", "kind": "class", "doc": "
    Subpart of a resource description
    \n", "bases": "bioimageio.spec._internal.node.Node"}, "bioimageio.spec.generic.v0_3.CiteEntry.text": {"fullname": "bioimageio.spec.generic.v0_3.CiteEntry.text", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "CiteEntry.text", "kind": "variable", "doc": "
    free text description
    \n", "annotation": ": str"}, "bioimageio.spec.generic.v0_3.CiteEntry.doi": {"fullname": "bioimageio.spec.generic.v0_3.CiteEntry.doi", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "CiteEntry.doi", "kind": "variable", "doc": "
    A digital object identifier (DOI) is the prefered citation reference.\nSee https://www.doi.org/ for details. (alternatively specify url)
    \n", "annotation": ": Optional[bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, StringConstraints]]]"}, "bioimageio.spec.generic.v0_3.CiteEntry.url": {"fullname": "bioimageio.spec.generic.v0_3.CiteEntry.url", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "CiteEntry.url", "kind": "variable", "doc": "
    URL to cite (preferably specify a doi instead)
    \n", "annotation": ": Optional[bioimageio.spec._internal.url.HttpUrl]"}, "bioimageio.spec.generic.v0_3.CiteEntry.model_config": {"fullname": "bioimageio.spec.generic.v0_3.CiteEntry.model_config", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "CiteEntry.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.generic.v0_3.CiteEntry.model_fields": {"fullname": "bioimageio.spec.generic.v0_3.CiteEntry.model_fields", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "CiteEntry.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'text': FieldInfo(annotation=str, required=True), 'doi': FieldInfo(annotation=Union[ValidatedString[Annotated[str, StringConstraints]], NoneType], required=False), 'url': FieldInfo(annotation=Union[HttpUrl, NoneType], required=False)}"}, "bioimageio.spec.generic.v0_3.CiteEntry.model_computed_fields": {"fullname": "bioimageio.spec.generic.v0_3.CiteEntry.model_computed_fields", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "CiteEntry.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.generic.v0_3.LinkedResource": {"fullname": "bioimageio.spec.generic.v0_3.LinkedResource", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "LinkedResource", "kind": "class", "doc": "
    Reference to a bioimage.io resource
    \n", "bases": "bioimageio.spec._internal.node.Node"}, "bioimageio.spec.generic.v0_3.LinkedResource.id": {"fullname": "bioimageio.spec.generic.v0_3.LinkedResource.id", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "LinkedResource.id", "kind": "variable", "doc": "
    A valid resource id from the official bioimage.io collection.
    \n", "annotation": ": bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]]"}, "bioimageio.spec.generic.v0_3.LinkedResource.version_number": {"fullname": "bioimageio.spec.generic.v0_3.LinkedResource.version_number", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "LinkedResource.version_number", "kind": "variable", "doc": "
    version number (n-th published version, not the semantic version) of linked resource
    \n", "annotation": ": int"}, "bioimageio.spec.generic.v0_3.LinkedResource.model_config": {"fullname": "bioimageio.spec.generic.v0_3.LinkedResource.model_config", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "LinkedResource.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.generic.v0_3.LinkedResource.model_fields": {"fullname": "bioimageio.spec.generic.v0_3.LinkedResource.model_fields", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "LinkedResource.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'id': FieldInfo(annotation=ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]], required=True), 'version_number': FieldInfo(annotation=int, required=True)}"}, "bioimageio.spec.generic.v0_3.LinkedResource.model_computed_fields": {"fullname": "bioimageio.spec.generic.v0_3.LinkedResource.model_computed_fields", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "LinkedResource.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.generic.v0_3.GenericModelDescrBase": {"fullname": "bioimageio.spec.generic.v0_3.GenericModelDescrBase", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "GenericModelDescrBase", "kind": "class", "doc": "
    Base for all resource descriptions including of model descriptions
    \n", "bases": "bioimageio.spec._internal.common_nodes.ResourceDescrBase"}, "bioimageio.spec.generic.v0_3.GenericModelDescrBase.name": {"fullname": "bioimageio.spec.generic.v0_3.GenericModelDescrBase.name", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "GenericModelDescrBase.name", "kind": "variable", "doc": "
    A human-friendly name of the resource description
    \n", "annotation": ": Annotated[str, MinLen(min_length=1), MaxLen(max_length=128)]"}, "bioimageio.spec.generic.v0_3.GenericModelDescrBase.description": {"fullname": "bioimageio.spec.generic.v0_3.GenericModelDescrBase.description", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "GenericModelDescrBase.description", "kind": "variable", "doc": "
    A string containing a brief description.
    \n", "annotation": ": Annotated[str, MaxLen(max_length=1024), AfterWarner(func=<function as_warning.<locals>.wrapper at 0x7afc92925f80>, severity=30, msg='Description longer than 512 characters.', context={'typ': Annotated[Any, MaxLen(max_length=512)]})]"}, "bioimageio.spec.generic.v0_3.GenericModelDescrBase.covers": {"fullname": "bioimageio.spec.generic.v0_3.GenericModelDescrBase.covers", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "GenericModelDescrBase.covers", "kind": "variable", "doc": "
    \u2208\ud83d\udce6 Cover images.
    \n", "annotation": ": Annotated[List[Annotated[Union[bioimageio.spec._internal.url.HttpUrl, Annotated[pathlib.Path, PathType(path_type='file'), Predicate(func=<function PurePath.is_absolute at 0x7afca4145940>)], bioimageio.spec._internal.io.RelativeFilePath], WithSuffix(suffix=('.gif', '.jpeg', '.jpg', '.png', '.svg'), case_sensitive=False), PlainSerializer(func=<function _package at 0x7afca0d91760>, return_type=PydanticUndefined, when_used='unless-none')]], FieldInfo(annotation=NoneType, required=True, description="Cover images. Please use an image smaller than 500KB and an aspect ratio width to height of 2:1 or 1:1.\\nThe supported image formats are: ('.gif', '.jpeg', '.jpg', '.png', '.svg')", examples=[])]"}, "bioimageio.spec.generic.v0_3.GenericModelDescrBase.id_emoji": {"fullname": "bioimageio.spec.generic.v0_3.GenericModelDescrBase.id_emoji", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "GenericModelDescrBase.id_emoji", "kind": "variable", "doc": "
    UTF-8 emoji for display alongside the id.
    \n", "annotation": ": Optional[Annotated[str, Len(min_length=1, max_length=1)]]"}, "bioimageio.spec.generic.v0_3.GenericModelDescrBase.authors": {"fullname": "bioimageio.spec.generic.v0_3.GenericModelDescrBase.authors", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "GenericModelDescrBase.authors", "kind": "variable", "doc": "
    The authors are the creators of this resource description and the primary points of contact.
    \n", "annotation": ": Annotated[List[bioimageio.spec.generic.v0_3.Author], MinLen(min_length=1)]"}, "bioimageio.spec.generic.v0_3.GenericModelDescrBase.attachments": {"fullname": "bioimageio.spec.generic.v0_3.GenericModelDescrBase.attachments", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "GenericModelDescrBase.attachments", "kind": "variable", "doc": "
    file attachments
    \n", "annotation": ": List[bioimageio.spec._internal.io.FileDescr]"}, "bioimageio.spec.generic.v0_3.GenericModelDescrBase.cite": {"fullname": "bioimageio.spec.generic.v0_3.GenericModelDescrBase.cite", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "GenericModelDescrBase.cite", "kind": "variable", "doc": "
    citations
    \n", "annotation": ": Annotated[List[bioimageio.spec.generic.v0_3.CiteEntry], MinLen(min_length=1)]"}, "bioimageio.spec.generic.v0_3.GenericModelDescrBase.license": {"fullname": "bioimageio.spec.generic.v0_3.GenericModelDescrBase.license", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "GenericModelDescrBase.license", "kind": "variable", "doc": "
    A SPDX license identifier.\nWe do not support custom license beyond the SPDX license list, if you need that please\nopen a GitHub issue\nto discuss your intentions with the community.
    \n", "annotation": ": Annotated[Union[bioimageio.spec._internal.license_id.LicenseId, bioimageio.spec._internal.license_id.DeprecatedLicenseId], AfterWarner(func=<function as_warning.<locals>.wrapper at 0x7afc92925e40>, severity=30, msg='{value} is deprecated, see https://spdx.org/licenses/{value}.html', context={'typ': <class 'bioimageio.spec._internal.license_id.LicenseId'>}), FieldInfo(annotation=NoneType, required=True, examples=['CC-BY-4.0', 'MIT', 'BSD-2-Clause'])]"}, "bioimageio.spec.generic.v0_3.GenericModelDescrBase.config": {"fullname": "bioimageio.spec.generic.v0_3.GenericModelDescrBase.config", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "GenericModelDescrBase.config", "kind": "variable", "doc": "
    A field for custom configuration that can contain any keys not present in the RDF spec.\nThis means you should not store, for example, a GitHub repo URL in config since there is a git_repo field.\nKeys in config may be very specific to a tool or consumer software. To avoid conflicting definitions,\nit is recommended to wrap added configuration into a sub-field named with the specific domain or tool name,\nfor example:
    \n\n
    \n
    config:\n    bioimageio:  # here is the domain name\n        my_custom_key: 3837283\n        another_key:\n            nested: value\n    imagej:       # config specific to ImageJ\n        macro_dir: path/to/macro/file\n
    \n
    \n\n
    If possible, please use snake_case for keys in config.\nYou may want to list linked files additionally under attachments to include them when packaging a resource.\n(Packaging a resource means downloading/copying important linked files and creating a ZIP archive that contains\nan altered rdf.yaml file with local references to the downloaded files.)
    \n", "annotation": ": Annotated[Dict[str, YamlValue], FieldInfo(annotation=NoneType, required=True, examples=[{'bioimageio': {'my_custom_key': 3837283, 'another_key': {'nested': 'value'}}, 'imagej': {'macro_dir': 'path/to/macro/file'}}])]"}, "bioimageio.spec.generic.v0_3.GenericModelDescrBase.git_repo": {"fullname": "bioimageio.spec.generic.v0_3.GenericModelDescrBase.git_repo", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "GenericModelDescrBase.git_repo", "kind": "variable", "doc": "
    A URL to the Git repository where the resource is being developed.
    \n", "annotation": ": Annotated[Optional[bioimageio.spec._internal.url.HttpUrl], FieldInfo(annotation=NoneType, required=True, examples=['https://github.com/bioimage-io/spec-bioimage-io/tree/main/example_descriptions/models/unet2d_nuclei_broad'])]"}, "bioimageio.spec.generic.v0_3.GenericModelDescrBase.icon": {"fullname": "bioimageio.spec.generic.v0_3.GenericModelDescrBase.icon", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "GenericModelDescrBase.icon", "kind": "variable", "doc": "
    An icon for illustration, e.g. on bioimage.io
    \n", "annotation": ": Union[Annotated[Union[Annotated[pathlib.Path, PathType(path_type='file')], bioimageio.spec._internal.io.RelativeFilePath, bioimageio.spec._internal.url.HttpUrl, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator(func=<function wo_special_file_name at 0x7afca0d90540>), PlainSerializer(func=<function _package at 0x7afca0d91760>, return_type=PydanticUndefined, when_used='unless-none')], Annotated[str, Len(min_length=1, max_length=2)], NoneType]"}, "bioimageio.spec.generic.v0_3.GenericModelDescrBase.links": {"fullname": "bioimageio.spec.generic.v0_3.GenericModelDescrBase.links", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "GenericModelDescrBase.links", "kind": "variable", "doc": "
    IDs of other bioimage.io resources
    \n", "annotation": ": Annotated[List[str], FieldInfo(annotation=NoneType, required=True, examples=[('ilastik/ilastik', 'deepimagej/deepimagej', 'zero/notebook_u-net_3d_zerocostdl4mic')])]"}, "bioimageio.spec.generic.v0_3.GenericModelDescrBase.uploader": {"fullname": "bioimageio.spec.generic.v0_3.GenericModelDescrBase.uploader", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "GenericModelDescrBase.uploader", "kind": "variable", "doc": "
    The person who uploaded the model (e.g. to bioimage.io)
    \n", "annotation": ": Optional[bioimageio.spec.generic.v0_2.Uploader]"}, "bioimageio.spec.generic.v0_3.GenericModelDescrBase.maintainers": {"fullname": "bioimageio.spec.generic.v0_3.GenericModelDescrBase.maintainers", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "GenericModelDescrBase.maintainers", "kind": "variable", "doc": "
    Maintainers of this resource.\nIf not specified, authors are maintainers and at least some of them has to specify their github_user name
    \n", "annotation": ": List[bioimageio.spec.generic.v0_3.Maintainer]"}, "bioimageio.spec.generic.v0_3.GenericModelDescrBase.check_maintainers_exist": {"fullname": "bioimageio.spec.generic.v0_3.GenericModelDescrBase.check_maintainers_exist", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "GenericModelDescrBase.check_maintainers_exist", "kind": "function", "doc": "
    \n", "signature": "(value: Any, info: pydantic_core.core_schema.ValidationInfo) -> Any:", "funcdef": "def"}, "bioimageio.spec.generic.v0_3.GenericModelDescrBase.tags": {"fullname": "bioimageio.spec.generic.v0_3.GenericModelDescrBase.tags", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "GenericModelDescrBase.tags", "kind": "variable", "doc": "
    Associated tags
    \n", "annotation": ": Annotated[List[str], FieldInfo(annotation=NoneType, required=True, examples=[('unet2d', 'pytorch', 'nucleus', 'segmentation', 'dsb2018')])]"}, "bioimageio.spec.generic.v0_3.GenericModelDescrBase.warn_about_tag_categories": {"fullname": "bioimageio.spec.generic.v0_3.GenericModelDescrBase.warn_about_tag_categories", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "GenericModelDescrBase.warn_about_tag_categories", "kind": "function", "doc": "
    \n", "signature": "(value: Any, info: pydantic_core.core_schema.ValidationInfo) -> Any:", "funcdef": "def"}, "bioimageio.spec.generic.v0_3.GenericModelDescrBase.version": {"fullname": "bioimageio.spec.generic.v0_3.GenericModelDescrBase.version", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "GenericModelDescrBase.version", "kind": "variable", "doc": "
    The version of the resource following SemVer 2.0.
    \n", "annotation": ": Optional[bioimageio.spec._internal.version_type.Version]"}, "bioimageio.spec.generic.v0_3.GenericModelDescrBase.version_number": {"fullname": "bioimageio.spec.generic.v0_3.GenericModelDescrBase.version_number", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "GenericModelDescrBase.version_number", "kind": "variable", "doc": "
    version number (n-th published version, not the semantic version)
    \n", "annotation": ": Optional[int]"}, "bioimageio.spec.generic.v0_3.GenericModelDescrBase.model_config": {"fullname": "bioimageio.spec.generic.v0_3.GenericModelDescrBase.model_config", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "GenericModelDescrBase.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.generic.v0_3.GenericModelDescrBase.model_fields": {"fullname": "bioimageio.spec.generic.v0_3.GenericModelDescrBase.model_fields", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "GenericModelDescrBase.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'name': FieldInfo(annotation=str, required=True, metadata=[MinLen(min_length=1), MaxLen(max_length=128)]), 'description': FieldInfo(annotation=str, required=True, metadata=[MaxLen(max_length=1024), AfterWarner(func=<function as_warning.<locals>.wrapper>, severity=30, msg='Description longer than 512 characters.', context={'typ': typing.Annotated[typing.Any, MaxLen(max_length=512)]})]), 'covers': FieldInfo(annotation=List[Annotated[Union[HttpUrl, Annotated[Path, PathType, Predicate], RelativeFilePath], WithSuffix, PlainSerializer]], required=False, default_factory=list, description="Cover images. Please use an image smaller than 500KB and an aspect ratio width to height of 2:1 or 1:1.\\nThe supported image formats are: ('.gif', '.jpeg', '.jpg', '.png', '.svg')", examples=[]), 'id_emoji': FieldInfo(annotation=Union[Annotated[str, Len], NoneType], required=False), 'authors': FieldInfo(annotation=List[Author], required=True, metadata=[MinLen(min_length=1)]), 'attachments': FieldInfo(annotation=List[FileDescr], required=False, default_factory=list), 'cite': FieldInfo(annotation=List[CiteEntry], required=True, metadata=[MinLen(min_length=1)]), 'license': FieldInfo(annotation=Union[LicenseId, DeprecatedLicenseId], required=True, examples=['CC-BY-4.0', 'MIT', 'BSD-2-Clause'], metadata=[AfterWarner(func=<function as_warning.<locals>.wrapper>, severity=30, msg='{value} is deprecated, see https://spdx.org/licenses/{value}.html', context={'typ': <class 'bioimageio.spec._internal.license_id.LicenseId'>})]), 'config': FieldInfo(annotation=Dict[str, YamlValue], required=False, default_factory=dict, examples=[{'bioimageio': {'my_custom_key': 3837283, 'another_key': {'nested': 'value'}}, 'imagej': {'macro_dir': 'path/to/macro/file'}}]), 'git_repo': FieldInfo(annotation=Union[HttpUrl, NoneType], required=False, examples=['https://github.com/bioimage-io/spec-bioimage-io/tree/main/example_descriptions/models/unet2d_nuclei_broad']), 'icon': FieldInfo(annotation=Union[Annotated[Union[Annotated[Path, PathType], RelativeFilePath, HttpUrl, Annotated[Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator, PlainSerializer], Annotated[str, Len], NoneType], required=False), 'links': FieldInfo(annotation=List[str], required=False, default_factory=list, examples=[('ilastik/ilastik', 'deepimagej/deepimagej', 'zero/notebook_u-net_3d_zerocostdl4mic')]), 'uploader': FieldInfo(annotation=Union[Uploader, NoneType], required=False), 'maintainers': FieldInfo(annotation=List[Maintainer], required=False, default_factory=list), 'tags': FieldInfo(annotation=List[str], required=False, default_factory=list, examples=[('unet2d', 'pytorch', 'nucleus', 'segmentation', 'dsb2018')]), 'version': FieldInfo(annotation=Union[Version, NoneType], required=False), 'version_number': FieldInfo(annotation=Union[int, NoneType], required=False)}"}, "bioimageio.spec.generic.v0_3.GenericModelDescrBase.model_computed_fields": {"fullname": "bioimageio.spec.generic.v0_3.GenericModelDescrBase.model_computed_fields", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "GenericModelDescrBase.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.generic.v0_3.GenericDescrBase": {"fullname": "bioimageio.spec.generic.v0_3.GenericDescrBase", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "GenericDescrBase", "kind": "class", "doc": "
    Base for all resource descriptions except for the model descriptions
    \n", "bases": "GenericModelDescrBase"}, "bioimageio.spec.generic.v0_3.GenericDescrBase.format_version": {"fullname": "bioimageio.spec.generic.v0_3.GenericDescrBase.format_version", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "GenericDescrBase.format_version", "kind": "variable", "doc": "
    The format version of this resource specification
    \n", "annotation": ": Literal['0.3.0']"}, "bioimageio.spec.generic.v0_3.GenericDescrBase.documentation": {"fullname": "bioimageio.spec.generic.v0_3.GenericDescrBase.documentation", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "GenericDescrBase.documentation", "kind": "variable", "doc": "
    \u2208\ud83d\udce6 URL or relative path to a markdown file with additional documentation.\nThe recommended documentation file name is README.md. An .md suffix is mandatory.
    \n", "annotation": ": Annotated[Optional[Annotated[Union[Annotated[pathlib.Path, PathType(path_type='file'), Predicate(func=<function PurePath.is_absolute at 0x7afca4145940>)], bioimageio.spec._internal.io.RelativeFilePath, bioimageio.spec._internal.url.HttpUrl], AfterValidator(func=<function _validate_md_suffix at 0x7afca0c06ca0>), PlainSerializer(func=<function _package at 0x7afca0d91760>, return_type=PydanticUndefined, when_used='unless-none')]], FieldInfo(annotation=NoneType, required=True, examples=['https://raw.githubusercontent.com/bioimage-io/spec-bioimage-io/main/example_descriptions/models/unet2d_nuclei_broad/README.md', 'README.md'])]"}, "bioimageio.spec.generic.v0_3.GenericDescrBase.badges": {"fullname": "bioimageio.spec.generic.v0_3.GenericDescrBase.badges", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "GenericDescrBase.badges", "kind": "variable", "doc": "
    badges associated with this resource
    \n", "annotation": ": List[bioimageio.spec.generic.v0_2.BadgeDescr]"}, "bioimageio.spec.generic.v0_3.GenericDescrBase.implemented_format_version": {"fullname": "bioimageio.spec.generic.v0_3.GenericDescrBase.implemented_format_version", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "GenericDescrBase.implemented_format_version", "kind": "variable", "doc": "
    \n", "annotation": ": ClassVar[str]", "default_value": "'0.3.0'"}, "bioimageio.spec.generic.v0_3.GenericDescrBase.implemented_format_version_tuple": {"fullname": "bioimageio.spec.generic.v0_3.GenericDescrBase.implemented_format_version_tuple", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "GenericDescrBase.implemented_format_version_tuple", "kind": "variable", "doc": "
    \n", "annotation": ": ClassVar[Tuple[int, int, int]]", "default_value": "(0, 3, 0)"}, "bioimageio.spec.generic.v0_3.GenericDescrBase.model_config": {"fullname": "bioimageio.spec.generic.v0_3.GenericDescrBase.model_config", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "GenericDescrBase.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.generic.v0_3.GenericDescrBase.model_fields": {"fullname": "bioimageio.spec.generic.v0_3.GenericDescrBase.model_fields", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "GenericDescrBase.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'name': FieldInfo(annotation=str, required=True, metadata=[MinLen(min_length=1), MaxLen(max_length=128)]), 'description': FieldInfo(annotation=str, required=True, metadata=[MaxLen(max_length=1024), AfterWarner(func=<function as_warning.<locals>.wrapper>, severity=30, msg='Description longer than 512 characters.', context={'typ': typing.Annotated[typing.Any, MaxLen(max_length=512)]})]), 'covers': FieldInfo(annotation=List[Annotated[Union[HttpUrl, Annotated[Path, PathType, Predicate], RelativeFilePath], WithSuffix, PlainSerializer]], required=False, default_factory=list, description="Cover images. Please use an image smaller than 500KB and an aspect ratio width to height of 2:1 or 1:1.\\nThe supported image formats are: ('.gif', '.jpeg', '.jpg', '.png', '.svg')", examples=[]), 'id_emoji': FieldInfo(annotation=Union[Annotated[str, Len], NoneType], required=False), 'authors': FieldInfo(annotation=List[Author], required=True, metadata=[MinLen(min_length=1)]), 'attachments': FieldInfo(annotation=List[FileDescr], required=False, default_factory=list), 'cite': FieldInfo(annotation=List[CiteEntry], required=True, metadata=[MinLen(min_length=1)]), 'license': FieldInfo(annotation=Union[LicenseId, DeprecatedLicenseId], required=True, examples=['CC-BY-4.0', 'MIT', 'BSD-2-Clause'], metadata=[AfterWarner(func=<function as_warning.<locals>.wrapper>, severity=30, msg='{value} is deprecated, see https://spdx.org/licenses/{value}.html', context={'typ': <class 'bioimageio.spec._internal.license_id.LicenseId'>})]), 'config': FieldInfo(annotation=Dict[str, YamlValue], required=False, default_factory=dict, examples=[{'bioimageio': {'my_custom_key': 3837283, 'another_key': {'nested': 'value'}}, 'imagej': {'macro_dir': 'path/to/macro/file'}}]), 'git_repo': FieldInfo(annotation=Union[HttpUrl, NoneType], required=False, examples=['https://github.com/bioimage-io/spec-bioimage-io/tree/main/example_descriptions/models/unet2d_nuclei_broad']), 'icon': FieldInfo(annotation=Union[Annotated[Union[Annotated[Path, PathType], RelativeFilePath, HttpUrl, Annotated[Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator, PlainSerializer], Annotated[str, Len], NoneType], required=False), 'links': FieldInfo(annotation=List[str], required=False, default_factory=list, examples=[('ilastik/ilastik', 'deepimagej/deepimagej', 'zero/notebook_u-net_3d_zerocostdl4mic')]), 'uploader': FieldInfo(annotation=Union[Uploader, NoneType], required=False), 'maintainers': FieldInfo(annotation=List[Maintainer], required=False, default_factory=list), 'tags': FieldInfo(annotation=List[str], required=False, default_factory=list, examples=[('unet2d', 'pytorch', 'nucleus', 'segmentation', 'dsb2018')]), 'version': FieldInfo(annotation=Union[Version, NoneType], required=False), 'version_number': FieldInfo(annotation=Union[int, NoneType], required=False), 'format_version': FieldInfo(annotation=Literal['0.3.0'], required=False, default='0.3.0'), 'documentation': FieldInfo(annotation=Union[Annotated[Union[Annotated[Path, PathType, Predicate], RelativeFilePath, HttpUrl], AfterValidator, PlainSerializer], NoneType], required=False, examples=['https://raw.githubusercontent.com/bioimage-io/spec-bioimage-io/main/example_descriptions/models/unet2d_nuclei_broad/README.md', 'README.md']), 'badges': FieldInfo(annotation=List[BadgeDescr], required=False, default_factory=list)}"}, "bioimageio.spec.generic.v0_3.GenericDescrBase.model_computed_fields": {"fullname": "bioimageio.spec.generic.v0_3.GenericDescrBase.model_computed_fields", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "GenericDescrBase.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.generic.v0_3.GenericDescr": {"fullname": "bioimageio.spec.generic.v0_3.GenericDescr", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "GenericDescr", "kind": "class", "doc": "
    Specification of the fields used in a generic bioimage.io-compliant resource description file (RDF).
    \n\n
    An RDF is a YAML file that describes a resource such as a model, a dataset, or a notebook.\nNote that those resources are described with a type-specific RDF.\nUse this generic resource description, if none of the known specific types matches your resource.
    \n", "bases": "GenericDescrBase"}, "bioimageio.spec.generic.v0_3.GenericDescr.type": {"fullname": "bioimageio.spec.generic.v0_3.GenericDescr.type", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "GenericDescr.type", "kind": "variable", "doc": "
    The resource type assigns a broad category to the resource.
    \n", "annotation": ": Annotated[str, Annotated[~_StrType, Predicate(func=<method 'islower' of 'str' objects>)]]"}, "bioimageio.spec.generic.v0_3.GenericDescr.id": {"fullname": "bioimageio.spec.generic.v0_3.GenericDescr.id", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "GenericDescr.id", "kind": "variable", "doc": "
    Model zoo (bioimage.io) wide, unique identifier (assigned by bioimage.io)
    \n", "annotation": ": Optional[bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]]]"}, "bioimageio.spec.generic.v0_3.GenericDescr.parent": {"fullname": "bioimageio.spec.generic.v0_3.GenericDescr.parent", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "GenericDescr.parent", "kind": "variable", "doc": "
    The description from which this one is derived
    \n", "annotation": ": Optional[bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]]]"}, "bioimageio.spec.generic.v0_3.GenericDescr.source": {"fullname": "bioimageio.spec.generic.v0_3.GenericDescr.source", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "GenericDescr.source", "kind": "variable", "doc": "
    The primary source of the resource
    \n", "annotation": ": Optional[bioimageio.spec._internal.url.HttpUrl]"}, "bioimageio.spec.generic.v0_3.GenericDescr.check_specific_types": {"fullname": "bioimageio.spec.generic.v0_3.GenericDescr.check_specific_types", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "GenericDescr.check_specific_types", "kind": "function", "doc": "
    \n", "signature": "(cls, value: str) -> str:", "funcdef": "def"}, "bioimageio.spec.generic.v0_3.GenericDescr.implemented_format_version": {"fullname": "bioimageio.spec.generic.v0_3.GenericDescr.implemented_format_version", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "GenericDescr.implemented_format_version", "kind": "variable", "doc": "
    \n", "annotation": ": ClassVar[str]", "default_value": "'0.3.0'"}, "bioimageio.spec.generic.v0_3.GenericDescr.implemented_format_version_tuple": {"fullname": "bioimageio.spec.generic.v0_3.GenericDescr.implemented_format_version_tuple", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "GenericDescr.implemented_format_version_tuple", "kind": "variable", "doc": "
    \n", "annotation": ": ClassVar[Tuple[int, int, int]]", "default_value": "(0, 3, 0)"}, "bioimageio.spec.generic.v0_3.GenericDescr.model_config": {"fullname": "bioimageio.spec.generic.v0_3.GenericDescr.model_config", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "GenericDescr.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'ignore', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True, 'title': 'bioimage.io generic specification'}"}, "bioimageio.spec.generic.v0_3.GenericDescr.model_fields": {"fullname": "bioimageio.spec.generic.v0_3.GenericDescr.model_fields", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "GenericDescr.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'name': FieldInfo(annotation=str, required=True, metadata=[MinLen(min_length=1), MaxLen(max_length=128)]), 'description': FieldInfo(annotation=str, required=True, metadata=[MaxLen(max_length=1024), AfterWarner(func=<function as_warning.<locals>.wrapper>, severity=30, msg='Description longer than 512 characters.', context={'typ': typing.Annotated[typing.Any, MaxLen(max_length=512)]})]), 'covers': FieldInfo(annotation=List[Annotated[Union[HttpUrl, Annotated[Path, PathType, Predicate], RelativeFilePath], WithSuffix, PlainSerializer]], required=False, default_factory=list, description="Cover images. Please use an image smaller than 500KB and an aspect ratio width to height of 2:1 or 1:1.\\nThe supported image formats are: ('.gif', '.jpeg', '.jpg', '.png', '.svg')", examples=[]), 'id_emoji': FieldInfo(annotation=Union[Annotated[str, Len], NoneType], required=False), 'authors': FieldInfo(annotation=List[Author], required=True, metadata=[MinLen(min_length=1)]), 'attachments': FieldInfo(annotation=List[FileDescr], required=False, default_factory=list), 'cite': FieldInfo(annotation=List[CiteEntry], required=True, metadata=[MinLen(min_length=1)]), 'license': FieldInfo(annotation=Union[LicenseId, DeprecatedLicenseId], required=True, examples=['CC-BY-4.0', 'MIT', 'BSD-2-Clause'], metadata=[AfterWarner(func=<function as_warning.<locals>.wrapper>, severity=30, msg='{value} is deprecated, see https://spdx.org/licenses/{value}.html', context={'typ': <class 'bioimageio.spec._internal.license_id.LicenseId'>})]), 'config': FieldInfo(annotation=Dict[str, YamlValue], required=False, default_factory=dict, examples=[{'bioimageio': {'my_custom_key': 3837283, 'another_key': {'nested': 'value'}}, 'imagej': {'macro_dir': 'path/to/macro/file'}}]), 'git_repo': FieldInfo(annotation=Union[HttpUrl, NoneType], required=False, examples=['https://github.com/bioimage-io/spec-bioimage-io/tree/main/example_descriptions/models/unet2d_nuclei_broad']), 'icon': FieldInfo(annotation=Union[Annotated[Union[Annotated[Path, PathType], RelativeFilePath, HttpUrl, Annotated[Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator, PlainSerializer], Annotated[str, Len], NoneType], required=False), 'links': FieldInfo(annotation=List[str], required=False, default_factory=list, examples=[('ilastik/ilastik', 'deepimagej/deepimagej', 'zero/notebook_u-net_3d_zerocostdl4mic')]), 'uploader': FieldInfo(annotation=Union[Uploader, NoneType], required=False), 'maintainers': FieldInfo(annotation=List[Maintainer], required=False, default_factory=list), 'tags': FieldInfo(annotation=List[str], required=False, default_factory=list, examples=[('unet2d', 'pytorch', 'nucleus', 'segmentation', 'dsb2018')]), 'version': FieldInfo(annotation=Union[Version, NoneType], required=False), 'version_number': FieldInfo(annotation=Union[int, NoneType], required=False), 'format_version': FieldInfo(annotation=Literal['0.3.0'], required=False, default='0.3.0'), 'documentation': FieldInfo(annotation=Union[Annotated[Union[Annotated[Path, PathType, Predicate], RelativeFilePath, HttpUrl], AfterValidator, PlainSerializer], NoneType], required=False, examples=['https://raw.githubusercontent.com/bioimage-io/spec-bioimage-io/main/example_descriptions/models/unet2d_nuclei_broad/README.md', 'README.md']), 'badges': FieldInfo(annotation=List[BadgeDescr], required=False, default_factory=list), 'type': FieldInfo(annotation=str, required=False, default='generic', frozen=True, metadata=[typing.Annotated[~_StrType, Predicate(func=<method 'islower' of 'str' objects>)]]), 'id': FieldInfo(annotation=Union[ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]], NoneType], required=False), 'parent': FieldInfo(annotation=Union[ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]], NoneType], required=False), 'source': FieldInfo(annotation=Union[HttpUrl, NoneType], required=False)}"}, "bioimageio.spec.generic.v0_3.GenericDescr.model_computed_fields": {"fullname": "bioimageio.spec.generic.v0_3.GenericDescr.model_computed_fields", "modulename": "bioimageio.spec.generic.v0_3", "qualname": "GenericDescr.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model": {"fullname": "bioimageio.spec.model", "modulename": "bioimageio.spec.model", "kind": "module", "doc": "
    implementaions of all released minor versions are available in submodules:
    \n\n\n"}, "bioimageio.spec.model.AnyModelDescr": {"fullname": "bioimageio.spec.model.AnyModelDescr", "modulename": "bioimageio.spec.model", "qualname": "AnyModelDescr", "kind": "variable", "doc": "
    Union of any released model desription
    \n", "default_value": "typing.Annotated[typing.Union[bioimageio.spec.model.v0_4.ModelDescr, bioimageio.spec.model.v0_5.ModelDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)]"}, "bioimageio.spec.model.v0_4": {"fullname": "bioimageio.spec.model.v0_4", "modulename": "bioimageio.spec.model.v0_4", "kind": "module", "doc": "
    \n"}, "bioimageio.spec.model.v0_4.AxesStr": {"fullname": "bioimageio.spec.model.v0_4.AxesStr", "modulename": "bioimageio.spec.model.v0_4", "qualname": "AxesStr", "kind": "variable", "doc": "
    \n", "default_value": "typing.Annotated[str, RestrictCharacters(alphabet='bitczyx'), AfterValidator(func=<function validate_unique_entries>)]"}, "bioimageio.spec.model.v0_4.AxesInCZYX": {"fullname": "bioimageio.spec.model.v0_4.AxesInCZYX", "modulename": "bioimageio.spec.model.v0_4", "qualname": "AxesInCZYX", "kind": "variable", "doc": "
    \n", "default_value": "typing.Annotated[str, RestrictCharacters(alphabet='czyx'), AfterValidator(func=<function validate_unique_entries>)]"}, "bioimageio.spec.model.v0_4.PostprocessingName": {"fullname": "bioimageio.spec.model.v0_4.PostprocessingName", "modulename": "bioimageio.spec.model.v0_4", "qualname": "PostprocessingName", "kind": "variable", "doc": "
    \n", "default_value": "typing.Literal['binarize', 'clip', 'scale_linear', 'sigmoid', 'zero_mean_unit_variance', 'scale_range', 'scale_mean_variance']"}, "bioimageio.spec.model.v0_4.PreprocessingName": {"fullname": "bioimageio.spec.model.v0_4.PreprocessingName", "modulename": "bioimageio.spec.model.v0_4", "qualname": "PreprocessingName", "kind": "variable", "doc": "
    \n", "default_value": "typing.Literal['binarize', 'clip', 'scale_linear', 'sigmoid', 'zero_mean_unit_variance', 'scale_range']"}, "bioimageio.spec.model.v0_4.TensorName": {"fullname": "bioimageio.spec.model.v0_4.TensorName", "modulename": "bioimageio.spec.model.v0_4", "qualname": "TensorName", "kind": "variable", "doc": "
    \n", "default_value": "<class 'bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate]]]'>"}, "bioimageio.spec.model.v0_4.CallableFromDepencency": {"fullname": "bioimageio.spec.model.v0_4.CallableFromDepencency", "modulename": "bioimageio.spec.model.v0_4", "qualname": "CallableFromDepencency", "kind": "class", "doc": "
    deprecated! don't use for new spec fields!
    \n", "bases": "bioimageio.spec._internal.common_nodes.StringNode"}, "bioimageio.spec.model.v0_4.CallableFromDepencency.module_name": {"fullname": "bioimageio.spec.model.v0_4.CallableFromDepencency.module_name", "modulename": "bioimageio.spec.model.v0_4", "qualname": "CallableFromDepencency.module_name", "kind": "variable", "doc": "
    \n", "annotation": ": str"}, "bioimageio.spec.model.v0_4.CallableFromDepencency.check_submodules": {"fullname": "bioimageio.spec.model.v0_4.CallableFromDepencency.check_submodules", "modulename": "bioimageio.spec.model.v0_4", "qualname": "CallableFromDepencency.check_submodules", "kind": "function", "doc": "
    \n", "signature": "(cls, module_name: str) -> str:", "funcdef": "def"}, "bioimageio.spec.model.v0_4.CallableFromDepencency.callable_name": {"fullname": "bioimageio.spec.model.v0_4.CallableFromDepencency.callable_name", "modulename": "bioimageio.spec.model.v0_4", "qualname": "CallableFromDepencency.callable_name", "kind": "variable", "doc": "
    \n", "annotation": ": bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator]]"}, "bioimageio.spec.model.v0_4.CallableFromFile": {"fullname": "bioimageio.spec.model.v0_4.CallableFromFile", "modulename": "bioimageio.spec.model.v0_4", "qualname": "CallableFromFile", "kind": "class", "doc": "
    deprecated! don't use for new spec fields!
    \n", "bases": "bioimageio.spec._internal.common_nodes.StringNode"}, "bioimageio.spec.model.v0_4.CallableFromFile.source_file": {"fullname": "bioimageio.spec.model.v0_4.CallableFromFile.source_file", "modulename": "bioimageio.spec.model.v0_4", "qualname": "CallableFromFile.source_file", "kind": "variable", "doc": "
    \u2208\ud83d\udce6 Python module that implements callable_name
    \n", "annotation": ": Annotated[Union[bioimageio.spec._internal.url.HttpUrl, bioimageio.spec._internal.io.RelativeFilePath], PlainSerializer(func=<function _package at 0x7afca0d91760>, return_type=PydanticUndefined, when_used='unless-none')]"}, "bioimageio.spec.model.v0_4.CallableFromFile.callable_name": {"fullname": "bioimageio.spec.model.v0_4.CallableFromFile.callable_name", "modulename": "bioimageio.spec.model.v0_4", "qualname": "CallableFromFile.callable_name", "kind": "variable", "doc": "
    The Python identifier of
    \n", "annotation": ": bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator]]"}, "bioimageio.spec.model.v0_4.CustomCallable": {"fullname": "bioimageio.spec.model.v0_4.CustomCallable", "modulename": "bioimageio.spec.model.v0_4", "qualname": "CustomCallable", "kind": "variable", "doc": "
    \n", "default_value": "typing.Union[bioimageio.spec.model.v0_4.CallableFromFile, bioimageio.spec.model.v0_4.CallableFromDepencency]"}, "bioimageio.spec.model.v0_4.Dependencies": {"fullname": "bioimageio.spec.model.v0_4.Dependencies", "modulename": "bioimageio.spec.model.v0_4", "qualname": "Dependencies", "kind": "class", "doc": "
    deprecated! don't use for new spec fields!
    \n", "bases": "bioimageio.spec._internal.common_nodes.StringNode"}, "bioimageio.spec.model.v0_4.Dependencies.manager": {"fullname": "bioimageio.spec.model.v0_4.Dependencies.manager", "modulename": "bioimageio.spec.model.v0_4", "qualname": "Dependencies.manager", "kind": "variable", "doc": "
    Dependency manager
    \n", "annotation": ": Annotated[str, MinLen(min_length=1), FieldInfo(annotation=NoneType, required=True, examples=['conda', 'maven', 'pip'])]"}, "bioimageio.spec.model.v0_4.Dependencies.file": {"fullname": "bioimageio.spec.model.v0_4.Dependencies.file", "modulename": "bioimageio.spec.model.v0_4", "qualname": "Dependencies.file", "kind": "variable", "doc": "
    \u2208\ud83d\udce6 Dependency file
    \n", "annotation": ": Annotated[Union[Annotated[pathlib.Path, PathType(path_type='file')], bioimageio.spec._internal.io.RelativeFilePath, bioimageio.spec._internal.url.HttpUrl, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator(func=<function wo_special_file_name at 0x7afca0d90540>), PlainSerializer(func=<function _package at 0x7afca0d91760>, return_type=PydanticUndefined, when_used='unless-none'), FieldInfo(annotation=NoneType, required=True, examples=['environment.yaml', 'pom.xml', 'requirements.txt'])]"}, "bioimageio.spec.model.v0_4.WeightsFormat": {"fullname": "bioimageio.spec.model.v0_4.WeightsFormat", "modulename": "bioimageio.spec.model.v0_4", "qualname": "WeightsFormat", "kind": "variable", "doc": "
    \n", "default_value": "typing.Literal['keras_hdf5', 'onnx', 'pytorch_state_dict', 'tensorflow_js', 'tensorflow_saved_model_bundle', 'torchscript']"}, "bioimageio.spec.model.v0_4.WeightsDescr": {"fullname": "bioimageio.spec.model.v0_4.WeightsDescr", "modulename": "bioimageio.spec.model.v0_4", "qualname": "WeightsDescr", "kind": "class", "doc": "
    Subpart of a resource description
    \n", "bases": "bioimageio.spec._internal.node.Node"}, "bioimageio.spec.model.v0_4.WeightsDescr.keras_hdf5": {"fullname": "bioimageio.spec.model.v0_4.WeightsDescr.keras_hdf5", "modulename": "bioimageio.spec.model.v0_4", "qualname": "WeightsDescr.keras_hdf5", "kind": "variable", "doc": "
    \n", "annotation": ": Optional[bioimageio.spec.model.v0_4.KerasHdf5WeightsDescr]"}, "bioimageio.spec.model.v0_4.WeightsDescr.onnx": {"fullname": "bioimageio.spec.model.v0_4.WeightsDescr.onnx", "modulename": "bioimageio.spec.model.v0_4", "qualname": "WeightsDescr.onnx", "kind": "variable", "doc": "
    \n", "annotation": ": Optional[bioimageio.spec.model.v0_4.OnnxWeightsDescr]"}, "bioimageio.spec.model.v0_4.WeightsDescr.pytorch_state_dict": {"fullname": "bioimageio.spec.model.v0_4.WeightsDescr.pytorch_state_dict", "modulename": "bioimageio.spec.model.v0_4", "qualname": "WeightsDescr.pytorch_state_dict", "kind": "variable", "doc": "
    \n", "annotation": ": Optional[bioimageio.spec.model.v0_4.PytorchStateDictWeightsDescr]"}, "bioimageio.spec.model.v0_4.WeightsDescr.tensorflow_js": {"fullname": "bioimageio.spec.model.v0_4.WeightsDescr.tensorflow_js", "modulename": "bioimageio.spec.model.v0_4", "qualname": "WeightsDescr.tensorflow_js", "kind": "variable", "doc": "
    \n", "annotation": ": Optional[bioimageio.spec.model.v0_4.TensorflowJsWeightsDescr]"}, "bioimageio.spec.model.v0_4.WeightsDescr.tensorflow_saved_model_bundle": {"fullname": "bioimageio.spec.model.v0_4.WeightsDescr.tensorflow_saved_model_bundle", "modulename": "bioimageio.spec.model.v0_4", "qualname": "WeightsDescr.tensorflow_saved_model_bundle", "kind": "variable", "doc": "
    \n", "annotation": ": Optional[bioimageio.spec.model.v0_4.TensorflowSavedModelBundleWeightsDescr]"}, "bioimageio.spec.model.v0_4.WeightsDescr.torchscript": {"fullname": "bioimageio.spec.model.v0_4.WeightsDescr.torchscript", "modulename": "bioimageio.spec.model.v0_4", "qualname": "WeightsDescr.torchscript", "kind": "variable", "doc": "
    \n", "annotation": ": Optional[bioimageio.spec.model.v0_4.TorchscriptWeightsDescr]"}, "bioimageio.spec.model.v0_4.WeightsDescr.check_one_entry": {"fullname": "bioimageio.spec.model.v0_4.WeightsDescr.check_one_entry", "modulename": "bioimageio.spec.model.v0_4", "qualname": "WeightsDescr.check_one_entry", "kind": "function", "doc": "
    \n", "signature": "(self) -> Self:", "funcdef": "def"}, "bioimageio.spec.model.v0_4.WeightsDescr.model_config": {"fullname": "bioimageio.spec.model.v0_4.WeightsDescr.model_config", "modulename": "bioimageio.spec.model.v0_4", "qualname": "WeightsDescr.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_4.WeightsDescr.model_fields": {"fullname": "bioimageio.spec.model.v0_4.WeightsDescr.model_fields", "modulename": "bioimageio.spec.model.v0_4", "qualname": "WeightsDescr.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'keras_hdf5': FieldInfo(annotation=Union[KerasHdf5WeightsDescr, NoneType], required=False), 'onnx': FieldInfo(annotation=Union[OnnxWeightsDescr, NoneType], required=False), 'pytorch_state_dict': FieldInfo(annotation=Union[PytorchStateDictWeightsDescr, NoneType], required=False), 'tensorflow_js': FieldInfo(annotation=Union[TensorflowJsWeightsDescr, NoneType], required=False), 'tensorflow_saved_model_bundle': FieldInfo(annotation=Union[TensorflowSavedModelBundleWeightsDescr, NoneType], required=False), 'torchscript': FieldInfo(annotation=Union[TorchscriptWeightsDescr, NoneType], required=False)}"}, "bioimageio.spec.model.v0_4.WeightsDescr.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_4.WeightsDescr.model_computed_fields", "modulename": "bioimageio.spec.model.v0_4", "qualname": "WeightsDescr.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_4.WeightsEntryDescrBase": {"fullname": "bioimageio.spec.model.v0_4.WeightsEntryDescrBase", "modulename": "bioimageio.spec.model.v0_4", "qualname": "WeightsEntryDescrBase", "kind": "class", "doc": "
    Subpart of a resource description
    \n", "bases": "bioimageio.spec._internal.io.FileDescr"}, "bioimageio.spec.model.v0_4.WeightsEntryDescrBase.type": {"fullname": "bioimageio.spec.model.v0_4.WeightsEntryDescrBase.type", "modulename": "bioimageio.spec.model.v0_4", "qualname": "WeightsEntryDescrBase.type", "kind": "variable", "doc": "
    \n", "annotation": ": ClassVar[Literal['keras_hdf5', 'onnx', 'pytorch_state_dict', 'tensorflow_js', 'tensorflow_saved_model_bundle', 'torchscript']]"}, "bioimageio.spec.model.v0_4.WeightsEntryDescrBase.weights_format_name": {"fullname": "bioimageio.spec.model.v0_4.WeightsEntryDescrBase.weights_format_name", "modulename": "bioimageio.spec.model.v0_4", "qualname": "WeightsEntryDescrBase.weights_format_name", "kind": "variable", "doc": "
    \n", "annotation": ": ClassVar[str]"}, "bioimageio.spec.model.v0_4.WeightsEntryDescrBase.source": {"fullname": "bioimageio.spec.model.v0_4.WeightsEntryDescrBase.source", "modulename": "bioimageio.spec.model.v0_4", "qualname": "WeightsEntryDescrBase.source", "kind": "variable", "doc": "
    \u2208\ud83d\udce6 The weights file.
    \n", "annotation": ": Annotated[Union[Annotated[pathlib.Path, PathType(path_type='file')], bioimageio.spec._internal.io.RelativeFilePath, bioimageio.spec._internal.url.HttpUrl, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator(func=<function wo_special_file_name at 0x7afca0d90540>), PlainSerializer(func=<function _package at 0x7afca0d91760>, return_type=PydanticUndefined, when_used='unless-none')]"}, "bioimageio.spec.model.v0_4.WeightsEntryDescrBase.attachments": {"fullname": "bioimageio.spec.model.v0_4.WeightsEntryDescrBase.attachments", "modulename": "bioimageio.spec.model.v0_4", "qualname": "WeightsEntryDescrBase.attachments", "kind": "variable", "doc": "
    Attachments that are specific to this weights entry.
    \n", "annotation": ": Annotated[Optional[bioimageio.spec.generic.v0_2.AttachmentsDescr], AfterWarner(func=<function as_warning.<locals>.wrapper at 0x7afc91ef1b20>, severity=35, msg='Weights entry depends on additional attachments.', context={'typ': None})]"}, "bioimageio.spec.model.v0_4.WeightsEntryDescrBase.authors": {"fullname": "bioimageio.spec.model.v0_4.WeightsEntryDescrBase.authors", "modulename": "bioimageio.spec.model.v0_4", "qualname": "WeightsEntryDescrBase.authors", "kind": "variable", "doc": "
    Authors\nEither the person(s) that have trained this model resulting in the original weights file.\n    (If this is the initial weights entry, i.e. it does not have a parent)\nOr the person(s) who have converted the weights to this weights format.\n    (If this is a child weight, i.e. it has a parent field)
    \n", "annotation": ": Optional[List[bioimageio.spec.generic.v0_2.Author]]"}, "bioimageio.spec.model.v0_4.WeightsEntryDescrBase.dependencies": {"fullname": "bioimageio.spec.model.v0_4.WeightsEntryDescrBase.dependencies", "modulename": "bioimageio.spec.model.v0_4", "qualname": "WeightsEntryDescrBase.dependencies", "kind": "variable", "doc": "
    Dependency manager and dependency file, specified as <dependency manager>:<relative file path>.
    \n", "annotation": ": Annotated[Optional[bioimageio.spec.model.v0_4.Dependencies], AfterWarner(func=<function as_warning.<locals>.wrapper at 0x7afc91ef0b80>, severity=30, msg='Custom dependencies ({value}) specified. Avoid this whenever possible to allow execution in a wider range of software environments.', context={'typ': None}), FieldInfo(annotation=NoneType, required=True, examples=['conda:environment.yaml', 'maven:./pom.xml', 'pip:./requirements.txt'])]"}, "bioimageio.spec.model.v0_4.WeightsEntryDescrBase.parent": {"fullname": "bioimageio.spec.model.v0_4.WeightsEntryDescrBase.parent", "modulename": "bioimageio.spec.model.v0_4", "qualname": "WeightsEntryDescrBase.parent", "kind": "variable", "doc": "
    The source weights these weights were converted from.\nFor example, if a model's weights were converted from the pytorch_state_dict format to torchscript,\nThe pytorch_state_dict weights entry has no parent and is the parent of the torchscript weights.\nAll weight entries except one (the initial set of weights resulting from training the model),\nneed to have this field.
    \n", "annotation": ": Annotated[Optional[Literal['keras_hdf5', 'onnx', 'pytorch_state_dict', 'tensorflow_js', 'tensorflow_saved_model_bundle', 'torchscript']], FieldInfo(annotation=NoneType, required=True, examples=['pytorch_state_dict'])]"}, "bioimageio.spec.model.v0_4.WeightsEntryDescrBase.check_parent_is_not_self": {"fullname": "bioimageio.spec.model.v0_4.WeightsEntryDescrBase.check_parent_is_not_self", "modulename": "bioimageio.spec.model.v0_4", "qualname": "WeightsEntryDescrBase.check_parent_is_not_self", "kind": "function", "doc": "
    \n", "signature": "(self) -> Self:", "funcdef": "def"}, "bioimageio.spec.model.v0_4.WeightsEntryDescrBase.model_config": {"fullname": "bioimageio.spec.model.v0_4.WeightsEntryDescrBase.model_config", "modulename": "bioimageio.spec.model.v0_4", "qualname": "WeightsEntryDescrBase.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_4.WeightsEntryDescrBase.model_fields": {"fullname": "bioimageio.spec.model.v0_4.WeightsEntryDescrBase.model_fields", "modulename": "bioimageio.spec.model.v0_4", "qualname": "WeightsEntryDescrBase.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'source': FieldInfo(annotation=Union[Annotated[Path, PathType], RelativeFilePath, HttpUrl, Annotated[Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], required=True, metadata=[AfterValidator(func=<function wo_special_file_name>), PlainSerializer(func=<function _package>, return_type=PydanticUndefined, when_used='unless-none')]), 'sha256': FieldInfo(annotation=Union[Sha256, NoneType], required=False), 'attachments': FieldInfo(annotation=Union[AttachmentsDescr, NoneType], required=False, metadata=[AfterWarner(func=<function as_warning.<locals>.wrapper>, severity=35, msg='Weights entry depends on additional attachments.', context={'typ': None})]), 'authors': FieldInfo(annotation=Union[List[Author], NoneType], required=False), 'dependencies': FieldInfo(annotation=Union[Dependencies, NoneType], required=False, examples=['conda:environment.yaml', 'maven:./pom.xml', 'pip:./requirements.txt'], metadata=[AfterWarner(func=<function as_warning.<locals>.wrapper>, severity=30, msg='Custom dependencies ({value}) specified. Avoid this whenever possible to allow execution in a wider range of software environments.', context={'typ': None})]), 'parent': FieldInfo(annotation=Union[Literal['keras_hdf5', 'onnx', 'pytorch_state_dict', 'tensorflow_js', 'tensorflow_saved_model_bundle', 'torchscript'], NoneType], required=False, examples=['pytorch_state_dict'])}"}, "bioimageio.spec.model.v0_4.WeightsEntryDescrBase.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_4.WeightsEntryDescrBase.model_computed_fields", "modulename": "bioimageio.spec.model.v0_4", "qualname": "WeightsEntryDescrBase.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_4.KerasHdf5WeightsDescr": {"fullname": "bioimageio.spec.model.v0_4.KerasHdf5WeightsDescr", "modulename": "bioimageio.spec.model.v0_4", "qualname": "KerasHdf5WeightsDescr", "kind": "class", "doc": "
    Subpart of a resource description
    \n", "bases": "WeightsEntryDescrBase"}, "bioimageio.spec.model.v0_4.KerasHdf5WeightsDescr.type": {"fullname": "bioimageio.spec.model.v0_4.KerasHdf5WeightsDescr.type", "modulename": "bioimageio.spec.model.v0_4", "qualname": "KerasHdf5WeightsDescr.type", "kind": "variable", "doc": "
    \n", "default_value": "'keras_hdf5'"}, "bioimageio.spec.model.v0_4.KerasHdf5WeightsDescr.weights_format_name": {"fullname": "bioimageio.spec.model.v0_4.KerasHdf5WeightsDescr.weights_format_name", "modulename": "bioimageio.spec.model.v0_4", "qualname": "KerasHdf5WeightsDescr.weights_format_name", "kind": "variable", "doc": "
    \n", "annotation": ": ClassVar[str]", "default_value": "'Keras HDF5'"}, "bioimageio.spec.model.v0_4.KerasHdf5WeightsDescr.tensorflow_version": {"fullname": "bioimageio.spec.model.v0_4.KerasHdf5WeightsDescr.tensorflow_version", "modulename": "bioimageio.spec.model.v0_4", "qualname": "KerasHdf5WeightsDescr.tensorflow_version", "kind": "variable", "doc": "
    TensorFlow version used to create these weights
    \n", "annotation": ": Optional[bioimageio.spec._internal.version_type.Version]"}, "bioimageio.spec.model.v0_4.KerasHdf5WeightsDescr.model_config": {"fullname": "bioimageio.spec.model.v0_4.KerasHdf5WeightsDescr.model_config", "modulename": "bioimageio.spec.model.v0_4", "qualname": "KerasHdf5WeightsDescr.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_4.KerasHdf5WeightsDescr.model_fields": {"fullname": "bioimageio.spec.model.v0_4.KerasHdf5WeightsDescr.model_fields", "modulename": "bioimageio.spec.model.v0_4", "qualname": "KerasHdf5WeightsDescr.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'source': FieldInfo(annotation=Union[Annotated[Path, PathType], RelativeFilePath, HttpUrl, Annotated[Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], required=True, metadata=[AfterValidator(func=<function wo_special_file_name>), PlainSerializer(func=<function _package>, return_type=PydanticUndefined, when_used='unless-none')]), 'sha256': FieldInfo(annotation=Union[Sha256, NoneType], required=False), 'attachments': FieldInfo(annotation=Union[AttachmentsDescr, NoneType], required=False, metadata=[AfterWarner(func=<function as_warning.<locals>.wrapper>, severity=35, msg='Weights entry depends on additional attachments.', context={'typ': None})]), 'authors': FieldInfo(annotation=Union[List[Author], NoneType], required=False), 'dependencies': FieldInfo(annotation=Union[Dependencies, NoneType], required=False, examples=['conda:environment.yaml', 'maven:./pom.xml', 'pip:./requirements.txt'], metadata=[AfterWarner(func=<function as_warning.<locals>.wrapper>, severity=30, msg='Custom dependencies ({value}) specified. Avoid this whenever possible to allow execution in a wider range of software environments.', context={'typ': None})]), 'parent': FieldInfo(annotation=Union[Literal['keras_hdf5', 'onnx', 'pytorch_state_dict', 'tensorflow_js', 'tensorflow_saved_model_bundle', 'torchscript'], NoneType], required=False, examples=['pytorch_state_dict']), 'tensorflow_version': FieldInfo(annotation=Union[Version, NoneType], required=False)}"}, "bioimageio.spec.model.v0_4.KerasHdf5WeightsDescr.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_4.KerasHdf5WeightsDescr.model_computed_fields", "modulename": "bioimageio.spec.model.v0_4", "qualname": "KerasHdf5WeightsDescr.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_4.OnnxWeightsDescr": {"fullname": "bioimageio.spec.model.v0_4.OnnxWeightsDescr", "modulename": "bioimageio.spec.model.v0_4", "qualname": "OnnxWeightsDescr", "kind": "class", "doc": "
    Subpart of a resource description
    \n", "bases": "WeightsEntryDescrBase"}, "bioimageio.spec.model.v0_4.OnnxWeightsDescr.type": {"fullname": "bioimageio.spec.model.v0_4.OnnxWeightsDescr.type", "modulename": "bioimageio.spec.model.v0_4", "qualname": "OnnxWeightsDescr.type", "kind": "variable", "doc": "
    \n", "default_value": "'onnx'"}, "bioimageio.spec.model.v0_4.OnnxWeightsDescr.weights_format_name": {"fullname": "bioimageio.spec.model.v0_4.OnnxWeightsDescr.weights_format_name", "modulename": "bioimageio.spec.model.v0_4", "qualname": "OnnxWeightsDescr.weights_format_name", "kind": "variable", "doc": "
    \n", "annotation": ": ClassVar[str]", "default_value": "'ONNX'"}, "bioimageio.spec.model.v0_4.OnnxWeightsDescr.opset_version": {"fullname": "bioimageio.spec.model.v0_4.OnnxWeightsDescr.opset_version", "modulename": "bioimageio.spec.model.v0_4", "qualname": "OnnxWeightsDescr.opset_version", "kind": "variable", "doc": "
    ONNX opset version
    \n", "annotation": ": Optional[Annotated[int, Ge(ge=7)]]"}, "bioimageio.spec.model.v0_4.OnnxWeightsDescr.model_config": {"fullname": "bioimageio.spec.model.v0_4.OnnxWeightsDescr.model_config", "modulename": "bioimageio.spec.model.v0_4", "qualname": "OnnxWeightsDescr.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_4.OnnxWeightsDescr.model_fields": {"fullname": "bioimageio.spec.model.v0_4.OnnxWeightsDescr.model_fields", "modulename": "bioimageio.spec.model.v0_4", "qualname": "OnnxWeightsDescr.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'source': FieldInfo(annotation=Union[Annotated[Path, PathType], RelativeFilePath, HttpUrl, Annotated[Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], required=True, metadata=[AfterValidator(func=<function wo_special_file_name>), PlainSerializer(func=<function _package>, return_type=PydanticUndefined, when_used='unless-none')]), 'sha256': FieldInfo(annotation=Union[Sha256, NoneType], required=False), 'attachments': FieldInfo(annotation=Union[AttachmentsDescr, NoneType], required=False, metadata=[AfterWarner(func=<function as_warning.<locals>.wrapper>, severity=35, msg='Weights entry depends on additional attachments.', context={'typ': None})]), 'authors': FieldInfo(annotation=Union[List[Author], NoneType], required=False), 'dependencies': FieldInfo(annotation=Union[Dependencies, NoneType], required=False, examples=['conda:environment.yaml', 'maven:./pom.xml', 'pip:./requirements.txt'], metadata=[AfterWarner(func=<function as_warning.<locals>.wrapper>, severity=30, msg='Custom dependencies ({value}) specified. Avoid this whenever possible to allow execution in a wider range of software environments.', context={'typ': None})]), 'parent': FieldInfo(annotation=Union[Literal['keras_hdf5', 'onnx', 'pytorch_state_dict', 'tensorflow_js', 'tensorflow_saved_model_bundle', 'torchscript'], NoneType], required=False, examples=['pytorch_state_dict']), 'opset_version': FieldInfo(annotation=Union[Annotated[int, Ge], NoneType], required=False)}"}, "bioimageio.spec.model.v0_4.OnnxWeightsDescr.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_4.OnnxWeightsDescr.model_computed_fields", "modulename": "bioimageio.spec.model.v0_4", "qualname": "OnnxWeightsDescr.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_4.PytorchStateDictWeightsDescr": {"fullname": "bioimageio.spec.model.v0_4.PytorchStateDictWeightsDescr", "modulename": "bioimageio.spec.model.v0_4", "qualname": "PytorchStateDictWeightsDescr", "kind": "class", "doc": "
    Subpart of a resource description
    \n", "bases": "WeightsEntryDescrBase"}, "bioimageio.spec.model.v0_4.PytorchStateDictWeightsDescr.type": {"fullname": "bioimageio.spec.model.v0_4.PytorchStateDictWeightsDescr.type", "modulename": "bioimageio.spec.model.v0_4", "qualname": "PytorchStateDictWeightsDescr.type", "kind": "variable", "doc": "
    \n", "default_value": "'pytorch_state_dict'"}, "bioimageio.spec.model.v0_4.PytorchStateDictWeightsDescr.weights_format_name": {"fullname": "bioimageio.spec.model.v0_4.PytorchStateDictWeightsDescr.weights_format_name", "modulename": "bioimageio.spec.model.v0_4", "qualname": "PytorchStateDictWeightsDescr.weights_format_name", "kind": "variable", "doc": "
    \n", "annotation": ": ClassVar[str]", "default_value": "'Pytorch State Dict'"}, "bioimageio.spec.model.v0_4.PytorchStateDictWeightsDescr.architecture": {"fullname": "bioimageio.spec.model.v0_4.PytorchStateDictWeightsDescr.architecture", "modulename": "bioimageio.spec.model.v0_4", "qualname": "PytorchStateDictWeightsDescr.architecture", "kind": "variable", "doc": "
    callable returning a torch.nn.Module instance.\nLocal implementation: <relative path to file>:<identifier of implementation within the file>.\nImplementation in a dependency: <dependency-package>.<[dependency-module]>.<identifier>.
    \n", "annotation": ": Union[bioimageio.spec.model.v0_4.CallableFromFile, bioimageio.spec.model.v0_4.CallableFromDepencency]"}, "bioimageio.spec.model.v0_4.PytorchStateDictWeightsDescr.architecture_sha256": {"fullname": "bioimageio.spec.model.v0_4.PytorchStateDictWeightsDescr.architecture_sha256", "modulename": "bioimageio.spec.model.v0_4", "qualname": "PytorchStateDictWeightsDescr.architecture_sha256", "kind": "variable", "doc": "
    The SHA256 of the architecture source file,\nif the architecture is not defined in a module listed in dependencies
    \n", "annotation": ": Annotated[Optional[bioimageio.spec._internal.io.Sha256], FieldInfo(annotation=NoneType, required=True, description="The SHA256 of the architecture source file, if the architecture is not defined in a module listed in `dependencies`\\nYou can drag and drop your file to this\\n[online tool](http://emn178.github.io/online-tools/sha256_checksum.html) to generate a SHA256 in your browser.\\nOr you can generate a SHA256 checksum with Python's `hashlib`,\\n[here is a codesnippet](https://gist.github.com/FynnBe/e64460463df89439cff218bbf59c1100).")]"}, "bioimageio.spec.model.v0_4.PytorchStateDictWeightsDescr.check_architecture_sha256": {"fullname": "bioimageio.spec.model.v0_4.PytorchStateDictWeightsDescr.check_architecture_sha256", "modulename": "bioimageio.spec.model.v0_4", "qualname": "PytorchStateDictWeightsDescr.check_architecture_sha256", "kind": "function", "doc": "
    \n", "signature": "(self) -> Self:", "funcdef": "def"}, "bioimageio.spec.model.v0_4.PytorchStateDictWeightsDescr.kwargs": {"fullname": "bioimageio.spec.model.v0_4.PytorchStateDictWeightsDescr.kwargs", "modulename": "bioimageio.spec.model.v0_4", "qualname": "PytorchStateDictWeightsDescr.kwargs", "kind": "variable", "doc": "
    key word arguments for the architecture callable
    \n", "annotation": ": Dict[str, Any]"}, "bioimageio.spec.model.v0_4.PytorchStateDictWeightsDescr.pytorch_version": {"fullname": "bioimageio.spec.model.v0_4.PytorchStateDictWeightsDescr.pytorch_version", "modulename": "bioimageio.spec.model.v0_4", "qualname": "PytorchStateDictWeightsDescr.pytorch_version", "kind": "variable", "doc": "
    Version of the PyTorch library used.\nIf depencencies is specified it should include pytorch and the verison has to match.\n(dependencies overrules pytorch_version)
    \n", "annotation": ": Optional[bioimageio.spec._internal.version_type.Version]"}, "bioimageio.spec.model.v0_4.PytorchStateDictWeightsDescr.model_config": {"fullname": "bioimageio.spec.model.v0_4.PytorchStateDictWeightsDescr.model_config", "modulename": "bioimageio.spec.model.v0_4", "qualname": "PytorchStateDictWeightsDescr.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_4.PytorchStateDictWeightsDescr.model_fields": {"fullname": "bioimageio.spec.model.v0_4.PytorchStateDictWeightsDescr.model_fields", "modulename": "bioimageio.spec.model.v0_4", "qualname": "PytorchStateDictWeightsDescr.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'source': FieldInfo(annotation=Union[Annotated[Path, PathType], RelativeFilePath, HttpUrl, Annotated[Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], required=True, metadata=[AfterValidator(func=<function wo_special_file_name>), PlainSerializer(func=<function _package>, return_type=PydanticUndefined, when_used='unless-none')]), 'sha256': FieldInfo(annotation=Union[Sha256, NoneType], required=False), 'attachments': FieldInfo(annotation=Union[AttachmentsDescr, NoneType], required=False, metadata=[AfterWarner(func=<function as_warning.<locals>.wrapper>, severity=35, msg='Weights entry depends on additional attachments.', context={'typ': None})]), 'authors': FieldInfo(annotation=Union[List[Author], NoneType], required=False), 'dependencies': FieldInfo(annotation=Union[Dependencies, NoneType], required=False, examples=['conda:environment.yaml', 'maven:./pom.xml', 'pip:./requirements.txt'], metadata=[AfterWarner(func=<function as_warning.<locals>.wrapper>, severity=30, msg='Custom dependencies ({value}) specified. Avoid this whenever possible to allow execution in a wider range of software environments.', context={'typ': None})]), 'parent': FieldInfo(annotation=Union[Literal['keras_hdf5', 'onnx', 'pytorch_state_dict', 'tensorflow_js', 'tensorflow_saved_model_bundle', 'torchscript'], NoneType], required=False, examples=['pytorch_state_dict']), 'architecture': FieldInfo(annotation=Union[CallableFromFile, CallableFromDepencency], required=True, examples=['my_function.py:MyNetworkClass', 'my_module.submodule.get_my_model']), 'architecture_sha256': FieldInfo(annotation=Union[Sha256, NoneType], required=False, description="The SHA256 of the architecture source file, if the architecture is not defined in a module listed in `dependencies`\\nYou can drag and drop your file to this\\n[online tool](http://emn178.github.io/online-tools/sha256_checksum.html) to generate a SHA256 in your browser.\\nOr you can generate a SHA256 checksum with Python's `hashlib`,\\n[here is a codesnippet](https://gist.github.com/FynnBe/e64460463df89439cff218bbf59c1100)."), 'kwargs': FieldInfo(annotation=Dict[str, Any], required=False, default_factory=dict), 'pytorch_version': FieldInfo(annotation=Union[Version, NoneType], required=False)}"}, "bioimageio.spec.model.v0_4.PytorchStateDictWeightsDescr.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_4.PytorchStateDictWeightsDescr.model_computed_fields", "modulename": "bioimageio.spec.model.v0_4", "qualname": "PytorchStateDictWeightsDescr.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_4.TorchscriptWeightsDescr": {"fullname": "bioimageio.spec.model.v0_4.TorchscriptWeightsDescr", "modulename": "bioimageio.spec.model.v0_4", "qualname": "TorchscriptWeightsDescr", "kind": "class", "doc": "
    Subpart of a resource description
    \n", "bases": "WeightsEntryDescrBase"}, "bioimageio.spec.model.v0_4.TorchscriptWeightsDescr.type": {"fullname": "bioimageio.spec.model.v0_4.TorchscriptWeightsDescr.type", "modulename": "bioimageio.spec.model.v0_4", "qualname": "TorchscriptWeightsDescr.type", "kind": "variable", "doc": "
    \n", "default_value": "'torchscript'"}, "bioimageio.spec.model.v0_4.TorchscriptWeightsDescr.weights_format_name": {"fullname": "bioimageio.spec.model.v0_4.TorchscriptWeightsDescr.weights_format_name", "modulename": "bioimageio.spec.model.v0_4", "qualname": "TorchscriptWeightsDescr.weights_format_name", "kind": "variable", "doc": "
    \n", "annotation": ": ClassVar[str]", "default_value": "'TorchScript'"}, "bioimageio.spec.model.v0_4.TorchscriptWeightsDescr.pytorch_version": {"fullname": "bioimageio.spec.model.v0_4.TorchscriptWeightsDescr.pytorch_version", "modulename": "bioimageio.spec.model.v0_4", "qualname": "TorchscriptWeightsDescr.pytorch_version", "kind": "variable", "doc": "
    Version of the PyTorch library used.
    \n", "annotation": ": Optional[bioimageio.spec._internal.version_type.Version]"}, "bioimageio.spec.model.v0_4.TorchscriptWeightsDescr.model_config": {"fullname": "bioimageio.spec.model.v0_4.TorchscriptWeightsDescr.model_config", "modulename": "bioimageio.spec.model.v0_4", "qualname": "TorchscriptWeightsDescr.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_4.TorchscriptWeightsDescr.model_fields": {"fullname": "bioimageio.spec.model.v0_4.TorchscriptWeightsDescr.model_fields", "modulename": "bioimageio.spec.model.v0_4", "qualname": "TorchscriptWeightsDescr.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'source': FieldInfo(annotation=Union[Annotated[Path, PathType], RelativeFilePath, HttpUrl, Annotated[Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], required=True, metadata=[AfterValidator(func=<function wo_special_file_name>), PlainSerializer(func=<function _package>, return_type=PydanticUndefined, when_used='unless-none')]), 'sha256': FieldInfo(annotation=Union[Sha256, NoneType], required=False), 'attachments': FieldInfo(annotation=Union[AttachmentsDescr, NoneType], required=False, metadata=[AfterWarner(func=<function as_warning.<locals>.wrapper>, severity=35, msg='Weights entry depends on additional attachments.', context={'typ': None})]), 'authors': FieldInfo(annotation=Union[List[Author], NoneType], required=False), 'dependencies': FieldInfo(annotation=Union[Dependencies, NoneType], required=False, examples=['conda:environment.yaml', 'maven:./pom.xml', 'pip:./requirements.txt'], metadata=[AfterWarner(func=<function as_warning.<locals>.wrapper>, severity=30, msg='Custom dependencies ({value}) specified. Avoid this whenever possible to allow execution in a wider range of software environments.', context={'typ': None})]), 'parent': FieldInfo(annotation=Union[Literal['keras_hdf5', 'onnx', 'pytorch_state_dict', 'tensorflow_js', 'tensorflow_saved_model_bundle', 'torchscript'], NoneType], required=False, examples=['pytorch_state_dict']), 'pytorch_version': FieldInfo(annotation=Union[Version, NoneType], required=False)}"}, "bioimageio.spec.model.v0_4.TorchscriptWeightsDescr.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_4.TorchscriptWeightsDescr.model_computed_fields", "modulename": "bioimageio.spec.model.v0_4", "qualname": "TorchscriptWeightsDescr.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_4.TensorflowJsWeightsDescr": {"fullname": "bioimageio.spec.model.v0_4.TensorflowJsWeightsDescr", "modulename": "bioimageio.spec.model.v0_4", "qualname": "TensorflowJsWeightsDescr", "kind": "class", "doc": "
    Subpart of a resource description
    \n", "bases": "WeightsEntryDescrBase"}, "bioimageio.spec.model.v0_4.TensorflowJsWeightsDescr.type": {"fullname": "bioimageio.spec.model.v0_4.TensorflowJsWeightsDescr.type", "modulename": "bioimageio.spec.model.v0_4", "qualname": "TensorflowJsWeightsDescr.type", "kind": "variable", "doc": "
    \n", "default_value": "'tensorflow_js'"}, "bioimageio.spec.model.v0_4.TensorflowJsWeightsDescr.weights_format_name": {"fullname": "bioimageio.spec.model.v0_4.TensorflowJsWeightsDescr.weights_format_name", "modulename": "bioimageio.spec.model.v0_4", "qualname": "TensorflowJsWeightsDescr.weights_format_name", "kind": "variable", "doc": "
    \n", "annotation": ": ClassVar[str]", "default_value": "'Tensorflow.js'"}, "bioimageio.spec.model.v0_4.TensorflowJsWeightsDescr.tensorflow_version": {"fullname": "bioimageio.spec.model.v0_4.TensorflowJsWeightsDescr.tensorflow_version", "modulename": "bioimageio.spec.model.v0_4", "qualname": "TensorflowJsWeightsDescr.tensorflow_version", "kind": "variable", "doc": "
    Version of the TensorFlow library used.
    \n", "annotation": ": Optional[bioimageio.spec._internal.version_type.Version]"}, "bioimageio.spec.model.v0_4.TensorflowJsWeightsDescr.source": {"fullname": "bioimageio.spec.model.v0_4.TensorflowJsWeightsDescr.source", "modulename": "bioimageio.spec.model.v0_4", "qualname": "TensorflowJsWeightsDescr.source", "kind": "variable", "doc": "
    \u2208\ud83d\udce6 The multi-file weights.\nAll required files/folders should be a zip archive.
    \n", "annotation": ": Annotated[Union[Annotated[pathlib.Path, PathType(path_type='file')], bioimageio.spec._internal.io.RelativeFilePath, bioimageio.spec._internal.url.HttpUrl, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator(func=<function wo_special_file_name at 0x7afca0d90540>), PlainSerializer(func=<function _package at 0x7afca0d91760>, return_type=PydanticUndefined, when_used='unless-none')]"}, "bioimageio.spec.model.v0_4.TensorflowJsWeightsDescr.model_config": {"fullname": "bioimageio.spec.model.v0_4.TensorflowJsWeightsDescr.model_config", "modulename": "bioimageio.spec.model.v0_4", "qualname": "TensorflowJsWeightsDescr.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_4.TensorflowJsWeightsDescr.model_fields": {"fullname": "bioimageio.spec.model.v0_4.TensorflowJsWeightsDescr.model_fields", "modulename": "bioimageio.spec.model.v0_4", "qualname": "TensorflowJsWeightsDescr.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'source': FieldInfo(annotation=Union[Annotated[Path, PathType], RelativeFilePath, HttpUrl, Annotated[Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], required=True, metadata=[AfterValidator(func=<function wo_special_file_name>), PlainSerializer(func=<function _package>, return_type=PydanticUndefined, when_used='unless-none')]), 'sha256': FieldInfo(annotation=Union[Sha256, NoneType], required=False), 'attachments': FieldInfo(annotation=Union[AttachmentsDescr, NoneType], required=False, metadata=[AfterWarner(func=<function as_warning.<locals>.wrapper>, severity=35, msg='Weights entry depends on additional attachments.', context={'typ': None})]), 'authors': FieldInfo(annotation=Union[List[Author], NoneType], required=False), 'dependencies': FieldInfo(annotation=Union[Dependencies, NoneType], required=False, examples=['conda:environment.yaml', 'maven:./pom.xml', 'pip:./requirements.txt'], metadata=[AfterWarner(func=<function as_warning.<locals>.wrapper>, severity=30, msg='Custom dependencies ({value}) specified. Avoid this whenever possible to allow execution in a wider range of software environments.', context={'typ': None})]), 'parent': FieldInfo(annotation=Union[Literal['keras_hdf5', 'onnx', 'pytorch_state_dict', 'tensorflow_js', 'tensorflow_saved_model_bundle', 'torchscript'], NoneType], required=False, examples=['pytorch_state_dict']), 'tensorflow_version': FieldInfo(annotation=Union[Version, NoneType], required=False)}"}, "bioimageio.spec.model.v0_4.TensorflowJsWeightsDescr.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_4.TensorflowJsWeightsDescr.model_computed_fields", "modulename": "bioimageio.spec.model.v0_4", "qualname": "TensorflowJsWeightsDescr.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_4.TensorflowSavedModelBundleWeightsDescr": {"fullname": "bioimageio.spec.model.v0_4.TensorflowSavedModelBundleWeightsDescr", "modulename": "bioimageio.spec.model.v0_4", "qualname": "TensorflowSavedModelBundleWeightsDescr", "kind": "class", "doc": "
    Subpart of a resource description
    \n", "bases": "WeightsEntryDescrBase"}, "bioimageio.spec.model.v0_4.TensorflowSavedModelBundleWeightsDescr.type": {"fullname": "bioimageio.spec.model.v0_4.TensorflowSavedModelBundleWeightsDescr.type", "modulename": "bioimageio.spec.model.v0_4", "qualname": "TensorflowSavedModelBundleWeightsDescr.type", "kind": "variable", "doc": "
    \n", "default_value": "'tensorflow_saved_model_bundle'"}, "bioimageio.spec.model.v0_4.TensorflowSavedModelBundleWeightsDescr.weights_format_name": {"fullname": "bioimageio.spec.model.v0_4.TensorflowSavedModelBundleWeightsDescr.weights_format_name", "modulename": "bioimageio.spec.model.v0_4", "qualname": "TensorflowSavedModelBundleWeightsDescr.weights_format_name", "kind": "variable", "doc": "
    \n", "annotation": ": ClassVar[str]", "default_value": "'Tensorflow Saved Model'"}, "bioimageio.spec.model.v0_4.TensorflowSavedModelBundleWeightsDescr.tensorflow_version": {"fullname": "bioimageio.spec.model.v0_4.TensorflowSavedModelBundleWeightsDescr.tensorflow_version", "modulename": "bioimageio.spec.model.v0_4", "qualname": "TensorflowSavedModelBundleWeightsDescr.tensorflow_version", "kind": "variable", "doc": "
    Version of the TensorFlow library used.
    \n", "annotation": ": Optional[bioimageio.spec._internal.version_type.Version]"}, "bioimageio.spec.model.v0_4.TensorflowSavedModelBundleWeightsDescr.model_config": {"fullname": "bioimageio.spec.model.v0_4.TensorflowSavedModelBundleWeightsDescr.model_config", "modulename": "bioimageio.spec.model.v0_4", "qualname": "TensorflowSavedModelBundleWeightsDescr.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_4.TensorflowSavedModelBundleWeightsDescr.model_fields": {"fullname": "bioimageio.spec.model.v0_4.TensorflowSavedModelBundleWeightsDescr.model_fields", "modulename": "bioimageio.spec.model.v0_4", "qualname": "TensorflowSavedModelBundleWeightsDescr.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'source': FieldInfo(annotation=Union[Annotated[Path, PathType], RelativeFilePath, HttpUrl, Annotated[Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], required=True, metadata=[AfterValidator(func=<function wo_special_file_name>), PlainSerializer(func=<function _package>, return_type=PydanticUndefined, when_used='unless-none')]), 'sha256': FieldInfo(annotation=Union[Sha256, NoneType], required=False), 'attachments': FieldInfo(annotation=Union[AttachmentsDescr, NoneType], required=False, metadata=[AfterWarner(func=<function as_warning.<locals>.wrapper>, severity=35, msg='Weights entry depends on additional attachments.', context={'typ': None})]), 'authors': FieldInfo(annotation=Union[List[Author], NoneType], required=False), 'dependencies': FieldInfo(annotation=Union[Dependencies, NoneType], required=False, examples=['conda:environment.yaml', 'maven:./pom.xml', 'pip:./requirements.txt'], metadata=[AfterWarner(func=<function as_warning.<locals>.wrapper>, severity=30, msg='Custom dependencies ({value}) specified. Avoid this whenever possible to allow execution in a wider range of software environments.', context={'typ': None})]), 'parent': FieldInfo(annotation=Union[Literal['keras_hdf5', 'onnx', 'pytorch_state_dict', 'tensorflow_js', 'tensorflow_saved_model_bundle', 'torchscript'], NoneType], required=False, examples=['pytorch_state_dict']), 'tensorflow_version': FieldInfo(annotation=Union[Version, NoneType], required=False)}"}, "bioimageio.spec.model.v0_4.TensorflowSavedModelBundleWeightsDescr.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_4.TensorflowSavedModelBundleWeightsDescr.model_computed_fields", "modulename": "bioimageio.spec.model.v0_4", "qualname": "TensorflowSavedModelBundleWeightsDescr.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_4.ParameterizedInputShape": {"fullname": "bioimageio.spec.model.v0_4.ParameterizedInputShape", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ParameterizedInputShape", "kind": "class", "doc": "
    A sequence of valid shapes given by shape_k = min + k * step for k in {0, 1, ...}.
    \n", "bases": "bioimageio.spec._internal.node.Node"}, "bioimageio.spec.model.v0_4.ParameterizedInputShape.min": {"fullname": "bioimageio.spec.model.v0_4.ParameterizedInputShape.min", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ParameterizedInputShape.min", "kind": "variable", "doc": "
    The minimum input shape
    \n", "annotation": ": Annotated[List[int], MinLen(min_length=1)]"}, "bioimageio.spec.model.v0_4.ParameterizedInputShape.step": {"fullname": "bioimageio.spec.model.v0_4.ParameterizedInputShape.step", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ParameterizedInputShape.step", "kind": "variable", "doc": "
    The minimum shape change
    \n", "annotation": ": Annotated[List[int], MinLen(min_length=1)]"}, "bioimageio.spec.model.v0_4.ParameterizedInputShape.matching_lengths": {"fullname": "bioimageio.spec.model.v0_4.ParameterizedInputShape.matching_lengths", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ParameterizedInputShape.matching_lengths", "kind": "function", "doc": "
    \n", "signature": "(self) -> Self:", "funcdef": "def"}, "bioimageio.spec.model.v0_4.ParameterizedInputShape.model_config": {"fullname": "bioimageio.spec.model.v0_4.ParameterizedInputShape.model_config", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ParameterizedInputShape.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_4.ParameterizedInputShape.model_fields": {"fullname": "bioimageio.spec.model.v0_4.ParameterizedInputShape.model_fields", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ParameterizedInputShape.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'min': FieldInfo(annotation=List[int], required=True, metadata=[MinLen(min_length=1)]), 'step': FieldInfo(annotation=List[int], required=True, metadata=[MinLen(min_length=1)])}"}, "bioimageio.spec.model.v0_4.ParameterizedInputShape.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_4.ParameterizedInputShape.model_computed_fields", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ParameterizedInputShape.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_4.ImplicitOutputShape": {"fullname": "bioimageio.spec.model.v0_4.ImplicitOutputShape", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ImplicitOutputShape", "kind": "class", "doc": "
    Output tensor shape depending on an input tensor shape.\nshape(output_tensor) = shape(input_tensor) * scale + 2 * offset
    \n", "bases": "bioimageio.spec._internal.node.Node"}, "bioimageio.spec.model.v0_4.ImplicitOutputShape.reference_tensor": {"fullname": "bioimageio.spec.model.v0_4.ImplicitOutputShape.reference_tensor", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ImplicitOutputShape.reference_tensor", "kind": "variable", "doc": "
    Name of the reference tensor.
    \n", "annotation": ": bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate]]]"}, "bioimageio.spec.model.v0_4.ImplicitOutputShape.scale": {"fullname": "bioimageio.spec.model.v0_4.ImplicitOutputShape.scale", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ImplicitOutputShape.scale", "kind": "variable", "doc": "
    output_pix/input_pix for each dimension.\n'null' values indicate new dimensions, whose length is defined by 2*offset
    \n", "annotation": ": Annotated[List[Optional[float]], MinLen(min_length=1)]"}, "bioimageio.spec.model.v0_4.ImplicitOutputShape.offset": {"fullname": "bioimageio.spec.model.v0_4.ImplicitOutputShape.offset", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ImplicitOutputShape.offset", "kind": "variable", "doc": "
    Position of origin wrt to input.
    \n", "annotation": ": Annotated[List[Union[int, Annotated[float, MultipleOf(multiple_of=0.5)]]], MinLen(min_length=1)]"}, "bioimageio.spec.model.v0_4.ImplicitOutputShape.matching_lengths": {"fullname": "bioimageio.spec.model.v0_4.ImplicitOutputShape.matching_lengths", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ImplicitOutputShape.matching_lengths", "kind": "function", "doc": "
    \n", "signature": "(self) -> Self:", "funcdef": "def"}, "bioimageio.spec.model.v0_4.ImplicitOutputShape.model_config": {"fullname": "bioimageio.spec.model.v0_4.ImplicitOutputShape.model_config", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ImplicitOutputShape.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_4.ImplicitOutputShape.model_fields": {"fullname": "bioimageio.spec.model.v0_4.ImplicitOutputShape.model_fields", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ImplicitOutputShape.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'reference_tensor': FieldInfo(annotation=ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate]]], required=True), 'scale': FieldInfo(annotation=List[Union[float, NoneType]], required=True, metadata=[MinLen(min_length=1)]), 'offset': FieldInfo(annotation=List[Union[int, Annotated[float, MultipleOf]]], required=True, metadata=[MinLen(min_length=1)])}"}, "bioimageio.spec.model.v0_4.ImplicitOutputShape.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_4.ImplicitOutputShape.model_computed_fields", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ImplicitOutputShape.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_4.TensorDescrBase": {"fullname": "bioimageio.spec.model.v0_4.TensorDescrBase", "modulename": "bioimageio.spec.model.v0_4", "qualname": "TensorDescrBase", "kind": "class", "doc": "
    Subpart of a resource description
    \n", "bases": "bioimageio.spec._internal.node.Node"}, "bioimageio.spec.model.v0_4.TensorDescrBase.name": {"fullname": "bioimageio.spec.model.v0_4.TensorDescrBase.name", "modulename": "bioimageio.spec.model.v0_4", "qualname": "TensorDescrBase.name", "kind": "variable", "doc": "
    Tensor name. No duplicates are allowed.
    \n", "annotation": ": bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate]]]"}, "bioimageio.spec.model.v0_4.TensorDescrBase.description": {"fullname": "bioimageio.spec.model.v0_4.TensorDescrBase.description", "modulename": "bioimageio.spec.model.v0_4", "qualname": "TensorDescrBase.description", "kind": "variable", "doc": "
    \n", "annotation": ": str"}, "bioimageio.spec.model.v0_4.TensorDescrBase.axes": {"fullname": "bioimageio.spec.model.v0_4.TensorDescrBase.axes", "modulename": "bioimageio.spec.model.v0_4", "qualname": "TensorDescrBase.axes", "kind": "variable", "doc": "
    Axes identifying characters. Same length and order as the axes in shape.\n| axis | description |\n| --- | --- |\n|  b  |  batch (groups multiple samples) |\n|  i  |  instance/index/element |\n|  t  |  time |\n|  c  |  channel |\n|  z  |  spatial dimension z |\n|  y  |  spatial dimension y |\n|  x  |  spatial dimension x |
    \n", "annotation": ": Annotated[str, RestrictCharacters(alphabet='bitczyx'), AfterValidator(func=<function validate_unique_entries at 0x7afca0a94b80>)]"}, "bioimageio.spec.model.v0_4.TensorDescrBase.data_range": {"fullname": "bioimageio.spec.model.v0_4.TensorDescrBase.data_range", "modulename": "bioimageio.spec.model.v0_4", "qualname": "TensorDescrBase.data_range", "kind": "variable", "doc": "
    Tuple (minimum, maximum) specifying the allowed range of the data in this tensor.\nIf not specified, the full data range that can be expressed in data_type is allowed.
    \n", "annotation": ": Optional[Tuple[Annotated[float, AllowInfNan(allow_inf_nan=True)], Annotated[float, AllowInfNan(allow_inf_nan=True)]]]"}, "bioimageio.spec.model.v0_4.TensorDescrBase.model_config": {"fullname": "bioimageio.spec.model.v0_4.TensorDescrBase.model_config", "modulename": "bioimageio.spec.model.v0_4", "qualname": "TensorDescrBase.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_4.TensorDescrBase.model_fields": {"fullname": "bioimageio.spec.model.v0_4.TensorDescrBase.model_fields", "modulename": "bioimageio.spec.model.v0_4", "qualname": "TensorDescrBase.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'name': FieldInfo(annotation=ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate]]], required=True), 'description': FieldInfo(annotation=str, required=False, default=''), 'axes': FieldInfo(annotation=str, required=True, metadata=[RestrictCharacters(alphabet='bitczyx'), AfterValidator(func=<function validate_unique_entries>)]), 'data_range': FieldInfo(annotation=Union[Tuple[Annotated[float, AllowInfNan(allow_inf_nan=True)], Annotated[float, AllowInfNan(allow_inf_nan=True)]], NoneType], required=False)}"}, "bioimageio.spec.model.v0_4.TensorDescrBase.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_4.TensorDescrBase.model_computed_fields", "modulename": "bioimageio.spec.model.v0_4", "qualname": "TensorDescrBase.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_4.ProcessingKwargs": {"fullname": "bioimageio.spec.model.v0_4.ProcessingKwargs", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ProcessingKwargs", "kind": "class", "doc": "
    base class for pre-/postprocessing key word arguments
    \n", "bases": "bioimageio.spec._internal.common_nodes.KwargsNode"}, "bioimageio.spec.model.v0_4.ProcessingKwargs.model_config": {"fullname": "bioimageio.spec.model.v0_4.ProcessingKwargs.model_config", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ProcessingKwargs.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_4.ProcessingKwargs.model_fields": {"fullname": "bioimageio.spec.model.v0_4.ProcessingKwargs.model_fields", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ProcessingKwargs.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_4.ProcessingKwargs.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_4.ProcessingKwargs.model_computed_fields", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ProcessingKwargs.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_4.ProcessingDescrBase": {"fullname": "bioimageio.spec.model.v0_4.ProcessingDescrBase", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ProcessingDescrBase", "kind": "class", "doc": "
    processing base class
    \n", "bases": "bioimageio.spec._internal.common_nodes.NodeWithExplicitlySetFields"}, "bioimageio.spec.model.v0_4.ProcessingDescrBase.fields_to_set_explicitly": {"fullname": "bioimageio.spec.model.v0_4.ProcessingDescrBase.fields_to_set_explicitly", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ProcessingDescrBase.fields_to_set_explicitly", "kind": "variable", "doc": "
    set set these fields explicitly with their default value if they are not set,\nsuch that they are always included even when dumping with 'exlude_unset'
    \n", "annotation": ": ClassVar[FrozenSet[LiteralString]]", "default_value": "frozenset({'name'})"}, "bioimageio.spec.model.v0_4.ProcessingDescrBase.model_config": {"fullname": "bioimageio.spec.model.v0_4.ProcessingDescrBase.model_config", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ProcessingDescrBase.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_4.ProcessingDescrBase.model_fields": {"fullname": "bioimageio.spec.model.v0_4.ProcessingDescrBase.model_fields", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ProcessingDescrBase.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_4.ProcessingDescrBase.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_4.ProcessingDescrBase.model_computed_fields", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ProcessingDescrBase.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_4.BinarizeKwargs": {"fullname": "bioimageio.spec.model.v0_4.BinarizeKwargs", "modulename": "bioimageio.spec.model.v0_4", "qualname": "BinarizeKwargs", "kind": "class", "doc": "
    base class for pre-/postprocessing key word arguments
    \n", "bases": "ProcessingKwargs"}, "bioimageio.spec.model.v0_4.BinarizeKwargs.threshold": {"fullname": "bioimageio.spec.model.v0_4.BinarizeKwargs.threshold", "modulename": "bioimageio.spec.model.v0_4", "qualname": "BinarizeKwargs.threshold", "kind": "variable", "doc": "
    The fixed threshold
    \n", "annotation": ": float"}, "bioimageio.spec.model.v0_4.BinarizeKwargs.model_config": {"fullname": "bioimageio.spec.model.v0_4.BinarizeKwargs.model_config", "modulename": "bioimageio.spec.model.v0_4", "qualname": "BinarizeKwargs.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_4.BinarizeKwargs.model_fields": {"fullname": "bioimageio.spec.model.v0_4.BinarizeKwargs.model_fields", "modulename": "bioimageio.spec.model.v0_4", "qualname": "BinarizeKwargs.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'threshold': FieldInfo(annotation=float, required=True)}"}, "bioimageio.spec.model.v0_4.BinarizeKwargs.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_4.BinarizeKwargs.model_computed_fields", "modulename": "bioimageio.spec.model.v0_4", "qualname": "BinarizeKwargs.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_4.BinarizeDescr": {"fullname": "bioimageio.spec.model.v0_4.BinarizeDescr", "modulename": "bioimageio.spec.model.v0_4", "qualname": "BinarizeDescr", "kind": "class", "doc": "
    BinarizeDescr the tensor with a fixed threshold.\nValues above the threshold will be set to one, values below the threshold to zero.
    \n", "bases": "ProcessingDescrBase"}, "bioimageio.spec.model.v0_4.BinarizeDescr.name": {"fullname": "bioimageio.spec.model.v0_4.BinarizeDescr.name", "modulename": "bioimageio.spec.model.v0_4", "qualname": "BinarizeDescr.name", "kind": "variable", "doc": "
    \n", "annotation": ": Literal['binarize']"}, "bioimageio.spec.model.v0_4.BinarizeDescr.kwargs": {"fullname": "bioimageio.spec.model.v0_4.BinarizeDescr.kwargs", "modulename": "bioimageio.spec.model.v0_4", "qualname": "BinarizeDescr.kwargs", "kind": "variable", "doc": "
    \n", "annotation": ": bioimageio.spec.model.v0_4.BinarizeKwargs"}, "bioimageio.spec.model.v0_4.BinarizeDescr.model_config": {"fullname": "bioimageio.spec.model.v0_4.BinarizeDescr.model_config", "modulename": "bioimageio.spec.model.v0_4", "qualname": "BinarizeDescr.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_4.BinarizeDescr.model_fields": {"fullname": "bioimageio.spec.model.v0_4.BinarizeDescr.model_fields", "modulename": "bioimageio.spec.model.v0_4", "qualname": "BinarizeDescr.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'name': FieldInfo(annotation=Literal['binarize'], required=False, default='binarize'), 'kwargs': FieldInfo(annotation=BinarizeKwargs, required=True)}"}, "bioimageio.spec.model.v0_4.BinarizeDescr.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_4.BinarizeDescr.model_computed_fields", "modulename": "bioimageio.spec.model.v0_4", "qualname": "BinarizeDescr.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_4.ClipKwargs": {"fullname": "bioimageio.spec.model.v0_4.ClipKwargs", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ClipKwargs", "kind": "class", "doc": "
    base class for pre-/postprocessing key word arguments
    \n", "bases": "ProcessingKwargs"}, "bioimageio.spec.model.v0_4.ClipKwargs.min": {"fullname": "bioimageio.spec.model.v0_4.ClipKwargs.min", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ClipKwargs.min", "kind": "variable", "doc": "
    minimum value for clipping
    \n", "annotation": ": float"}, "bioimageio.spec.model.v0_4.ClipKwargs.max": {"fullname": "bioimageio.spec.model.v0_4.ClipKwargs.max", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ClipKwargs.max", "kind": "variable", "doc": "
    maximum value for clipping
    \n", "annotation": ": float"}, "bioimageio.spec.model.v0_4.ClipKwargs.model_config": {"fullname": "bioimageio.spec.model.v0_4.ClipKwargs.model_config", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ClipKwargs.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_4.ClipKwargs.model_fields": {"fullname": "bioimageio.spec.model.v0_4.ClipKwargs.model_fields", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ClipKwargs.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'min': FieldInfo(annotation=float, required=True), 'max': FieldInfo(annotation=float, required=True)}"}, "bioimageio.spec.model.v0_4.ClipKwargs.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_4.ClipKwargs.model_computed_fields", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ClipKwargs.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_4.ClipDescr": {"fullname": "bioimageio.spec.model.v0_4.ClipDescr", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ClipDescr", "kind": "class", "doc": "
    Set tensor values below min to min and above max to max.
    \n", "bases": "ProcessingDescrBase"}, "bioimageio.spec.model.v0_4.ClipDescr.name": {"fullname": "bioimageio.spec.model.v0_4.ClipDescr.name", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ClipDescr.name", "kind": "variable", "doc": "
    \n", "annotation": ": Literal['clip']"}, "bioimageio.spec.model.v0_4.ClipDescr.kwargs": {"fullname": "bioimageio.spec.model.v0_4.ClipDescr.kwargs", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ClipDescr.kwargs", "kind": "variable", "doc": "
    \n", "annotation": ": bioimageio.spec.model.v0_4.ClipKwargs"}, "bioimageio.spec.model.v0_4.ClipDescr.model_config": {"fullname": "bioimageio.spec.model.v0_4.ClipDescr.model_config", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ClipDescr.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_4.ClipDescr.model_fields": {"fullname": "bioimageio.spec.model.v0_4.ClipDescr.model_fields", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ClipDescr.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'name': FieldInfo(annotation=Literal['clip'], required=False, default='clip'), 'kwargs': FieldInfo(annotation=ClipKwargs, required=True)}"}, "bioimageio.spec.model.v0_4.ClipDescr.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_4.ClipDescr.model_computed_fields", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ClipDescr.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_4.ScaleLinearKwargs": {"fullname": "bioimageio.spec.model.v0_4.ScaleLinearKwargs", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ScaleLinearKwargs", "kind": "class", "doc": "
    base class for pre-/postprocessing key word arguments
    \n", "bases": "ProcessingKwargs"}, "bioimageio.spec.model.v0_4.ScaleLinearKwargs.axes": {"fullname": "bioimageio.spec.model.v0_4.ScaleLinearKwargs.axes", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ScaleLinearKwargs.axes", "kind": "variable", "doc": "
    The subset of axes to scale jointly.\nFor example xy to scale the two image axes for 2d data jointly.
    \n", "annotation": ": Annotated[Optional[Annotated[str, RestrictCharacters(alphabet='czyx'), AfterValidator(func=<function validate_unique_entries at 0x7afca0a94b80>)]], FieldInfo(annotation=NoneType, required=True, examples=['xy'])]"}, "bioimageio.spec.model.v0_4.ScaleLinearKwargs.gain": {"fullname": "bioimageio.spec.model.v0_4.ScaleLinearKwargs.gain", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ScaleLinearKwargs.gain", "kind": "variable", "doc": "
    multiplicative factor
    \n", "annotation": ": Union[float, List[float]]"}, "bioimageio.spec.model.v0_4.ScaleLinearKwargs.offset": {"fullname": "bioimageio.spec.model.v0_4.ScaleLinearKwargs.offset", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ScaleLinearKwargs.offset", "kind": "variable", "doc": "
    additive term
    \n", "annotation": ": Union[float, List[float]]"}, "bioimageio.spec.model.v0_4.ScaleLinearKwargs.either_gain_or_offset": {"fullname": "bioimageio.spec.model.v0_4.ScaleLinearKwargs.either_gain_or_offset", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ScaleLinearKwargs.either_gain_or_offset", "kind": "function", "doc": "
    \n", "signature": "(self) -> Self:", "funcdef": "def"}, "bioimageio.spec.model.v0_4.ScaleLinearKwargs.model_config": {"fullname": "bioimageio.spec.model.v0_4.ScaleLinearKwargs.model_config", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ScaleLinearKwargs.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_4.ScaleLinearKwargs.model_fields": {"fullname": "bioimageio.spec.model.v0_4.ScaleLinearKwargs.model_fields", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ScaleLinearKwargs.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'axes': FieldInfo(annotation=Union[Annotated[str, RestrictCharacters, AfterValidator], NoneType], required=False, examples=['xy']), 'gain': FieldInfo(annotation=Union[float, List[float]], required=False, default=1.0), 'offset': FieldInfo(annotation=Union[float, List[float]], required=False, default=0.0)}"}, "bioimageio.spec.model.v0_4.ScaleLinearKwargs.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_4.ScaleLinearKwargs.model_computed_fields", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ScaleLinearKwargs.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_4.ScaleLinearDescr": {"fullname": "bioimageio.spec.model.v0_4.ScaleLinearDescr", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ScaleLinearDescr", "kind": "class", "doc": "
    Fixed linear scaling.
    \n", "bases": "ProcessingDescrBase"}, "bioimageio.spec.model.v0_4.ScaleLinearDescr.name": {"fullname": "bioimageio.spec.model.v0_4.ScaleLinearDescr.name", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ScaleLinearDescr.name", "kind": "variable", "doc": "
    \n", "annotation": ": Literal['scale_linear']"}, "bioimageio.spec.model.v0_4.ScaleLinearDescr.kwargs": {"fullname": "bioimageio.spec.model.v0_4.ScaleLinearDescr.kwargs", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ScaleLinearDescr.kwargs", "kind": "variable", "doc": "
    \n", "annotation": ": bioimageio.spec.model.v0_4.ScaleLinearKwargs"}, "bioimageio.spec.model.v0_4.ScaleLinearDescr.model_config": {"fullname": "bioimageio.spec.model.v0_4.ScaleLinearDescr.model_config", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ScaleLinearDescr.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_4.ScaleLinearDescr.model_fields": {"fullname": "bioimageio.spec.model.v0_4.ScaleLinearDescr.model_fields", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ScaleLinearDescr.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'name': FieldInfo(annotation=Literal['scale_linear'], required=False, default='scale_linear'), 'kwargs': FieldInfo(annotation=ScaleLinearKwargs, required=True)}"}, "bioimageio.spec.model.v0_4.ScaleLinearDescr.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_4.ScaleLinearDescr.model_computed_fields", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ScaleLinearDescr.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_4.SigmoidDescr": {"fullname": "bioimageio.spec.model.v0_4.SigmoidDescr", "modulename": "bioimageio.spec.model.v0_4", "qualname": "SigmoidDescr", "kind": "class", "doc": "
    The logistic sigmoid funciton, a.k.a. expit function.
    \n", "bases": "ProcessingDescrBase"}, "bioimageio.spec.model.v0_4.SigmoidDescr.name": {"fullname": "bioimageio.spec.model.v0_4.SigmoidDescr.name", "modulename": "bioimageio.spec.model.v0_4", "qualname": "SigmoidDescr.name", "kind": "variable", "doc": "
    \n", "annotation": ": Literal['sigmoid']"}, "bioimageio.spec.model.v0_4.SigmoidDescr.kwargs": {"fullname": "bioimageio.spec.model.v0_4.SigmoidDescr.kwargs", "modulename": "bioimageio.spec.model.v0_4", "qualname": "SigmoidDescr.kwargs", "kind": "variable", "doc": "
    empty kwargs
    \n", "annotation": ": bioimageio.spec.model.v0_4.ProcessingKwargs"}, "bioimageio.spec.model.v0_4.SigmoidDescr.model_config": {"fullname": "bioimageio.spec.model.v0_4.SigmoidDescr.model_config", "modulename": "bioimageio.spec.model.v0_4", "qualname": "SigmoidDescr.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_4.SigmoidDescr.model_fields": {"fullname": "bioimageio.spec.model.v0_4.SigmoidDescr.model_fields", "modulename": "bioimageio.spec.model.v0_4", "qualname": "SigmoidDescr.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'name': FieldInfo(annotation=Literal['sigmoid'], required=False, default='sigmoid')}"}, "bioimageio.spec.model.v0_4.SigmoidDescr.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_4.SigmoidDescr.model_computed_fields", "modulename": "bioimageio.spec.model.v0_4", "qualname": "SigmoidDescr.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_4.ZeroMeanUnitVarianceKwargs": {"fullname": "bioimageio.spec.model.v0_4.ZeroMeanUnitVarianceKwargs", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ZeroMeanUnitVarianceKwargs", "kind": "class", "doc": "
    base class for pre-/postprocessing key word arguments
    \n", "bases": "ProcessingKwargs"}, "bioimageio.spec.model.v0_4.ZeroMeanUnitVarianceKwargs.mode": {"fullname": "bioimageio.spec.model.v0_4.ZeroMeanUnitVarianceKwargs.mode", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ZeroMeanUnitVarianceKwargs.mode", "kind": "variable", "doc": "
    Mode for computing mean and variance.\n|     mode    |             description              |\n| ----------- | ------------------------------------ |\n|   fixed     | Fixed values for mean and variance   |\n| per_dataset | Compute for the entire dataset       |\n| per_sample  | Compute for each sample individually |
    \n", "annotation": ": Literal['fixed', 'per_dataset', 'per_sample']"}, "bioimageio.spec.model.v0_4.ZeroMeanUnitVarianceKwargs.axes": {"fullname": "bioimageio.spec.model.v0_4.ZeroMeanUnitVarianceKwargs.axes", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ZeroMeanUnitVarianceKwargs.axes", "kind": "variable", "doc": "
    The subset of axes to normalize jointly.\nFor example xy to normalize the two image axes for 2d data jointly.
    \n", "annotation": ": Annotated[str, RestrictCharacters(alphabet='czyx'), AfterValidator(func=<function validate_unique_entries at 0x7afca0a94b80>), FieldInfo(annotation=NoneType, required=True, examples=['xy'])]"}, "bioimageio.spec.model.v0_4.ZeroMeanUnitVarianceKwargs.mean": {"fullname": "bioimageio.spec.model.v0_4.ZeroMeanUnitVarianceKwargs.mean", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ZeroMeanUnitVarianceKwargs.mean", "kind": "variable", "doc": "
    The mean value(s) to use for mode: fixed.\nFor example [1.1, 2.2, 3.3] in the case of a 3 channel image with axes: xy.
    \n", "annotation": ": Annotated[Union[float, Annotated[List[float], MinLen(min_length=1)], NoneType], FieldInfo(annotation=NoneType, required=True, examples=[(1.1, 2.2, 3.3)])]"}, "bioimageio.spec.model.v0_4.ZeroMeanUnitVarianceKwargs.std": {"fullname": "bioimageio.spec.model.v0_4.ZeroMeanUnitVarianceKwargs.std", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ZeroMeanUnitVarianceKwargs.std", "kind": "variable", "doc": "
    The standard deviation values to use for mode: fixed. Analogous to mean.
    \n", "annotation": ": Annotated[Union[float, Annotated[List[float], MinLen(min_length=1)], NoneType], FieldInfo(annotation=NoneType, required=True, examples=[(0.1, 0.2, 0.3)])]"}, "bioimageio.spec.model.v0_4.ZeroMeanUnitVarianceKwargs.eps": {"fullname": "bioimageio.spec.model.v0_4.ZeroMeanUnitVarianceKwargs.eps", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ZeroMeanUnitVarianceKwargs.eps", "kind": "variable", "doc": "
    epsilon for numeric stability: out = (tensor - mean) / (std + eps).
    \n", "annotation": ": Annotated[float, Interval(gt=0, ge=None, lt=None, le=0.1)]"}, "bioimageio.spec.model.v0_4.ZeroMeanUnitVarianceKwargs.mean_and_std_match_mode": {"fullname": "bioimageio.spec.model.v0_4.ZeroMeanUnitVarianceKwargs.mean_and_std_match_mode", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ZeroMeanUnitVarianceKwargs.mean_and_std_match_mode", "kind": "function", "doc": "
    \n", "signature": "(self) -> Self:", "funcdef": "def"}, "bioimageio.spec.model.v0_4.ZeroMeanUnitVarianceKwargs.model_config": {"fullname": "bioimageio.spec.model.v0_4.ZeroMeanUnitVarianceKwargs.model_config", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ZeroMeanUnitVarianceKwargs.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_4.ZeroMeanUnitVarianceKwargs.model_fields": {"fullname": "bioimageio.spec.model.v0_4.ZeroMeanUnitVarianceKwargs.model_fields", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ZeroMeanUnitVarianceKwargs.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'mode': FieldInfo(annotation=Literal['fixed', 'per_dataset', 'per_sample'], required=False, default='fixed'), 'axes': FieldInfo(annotation=str, required=True, examples=['xy'], metadata=[RestrictCharacters(alphabet='czyx'), AfterValidator(func=<function validate_unique_entries>)]), 'mean': FieldInfo(annotation=Union[float, Annotated[List[float], MinLen], NoneType], required=False, examples=[(1.1, 2.2, 3.3)]), 'std': FieldInfo(annotation=Union[float, Annotated[List[float], MinLen], NoneType], required=False, examples=[(0.1, 0.2, 0.3)]), 'eps': FieldInfo(annotation=float, required=False, default=1e-06, metadata=[Interval(gt=0, ge=None, lt=None, le=0.1)])}"}, "bioimageio.spec.model.v0_4.ZeroMeanUnitVarianceKwargs.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_4.ZeroMeanUnitVarianceKwargs.model_computed_fields", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ZeroMeanUnitVarianceKwargs.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_4.ZeroMeanUnitVarianceDescr": {"fullname": "bioimageio.spec.model.v0_4.ZeroMeanUnitVarianceDescr", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ZeroMeanUnitVarianceDescr", "kind": "class", "doc": "
    Subtract mean and divide by variance.
    \n", "bases": "ProcessingDescrBase"}, "bioimageio.spec.model.v0_4.ZeroMeanUnitVarianceDescr.name": {"fullname": "bioimageio.spec.model.v0_4.ZeroMeanUnitVarianceDescr.name", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ZeroMeanUnitVarianceDescr.name", "kind": "variable", "doc": "
    \n", "annotation": ": Literal['zero_mean_unit_variance']"}, "bioimageio.spec.model.v0_4.ZeroMeanUnitVarianceDescr.kwargs": {"fullname": "bioimageio.spec.model.v0_4.ZeroMeanUnitVarianceDescr.kwargs", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ZeroMeanUnitVarianceDescr.kwargs", "kind": "variable", "doc": "
    \n", "annotation": ": bioimageio.spec.model.v0_4.ZeroMeanUnitVarianceKwargs"}, "bioimageio.spec.model.v0_4.ZeroMeanUnitVarianceDescr.model_config": {"fullname": "bioimageio.spec.model.v0_4.ZeroMeanUnitVarianceDescr.model_config", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ZeroMeanUnitVarianceDescr.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_4.ZeroMeanUnitVarianceDescr.model_fields": {"fullname": "bioimageio.spec.model.v0_4.ZeroMeanUnitVarianceDescr.model_fields", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ZeroMeanUnitVarianceDescr.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'name': FieldInfo(annotation=Literal['zero_mean_unit_variance'], required=False, default='zero_mean_unit_variance'), 'kwargs': FieldInfo(annotation=ZeroMeanUnitVarianceKwargs, required=True)}"}, "bioimageio.spec.model.v0_4.ZeroMeanUnitVarianceDescr.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_4.ZeroMeanUnitVarianceDescr.model_computed_fields", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ZeroMeanUnitVarianceDescr.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_4.ScaleRangeKwargs": {"fullname": "bioimageio.spec.model.v0_4.ScaleRangeKwargs", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ScaleRangeKwargs", "kind": "class", "doc": "
    base class for pre-/postprocessing key word arguments
    \n", "bases": "ProcessingKwargs"}, "bioimageio.spec.model.v0_4.ScaleRangeKwargs.mode": {"fullname": "bioimageio.spec.model.v0_4.ScaleRangeKwargs.mode", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ScaleRangeKwargs.mode", "kind": "variable", "doc": "
    Mode for computing percentiles.\n|     mode    |             description              |\n| ----------- | ------------------------------------ |\n| per_dataset | compute for the entire dataset       |\n| per_sample  | compute for each sample individually |
    \n", "annotation": ": Literal['per_dataset', 'per_sample']"}, "bioimageio.spec.model.v0_4.ScaleRangeKwargs.axes": {"fullname": "bioimageio.spec.model.v0_4.ScaleRangeKwargs.axes", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ScaleRangeKwargs.axes", "kind": "variable", "doc": "
    The subset of axes to normalize jointly.\nFor example xy to normalize the two image axes for 2d data jointly.
    \n", "annotation": ": Annotated[str, RestrictCharacters(alphabet='czyx'), AfterValidator(func=<function validate_unique_entries at 0x7afca0a94b80>), FieldInfo(annotation=NoneType, required=True, examples=['xy'])]"}, "bioimageio.spec.model.v0_4.ScaleRangeKwargs.min_percentile": {"fullname": "bioimageio.spec.model.v0_4.ScaleRangeKwargs.min_percentile", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ScaleRangeKwargs.min_percentile", "kind": "variable", "doc": "
    The lower percentile used for normalization.
    \n", "annotation": ": Annotated[Union[int, float], Interval(gt=None, ge=0, lt=100, le=None)]"}, "bioimageio.spec.model.v0_4.ScaleRangeKwargs.max_percentile": {"fullname": "bioimageio.spec.model.v0_4.ScaleRangeKwargs.max_percentile", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ScaleRangeKwargs.max_percentile", "kind": "variable", "doc": "
    The upper percentile used for normalization\nHas to be bigger than min_percentile.\nThe range is 1 to 100 instead of 0 to 100 to avoid mistakenly\naccepting percentiles specified in the range 0.0 to 1.0.
    \n", "annotation": ": Annotated[Union[int, float], Interval(gt=1, ge=None, lt=None, le=100)]"}, "bioimageio.spec.model.v0_4.ScaleRangeKwargs.min_smaller_max": {"fullname": "bioimageio.spec.model.v0_4.ScaleRangeKwargs.min_smaller_max", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ScaleRangeKwargs.min_smaller_max", "kind": "function", "doc": "
    \n", "signature": "(self, info: pydantic_core.core_schema.ValidationInfo) -> Self:", "funcdef": "def"}, "bioimageio.spec.model.v0_4.ScaleRangeKwargs.eps": {"fullname": "bioimageio.spec.model.v0_4.ScaleRangeKwargs.eps", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ScaleRangeKwargs.eps", "kind": "variable", "doc": "
    Epsilon for numeric stability.\nout = (tensor - v_lower) / (v_upper - v_lower + eps);\nwith v_lower,v_upper values at the respective percentiles.
    \n", "annotation": ": Annotated[float, Interval(gt=0, ge=None, lt=None, le=0.1)]"}, "bioimageio.spec.model.v0_4.ScaleRangeKwargs.reference_tensor": {"fullname": "bioimageio.spec.model.v0_4.ScaleRangeKwargs.reference_tensor", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ScaleRangeKwargs.reference_tensor", "kind": "variable", "doc": "
    Tensor name to compute the percentiles from. Default: The tensor itself.\nFor any tensor in inputs only input tensor references are allowed.\nFor a tensor in outputs only input tensor refereences are allowed if mode: per_dataset
    \n", "annotation": ": Optional[bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate]]]]"}, "bioimageio.spec.model.v0_4.ScaleRangeKwargs.model_config": {"fullname": "bioimageio.spec.model.v0_4.ScaleRangeKwargs.model_config", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ScaleRangeKwargs.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_4.ScaleRangeKwargs.model_fields": {"fullname": "bioimageio.spec.model.v0_4.ScaleRangeKwargs.model_fields", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ScaleRangeKwargs.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'mode': FieldInfo(annotation=Literal['per_dataset', 'per_sample'], required=True), 'axes': FieldInfo(annotation=str, required=True, examples=['xy'], metadata=[RestrictCharacters(alphabet='czyx'), AfterValidator(func=<function validate_unique_entries>)]), 'min_percentile': FieldInfo(annotation=Union[int, float], required=False, default=0.0, metadata=[Interval(gt=None, ge=0, lt=100, le=None)]), 'max_percentile': FieldInfo(annotation=Union[int, float], required=False, default=100.0, metadata=[Interval(gt=1, ge=None, lt=None, le=100)]), 'eps': FieldInfo(annotation=float, required=False, default=1e-06, metadata=[Interval(gt=0, ge=None, lt=None, le=0.1)]), 'reference_tensor': FieldInfo(annotation=Union[ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate]]], NoneType], required=False)}"}, "bioimageio.spec.model.v0_4.ScaleRangeKwargs.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_4.ScaleRangeKwargs.model_computed_fields", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ScaleRangeKwargs.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_4.ScaleRangeDescr": {"fullname": "bioimageio.spec.model.v0_4.ScaleRangeDescr", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ScaleRangeDescr", "kind": "class", "doc": "
    Scale with percentiles.
    \n", "bases": "ProcessingDescrBase"}, "bioimageio.spec.model.v0_4.ScaleRangeDescr.name": {"fullname": "bioimageio.spec.model.v0_4.ScaleRangeDescr.name", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ScaleRangeDescr.name", "kind": "variable", "doc": "
    \n", "annotation": ": Literal['scale_range']"}, "bioimageio.spec.model.v0_4.ScaleRangeDescr.kwargs": {"fullname": "bioimageio.spec.model.v0_4.ScaleRangeDescr.kwargs", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ScaleRangeDescr.kwargs", "kind": "variable", "doc": "
    \n", "annotation": ": bioimageio.spec.model.v0_4.ScaleRangeKwargs"}, "bioimageio.spec.model.v0_4.ScaleRangeDescr.model_config": {"fullname": "bioimageio.spec.model.v0_4.ScaleRangeDescr.model_config", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ScaleRangeDescr.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_4.ScaleRangeDescr.model_fields": {"fullname": "bioimageio.spec.model.v0_4.ScaleRangeDescr.model_fields", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ScaleRangeDescr.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'name': FieldInfo(annotation=Literal['scale_range'], required=False, default='scale_range'), 'kwargs': FieldInfo(annotation=ScaleRangeKwargs, required=True)}"}, "bioimageio.spec.model.v0_4.ScaleRangeDescr.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_4.ScaleRangeDescr.model_computed_fields", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ScaleRangeDescr.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_4.ScaleMeanVarianceKwargs": {"fullname": "bioimageio.spec.model.v0_4.ScaleMeanVarianceKwargs", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ScaleMeanVarianceKwargs", "kind": "class", "doc": "
    base class for pre-/postprocessing key word arguments
    \n", "bases": "ProcessingKwargs"}, "bioimageio.spec.model.v0_4.ScaleMeanVarianceKwargs.mode": {"fullname": "bioimageio.spec.model.v0_4.ScaleMeanVarianceKwargs.mode", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ScaleMeanVarianceKwargs.mode", "kind": "variable", "doc": "
    Mode for computing mean and variance.\n|     mode    |             description              |\n| ----------- | ------------------------------------ |\n| per_dataset | Compute for the entire dataset       |\n| per_sample  | Compute for each sample individually |
    \n", "annotation": ": Literal['per_dataset', 'per_sample']"}, "bioimageio.spec.model.v0_4.ScaleMeanVarianceKwargs.reference_tensor": {"fullname": "bioimageio.spec.model.v0_4.ScaleMeanVarianceKwargs.reference_tensor", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ScaleMeanVarianceKwargs.reference_tensor", "kind": "variable", "doc": "
    Name of tensor to match.
    \n", "annotation": ": bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate]]]"}, "bioimageio.spec.model.v0_4.ScaleMeanVarianceKwargs.axes": {"fullname": "bioimageio.spec.model.v0_4.ScaleMeanVarianceKwargs.axes", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ScaleMeanVarianceKwargs.axes", "kind": "variable", "doc": "
    The subset of axes to scale jointly.\nFor example xy to normalize the two image axes for 2d data jointly.\nDefault: scale all non-batch axes jointly.
    \n", "annotation": ": Annotated[Optional[Annotated[str, RestrictCharacters(alphabet='czyx'), AfterValidator(func=<function validate_unique_entries at 0x7afca0a94b80>)]], FieldInfo(annotation=NoneType, required=True, examples=['xy'])]"}, "bioimageio.spec.model.v0_4.ScaleMeanVarianceKwargs.eps": {"fullname": "bioimageio.spec.model.v0_4.ScaleMeanVarianceKwargs.eps", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ScaleMeanVarianceKwargs.eps", "kind": "variable", "doc": "
    Epsilon for numeric stability:\n\"`out  = (tensor - mean) / (std + eps) * (ref_std + eps) + ref_mean.
    \n", "annotation": ": Annotated[float, Interval(gt=0, ge=None, lt=None, le=0.1)]"}, "bioimageio.spec.model.v0_4.ScaleMeanVarianceKwargs.model_config": {"fullname": "bioimageio.spec.model.v0_4.ScaleMeanVarianceKwargs.model_config", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ScaleMeanVarianceKwargs.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_4.ScaleMeanVarianceKwargs.model_fields": {"fullname": "bioimageio.spec.model.v0_4.ScaleMeanVarianceKwargs.model_fields", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ScaleMeanVarianceKwargs.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'mode': FieldInfo(annotation=Literal['per_dataset', 'per_sample'], required=True), 'reference_tensor': FieldInfo(annotation=ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate]]], required=True), 'axes': FieldInfo(annotation=Union[Annotated[str, RestrictCharacters, AfterValidator], NoneType], required=False, examples=['xy']), 'eps': FieldInfo(annotation=float, required=False, default=1e-06, metadata=[Interval(gt=0, ge=None, lt=None, le=0.1)])}"}, "bioimageio.spec.model.v0_4.ScaleMeanVarianceKwargs.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_4.ScaleMeanVarianceKwargs.model_computed_fields", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ScaleMeanVarianceKwargs.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_4.ScaleMeanVarianceDescr": {"fullname": "bioimageio.spec.model.v0_4.ScaleMeanVarianceDescr", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ScaleMeanVarianceDescr", "kind": "class", "doc": "
    Scale the tensor s.t. its mean and variance match a reference tensor.
    \n", "bases": "ProcessingDescrBase"}, "bioimageio.spec.model.v0_4.ScaleMeanVarianceDescr.name": {"fullname": "bioimageio.spec.model.v0_4.ScaleMeanVarianceDescr.name", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ScaleMeanVarianceDescr.name", "kind": "variable", "doc": "
    \n", "annotation": ": Literal['scale_mean_variance']"}, "bioimageio.spec.model.v0_4.ScaleMeanVarianceDescr.kwargs": {"fullname": "bioimageio.spec.model.v0_4.ScaleMeanVarianceDescr.kwargs", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ScaleMeanVarianceDescr.kwargs", "kind": "variable", "doc": "
    \n", "annotation": ": bioimageio.spec.model.v0_4.ScaleMeanVarianceKwargs"}, "bioimageio.spec.model.v0_4.ScaleMeanVarianceDescr.model_config": {"fullname": "bioimageio.spec.model.v0_4.ScaleMeanVarianceDescr.model_config", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ScaleMeanVarianceDescr.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_4.ScaleMeanVarianceDescr.model_fields": {"fullname": "bioimageio.spec.model.v0_4.ScaleMeanVarianceDescr.model_fields", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ScaleMeanVarianceDescr.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'name': FieldInfo(annotation=Literal['scale_mean_variance'], required=False, default='scale_mean_variance'), 'kwargs': FieldInfo(annotation=ScaleMeanVarianceKwargs, required=True)}"}, "bioimageio.spec.model.v0_4.ScaleMeanVarianceDescr.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_4.ScaleMeanVarianceDescr.model_computed_fields", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ScaleMeanVarianceDescr.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_4.PreprocessingDescr": {"fullname": "bioimageio.spec.model.v0_4.PreprocessingDescr", "modulename": "bioimageio.spec.model.v0_4", "qualname": "PreprocessingDescr", "kind": "variable", "doc": "
    \n", "default_value": "typing.Annotated[typing.Union[bioimageio.spec.model.v0_4.BinarizeDescr, bioimageio.spec.model.v0_4.ClipDescr, bioimageio.spec.model.v0_4.ScaleLinearDescr, bioimageio.spec.model.v0_4.SigmoidDescr, bioimageio.spec.model.v0_4.ZeroMeanUnitVarianceDescr, bioimageio.spec.model.v0_4.ScaleRangeDescr], FieldInfo(annotation=NoneType, required=True, discriminator='name')]"}, "bioimageio.spec.model.v0_4.PostprocessingDescr": {"fullname": "bioimageio.spec.model.v0_4.PostprocessingDescr", "modulename": "bioimageio.spec.model.v0_4", "qualname": "PostprocessingDescr", "kind": "variable", "doc": "
    \n", "default_value": "typing.Annotated[typing.Union[bioimageio.spec.model.v0_4.BinarizeDescr, bioimageio.spec.model.v0_4.ClipDescr, bioimageio.spec.model.v0_4.ScaleLinearDescr, bioimageio.spec.model.v0_4.SigmoidDescr, bioimageio.spec.model.v0_4.ZeroMeanUnitVarianceDescr, bioimageio.spec.model.v0_4.ScaleRangeDescr, bioimageio.spec.model.v0_4.ScaleMeanVarianceDescr], FieldInfo(annotation=NoneType, required=True, discriminator='name')]"}, "bioimageio.spec.model.v0_4.InputTensorDescr": {"fullname": "bioimageio.spec.model.v0_4.InputTensorDescr", "modulename": "bioimageio.spec.model.v0_4", "qualname": "InputTensorDescr", "kind": "class", "doc": "
    Subpart of a resource description
    \n", "bases": "TensorDescrBase"}, "bioimageio.spec.model.v0_4.InputTensorDescr.data_type": {"fullname": "bioimageio.spec.model.v0_4.InputTensorDescr.data_type", "modulename": "bioimageio.spec.model.v0_4", "qualname": "InputTensorDescr.data_type", "kind": "variable", "doc": "
    For now an input tensor is expected to be given as float32.\nThe data flow in bioimage.io models is explained\nin this diagram..
    \n", "annotation": ": Literal['float32', 'uint8', 'uint16']"}, "bioimageio.spec.model.v0_4.InputTensorDescr.shape": {"fullname": "bioimageio.spec.model.v0_4.InputTensorDescr.shape", "modulename": "bioimageio.spec.model.v0_4", "qualname": "InputTensorDescr.shape", "kind": "variable", "doc": "
    Specification of input tensor shape.
    \n", "annotation": ": Annotated[Union[Sequence[int], bioimageio.spec.model.v0_4.ParameterizedInputShape], FieldInfo(annotation=NoneType, required=True, examples=[(1, 512, 512, 1), {'min': (1, 64, 64, 1), 'step': (0, 32, 32, 0)}])]"}, "bioimageio.spec.model.v0_4.InputTensorDescr.preprocessing": {"fullname": "bioimageio.spec.model.v0_4.InputTensorDescr.preprocessing", "modulename": "bioimageio.spec.model.v0_4", "qualname": "InputTensorDescr.preprocessing", "kind": "variable", "doc": "
    Description of how this input should be preprocessed.
    \n", "annotation": ": List[Annotated[Union[bioimageio.spec.model.v0_4.BinarizeDescr, bioimageio.spec.model.v0_4.ClipDescr, bioimageio.spec.model.v0_4.ScaleLinearDescr, bioimageio.spec.model.v0_4.SigmoidDescr, bioimageio.spec.model.v0_4.ZeroMeanUnitVarianceDescr, bioimageio.spec.model.v0_4.ScaleRangeDescr], FieldInfo(annotation=NoneType, required=True, discriminator='name')]]"}, "bioimageio.spec.model.v0_4.InputTensorDescr.zero_batch_step_and_one_batch_size": {"fullname": "bioimageio.spec.model.v0_4.InputTensorDescr.zero_batch_step_and_one_batch_size", "modulename": "bioimageio.spec.model.v0_4", "qualname": "InputTensorDescr.zero_batch_step_and_one_batch_size", "kind": "function", "doc": "
    \n", "signature": "(self) -> Self:", "funcdef": "def"}, "bioimageio.spec.model.v0_4.InputTensorDescr.validate_preprocessing_kwargs": {"fullname": "bioimageio.spec.model.v0_4.InputTensorDescr.validate_preprocessing_kwargs", "modulename": "bioimageio.spec.model.v0_4", "qualname": "InputTensorDescr.validate_preprocessing_kwargs", "kind": "function", "doc": "
    \n", "signature": "(self) -> Self:", "funcdef": "def"}, "bioimageio.spec.model.v0_4.InputTensorDescr.model_config": {"fullname": "bioimageio.spec.model.v0_4.InputTensorDescr.model_config", "modulename": "bioimageio.spec.model.v0_4", "qualname": "InputTensorDescr.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_4.InputTensorDescr.model_fields": {"fullname": "bioimageio.spec.model.v0_4.InputTensorDescr.model_fields", "modulename": "bioimageio.spec.model.v0_4", "qualname": "InputTensorDescr.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'name': FieldInfo(annotation=ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate]]], required=True), 'description': FieldInfo(annotation=str, required=False, default=''), 'axes': FieldInfo(annotation=str, required=True, metadata=[RestrictCharacters(alphabet='bitczyx'), AfterValidator(func=<function validate_unique_entries>)]), 'data_range': FieldInfo(annotation=Union[Tuple[Annotated[float, AllowInfNan(allow_inf_nan=True)], Annotated[float, AllowInfNan(allow_inf_nan=True)]], NoneType], required=False), 'data_type': FieldInfo(annotation=Literal['float32', 'uint8', 'uint16'], required=True), 'shape': FieldInfo(annotation=Union[Sequence[int], ParameterizedInputShape], required=True, examples=[(1, 512, 512, 1), {'min': (1, 64, 64, 1), 'step': (0, 32, 32, 0)}]), 'preprocessing': FieldInfo(annotation=List[Annotated[Union[BinarizeDescr, ClipDescr, ScaleLinearDescr, SigmoidDescr, ZeroMeanUnitVarianceDescr, ScaleRangeDescr], FieldInfo(annotation=NoneType, required=True, discriminator='name')]], required=False, default_factory=list)}"}, "bioimageio.spec.model.v0_4.InputTensorDescr.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_4.InputTensorDescr.model_computed_fields", "modulename": "bioimageio.spec.model.v0_4", "qualname": "InputTensorDescr.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_4.OutputTensorDescr": {"fullname": "bioimageio.spec.model.v0_4.OutputTensorDescr", "modulename": "bioimageio.spec.model.v0_4", "qualname": "OutputTensorDescr", "kind": "class", "doc": "
    Subpart of a resource description
    \n", "bases": "TensorDescrBase"}, "bioimageio.spec.model.v0_4.OutputTensorDescr.data_type": {"fullname": "bioimageio.spec.model.v0_4.OutputTensorDescr.data_type", "modulename": "bioimageio.spec.model.v0_4", "qualname": "OutputTensorDescr.data_type", "kind": "variable", "doc": "
    Data type.\nThe data flow in bioimage.io models is explained\nin this diagram..
    \n", "annotation": ": Literal['float32', 'float64', 'uint8', 'int8', 'uint16', 'int16', 'uint32', 'int32', 'uint64', 'int64', 'bool']"}, "bioimageio.spec.model.v0_4.OutputTensorDescr.shape": {"fullname": "bioimageio.spec.model.v0_4.OutputTensorDescr.shape", "modulename": "bioimageio.spec.model.v0_4", "qualname": "OutputTensorDescr.shape", "kind": "variable", "doc": "
    Output tensor shape.
    \n", "annotation": ": Union[Sequence[int], bioimageio.spec.model.v0_4.ImplicitOutputShape]"}, "bioimageio.spec.model.v0_4.OutputTensorDescr.halo": {"fullname": "bioimageio.spec.model.v0_4.OutputTensorDescr.halo", "modulename": "bioimageio.spec.model.v0_4", "qualname": "OutputTensorDescr.halo", "kind": "variable", "doc": "
    The halo that should be cropped from the output tensor to avoid boundary effects.\nThe halo is to be cropped from both sides, i.e. shape_after_crop = shape - 2 * halo.\nTo document a halo that is already cropped by the model shape.offset has to be used instead.
    \n", "annotation": ": Optional[Sequence[int]]"}, "bioimageio.spec.model.v0_4.OutputTensorDescr.postprocessing": {"fullname": "bioimageio.spec.model.v0_4.OutputTensorDescr.postprocessing", "modulename": "bioimageio.spec.model.v0_4", "qualname": "OutputTensorDescr.postprocessing", "kind": "variable", "doc": "
    Description of how this output should be postprocessed.
    \n", "annotation": ": List[Annotated[Union[bioimageio.spec.model.v0_4.BinarizeDescr, bioimageio.spec.model.v0_4.ClipDescr, bioimageio.spec.model.v0_4.ScaleLinearDescr, bioimageio.spec.model.v0_4.SigmoidDescr, bioimageio.spec.model.v0_4.ZeroMeanUnitVarianceDescr, bioimageio.spec.model.v0_4.ScaleRangeDescr, bioimageio.spec.model.v0_4.ScaleMeanVarianceDescr], FieldInfo(annotation=NoneType, required=True, discriminator='name')]]"}, "bioimageio.spec.model.v0_4.OutputTensorDescr.matching_halo_length": {"fullname": "bioimageio.spec.model.v0_4.OutputTensorDescr.matching_halo_length", "modulename": "bioimageio.spec.model.v0_4", "qualname": "OutputTensorDescr.matching_halo_length", "kind": "function", "doc": "
    \n", "signature": "(self) -> Self:", "funcdef": "def"}, "bioimageio.spec.model.v0_4.OutputTensorDescr.validate_postprocessing_kwargs": {"fullname": "bioimageio.spec.model.v0_4.OutputTensorDescr.validate_postprocessing_kwargs", "modulename": "bioimageio.spec.model.v0_4", "qualname": "OutputTensorDescr.validate_postprocessing_kwargs", "kind": "function", "doc": "
    \n", "signature": "(self) -> Self:", "funcdef": "def"}, "bioimageio.spec.model.v0_4.OutputTensorDescr.model_config": {"fullname": "bioimageio.spec.model.v0_4.OutputTensorDescr.model_config", "modulename": "bioimageio.spec.model.v0_4", "qualname": "OutputTensorDescr.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_4.OutputTensorDescr.model_fields": {"fullname": "bioimageio.spec.model.v0_4.OutputTensorDescr.model_fields", "modulename": "bioimageio.spec.model.v0_4", "qualname": "OutputTensorDescr.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'name': FieldInfo(annotation=ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate]]], required=True), 'description': FieldInfo(annotation=str, required=False, default=''), 'axes': FieldInfo(annotation=str, required=True, metadata=[RestrictCharacters(alphabet='bitczyx'), AfterValidator(func=<function validate_unique_entries>)]), 'data_range': FieldInfo(annotation=Union[Tuple[Annotated[float, AllowInfNan(allow_inf_nan=True)], Annotated[float, AllowInfNan(allow_inf_nan=True)]], NoneType], required=False), 'data_type': FieldInfo(annotation=Literal['float32', 'float64', 'uint8', 'int8', 'uint16', 'int16', 'uint32', 'int32', 'uint64', 'int64', 'bool'], required=True), 'shape': FieldInfo(annotation=Union[Sequence[int], ImplicitOutputShape], required=True), 'halo': FieldInfo(annotation=Union[Sequence[int], NoneType], required=False), 'postprocessing': FieldInfo(annotation=List[Annotated[Union[BinarizeDescr, ClipDescr, ScaleLinearDescr, SigmoidDescr, ZeroMeanUnitVarianceDescr, ScaleRangeDescr, ScaleMeanVarianceDescr], FieldInfo(annotation=NoneType, required=True, discriminator='name')]], required=False, default_factory=list)}"}, "bioimageio.spec.model.v0_4.OutputTensorDescr.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_4.OutputTensorDescr.model_computed_fields", "modulename": "bioimageio.spec.model.v0_4", "qualname": "OutputTensorDescr.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_4.KnownRunMode": {"fullname": "bioimageio.spec.model.v0_4.KnownRunMode", "modulename": "bioimageio.spec.model.v0_4", "qualname": "KnownRunMode", "kind": "variable", "doc": "
    \n", "default_value": "typing.Literal['deepimagej']"}, "bioimageio.spec.model.v0_4.RunMode": {"fullname": "bioimageio.spec.model.v0_4.RunMode", "modulename": "bioimageio.spec.model.v0_4", "qualname": "RunMode", "kind": "class", "doc": "
    Subpart of a resource description
    \n", "bases": "bioimageio.spec._internal.node.Node"}, "bioimageio.spec.model.v0_4.RunMode.name": {"fullname": "bioimageio.spec.model.v0_4.RunMode.name", "modulename": "bioimageio.spec.model.v0_4", "qualname": "RunMode.name", "kind": "variable", "doc": "
    Run mode name
    \n", "annotation": ": Annotated[Union[Literal['deepimagej'], str], AfterWarner(func=<function as_warning.<locals>.wrapper at 0x7afc91ef3060>, severity=30, msg="Unknown run mode '{value}'.", context={'typ': Literal['deepimagej']})]"}, "bioimageio.spec.model.v0_4.RunMode.kwargs": {"fullname": "bioimageio.spec.model.v0_4.RunMode.kwargs", "modulename": "bioimageio.spec.model.v0_4", "qualname": "RunMode.kwargs", "kind": "variable", "doc": "
    Run mode specific key word arguments
    \n", "annotation": ": Dict[str, Any]"}, "bioimageio.spec.model.v0_4.RunMode.model_config": {"fullname": "bioimageio.spec.model.v0_4.RunMode.model_config", "modulename": "bioimageio.spec.model.v0_4", "qualname": "RunMode.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_4.RunMode.model_fields": {"fullname": "bioimageio.spec.model.v0_4.RunMode.model_fields", "modulename": "bioimageio.spec.model.v0_4", "qualname": "RunMode.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'name': FieldInfo(annotation=Union[Literal['deepimagej'], str], required=True, metadata=[AfterWarner(func=<function as_warning.<locals>.wrapper>, severity=30, msg="Unknown run mode '{value}'.", context={'typ': typing.Literal['deepimagej']})]), 'kwargs': FieldInfo(annotation=Dict[str, Any], required=False, default_factory=dict)}"}, "bioimageio.spec.model.v0_4.RunMode.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_4.RunMode.model_computed_fields", "modulename": "bioimageio.spec.model.v0_4", "qualname": "RunMode.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_4.LinkedModel": {"fullname": "bioimageio.spec.model.v0_4.LinkedModel", "modulename": "bioimageio.spec.model.v0_4", "qualname": "LinkedModel", "kind": "class", "doc": "
    Reference to a bioimage.io model.
    \n", "bases": "bioimageio.spec._internal.node.Node"}, "bioimageio.spec.model.v0_4.LinkedModel.id": {"fullname": "bioimageio.spec.model.v0_4.LinkedModel.id", "modulename": "bioimageio.spec.model.v0_4", "qualname": "LinkedModel.id", "kind": "variable", "doc": "
    A valid model id from the bioimage.io collection.
    \n", "annotation": ": bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]]"}, "bioimageio.spec.model.v0_4.LinkedModel.version_number": {"fullname": "bioimageio.spec.model.v0_4.LinkedModel.version_number", "modulename": "bioimageio.spec.model.v0_4", "qualname": "LinkedModel.version_number", "kind": "variable", "doc": "
    version number (n-th published version, not the semantic version) of linked model
    \n", "annotation": ": Optional[int]"}, "bioimageio.spec.model.v0_4.LinkedModel.model_config": {"fullname": "bioimageio.spec.model.v0_4.LinkedModel.model_config", "modulename": "bioimageio.spec.model.v0_4", "qualname": "LinkedModel.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_4.LinkedModel.model_fields": {"fullname": "bioimageio.spec.model.v0_4.LinkedModel.model_fields", "modulename": "bioimageio.spec.model.v0_4", "qualname": "LinkedModel.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'id': FieldInfo(annotation=ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]], required=True), 'version_number': FieldInfo(annotation=Union[int, NoneType], required=False)}"}, "bioimageio.spec.model.v0_4.LinkedModel.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_4.LinkedModel.model_computed_fields", "modulename": "bioimageio.spec.model.v0_4", "qualname": "LinkedModel.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_4.ModelDescr": {"fullname": "bioimageio.spec.model.v0_4.ModelDescr", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ModelDescr", "kind": "class", "doc": "
    Specification of the fields used in a bioimage.io-compliant RDF that describes AI models with pretrained weights.
    \n\n
    These fields are typically stored in a YAML file which we call a model resource description file (model RDF).
    \n", "bases": "bioimageio.spec.generic.v0_2.GenericModelDescrBase"}, "bioimageio.spec.model.v0_4.ModelDescr.format_version": {"fullname": "bioimageio.spec.model.v0_4.ModelDescr.format_version", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ModelDescr.format_version", "kind": "variable", "doc": "
    Version of the bioimage.io model description specification used.\nWhen creating a new model always use the latest micro/patch version described here.\nThe format_version is important for any consumer software to understand how to parse the fields.
    \n", "annotation": ": Literal['0.4.10']"}, "bioimageio.spec.model.v0_4.ModelDescr.type": {"fullname": "bioimageio.spec.model.v0_4.ModelDescr.type", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ModelDescr.type", "kind": "variable", "doc": "
    Specialized resource type 'model'
    \n", "annotation": ": Literal['model']"}, "bioimageio.spec.model.v0_4.ModelDescr.id": {"fullname": "bioimageio.spec.model.v0_4.ModelDescr.id", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ModelDescr.id", "kind": "variable", "doc": "
    Model zoo (bioimage.io) wide, unique identifier (assigned by bioimage.io)
    \n", "annotation": ": Optional[bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]]]"}, "bioimageio.spec.model.v0_4.ModelDescr.authors": {"fullname": "bioimageio.spec.model.v0_4.ModelDescr.authors", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ModelDescr.authors", "kind": "variable", "doc": "
    The authors are the creators of the model RDF and the primary points of contact.
    \n", "annotation": ": Annotated[List[bioimageio.spec.generic.v0_2.Author], MinLen(min_length=1)]"}, "bioimageio.spec.model.v0_4.ModelDescr.documentation": {"fullname": "bioimageio.spec.model.v0_4.ModelDescr.documentation", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ModelDescr.documentation", "kind": "variable", "doc": "
    \u2208\ud83d\udce6 URL or relative path to a markdown file with additional documentation.\nThe recommended documentation file name is README.md. An .md suffix is mandatory.\nThe documentation should include a '[#[#]]# Validation' (sub)section\nwith details on how to quantitatively validate the model on unseen data.
    \n", "annotation": ": Annotated[Union[Annotated[pathlib.Path, PathType(path_type='file')], bioimageio.spec._internal.io.RelativeFilePath, bioimageio.spec._internal.url.HttpUrl, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator(func=<function wo_special_file_name at 0x7afca0d90540>), PlainSerializer(func=<function _package at 0x7afca0d91760>, return_type=PydanticUndefined, when_used='unless-none'), FieldInfo(annotation=NoneType, required=True, examples=['https://raw.githubusercontent.com/bioimage-io/spec-bioimage-io/main/example_descriptions/models/unet2d_nuclei_broad/README.md', 'README.md'])]"}, "bioimageio.spec.model.v0_4.ModelDescr.inputs": {"fullname": "bioimageio.spec.model.v0_4.ModelDescr.inputs", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ModelDescr.inputs", "kind": "variable", "doc": "
    Describes the input tensors expected by this model.
    \n", "annotation": ": Annotated[List[bioimageio.spec.model.v0_4.InputTensorDescr], MinLen(min_length=1)]"}, "bioimageio.spec.model.v0_4.ModelDescr.license": {"fullname": "bioimageio.spec.model.v0_4.ModelDescr.license", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ModelDescr.license", "kind": "variable", "doc": "
    A SPDX license identifier.\nWe do notsupport custom license beyond the SPDX license list, if you need that please\nopen a GitHub issue to discuss your intentions with the community.
    \n", "annotation": ": Annotated[Union[bioimageio.spec._internal.license_id.LicenseId, str], AfterWarner(func=<function as_warning.<locals>.wrapper at 0x7afc91ef31a0>, severity=30, msg="Unknown license id '{value}'.", context={'typ': <class 'bioimageio.spec._internal.license_id.LicenseId'>}), FieldInfo(annotation=NoneType, required=True, examples=['CC-BY-4.0', 'MIT', 'BSD-2-Clause'])]"}, "bioimageio.spec.model.v0_4.ModelDescr.name": {"fullname": "bioimageio.spec.model.v0_4.ModelDescr.name", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ModelDescr.name", "kind": "variable", "doc": "
    A human-readable name of this model.\nIt should be no longer than 64 characters and only contain letter, number, underscore, minus or space characters.
    \n", "annotation": ": Annotated[str, MinLen(min_length=1), AfterWarner(func=<function as_warning.<locals>.wrapper at 0x7afc91ef2340>, severity=20, msg='Name shorter than 5 characters.', context={'typ': Annotated[Any, MinLen(min_length=5)]}), AfterWarner(func=<function as_warning.<locals>.wrapper at 0x7afc91ef2160>, severity=20, msg='Name longer than 64 characters.', context={'typ': Annotated[Any, MaxLen(max_length=64)]})]"}, "bioimageio.spec.model.v0_4.ModelDescr.outputs": {"fullname": "bioimageio.spec.model.v0_4.ModelDescr.outputs", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ModelDescr.outputs", "kind": "variable", "doc": "
    Describes the output tensors.
    \n", "annotation": ": Annotated[List[bioimageio.spec.model.v0_4.OutputTensorDescr], MinLen(min_length=1)]"}, "bioimageio.spec.model.v0_4.ModelDescr.unique_tensor_descr_names": {"fullname": "bioimageio.spec.model.v0_4.ModelDescr.unique_tensor_descr_names", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ModelDescr.unique_tensor_descr_names", "kind": "function", "doc": "
    \n", "signature": "(\tcls,\tvalue: Sequence[Union[bioimageio.spec.model.v0_4.InputTensorDescr, bioimageio.spec.model.v0_4.OutputTensorDescr]]) -> Sequence[Union[bioimageio.spec.model.v0_4.InputTensorDescr, bioimageio.spec.model.v0_4.OutputTensorDescr]]:", "funcdef": "def"}, "bioimageio.spec.model.v0_4.ModelDescr.unique_io_names": {"fullname": "bioimageio.spec.model.v0_4.ModelDescr.unique_io_names", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ModelDescr.unique_io_names", "kind": "function", "doc": "
    \n", "signature": "(self) -> Self:", "funcdef": "def"}, "bioimageio.spec.model.v0_4.ModelDescr.minimum_shape2valid_output": {"fullname": "bioimageio.spec.model.v0_4.ModelDescr.minimum_shape2valid_output", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ModelDescr.minimum_shape2valid_output", "kind": "function", "doc": "
    \n", "signature": "(self) -> Self:", "funcdef": "def"}, "bioimageio.spec.model.v0_4.ModelDescr.validate_tensor_references_in_inputs": {"fullname": "bioimageio.spec.model.v0_4.ModelDescr.validate_tensor_references_in_inputs", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ModelDescr.validate_tensor_references_in_inputs", "kind": "function", "doc": "
    \n", "signature": "(self) -> Self:", "funcdef": "def"}, "bioimageio.spec.model.v0_4.ModelDescr.validate_tensor_references_in_outputs": {"fullname": "bioimageio.spec.model.v0_4.ModelDescr.validate_tensor_references_in_outputs", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ModelDescr.validate_tensor_references_in_outputs", "kind": "function", "doc": "
    \n", "signature": "(self) -> Self:", "funcdef": "def"}, "bioimageio.spec.model.v0_4.ModelDescr.packaged_by": {"fullname": "bioimageio.spec.model.v0_4.ModelDescr.packaged_by", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ModelDescr.packaged_by", "kind": "variable", "doc": "
    The persons that have packaged and uploaded this model.\nOnly required if those persons differ from the authors.
    \n", "annotation": ": List[bioimageio.spec.generic.v0_2.Author]"}, "bioimageio.spec.model.v0_4.ModelDescr.parent": {"fullname": "bioimageio.spec.model.v0_4.ModelDescr.parent", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ModelDescr.parent", "kind": "variable", "doc": "
    The model from which this model is derived, e.g. by fine-tuning the weights.
    \n", "annotation": ": Optional[bioimageio.spec.model.v0_4.LinkedModel]"}, "bioimageio.spec.model.v0_4.ModelDescr.ignore_url_parent": {"fullname": "bioimageio.spec.model.v0_4.ModelDescr.ignore_url_parent", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ModelDescr.ignore_url_parent", "kind": "function", "doc": "
    \n", "signature": "(cls, parent: Any):", "funcdef": "def"}, "bioimageio.spec.model.v0_4.ModelDescr.run_mode": {"fullname": "bioimageio.spec.model.v0_4.ModelDescr.run_mode", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ModelDescr.run_mode", "kind": "variable", "doc": "
    Custom run mode for this model: for more complex prediction procedures like test time\ndata augmentation that currently cannot be expressed in the specification.\nNo standard run modes are defined yet.
    \n", "annotation": ": Optional[bioimageio.spec.model.v0_4.RunMode]"}, "bioimageio.spec.model.v0_4.ModelDescr.sample_inputs": {"fullname": "bioimageio.spec.model.v0_4.ModelDescr.sample_inputs", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ModelDescr.sample_inputs", "kind": "variable", "doc": "
    \u2208\ud83d\udce6 URLs/relative paths to sample inputs to illustrate possible inputs for the model,\nfor example stored as PNG or TIFF images.\nThe sample files primarily serve to inform a human user about an example use case
    \n", "annotation": ": List[Annotated[Union[Annotated[pathlib.Path, PathType(path_type='file')], bioimageio.spec._internal.io.RelativeFilePath, bioimageio.spec._internal.url.HttpUrl, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator(func=<function wo_special_file_name at 0x7afca0d90540>), PlainSerializer(func=<function _package at 0x7afca0d91760>, return_type=PydanticUndefined, when_used='unless-none')]]"}, "bioimageio.spec.model.v0_4.ModelDescr.sample_outputs": {"fullname": "bioimageio.spec.model.v0_4.ModelDescr.sample_outputs", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ModelDescr.sample_outputs", "kind": "variable", "doc": "
    \u2208\ud83d\udce6 URLs/relative paths to sample outputs corresponding to the sample_inputs.
    \n", "annotation": ": List[Annotated[Union[Annotated[pathlib.Path, PathType(path_type='file')], bioimageio.spec._internal.io.RelativeFilePath, bioimageio.spec._internal.url.HttpUrl, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator(func=<function wo_special_file_name at 0x7afca0d90540>), PlainSerializer(func=<function _package at 0x7afca0d91760>, return_type=PydanticUndefined, when_used='unless-none')]]"}, "bioimageio.spec.model.v0_4.ModelDescr.test_inputs": {"fullname": "bioimageio.spec.model.v0_4.ModelDescr.test_inputs", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ModelDescr.test_inputs", "kind": "variable", "doc": "
    \u2208\ud83d\udce6 Test input tensors compatible with the inputs description for a single test case.\nThis means if your model has more than one input, you should provide one URL/relative path for each input.\nEach test input should be a file with an ndarray in\nnumpy.lib file format.\nThe extension must be '.npy'.
    \n", "annotation": ": Annotated[List[Annotated[Union[Annotated[pathlib.Path, PathType(path_type='file')], bioimageio.spec._internal.io.RelativeFilePath, bioimageio.spec._internal.url.HttpUrl, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator(func=<function wo_special_file_name at 0x7afca0d90540>), PlainSerializer(func=<function _package at 0x7afca0d91760>, return_type=PydanticUndefined, when_used='unless-none'), WithSuffix(suffix='.npy', case_sensitive=True)]], MinLen(min_length=1)]"}, "bioimageio.spec.model.v0_4.ModelDescr.test_outputs": {"fullname": "bioimageio.spec.model.v0_4.ModelDescr.test_outputs", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ModelDescr.test_outputs", "kind": "variable", "doc": "
    \u2208\ud83d\udce6 Analog to test_inputs.
    \n", "annotation": ": Annotated[List[Annotated[Union[Annotated[pathlib.Path, PathType(path_type='file')], bioimageio.spec._internal.io.RelativeFilePath, bioimageio.spec._internal.url.HttpUrl, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator(func=<function wo_special_file_name at 0x7afca0d90540>), PlainSerializer(func=<function _package at 0x7afca0d91760>, return_type=PydanticUndefined, when_used='unless-none'), WithSuffix(suffix='.npy', case_sensitive=True)]], MinLen(min_length=1)]"}, "bioimageio.spec.model.v0_4.ModelDescr.timestamp": {"fullname": "bioimageio.spec.model.v0_4.ModelDescr.timestamp", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ModelDescr.timestamp", "kind": "variable", "doc": "
    Timestamp in ISO 8601 format\nwith a few restrictions listed here.
    \n", "annotation": ": bioimageio.spec._internal.types.Datetime"}, "bioimageio.spec.model.v0_4.ModelDescr.training_data": {"fullname": "bioimageio.spec.model.v0_4.ModelDescr.training_data", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ModelDescr.training_data", "kind": "variable", "doc": "
    The dataset used to train this model
    \n", "annotation": ": Union[bioimageio.spec.dataset.v0_2.LinkedDataset, bioimageio.spec.dataset.v0_2.DatasetDescr, NoneType]"}, "bioimageio.spec.model.v0_4.ModelDescr.weights": {"fullname": "bioimageio.spec.model.v0_4.ModelDescr.weights", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ModelDescr.weights", "kind": "variable", "doc": "
    The weights for this model.\nWeights can be given for different formats, but should otherwise be equivalent.\nThe available weight formats determine which consumers can use this model.
    \n", "annotation": ": bioimageio.spec.model.v0_4.WeightsDescr"}, "bioimageio.spec.model.v0_4.ModelDescr.get_input_test_arrays": {"fullname": "bioimageio.spec.model.v0_4.ModelDescr.get_input_test_arrays", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ModelDescr.get_input_test_arrays", "kind": "function", "doc": "
    \n", "signature": "(self) -> List[numpy.ndarray[Any, numpy.dtype[Any]]]:", "funcdef": "def"}, "bioimageio.spec.model.v0_4.ModelDescr.get_output_test_arrays": {"fullname": "bioimageio.spec.model.v0_4.ModelDescr.get_output_test_arrays", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ModelDescr.get_output_test_arrays", "kind": "function", "doc": "
    \n", "signature": "(self) -> List[numpy.ndarray[Any, numpy.dtype[Any]]]:", "funcdef": "def"}, "bioimageio.spec.model.v0_4.ModelDescr.implemented_format_version": {"fullname": "bioimageio.spec.model.v0_4.ModelDescr.implemented_format_version", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ModelDescr.implemented_format_version", "kind": "variable", "doc": "
    \n", "annotation": ": ClassVar[str]", "default_value": "'0.4.10'"}, "bioimageio.spec.model.v0_4.ModelDescr.implemented_format_version_tuple": {"fullname": "bioimageio.spec.model.v0_4.ModelDescr.implemented_format_version_tuple", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ModelDescr.implemented_format_version_tuple", "kind": "variable", "doc": "
    \n", "annotation": ": ClassVar[Tuple[int, int, int]]", "default_value": "(0, 4, 10)"}, "bioimageio.spec.model.v0_4.ModelDescr.model_config": {"fullname": "bioimageio.spec.model.v0_4.ModelDescr.model_config", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ModelDescr.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True, 'title': 'bioimage.io model specification'}"}, "bioimageio.spec.model.v0_4.ModelDescr.model_fields": {"fullname": "bioimageio.spec.model.v0_4.ModelDescr.model_fields", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ModelDescr.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'name': FieldInfo(annotation=str, required=True, metadata=[MinLen(min_length=1), AfterWarner(func=<function as_warning.<locals>.wrapper>, severity=20, msg='Name shorter than 5 characters.', context={'typ': typing.Annotated[typing.Any, MinLen(min_length=5)]}), AfterWarner(func=<function as_warning.<locals>.wrapper>, severity=20, msg='Name longer than 64 characters.', context={'typ': typing.Annotated[typing.Any, MaxLen(max_length=64)]})]), 'description': FieldInfo(annotation=str, required=True), 'covers': FieldInfo(annotation=List[Annotated[Union[HttpUrl, Annotated[Path, PathType, Predicate], RelativeFilePath], WithSuffix, PlainSerializer]], required=False, default_factory=list, description="Cover images. Please use an image smaller than 500KB and an aspect ratio width to height of 2:1.\\nThe supported image formats are: ('.gif', '.jpeg', '.jpg', '.png', '.svg')", examples=['cover.png']), 'id_emoji': FieldInfo(annotation=Union[Annotated[str, Len], NoneType], required=False), 'authors': FieldInfo(annotation=List[Author], required=True, metadata=[MinLen(min_length=1)]), 'attachments': FieldInfo(annotation=Union[AttachmentsDescr, NoneType], required=False), 'cite': FieldInfo(annotation=List[CiteEntry], required=False, default_factory=list), 'config': FieldInfo(annotation=Dict[str, YamlValue], required=False, default_factory=dict, examples=[{'bioimageio': {'my_custom_key': 3837283, 'another_key': {'nested': 'value'}}, 'imagej': {'macro_dir': 'path/to/macro/file'}}]), 'download_url': FieldInfo(annotation=Union[HttpUrl, NoneType], required=False), 'git_repo': FieldInfo(annotation=Union[str, NoneType], required=False, examples=['https://github.com/bioimage-io/spec-bioimage-io/tree/main/example_descriptions/models/unet2d_nuclei_broad']), 'icon': FieldInfo(annotation=Union[Annotated[Union[Annotated[Path, PathType], RelativeFilePath, HttpUrl, Annotated[Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator, PlainSerializer], Annotated[str, Len], NoneType], required=False), 'links': FieldInfo(annotation=List[str], required=False, default_factory=list, examples=[('ilastik/ilastik', 'deepimagej/deepimagej', 'zero/notebook_u-net_3d_zerocostdl4mic')]), 'uploader': FieldInfo(annotation=Union[Uploader, NoneType], required=False), 'maintainers': FieldInfo(annotation=List[Maintainer], required=False, default_factory=list), 'rdf_source': FieldInfo(annotation=Union[Annotated[Path, PathType], RelativeFilePath, HttpUrl, Annotated[Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)], NoneType], required=False), 'tags': FieldInfo(annotation=List[str], required=False, default_factory=list, examples=[('unet2d', 'pytorch', 'nucleus', 'segmentation', 'dsb2018')]), 'version': FieldInfo(annotation=Union[Version, NoneType], required=False), 'version_number': FieldInfo(annotation=Union[int, NoneType], required=False), 'format_version': FieldInfo(annotation=Literal['0.4.10'], required=False, default='0.4.10'), 'type': FieldInfo(annotation=Literal['model'], required=False, default='model'), 'id': FieldInfo(annotation=Union[ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]], NoneType], required=False), 'documentation': FieldInfo(annotation=Union[Annotated[Path, PathType], RelativeFilePath, HttpUrl, Annotated[Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], required=True, examples=['https://raw.githubusercontent.com/bioimage-io/spec-bioimage-io/main/example_descriptions/models/unet2d_nuclei_broad/README.md', 'README.md'], metadata=[AfterValidator(func=<function wo_special_file_name>), PlainSerializer(func=<function _package>, return_type=PydanticUndefined, when_used='unless-none')]), 'inputs': FieldInfo(annotation=List[InputTensorDescr], required=True, metadata=[MinLen(min_length=1)]), 'license': FieldInfo(annotation=Union[LicenseId, str], required=True, examples=['CC-BY-4.0', 'MIT', 'BSD-2-Clause'], metadata=[AfterWarner(func=<function as_warning.<locals>.wrapper>, severity=30, msg="Unknown license id '{value}'.", context={'typ': <class 'bioimageio.spec._internal.license_id.LicenseId'>})]), 'outputs': FieldInfo(annotation=List[OutputTensorDescr], required=True, metadata=[MinLen(min_length=1)]), 'packaged_by': FieldInfo(annotation=List[Author], required=False, default_factory=list), 'parent': FieldInfo(annotation=Union[LinkedModel, NoneType], required=False), 'run_mode': FieldInfo(annotation=Union[RunMode, NoneType], required=False), 'sample_inputs': FieldInfo(annotation=List[Annotated[Union[Annotated[Path, PathType], RelativeFilePath, HttpUrl, Annotated[Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator, PlainSerializer]], required=False, default_factory=list), 'sample_outputs': FieldInfo(annotation=List[Annotated[Union[Annotated[Path, PathType], RelativeFilePath, HttpUrl, Annotated[Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator, PlainSerializer]], required=False, default_factory=list), 'test_inputs': FieldInfo(annotation=List[Annotated[Union[Annotated[Path, PathType], RelativeFilePath, HttpUrl, Annotated[Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator, PlainSerializer, WithSuffix]], required=True, metadata=[MinLen(min_length=1)]), 'test_outputs': FieldInfo(annotation=List[Annotated[Union[Annotated[Path, PathType], RelativeFilePath, HttpUrl, Annotated[Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator, PlainSerializer, WithSuffix]], required=True, metadata=[MinLen(min_length=1)]), 'timestamp': FieldInfo(annotation=Datetime, required=True), 'training_data': FieldInfo(annotation=Union[LinkedDataset, DatasetDescr, NoneType], required=False), 'weights': FieldInfo(annotation=WeightsDescr, required=True)}"}, "bioimageio.spec.model.v0_4.ModelDescr.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_4.ModelDescr.model_computed_fields", "modulename": "bioimageio.spec.model.v0_4", "qualname": "ModelDescr.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_5": {"fullname": "bioimageio.spec.model.v0_5", "modulename": "bioimageio.spec.model.v0_5", "kind": "module", "doc": "
    \n"}, "bioimageio.spec.model.v0_5.SpaceUnit": {"fullname": "bioimageio.spec.model.v0_5.SpaceUnit", "modulename": "bioimageio.spec.model.v0_5", "qualname": "SpaceUnit", "kind": "variable", "doc": "
    \n", "default_value": "typing.Literal['attometer', 'angstrom', 'centimeter', 'decimeter', 'exameter', 'femtometer', 'foot', 'gigameter', 'hectometer', 'inch', 'kilometer', 'megameter', 'meter', 'micrometer', 'mile', 'millimeter', 'nanometer', 'parsec', 'petameter', 'picometer', 'terameter', 'yard', 'yoctometer', 'yottameter', 'zeptometer', 'zettameter']"}, "bioimageio.spec.model.v0_5.TimeUnit": {"fullname": "bioimageio.spec.model.v0_5.TimeUnit", "modulename": "bioimageio.spec.model.v0_5", "qualname": "TimeUnit", "kind": "variable", "doc": "
    \n", "default_value": "typing.Literal['attosecond', 'centisecond', 'day', 'decisecond', 'exasecond', 'femtosecond', 'gigasecond', 'hectosecond', 'hour', 'kilosecond', 'megasecond', 'microsecond', 'millisecond', 'minute', 'nanosecond', 'petasecond', 'picosecond', 'second', 'terasecond', 'yoctosecond', 'yottasecond', 'zeptosecond', 'zettasecond']"}, "bioimageio.spec.model.v0_5.AxisType": {"fullname": "bioimageio.spec.model.v0_5.AxisType", "modulename": "bioimageio.spec.model.v0_5", "qualname": "AxisType", "kind": "variable", "doc": "
    \n", "default_value": "typing.Literal['batch', 'channel', 'index', 'time', 'space']"}, "bioimageio.spec.model.v0_5.TensorId": {"fullname": "bioimageio.spec.model.v0_5.TensorId", "modulename": "bioimageio.spec.model.v0_5", "qualname": "TensorId", "kind": "variable", "doc": "
    \n", "default_value": "<class 'bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]'>"}, "bioimageio.spec.model.v0_5.AxisId": {"fullname": "bioimageio.spec.model.v0_5.AxisId", "modulename": "bioimageio.spec.model.v0_5", "qualname": "AxisId", "kind": "class", "doc": "
    str(object='') -> str\nstr(bytes_or_buffer[, encoding[, errors]]) -> str
    \n\n
    Create a new string object from the given object. If encoding or\nerrors is specified, then the object must expose a data buffer\nthat will be decoded using the given encoding and error handler.\nOtherwise, returns the result of object.__str__() (if defined)\nor repr(object).\nencoding defaults to sys.getdefaultencoding().\nerrors defaults to 'strict'.
    \n", "bases": "builtins.str"}, "bioimageio.spec.model.v0_5.AxisId.root_model": {"fullname": "bioimageio.spec.model.v0_5.AxisId.root_model", "modulename": "bioimageio.spec.model.v0_5", "qualname": "AxisId.root_model", "kind": "variable", "doc": "
    \n", "default_value": "<class 'bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]'>"}, "bioimageio.spec.model.v0_5.NonBatchAxisId": {"fullname": "bioimageio.spec.model.v0_5.NonBatchAxisId", "modulename": "bioimageio.spec.model.v0_5", "qualname": "NonBatchAxisId", "kind": "variable", "doc": "
    \n", "default_value": "typing.Annotated[bioimageio.spec.model.v0_5.AxisId, Predicate(func=<function <lambda>>)]"}, "bioimageio.spec.model.v0_5.PostprocessingId": {"fullname": "bioimageio.spec.model.v0_5.PostprocessingId", "modulename": "bioimageio.spec.model.v0_5", "qualname": "PostprocessingId", "kind": "variable", "doc": "
    \n", "default_value": "typing.Literal['binarize', 'clip', 'ensure_dtype', 'fixed_zero_mean_unit_variance', 'scale_linear', 'scale_mean_variance', 'scale_range', 'sigmoid', 'zero_mean_unit_variance']"}, "bioimageio.spec.model.v0_5.PreprocessingId": {"fullname": "bioimageio.spec.model.v0_5.PreprocessingId", "modulename": "bioimageio.spec.model.v0_5", "qualname": "PreprocessingId", "kind": "variable", "doc": "
    \n", "default_value": "typing.Literal['binarize', 'clip', 'ensure_dtype', 'scale_linear', 'sigmoid', 'zero_mean_unit_variance', 'scale_range']"}, "bioimageio.spec.model.v0_5.SAME_AS_TYPE": {"fullname": "bioimageio.spec.model.v0_5.SAME_AS_TYPE", "modulename": "bioimageio.spec.model.v0_5", "qualname": "SAME_AS_TYPE", "kind": "variable", "doc": "
    \n", "default_value": "'<same as type>'"}, "bioimageio.spec.model.v0_5.ParameterizedSize": {"fullname": "bioimageio.spec.model.v0_5.ParameterizedSize", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ParameterizedSize", "kind": "class", "doc": "
    Describes a range of valid tensor axis sizes as size = min + n*step.\nn in this equation is the same for all axis parameterized in this manner across the whole model.
    \n", "bases": "bioimageio.spec._internal.node.Node"}, "bioimageio.spec.model.v0_5.ParameterizedSize.N": {"fullname": "bioimageio.spec.model.v0_5.ParameterizedSize.N", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ParameterizedSize.N", "kind": "variable", "doc": "
    integer to parameterize all axes with a ParameterizedSize
    \n", "annotation": ": ClassVar[Type[int]]", "default_value": "<class 'int'>"}, "bioimageio.spec.model.v0_5.ParameterizedSize.min": {"fullname": "bioimageio.spec.model.v0_5.ParameterizedSize.min", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ParameterizedSize.min", "kind": "variable", "doc": "
    \n", "annotation": ": Annotated[int, Gt(gt=0)]"}, "bioimageio.spec.model.v0_5.ParameterizedSize.step": {"fullname": "bioimageio.spec.model.v0_5.ParameterizedSize.step", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ParameterizedSize.step", "kind": "variable", "doc": "
    \n", "annotation": ": Annotated[int, Gt(gt=0)]"}, "bioimageio.spec.model.v0_5.ParameterizedSize.validate_size": {"fullname": "bioimageio.spec.model.v0_5.ParameterizedSize.validate_size", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ParameterizedSize.validate_size", "kind": "function", "doc": "
    \n", "signature": "(self, size: int) -> int:", "funcdef": "def"}, "bioimageio.spec.model.v0_5.ParameterizedSize.get_size": {"fullname": "bioimageio.spec.model.v0_5.ParameterizedSize.get_size", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ParameterizedSize.get_size", "kind": "function", "doc": "
    \n", "signature": "(self, n: int) -> int:", "funcdef": "def"}, "bioimageio.spec.model.v0_5.ParameterizedSize.model_config": {"fullname": "bioimageio.spec.model.v0_5.ParameterizedSize.model_config", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ParameterizedSize.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_5.ParameterizedSize.model_fields": {"fullname": "bioimageio.spec.model.v0_5.ParameterizedSize.model_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ParameterizedSize.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'min': FieldInfo(annotation=int, required=True, metadata=[Gt(gt=0)]), 'step': FieldInfo(annotation=int, required=True, metadata=[Gt(gt=0)])}"}, "bioimageio.spec.model.v0_5.ParameterizedSize.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_5.ParameterizedSize.model_computed_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ParameterizedSize.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_5.SizeReference": {"fullname": "bioimageio.spec.model.v0_5.SizeReference", "modulename": "bioimageio.spec.model.v0_5", "qualname": "SizeReference", "kind": "class", "doc": "
    A tensor axis size (extent in pixels/frames) defined in relation to a reference axis.
    \n\n
    axis.size = reference.size * reference.scale / axis.scale + offset
    \n\n
    note:
    \n\n
      \n
    1. The axis and the referenced axis need to have the same unit (or no unit).
      2. \n
    2. Batch axes may not be referenced.
      3. \n
    3. Fractions are rounded down.
      4. \n
    \n\n
    example:\nAn unisotropic input image of wh=10049 pixels depicts a phsical space of 200196mm\u00b2.\nLet's assume that we want to express the image height h in relation to its width w\ninstead of only accepting input images of exactly 10049 pixels\n(for example to express a range of valid image shapes by parametrizing w, see ParameterizedSize).
    \n\n
    \n
    >>> w = SpaceInputAxis(id=AxisId("w"), size=100, unit="millimeter", scale=2)\n>>> h = SpaceInputAxis(\n...     id=AxisId("h"),\n...     size=SizeReference(tensor_id=TensorId("input"), axis_id=AxisId("w"), offset=-1),\n...     unit="millimeter",\n...     scale=4,\n... )\n>>> print(h.size.compute(h, w))\n49\n
    \n
    \n\n
    -> h = w * w.scale / h.scale + offset = 100 * 2mm / 4mm - 1 = 49
    \n", "bases": "bioimageio.spec._internal.node.Node"}, "bioimageio.spec.model.v0_5.SizeReference.tensor_id": {"fullname": "bioimageio.spec.model.v0_5.SizeReference.tensor_id", "modulename": "bioimageio.spec.model.v0_5", "qualname": "SizeReference.tensor_id", "kind": "variable", "doc": "
    tensor id of the reference axis
    \n", "annotation": ": bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]"}, "bioimageio.spec.model.v0_5.SizeReference.axis_id": {"fullname": "bioimageio.spec.model.v0_5.SizeReference.axis_id", "modulename": "bioimageio.spec.model.v0_5", "qualname": "SizeReference.axis_id", "kind": "variable", "doc": "
    axis id of the reference axis
    \n", "annotation": ": bioimageio.spec.model.v0_5.AxisId"}, "bioimageio.spec.model.v0_5.SizeReference.offset": {"fullname": "bioimageio.spec.model.v0_5.SizeReference.offset", "modulename": "bioimageio.spec.model.v0_5", "qualname": "SizeReference.offset", "kind": "variable", "doc": "
    \n", "annotation": ": int"}, "bioimageio.spec.model.v0_5.SizeReference.get_size": {"fullname": "bioimageio.spec.model.v0_5.SizeReference.get_size", "modulename": "bioimageio.spec.model.v0_5", "qualname": "SizeReference.get_size", "kind": "function", "doc": "
    helper method to compute concrete size for a given axis and its reference axis.\nIf the reference axis is parameterized, n is used to compute the concrete size of it, see ParameterizedSize.
    \n", "signature": "(\tself,\taxis: Union[bioimageio.spec.model.v0_5.ChannelAxis, bioimageio.spec.model.v0_5.IndexAxis, bioimageio.spec.model.v0_5.TimeInputAxis, bioimageio.spec.model.v0_5.SpaceInputAxis, bioimageio.spec.model.v0_5.TimeOutputAxis, bioimageio.spec.model.v0_5.SpaceOutputAxis],\tref_axis: Union[bioimageio.spec.model.v0_5.ChannelAxis, bioimageio.spec.model.v0_5.IndexAxis, bioimageio.spec.model.v0_5.TimeInputAxis, bioimageio.spec.model.v0_5.SpaceInputAxis, bioimageio.spec.model.v0_5.TimeOutputAxis, bioimageio.spec.model.v0_5.SpaceOutputAxis],\tn: int):", "funcdef": "def"}, "bioimageio.spec.model.v0_5.SizeReference.model_config": {"fullname": "bioimageio.spec.model.v0_5.SizeReference.model_config", "modulename": "bioimageio.spec.model.v0_5", "qualname": "SizeReference.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_5.SizeReference.model_fields": {"fullname": "bioimageio.spec.model.v0_5.SizeReference.model_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "SizeReference.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'tensor_id': FieldInfo(annotation=ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]], required=True), 'axis_id': FieldInfo(annotation=AxisId, required=True), 'offset': FieldInfo(annotation=int, required=False, default=0)}"}, "bioimageio.spec.model.v0_5.SizeReference.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_5.SizeReference.model_computed_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "SizeReference.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_5.AxisBase": {"fullname": "bioimageio.spec.model.v0_5.AxisBase", "modulename": "bioimageio.spec.model.v0_5", "qualname": "AxisBase", "kind": "class", "doc": "
    Subpart of a resource description
    \n", "bases": "bioimageio.spec._internal.common_nodes.NodeWithExplicitlySetFields"}, "bioimageio.spec.model.v0_5.AxisBase.fields_to_set_explicitly": {"fullname": "bioimageio.spec.model.v0_5.AxisBase.fields_to_set_explicitly", "modulename": "bioimageio.spec.model.v0_5", "qualname": "AxisBase.fields_to_set_explicitly", "kind": "variable", "doc": "
    set set these fields explicitly with their default value if they are not set,\nsuch that they are always included even when dumping with 'exlude_unset'
    \n", "annotation": ": ClassVar[FrozenSet[LiteralString]]", "default_value": "frozenset({'type'})"}, "bioimageio.spec.model.v0_5.AxisBase.id": {"fullname": "bioimageio.spec.model.v0_5.AxisBase.id", "modulename": "bioimageio.spec.model.v0_5", "qualname": "AxisBase.id", "kind": "variable", "doc": "
    An axis id unique across all axes of one tensor.
    \n", "annotation": ": bioimageio.spec.model.v0_5.AxisId"}, "bioimageio.spec.model.v0_5.AxisBase.description": {"fullname": "bioimageio.spec.model.v0_5.AxisBase.description", "modulename": "bioimageio.spec.model.v0_5", "qualname": "AxisBase.description", "kind": "variable", "doc": "
    \n", "annotation": ": Annotated[str, MaxLen(max_length=128)]"}, "bioimageio.spec.model.v0_5.AxisBase.model_config": {"fullname": "bioimageio.spec.model.v0_5.AxisBase.model_config", "modulename": "bioimageio.spec.model.v0_5", "qualname": "AxisBase.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_5.AxisBase.model_fields": {"fullname": "bioimageio.spec.model.v0_5.AxisBase.model_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "AxisBase.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'id': FieldInfo(annotation=AxisId, required=True), 'description': FieldInfo(annotation=str, required=False, default='', metadata=[MaxLen(max_length=128)])}"}, "bioimageio.spec.model.v0_5.AxisBase.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_5.AxisBase.model_computed_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "AxisBase.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_5.WithHalo": {"fullname": "bioimageio.spec.model.v0_5.WithHalo", "modulename": "bioimageio.spec.model.v0_5", "qualname": "WithHalo", "kind": "class", "doc": "
    Subpart of a resource description
    \n", "bases": "bioimageio.spec._internal.node.Node"}, "bioimageio.spec.model.v0_5.WithHalo.halo": {"fullname": "bioimageio.spec.model.v0_5.WithHalo.halo", "modulename": "bioimageio.spec.model.v0_5", "qualname": "WithHalo.halo", "kind": "variable", "doc": "
    The halo should be cropped from the output tensor to avoid boundary effects.\nIt is to be cropped from both sides, i.e. size_after_crop = size - 2 * halo.\nTo document a halo that is already cropped by the model use size.offset instead.
    \n", "annotation": ": Annotated[int, Ge(ge=0)]"}, "bioimageio.spec.model.v0_5.WithHalo.model_config": {"fullname": "bioimageio.spec.model.v0_5.WithHalo.model_config", "modulename": "bioimageio.spec.model.v0_5", "qualname": "WithHalo.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_5.WithHalo.model_fields": {"fullname": "bioimageio.spec.model.v0_5.WithHalo.model_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "WithHalo.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'halo': FieldInfo(annotation=int, required=False, default=0, metadata=[Ge(ge=0)])}"}, "bioimageio.spec.model.v0_5.WithHalo.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_5.WithHalo.model_computed_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "WithHalo.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_5.BatchAxis": {"fullname": "bioimageio.spec.model.v0_5.BatchAxis", "modulename": "bioimageio.spec.model.v0_5", "qualname": "BatchAxis", "kind": "class", "doc": "
    Subpart of a resource description
    \n", "bases": "AxisBase"}, "bioimageio.spec.model.v0_5.BatchAxis.type": {"fullname": "bioimageio.spec.model.v0_5.BatchAxis.type", "modulename": "bioimageio.spec.model.v0_5", "qualname": "BatchAxis.type", "kind": "variable", "doc": "
    \n", "annotation": ": Literal['batch']"}, "bioimageio.spec.model.v0_5.BatchAxis.id": {"fullname": "bioimageio.spec.model.v0_5.BatchAxis.id", "modulename": "bioimageio.spec.model.v0_5", "qualname": "BatchAxis.id", "kind": "variable", "doc": "
    An axis id unique across all axes of one tensor.
    \n", "annotation": ": Annotated[bioimageio.spec.model.v0_5.AxisId, Predicate(func=<function <lambda> at 0x7afc933b6b60>)]"}, "bioimageio.spec.model.v0_5.BatchAxis.size": {"fullname": "bioimageio.spec.model.v0_5.BatchAxis.size", "modulename": "bioimageio.spec.model.v0_5", "qualname": "BatchAxis.size", "kind": "variable", "doc": "
    The batch size may be fixed to 1,\notherwise (the default) it may be chosen arbitrarily depending on available memory
    \n", "annotation": ": Optional[Literal[1]]"}, "bioimageio.spec.model.v0_5.BatchAxis.scale": {"fullname": "bioimageio.spec.model.v0_5.BatchAxis.scale", "modulename": "bioimageio.spec.model.v0_5", "qualname": "BatchAxis.scale", "kind": "variable", "doc": "
    \n"}, "bioimageio.spec.model.v0_5.BatchAxis.unit": {"fullname": "bioimageio.spec.model.v0_5.BatchAxis.unit", "modulename": "bioimageio.spec.model.v0_5", "qualname": "BatchAxis.unit", "kind": "variable", "doc": "
    \n"}, "bioimageio.spec.model.v0_5.BatchAxis.model_config": {"fullname": "bioimageio.spec.model.v0_5.BatchAxis.model_config", "modulename": "bioimageio.spec.model.v0_5", "qualname": "BatchAxis.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_5.BatchAxis.model_fields": {"fullname": "bioimageio.spec.model.v0_5.BatchAxis.model_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "BatchAxis.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'id': FieldInfo(annotation=AxisId, required=False, default='batch', metadata=[Predicate(func=<function <lambda>>)]), 'description': FieldInfo(annotation=str, required=False, default='', metadata=[MaxLen(max_length=128)]), 'type': FieldInfo(annotation=Literal['batch'], required=False, default='batch'), 'size': FieldInfo(annotation=Union[Literal[1], NoneType], required=False)}"}, "bioimageio.spec.model.v0_5.BatchAxis.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_5.BatchAxis.model_computed_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "BatchAxis.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_5.ChannelAxis": {"fullname": "bioimageio.spec.model.v0_5.ChannelAxis", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ChannelAxis", "kind": "class", "doc": "
    Subpart of a resource description
    \n", "bases": "AxisBase"}, "bioimageio.spec.model.v0_5.ChannelAxis.type": {"fullname": "bioimageio.spec.model.v0_5.ChannelAxis.type", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ChannelAxis.type", "kind": "variable", "doc": "
    \n", "annotation": ": Literal['channel']"}, "bioimageio.spec.model.v0_5.ChannelAxis.id": {"fullname": "bioimageio.spec.model.v0_5.ChannelAxis.id", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ChannelAxis.id", "kind": "variable", "doc": "
    An axis id unique across all axes of one tensor.
    \n", "annotation": ": Annotated[bioimageio.spec.model.v0_5.AxisId, Predicate(func=<function <lambda> at 0x7afc943332e0>)]"}, "bioimageio.spec.model.v0_5.ChannelAxis.channel_names": {"fullname": "bioimageio.spec.model.v0_5.ChannelAxis.channel_names", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ChannelAxis.channel_names", "kind": "variable", "doc": "
    \n", "annotation": ": List[bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator]]]"}, "bioimageio.spec.model.v0_5.ChannelAxis.size": {"fullname": "bioimageio.spec.model.v0_5.ChannelAxis.size", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ChannelAxis.size", "kind": "variable", "doc": "
    \n", "annotation": ": int"}, "bioimageio.spec.model.v0_5.ChannelAxis.scale": {"fullname": "bioimageio.spec.model.v0_5.ChannelAxis.scale", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ChannelAxis.scale", "kind": "variable", "doc": "
    \n", "annotation": ": float"}, "bioimageio.spec.model.v0_5.ChannelAxis.unit": {"fullname": "bioimageio.spec.model.v0_5.ChannelAxis.unit", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ChannelAxis.unit", "kind": "variable", "doc": "
    \n"}, "bioimageio.spec.model.v0_5.ChannelAxis.model_config": {"fullname": "bioimageio.spec.model.v0_5.ChannelAxis.model_config", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ChannelAxis.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_5.ChannelAxis.model_fields": {"fullname": "bioimageio.spec.model.v0_5.ChannelAxis.model_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ChannelAxis.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'id': FieldInfo(annotation=AxisId, required=False, default='channel', metadata=[Predicate(func=<function <lambda>>)]), 'description': FieldInfo(annotation=str, required=False, default='', metadata=[MaxLen(max_length=128)]), 'type': FieldInfo(annotation=Literal['channel'], required=False, default='channel'), 'channel_names': FieldInfo(annotation=List[ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator]]], required=True)}"}, "bioimageio.spec.model.v0_5.ChannelAxis.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_5.ChannelAxis.model_computed_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ChannelAxis.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_5.IndexTimeSpaceAxisBase": {"fullname": "bioimageio.spec.model.v0_5.IndexTimeSpaceAxisBase", "modulename": "bioimageio.spec.model.v0_5", "qualname": "IndexTimeSpaceAxisBase", "kind": "class", "doc": "
    Subpart of a resource description
    \n", "bases": "AxisBase"}, "bioimageio.spec.model.v0_5.IndexTimeSpaceAxisBase.size": {"fullname": "bioimageio.spec.model.v0_5.IndexTimeSpaceAxisBase.size", "modulename": "bioimageio.spec.model.v0_5", "qualname": "IndexTimeSpaceAxisBase.size", "kind": "variable", "doc": "
    The size/length of an axis can be specified as
    \n\n
      \n
    • fixed integer
      • \n
    • parameterized series of valid sizes (ParameterizedSize)
      • \n
    • reference to another axis with an optional offset (SizeReference)
      • \n
    \n", "annotation": ": Annotated[Union[Annotated[int, Gt(gt=0)], bioimageio.spec.model.v0_5.ParameterizedSize, bioimageio.spec.model.v0_5.SizeReference], FieldInfo(annotation=NoneType, required=True, examples=[10, {'min': 32, 'step': 16}, {'tensor_id': 't', 'axis_id': 'a', 'offset': 5}])]"}, "bioimageio.spec.model.v0_5.IndexTimeSpaceAxisBase.model_config": {"fullname": "bioimageio.spec.model.v0_5.IndexTimeSpaceAxisBase.model_config", "modulename": "bioimageio.spec.model.v0_5", "qualname": "IndexTimeSpaceAxisBase.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_5.IndexTimeSpaceAxisBase.model_fields": {"fullname": "bioimageio.spec.model.v0_5.IndexTimeSpaceAxisBase.model_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "IndexTimeSpaceAxisBase.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'id': FieldInfo(annotation=AxisId, required=True), 'description': FieldInfo(annotation=str, required=False, default='', metadata=[MaxLen(max_length=128)]), 'size': FieldInfo(annotation=Union[Annotated[int, Gt], ParameterizedSize, SizeReference], required=True, examples=[10, {'min': 32, 'step': 16}, {'tensor_id': 't', 'axis_id': 'a', 'offset': 5}])}"}, "bioimageio.spec.model.v0_5.IndexTimeSpaceAxisBase.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_5.IndexTimeSpaceAxisBase.model_computed_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "IndexTimeSpaceAxisBase.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_5.IndexAxis": {"fullname": "bioimageio.spec.model.v0_5.IndexAxis", "modulename": "bioimageio.spec.model.v0_5", "qualname": "IndexAxis", "kind": "class", "doc": "
    Subpart of a resource description
    \n", "bases": "IndexTimeSpaceAxisBase"}, "bioimageio.spec.model.v0_5.IndexAxis.type": {"fullname": "bioimageio.spec.model.v0_5.IndexAxis.type", "modulename": "bioimageio.spec.model.v0_5", "qualname": "IndexAxis.type", "kind": "variable", "doc": "
    \n", "annotation": ": Literal['index']"}, "bioimageio.spec.model.v0_5.IndexAxis.id": {"fullname": "bioimageio.spec.model.v0_5.IndexAxis.id", "modulename": "bioimageio.spec.model.v0_5", "qualname": "IndexAxis.id", "kind": "variable", "doc": "
    An axis id unique across all axes of one tensor.
    \n", "annotation": ": Annotated[bioimageio.spec.model.v0_5.AxisId, Predicate(func=<function <lambda> at 0x7afc943332e0>)]"}, "bioimageio.spec.model.v0_5.IndexAxis.scale": {"fullname": "bioimageio.spec.model.v0_5.IndexAxis.scale", "modulename": "bioimageio.spec.model.v0_5", "qualname": "IndexAxis.scale", "kind": "variable", "doc": "
    \n", "annotation": ": float"}, "bioimageio.spec.model.v0_5.IndexAxis.unit": {"fullname": "bioimageio.spec.model.v0_5.IndexAxis.unit", "modulename": "bioimageio.spec.model.v0_5", "qualname": "IndexAxis.unit", "kind": "variable", "doc": "
    \n"}, "bioimageio.spec.model.v0_5.IndexAxis.model_config": {"fullname": "bioimageio.spec.model.v0_5.IndexAxis.model_config", "modulename": "bioimageio.spec.model.v0_5", "qualname": "IndexAxis.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_5.IndexAxis.model_fields": {"fullname": "bioimageio.spec.model.v0_5.IndexAxis.model_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "IndexAxis.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'id': FieldInfo(annotation=AxisId, required=False, default='index', metadata=[Predicate(func=<function <lambda>>)]), 'description': FieldInfo(annotation=str, required=False, default='', metadata=[MaxLen(max_length=128)]), 'size': FieldInfo(annotation=Union[Annotated[int, Gt], ParameterizedSize, SizeReference], required=True, examples=[10, {'min': 32, 'step': 16}, {'tensor_id': 't', 'axis_id': 'a', 'offset': 5}]), 'type': FieldInfo(annotation=Literal['index'], required=False, default='index')}"}, "bioimageio.spec.model.v0_5.IndexAxis.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_5.IndexAxis.model_computed_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "IndexAxis.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_5.TimeAxisBase": {"fullname": "bioimageio.spec.model.v0_5.TimeAxisBase", "modulename": "bioimageio.spec.model.v0_5", "qualname": "TimeAxisBase", "kind": "class", "doc": "
    Subpart of a resource description
    \n", "bases": "IndexTimeSpaceAxisBase"}, "bioimageio.spec.model.v0_5.TimeAxisBase.type": {"fullname": "bioimageio.spec.model.v0_5.TimeAxisBase.type", "modulename": "bioimageio.spec.model.v0_5", "qualname": "TimeAxisBase.type", "kind": "variable", "doc": "
    \n", "annotation": ": Literal['time']"}, "bioimageio.spec.model.v0_5.TimeAxisBase.id": {"fullname": "bioimageio.spec.model.v0_5.TimeAxisBase.id", "modulename": "bioimageio.spec.model.v0_5", "qualname": "TimeAxisBase.id", "kind": "variable", "doc": "
    An axis id unique across all axes of one tensor.
    \n", "annotation": ": Annotated[bioimageio.spec.model.v0_5.AxisId, Predicate(func=<function <lambda> at 0x7afc943332e0>)]"}, "bioimageio.spec.model.v0_5.TimeAxisBase.unit": {"fullname": "bioimageio.spec.model.v0_5.TimeAxisBase.unit", "modulename": "bioimageio.spec.model.v0_5", "qualname": "TimeAxisBase.unit", "kind": "variable", "doc": "
    \n", "annotation": ": Optional[Literal['attosecond', 'centisecond', 'day', 'decisecond', 'exasecond', 'femtosecond', 'gigasecond', 'hectosecond', 'hour', 'kilosecond', 'megasecond', 'microsecond', 'millisecond', 'minute', 'nanosecond', 'petasecond', 'picosecond', 'second', 'terasecond', 'yoctosecond', 'yottasecond', 'zeptosecond', 'zettasecond']]"}, "bioimageio.spec.model.v0_5.TimeAxisBase.scale": {"fullname": "bioimageio.spec.model.v0_5.TimeAxisBase.scale", "modulename": "bioimageio.spec.model.v0_5", "qualname": "TimeAxisBase.scale", "kind": "variable", "doc": "
    \n", "annotation": ": Annotated[float, Gt(gt=0)]"}, "bioimageio.spec.model.v0_5.TimeAxisBase.model_config": {"fullname": "bioimageio.spec.model.v0_5.TimeAxisBase.model_config", "modulename": "bioimageio.spec.model.v0_5", "qualname": "TimeAxisBase.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_5.TimeAxisBase.model_fields": {"fullname": "bioimageio.spec.model.v0_5.TimeAxisBase.model_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "TimeAxisBase.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'id': FieldInfo(annotation=AxisId, required=False, default='time', metadata=[Predicate(func=<function <lambda>>)]), 'description': FieldInfo(annotation=str, required=False, default='', metadata=[MaxLen(max_length=128)]), 'size': FieldInfo(annotation=Union[Annotated[int, Gt], ParameterizedSize, SizeReference], required=True, examples=[10, {'min': 32, 'step': 16}, {'tensor_id': 't', 'axis_id': 'a', 'offset': 5}]), 'type': FieldInfo(annotation=Literal['time'], required=False, default='time'), 'unit': FieldInfo(annotation=Union[Literal['attosecond', 'centisecond', 'day', 'decisecond', 'exasecond', 'femtosecond', 'gigasecond', 'hectosecond', 'hour', 'kilosecond', 'megasecond', 'microsecond', 'millisecond', 'minute', 'nanosecond', 'petasecond', 'picosecond', 'second', 'terasecond', 'yoctosecond', 'yottasecond', 'zeptosecond', 'zettasecond'], NoneType], required=False), 'scale': FieldInfo(annotation=float, required=False, default=1.0, metadata=[Gt(gt=0)])}"}, "bioimageio.spec.model.v0_5.TimeAxisBase.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_5.TimeAxisBase.model_computed_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "TimeAxisBase.model_computed_fields", "kind": "variable", "doc": "
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    Subpart of a resource description
    \n", "bases": "bioimageio.spec._internal.node.Node"}, "bioimageio.spec.model.v0_5.IntervalOrRatioDataDescr.type": {"fullname": "bioimageio.spec.model.v0_5.IntervalOrRatioDataDescr.type", "modulename": "bioimageio.spec.model.v0_5", "qualname": "IntervalOrRatioDataDescr.type", "kind": "variable", "doc": "
    \n", "annotation": ": Annotated[Literal['float32', 'float64', 'uint8', 'int8', 'uint16', 'int16', 'uint32', 'int32', 'uint64', 'int64'], FieldInfo(annotation=NoneType, required=True, examples=['float32', 'float64', 'uint8', 'uint16'])]"}, "bioimageio.spec.model.v0_5.IntervalOrRatioDataDescr.range": {"fullname": "bioimageio.spec.model.v0_5.IntervalOrRatioDataDescr.range", "modulename": "bioimageio.spec.model.v0_5", "qualname": "IntervalOrRatioDataDescr.range", "kind": "variable", "doc": "
    Tuple (minimum, maximum) specifying the allowed range of the data in this tensor.\nNone corresponds to min/max of what can be expressed by data_type.
    \n", "annotation": ": Tuple[Optional[float], Optional[float]]"}, "bioimageio.spec.model.v0_5.IntervalOrRatioDataDescr.unit": {"fullname": "bioimageio.spec.model.v0_5.IntervalOrRatioDataDescr.unit", "modulename": "bioimageio.spec.model.v0_5", "qualname": "IntervalOrRatioDataDescr.unit", "kind": "variable", "doc": "
    \n", "annotation": ": Union[Literal['arbitrary unit'], bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, StringConstraints, BeforeValidator]]]"}, "bioimageio.spec.model.v0_5.IntervalOrRatioDataDescr.scale": {"fullname": "bioimageio.spec.model.v0_5.IntervalOrRatioDataDescr.scale", "modulename": "bioimageio.spec.model.v0_5", "qualname": "IntervalOrRatioDataDescr.scale", "kind": "variable", "doc": "
    Scale for data on an interval (or ratio) scale.
    \n", "annotation": ": float"}, "bioimageio.spec.model.v0_5.IntervalOrRatioDataDescr.offset": {"fullname": "bioimageio.spec.model.v0_5.IntervalOrRatioDataDescr.offset", "modulename": "bioimageio.spec.model.v0_5", "qualname": "IntervalOrRatioDataDescr.offset", "kind": "variable", "doc": "
    Offset for data on a ratio scale.
    \n", "annotation": ": Optional[float]"}, "bioimageio.spec.model.v0_5.IntervalOrRatioDataDescr.model_config": {"fullname": "bioimageio.spec.model.v0_5.IntervalOrRatioDataDescr.model_config", "modulename": "bioimageio.spec.model.v0_5", "qualname": "IntervalOrRatioDataDescr.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_5.IntervalOrRatioDataDescr.model_fields": {"fullname": "bioimageio.spec.model.v0_5.IntervalOrRatioDataDescr.model_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "IntervalOrRatioDataDescr.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'type': FieldInfo(annotation=Literal['float32', 'float64', 'uint8', 'int8', 'uint16', 'int16', 'uint32', 'int32', 'uint64', 'int64'], required=False, default='float32', examples=['float32', 'float64', 'uint8', 'uint16']), 'range': FieldInfo(annotation=Tuple[Union[float, NoneType], Union[float, NoneType]], required=False, default=(None, None)), 'unit': FieldInfo(annotation=Union[Literal['arbitrary unit'], ValidatedString[Annotated[str, StringConstraints, BeforeValidator]]], required=False, default='arbitrary unit'), 'scale': FieldInfo(annotation=float, required=False, default=1.0), 'offset': FieldInfo(annotation=Union[float, NoneType], required=False)}"}, "bioimageio.spec.model.v0_5.IntervalOrRatioDataDescr.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_5.IntervalOrRatioDataDescr.model_computed_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "IntervalOrRatioDataDescr.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_5.TensorDataDescr": {"fullname": "bioimageio.spec.model.v0_5.TensorDataDescr", "modulename": "bioimageio.spec.model.v0_5", "qualname": "TensorDataDescr", "kind": "variable", "doc": "
    \n", "default_value": "typing.Union[bioimageio.spec.model.v0_5.NominalOrOrdinalDataDescr, bioimageio.spec.model.v0_5.IntervalOrRatioDataDescr]"}, "bioimageio.spec.model.v0_5.ProcessingDescrBase": {"fullname": "bioimageio.spec.model.v0_5.ProcessingDescrBase", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ProcessingDescrBase", "kind": "class", "doc": "
    processing base class
    \n", "bases": "bioimageio.spec._internal.common_nodes.NodeWithExplicitlySetFields, abc.ABC"}, "bioimageio.spec.model.v0_5.ProcessingDescrBase.fields_to_set_explicitly": {"fullname": "bioimageio.spec.model.v0_5.ProcessingDescrBase.fields_to_set_explicitly", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ProcessingDescrBase.fields_to_set_explicitly", "kind": "variable", "doc": "
    set set these fields explicitly with their default value if they are not set,\nsuch that they are always included even when dumping with 'exlude_unset'
    \n", "annotation": ": ClassVar[FrozenSet[LiteralString]]", "default_value": "frozenset({'id'})"}, "bioimageio.spec.model.v0_5.ProcessingDescrBase.model_config": {"fullname": "bioimageio.spec.model.v0_5.ProcessingDescrBase.model_config", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ProcessingDescrBase.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_5.ProcessingDescrBase.model_fields": {"fullname": "bioimageio.spec.model.v0_5.ProcessingDescrBase.model_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ProcessingDescrBase.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_5.ProcessingDescrBase.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_5.ProcessingDescrBase.model_computed_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ProcessingDescrBase.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_5.BinarizeDescr": {"fullname": "bioimageio.spec.model.v0_5.BinarizeDescr", "modulename": "bioimageio.spec.model.v0_5", "qualname": "BinarizeDescr", "kind": "class", "doc": "
    Binarize the tensor with a fixed threshold.\nValues above the threshold will be set to one, values below the threshold to zero.
    \n", "bases": "ProcessingDescrBase"}, "bioimageio.spec.model.v0_5.BinarizeDescr.id": {"fullname": "bioimageio.spec.model.v0_5.BinarizeDescr.id", "modulename": "bioimageio.spec.model.v0_5", "qualname": "BinarizeDescr.id", "kind": "variable", "doc": "
    \n", "annotation": ": Literal['binarize']"}, "bioimageio.spec.model.v0_5.BinarizeDescr.kwargs": {"fullname": "bioimageio.spec.model.v0_5.BinarizeDescr.kwargs", "modulename": "bioimageio.spec.model.v0_5", "qualname": "BinarizeDescr.kwargs", "kind": "variable", "doc": "
    \n", "annotation": ": bioimageio.spec.model.v0_4.BinarizeKwargs"}, "bioimageio.spec.model.v0_5.BinarizeDescr.model_config": {"fullname": "bioimageio.spec.model.v0_5.BinarizeDescr.model_config", "modulename": "bioimageio.spec.model.v0_5", "qualname": "BinarizeDescr.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_5.BinarizeDescr.model_fields": {"fullname": "bioimageio.spec.model.v0_5.BinarizeDescr.model_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "BinarizeDescr.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'id': FieldInfo(annotation=Literal['binarize'], required=False, default='binarize'), 'kwargs': FieldInfo(annotation=BinarizeKwargs, required=True)}"}, "bioimageio.spec.model.v0_5.BinarizeDescr.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_5.BinarizeDescr.model_computed_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "BinarizeDescr.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_5.ClipDescr": {"fullname": "bioimageio.spec.model.v0_5.ClipDescr", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ClipDescr", "kind": "class", "doc": "
    Set tensor values below min to min and above max to max.
    \n", "bases": "ProcessingDescrBase"}, "bioimageio.spec.model.v0_5.ClipDescr.id": {"fullname": "bioimageio.spec.model.v0_5.ClipDescr.id", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ClipDescr.id", "kind": "variable", "doc": "
    \n", "annotation": ": Literal['clip']"}, "bioimageio.spec.model.v0_5.ClipDescr.kwargs": {"fullname": "bioimageio.spec.model.v0_5.ClipDescr.kwargs", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ClipDescr.kwargs", "kind": "variable", "doc": "
    \n", "annotation": ": bioimageio.spec.model.v0_4.ClipKwargs"}, "bioimageio.spec.model.v0_5.ClipDescr.model_config": {"fullname": "bioimageio.spec.model.v0_5.ClipDescr.model_config", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ClipDescr.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_5.ClipDescr.model_fields": {"fullname": "bioimageio.spec.model.v0_5.ClipDescr.model_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ClipDescr.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'id': FieldInfo(annotation=Literal['clip'], required=False, default='clip'), 'kwargs': FieldInfo(annotation=ClipKwargs, required=True)}"}, "bioimageio.spec.model.v0_5.ClipDescr.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_5.ClipDescr.model_computed_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ClipDescr.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_5.EnsureDtypeKwargs": {"fullname": "bioimageio.spec.model.v0_5.EnsureDtypeKwargs", "modulename": "bioimageio.spec.model.v0_5", "qualname": "EnsureDtypeKwargs", "kind": "class", "doc": "
    base class for pre-/postprocessing key word arguments
    \n", "bases": "bioimageio.spec.model.v0_4.ProcessingKwargs"}, "bioimageio.spec.model.v0_5.EnsureDtypeKwargs.dtype": {"fullname": "bioimageio.spec.model.v0_5.EnsureDtypeKwargs.dtype", "modulename": "bioimageio.spec.model.v0_5", "qualname": "EnsureDtypeKwargs.dtype", "kind": "variable", "doc": "
    \n", "annotation": ": str"}, "bioimageio.spec.model.v0_5.EnsureDtypeKwargs.model_config": {"fullname": "bioimageio.spec.model.v0_5.EnsureDtypeKwargs.model_config", "modulename": "bioimageio.spec.model.v0_5", "qualname": "EnsureDtypeKwargs.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_5.EnsureDtypeKwargs.model_fields": {"fullname": "bioimageio.spec.model.v0_5.EnsureDtypeKwargs.model_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "EnsureDtypeKwargs.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'dtype': FieldInfo(annotation=str, required=True)}"}, "bioimageio.spec.model.v0_5.EnsureDtypeKwargs.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_5.EnsureDtypeKwargs.model_computed_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "EnsureDtypeKwargs.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_5.EnsureDtypeDescr": {"fullname": "bioimageio.spec.model.v0_5.EnsureDtypeDescr", "modulename": "bioimageio.spec.model.v0_5", "qualname": "EnsureDtypeDescr", "kind": "class", "doc": "
    processing base class
    \n", "bases": "ProcessingDescrBase"}, "bioimageio.spec.model.v0_5.EnsureDtypeDescr.id": {"fullname": "bioimageio.spec.model.v0_5.EnsureDtypeDescr.id", "modulename": "bioimageio.spec.model.v0_5", "qualname": "EnsureDtypeDescr.id", "kind": "variable", "doc": "
    \n", "annotation": ": Literal['ensure_dtype']"}, "bioimageio.spec.model.v0_5.EnsureDtypeDescr.kwargs": {"fullname": "bioimageio.spec.model.v0_5.EnsureDtypeDescr.kwargs", "modulename": "bioimageio.spec.model.v0_5", "qualname": "EnsureDtypeDescr.kwargs", "kind": "variable", "doc": "
    \n", "annotation": ": bioimageio.spec.model.v0_5.EnsureDtypeKwargs"}, "bioimageio.spec.model.v0_5.EnsureDtypeDescr.model_config": {"fullname": "bioimageio.spec.model.v0_5.EnsureDtypeDescr.model_config", "modulename": "bioimageio.spec.model.v0_5", "qualname": "EnsureDtypeDescr.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_5.EnsureDtypeDescr.model_fields": {"fullname": "bioimageio.spec.model.v0_5.EnsureDtypeDescr.model_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "EnsureDtypeDescr.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'id': FieldInfo(annotation=Literal['ensure_dtype'], required=False, default='ensure_dtype'), 'kwargs': FieldInfo(annotation=EnsureDtypeKwargs, required=True)}"}, "bioimageio.spec.model.v0_5.EnsureDtypeDescr.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_5.EnsureDtypeDescr.model_computed_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "EnsureDtypeDescr.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_5.ScaleLinearKwargs": {"fullname": "bioimageio.spec.model.v0_5.ScaleLinearKwargs", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ScaleLinearKwargs", "kind": "class", "doc": "
    base class for pre-/postprocessing key word arguments
    \n", "bases": "bioimageio.spec.model.v0_4.ProcessingKwargs"}, "bioimageio.spec.model.v0_5.ScaleLinearKwargs.axis": {"fullname": "bioimageio.spec.model.v0_5.ScaleLinearKwargs.axis", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ScaleLinearKwargs.axis", "kind": "variable", "doc": "
    The axis of non-scalar gains/offsets.\nInvalid for scalar gains/offsets.
    \n", "annotation": ": Annotated[Optional[Annotated[bioimageio.spec.model.v0_5.AxisId, Predicate(func=<function <lambda> at 0x7afc943332e0>)]], FieldInfo(annotation=NoneType, required=True, examples=['channel'])]"}, "bioimageio.spec.model.v0_5.ScaleLinearKwargs.gain": {"fullname": "bioimageio.spec.model.v0_5.ScaleLinearKwargs.gain", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ScaleLinearKwargs.gain", "kind": "variable", "doc": "
    multiplicative factor
    \n", "annotation": ": Union[float, Annotated[List[float], MinLen(min_length=1)]]"}, "bioimageio.spec.model.v0_5.ScaleLinearKwargs.offset": {"fullname": "bioimageio.spec.model.v0_5.ScaleLinearKwargs.offset", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ScaleLinearKwargs.offset", "kind": "variable", "doc": "
    additive term
    \n", "annotation": ": Union[float, Annotated[List[float], MinLen(min_length=1)]]"}, "bioimageio.spec.model.v0_5.ScaleLinearKwargs.either_gain_or_offset": {"fullname": "bioimageio.spec.model.v0_5.ScaleLinearKwargs.either_gain_or_offset", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ScaleLinearKwargs.either_gain_or_offset", "kind": "function", "doc": "
    \n", "signature": "(self) -> Self:", "funcdef": "def"}, "bioimageio.spec.model.v0_5.ScaleLinearKwargs.model_config": {"fullname": "bioimageio.spec.model.v0_5.ScaleLinearKwargs.model_config", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ScaleLinearKwargs.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_5.ScaleLinearKwargs.model_fields": {"fullname": "bioimageio.spec.model.v0_5.ScaleLinearKwargs.model_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ScaleLinearKwargs.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'axis': FieldInfo(annotation=Union[Annotated[AxisId, Predicate], NoneType], required=False, examples=['channel']), 'gain': FieldInfo(annotation=Union[float, Annotated[List[float], MinLen]], required=False, default=1.0), 'offset': FieldInfo(annotation=Union[float, Annotated[List[float], MinLen]], required=False, default=0.0)}"}, "bioimageio.spec.model.v0_5.ScaleLinearKwargs.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_5.ScaleLinearKwargs.model_computed_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ScaleLinearKwargs.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_5.ScaleLinearDescr": {"fullname": "bioimageio.spec.model.v0_5.ScaleLinearDescr", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ScaleLinearDescr", "kind": "class", "doc": "
    Fixed linear scaling.
    \n", "bases": "ProcessingDescrBase"}, "bioimageio.spec.model.v0_5.ScaleLinearDescr.id": {"fullname": "bioimageio.spec.model.v0_5.ScaleLinearDescr.id", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ScaleLinearDescr.id", "kind": "variable", "doc": "
    \n", "annotation": ": Literal['scale_linear']"}, "bioimageio.spec.model.v0_5.ScaleLinearDescr.kwargs": {"fullname": "bioimageio.spec.model.v0_5.ScaleLinearDescr.kwargs", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ScaleLinearDescr.kwargs", "kind": "variable", "doc": "
    \n", "annotation": ": bioimageio.spec.model.v0_5.ScaleLinearKwargs"}, "bioimageio.spec.model.v0_5.ScaleLinearDescr.model_config": {"fullname": "bioimageio.spec.model.v0_5.ScaleLinearDescr.model_config", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ScaleLinearDescr.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_5.ScaleLinearDescr.model_fields": {"fullname": "bioimageio.spec.model.v0_5.ScaleLinearDescr.model_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ScaleLinearDescr.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'id': FieldInfo(annotation=Literal['scale_linear'], required=False, default='scale_linear'), 'kwargs': FieldInfo(annotation=ScaleLinearKwargs, required=True)}"}, "bioimageio.spec.model.v0_5.ScaleLinearDescr.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_5.ScaleLinearDescr.model_computed_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ScaleLinearDescr.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_5.SigmoidDescr": {"fullname": "bioimageio.spec.model.v0_5.SigmoidDescr", "modulename": "bioimageio.spec.model.v0_5", "qualname": "SigmoidDescr", "kind": "class", "doc": "
    The logistic sigmoid funciton, a.k.a. expit function.
    \n", "bases": "ProcessingDescrBase"}, "bioimageio.spec.model.v0_5.SigmoidDescr.id": {"fullname": "bioimageio.spec.model.v0_5.SigmoidDescr.id", "modulename": "bioimageio.spec.model.v0_5", "qualname": "SigmoidDescr.id", "kind": "variable", "doc": "
    \n", "annotation": ": Literal['sigmoid']"}, "bioimageio.spec.model.v0_5.SigmoidDescr.kwargs": {"fullname": "bioimageio.spec.model.v0_5.SigmoidDescr.kwargs", "modulename": "bioimageio.spec.model.v0_5", "qualname": "SigmoidDescr.kwargs", "kind": "variable", "doc": "
    empty kwargs
    \n", "annotation": ": bioimageio.spec.model.v0_4.ProcessingKwargs"}, "bioimageio.spec.model.v0_5.SigmoidDescr.model_config": {"fullname": "bioimageio.spec.model.v0_5.SigmoidDescr.model_config", "modulename": "bioimageio.spec.model.v0_5", "qualname": "SigmoidDescr.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_5.SigmoidDescr.model_fields": {"fullname": "bioimageio.spec.model.v0_5.SigmoidDescr.model_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "SigmoidDescr.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'id': FieldInfo(annotation=Literal['sigmoid'], required=False, default='sigmoid')}"}, "bioimageio.spec.model.v0_5.SigmoidDescr.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_5.SigmoidDescr.model_computed_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "SigmoidDescr.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_5.FixedZeroMeanUnitVarianceKwargs": {"fullname": "bioimageio.spec.model.v0_5.FixedZeroMeanUnitVarianceKwargs", "modulename": "bioimageio.spec.model.v0_5", "qualname": "FixedZeroMeanUnitVarianceKwargs", "kind": "class", "doc": "
    Normalize with fixed, precomputed values for mean and variance.\nSee zero_mean_unit_variance for data dependent normalization.
    \n", "bases": "bioimageio.spec.model.v0_4.ProcessingKwargs"}, "bioimageio.spec.model.v0_5.FixedZeroMeanUnitVarianceKwargs.mean": {"fullname": "bioimageio.spec.model.v0_5.FixedZeroMeanUnitVarianceKwargs.mean", "modulename": "bioimageio.spec.model.v0_5", "qualname": "FixedZeroMeanUnitVarianceKwargs.mean", "kind": "variable", "doc": "
    The mean value(s) to normalize with. Specify axis for a sequence of mean values
    \n", "annotation": ": Annotated[Union[float, Annotated[Tuple[float, ...], MinLen(min_length=1)]], FieldInfo(annotation=NoneType, required=True, examples=[3.14, (1.1, -2.2, 3.3)])]"}, "bioimageio.spec.model.v0_5.FixedZeroMeanUnitVarianceKwargs.std": {"fullname": "bioimageio.spec.model.v0_5.FixedZeroMeanUnitVarianceKwargs.std", "modulename": "bioimageio.spec.model.v0_5", "qualname": "FixedZeroMeanUnitVarianceKwargs.std", "kind": "variable", "doc": "
    The standard deviation value(s) to normalize with. Size must match mean values.
    \n", "annotation": ": Annotated[Union[Annotated[float, Ge(ge=1e-06)], Annotated[Tuple[Annotated[float, Ge(ge=1e-06)], ...], MinLen(min_length=1)]], FieldInfo(annotation=NoneType, required=True, examples=[1.05, (0.1, 0.2, 0.3)])]"}, "bioimageio.spec.model.v0_5.FixedZeroMeanUnitVarianceKwargs.axis": {"fullname": "bioimageio.spec.model.v0_5.FixedZeroMeanUnitVarianceKwargs.axis", "modulename": "bioimageio.spec.model.v0_5", "qualname": "FixedZeroMeanUnitVarianceKwargs.axis", "kind": "variable", "doc": "
    The axis of the mean/std values to normalize each entry along that dimension separately.\nInvalid for scalar gains/offsets.
    \n", "annotation": ": Annotated[Optional[Annotated[bioimageio.spec.model.v0_5.AxisId, Predicate(func=<function <lambda> at 0x7afc943332e0>)]], FieldInfo(annotation=NoneType, required=True, examples=['channel', 'index'])]"}, "bioimageio.spec.model.v0_5.FixedZeroMeanUnitVarianceKwargs.mean_and_std_match": {"fullname": "bioimageio.spec.model.v0_5.FixedZeroMeanUnitVarianceKwargs.mean_and_std_match", "modulename": "bioimageio.spec.model.v0_5", "qualname": "FixedZeroMeanUnitVarianceKwargs.mean_and_std_match", "kind": "function", "doc": "
    \n", "signature": "(self) -> Self:", "funcdef": "def"}, "bioimageio.spec.model.v0_5.FixedZeroMeanUnitVarianceKwargs.model_config": {"fullname": "bioimageio.spec.model.v0_5.FixedZeroMeanUnitVarianceKwargs.model_config", "modulename": "bioimageio.spec.model.v0_5", "qualname": "FixedZeroMeanUnitVarianceKwargs.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_5.FixedZeroMeanUnitVarianceKwargs.model_fields": {"fullname": "bioimageio.spec.model.v0_5.FixedZeroMeanUnitVarianceKwargs.model_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "FixedZeroMeanUnitVarianceKwargs.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'mean': FieldInfo(annotation=Union[float, Annotated[Tuple[float, ...], MinLen]], required=True, examples=[3.14, (1.1, -2.2, 3.3)]), 'std': FieldInfo(annotation=Union[Annotated[float, Ge], Annotated[Tuple[Annotated[float, Ge], ...], MinLen]], required=True, examples=[1.05, (0.1, 0.2, 0.3)]), 'axis': FieldInfo(annotation=Union[Annotated[AxisId, Predicate], NoneType], required=False, examples=['channel', 'index'])}"}, "bioimageio.spec.model.v0_5.FixedZeroMeanUnitVarianceKwargs.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_5.FixedZeroMeanUnitVarianceKwargs.model_computed_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "FixedZeroMeanUnitVarianceKwargs.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_5.FixedZeroMeanUnitVarianceDescr": {"fullname": "bioimageio.spec.model.v0_5.FixedZeroMeanUnitVarianceDescr", "modulename": "bioimageio.spec.model.v0_5", "qualname": "FixedZeroMeanUnitVarianceDescr", "kind": "class", "doc": "
    Subtract a given mean and divide by a given variance.
    \n", "bases": "ProcessingDescrBase"}, "bioimageio.spec.model.v0_5.FixedZeroMeanUnitVarianceDescr.id": {"fullname": "bioimageio.spec.model.v0_5.FixedZeroMeanUnitVarianceDescr.id", "modulename": "bioimageio.spec.model.v0_5", "qualname": "FixedZeroMeanUnitVarianceDescr.id", "kind": "variable", "doc": "
    \n", "annotation": ": Literal['fixed_zero_mean_unit_variance']"}, "bioimageio.spec.model.v0_5.FixedZeroMeanUnitVarianceDescr.kwargs": {"fullname": "bioimageio.spec.model.v0_5.FixedZeroMeanUnitVarianceDescr.kwargs", "modulename": "bioimageio.spec.model.v0_5", "qualname": "FixedZeroMeanUnitVarianceDescr.kwargs", "kind": "variable", "doc": "
    \n", "annotation": ": bioimageio.spec.model.v0_5.FixedZeroMeanUnitVarianceKwargs"}, "bioimageio.spec.model.v0_5.FixedZeroMeanUnitVarianceDescr.model_config": {"fullname": "bioimageio.spec.model.v0_5.FixedZeroMeanUnitVarianceDescr.model_config", "modulename": "bioimageio.spec.model.v0_5", "qualname": "FixedZeroMeanUnitVarianceDescr.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_5.FixedZeroMeanUnitVarianceDescr.model_fields": {"fullname": "bioimageio.spec.model.v0_5.FixedZeroMeanUnitVarianceDescr.model_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "FixedZeroMeanUnitVarianceDescr.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'id': FieldInfo(annotation=Literal['fixed_zero_mean_unit_variance'], required=False, default='fixed_zero_mean_unit_variance'), 'kwargs': FieldInfo(annotation=FixedZeroMeanUnitVarianceKwargs, required=True)}"}, "bioimageio.spec.model.v0_5.FixedZeroMeanUnitVarianceDescr.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_5.FixedZeroMeanUnitVarianceDescr.model_computed_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "FixedZeroMeanUnitVarianceDescr.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_5.ZeroMeanUnitVarianceKwargs": {"fullname": "bioimageio.spec.model.v0_5.ZeroMeanUnitVarianceKwargs", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ZeroMeanUnitVarianceKwargs", "kind": "class", "doc": "
    base class for pre-/postprocessing key word arguments
    \n", "bases": "bioimageio.spec.model.v0_4.ProcessingKwargs"}, "bioimageio.spec.model.v0_5.ZeroMeanUnitVarianceKwargs.axes": {"fullname": "bioimageio.spec.model.v0_5.ZeroMeanUnitVarianceKwargs.axes", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ZeroMeanUnitVarianceKwargs.axes", "kind": "variable", "doc": "
    The subset of axes to normalize jointly, i.e. axes to reduce to compute mean/std.\nFor example to normalize 'batch', 'x' and 'y' jointly in a tensor ('batch', 'channel', 'y', 'x')\nresulting in a tensor of equal shape normalized per channel, specify axes=('batch', 'x', 'y').\nTo normalize each sample independently leave out the 'batch' axis.\nDefault: Scale all axes jointly.
    \n", "annotation": ": Annotated[Optional[Sequence[bioimageio.spec.model.v0_5.AxisId]], FieldInfo(annotation=NoneType, required=True, examples=[('batch', 'x', 'y')])]"}, "bioimageio.spec.model.v0_5.ZeroMeanUnitVarianceKwargs.eps": {"fullname": "bioimageio.spec.model.v0_5.ZeroMeanUnitVarianceKwargs.eps", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ZeroMeanUnitVarianceKwargs.eps", "kind": "variable", "doc": "
    epsilon for numeric stability: out = (tensor - mean) / (std + eps).
    \n", "annotation": ": Annotated[float, Interval(gt=0, ge=None, lt=None, le=0.1)]"}, "bioimageio.spec.model.v0_5.ZeroMeanUnitVarianceKwargs.model_config": {"fullname": "bioimageio.spec.model.v0_5.ZeroMeanUnitVarianceKwargs.model_config", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ZeroMeanUnitVarianceKwargs.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_5.ZeroMeanUnitVarianceKwargs.model_fields": {"fullname": "bioimageio.spec.model.v0_5.ZeroMeanUnitVarianceKwargs.model_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ZeroMeanUnitVarianceKwargs.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'axes': FieldInfo(annotation=Union[Sequence[AxisId], NoneType], required=False, examples=[('batch', 'x', 'y')]), 'eps': FieldInfo(annotation=float, required=False, default=1e-06, metadata=[Interval(gt=0, ge=None, lt=None, le=0.1)])}"}, "bioimageio.spec.model.v0_5.ZeroMeanUnitVarianceKwargs.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_5.ZeroMeanUnitVarianceKwargs.model_computed_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ZeroMeanUnitVarianceKwargs.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_5.ZeroMeanUnitVarianceDescr": {"fullname": "bioimageio.spec.model.v0_5.ZeroMeanUnitVarianceDescr", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ZeroMeanUnitVarianceDescr", "kind": "class", "doc": "
    Subtract mean and divide by variance.
    \n", "bases": "ProcessingDescrBase"}, "bioimageio.spec.model.v0_5.ZeroMeanUnitVarianceDescr.id": {"fullname": "bioimageio.spec.model.v0_5.ZeroMeanUnitVarianceDescr.id", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ZeroMeanUnitVarianceDescr.id", "kind": "variable", "doc": "
    \n", "annotation": ": Literal['zero_mean_unit_variance']"}, "bioimageio.spec.model.v0_5.ZeroMeanUnitVarianceDescr.kwargs": {"fullname": "bioimageio.spec.model.v0_5.ZeroMeanUnitVarianceDescr.kwargs", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ZeroMeanUnitVarianceDescr.kwargs", "kind": "variable", "doc": "
    \n", "annotation": ": bioimageio.spec.model.v0_5.ZeroMeanUnitVarianceKwargs"}, "bioimageio.spec.model.v0_5.ZeroMeanUnitVarianceDescr.model_config": {"fullname": "bioimageio.spec.model.v0_5.ZeroMeanUnitVarianceDescr.model_config", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ZeroMeanUnitVarianceDescr.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_5.ZeroMeanUnitVarianceDescr.model_fields": {"fullname": "bioimageio.spec.model.v0_5.ZeroMeanUnitVarianceDescr.model_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ZeroMeanUnitVarianceDescr.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'id': FieldInfo(annotation=Literal['zero_mean_unit_variance'], required=False, default='zero_mean_unit_variance'), 'kwargs': FieldInfo(annotation=ZeroMeanUnitVarianceKwargs, required=True)}"}, "bioimageio.spec.model.v0_5.ZeroMeanUnitVarianceDescr.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_5.ZeroMeanUnitVarianceDescr.model_computed_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ZeroMeanUnitVarianceDescr.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_5.ScaleRangeKwargs": {"fullname": "bioimageio.spec.model.v0_5.ScaleRangeKwargs", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ScaleRangeKwargs", "kind": "class", "doc": "
    base class for pre-/postprocessing key word arguments
    \n", "bases": "bioimageio.spec.model.v0_4.ProcessingKwargs"}, "bioimageio.spec.model.v0_5.ScaleRangeKwargs.axes": {"fullname": "bioimageio.spec.model.v0_5.ScaleRangeKwargs.axes", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ScaleRangeKwargs.axes", "kind": "variable", "doc": "
    The subset of axes to normalize jointly, i.e. axes to reduce to compute the min/max percentile value.\nFor example to normalize 'batch', 'x' and 'y' jointly in a tensor ('batch', 'channel', 'y', 'x')\nresulting in a tensor of equal shape normalized per channel, specify axes=('batch', 'x', 'y').\nTo normalize samples indepdencently, leave out the \"batch\" axis.\nDefault: Scale all axes jointly.
    \n", "annotation": ": Annotated[Optional[Sequence[bioimageio.spec.model.v0_5.AxisId]], FieldInfo(annotation=NoneType, required=True, examples=[('batch', 'x', 'y')])]"}, "bioimageio.spec.model.v0_5.ScaleRangeKwargs.min_percentile": {"fullname": "bioimageio.spec.model.v0_5.ScaleRangeKwargs.min_percentile", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ScaleRangeKwargs.min_percentile", "kind": "variable", "doc": "
    The lower percentile used for normalization.
    \n", "annotation": ": Annotated[float, Interval(gt=None, ge=0, lt=100, le=None)]"}, "bioimageio.spec.model.v0_5.ScaleRangeKwargs.max_percentile": {"fullname": "bioimageio.spec.model.v0_5.ScaleRangeKwargs.max_percentile", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ScaleRangeKwargs.max_percentile", "kind": "variable", "doc": "
    The upper percentile used for normalization\nHas to be bigger than min_percentile.\nThe range is 1 to 100 instead of 0 to 100 to avoid mistakenly\naccepting percentiles specified in the range 0.0 to 1.0.
    \n", "annotation": ": Annotated[float, Interval(gt=1, ge=None, lt=None, le=100)]"}, "bioimageio.spec.model.v0_5.ScaleRangeKwargs.eps": {"fullname": "bioimageio.spec.model.v0_5.ScaleRangeKwargs.eps", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ScaleRangeKwargs.eps", "kind": "variable", "doc": "
    Epsilon for numeric stability.\nout = (tensor - v_lower) / (v_upper - v_lower + eps);\nwith v_lower,v_upper values at the respective percentiles.
    \n", "annotation": ": Annotated[float, Interval(gt=0, ge=None, lt=None, le=0.1)]"}, "bioimageio.spec.model.v0_5.ScaleRangeKwargs.reference_tensor": {"fullname": "bioimageio.spec.model.v0_5.ScaleRangeKwargs.reference_tensor", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ScaleRangeKwargs.reference_tensor", "kind": "variable", "doc": "
    Tensor ID to compute the percentiles from. Default: The tensor itself.\nFor any tensor in inputs only input tensor references are allowed.
    \n", "annotation": ": Optional[bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]]"}, "bioimageio.spec.model.v0_5.ScaleRangeKwargs.min_smaller_max": {"fullname": "bioimageio.spec.model.v0_5.ScaleRangeKwargs.min_smaller_max", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ScaleRangeKwargs.min_smaller_max", "kind": "function", "doc": "
    \n", "signature": "(\tcls,\tvalue: float,\tinfo: pydantic_core.core_schema.ValidationInfo) -> float:", "funcdef": "def"}, "bioimageio.spec.model.v0_5.ScaleRangeKwargs.model_config": {"fullname": "bioimageio.spec.model.v0_5.ScaleRangeKwargs.model_config", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ScaleRangeKwargs.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_5.ScaleRangeKwargs.model_fields": {"fullname": "bioimageio.spec.model.v0_5.ScaleRangeKwargs.model_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ScaleRangeKwargs.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'axes': FieldInfo(annotation=Union[Sequence[AxisId], NoneType], required=False, examples=[('batch', 'x', 'y')]), 'min_percentile': FieldInfo(annotation=float, required=False, default=0.0, metadata=[Interval(gt=None, ge=0, lt=100, le=None)]), 'max_percentile': FieldInfo(annotation=float, required=False, default=100.0, metadata=[Interval(gt=1, ge=None, lt=None, le=100)]), 'eps': FieldInfo(annotation=float, required=False, default=1e-06, metadata=[Interval(gt=0, ge=None, lt=None, le=0.1)]), 'reference_tensor': FieldInfo(annotation=Union[ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]], NoneType], required=False)}"}, "bioimageio.spec.model.v0_5.ScaleRangeKwargs.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_5.ScaleRangeKwargs.model_computed_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ScaleRangeKwargs.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_5.ScaleRangeDescr": {"fullname": "bioimageio.spec.model.v0_5.ScaleRangeDescr", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ScaleRangeDescr", "kind": "class", "doc": "
    Scale with percentiles.
    \n", "bases": "ProcessingDescrBase"}, "bioimageio.spec.model.v0_5.ScaleRangeDescr.id": {"fullname": "bioimageio.spec.model.v0_5.ScaleRangeDescr.id", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ScaleRangeDescr.id", "kind": "variable", "doc": "
    \n", "annotation": ": Literal['scale_range']"}, "bioimageio.spec.model.v0_5.ScaleRangeDescr.kwargs": {"fullname": "bioimageio.spec.model.v0_5.ScaleRangeDescr.kwargs", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ScaleRangeDescr.kwargs", "kind": "variable", "doc": "
    \n", "annotation": ": bioimageio.spec.model.v0_5.ScaleRangeKwargs"}, "bioimageio.spec.model.v0_5.ScaleRangeDescr.model_config": {"fullname": "bioimageio.spec.model.v0_5.ScaleRangeDescr.model_config", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ScaleRangeDescr.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_5.ScaleRangeDescr.model_fields": {"fullname": "bioimageio.spec.model.v0_5.ScaleRangeDescr.model_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ScaleRangeDescr.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'id': FieldInfo(annotation=Literal['scale_range'], required=False, default='scale_range'), 'kwargs': FieldInfo(annotation=ScaleRangeKwargs, required=True)}"}, "bioimageio.spec.model.v0_5.ScaleRangeDescr.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_5.ScaleRangeDescr.model_computed_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ScaleRangeDescr.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_5.ScaleMeanVarianceKwargs": {"fullname": "bioimageio.spec.model.v0_5.ScaleMeanVarianceKwargs", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ScaleMeanVarianceKwargs", "kind": "class", "doc": "
    Scale a tensor's data distribution to match another tensor's mean/std.\nout  = (tensor - mean) / (std + eps) * (ref_std + eps) + ref_mean.
    \n", "bases": "bioimageio.spec.model.v0_4.ProcessingKwargs"}, "bioimageio.spec.model.v0_5.ScaleMeanVarianceKwargs.reference_tensor": {"fullname": "bioimageio.spec.model.v0_5.ScaleMeanVarianceKwargs.reference_tensor", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ScaleMeanVarianceKwargs.reference_tensor", "kind": "variable", "doc": "
    Name of tensor to match.
    \n", "annotation": ": bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]"}, "bioimageio.spec.model.v0_5.ScaleMeanVarianceKwargs.axes": {"fullname": "bioimageio.spec.model.v0_5.ScaleMeanVarianceKwargs.axes", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ScaleMeanVarianceKwargs.axes", "kind": "variable", "doc": "
    The subset of axes to normalize jointly, i.e. axes to reduce to compute mean/std.\nFor example to normalize 'batch', 'x' and 'y' jointly in a tensor ('batch', 'channel', 'y', 'x')\nresulting in a tensor of equal shape normalized per channel, specify axes=('batch', 'x', 'y').\nTo normalize samples independently, leave out the 'batch' axis.\nDefault: Scale all axes jointly.
    \n", "annotation": ": Annotated[Optional[Sequence[bioimageio.spec.model.v0_5.AxisId]], FieldInfo(annotation=NoneType, required=True, examples=[('batch', 'x', 'y')])]"}, "bioimageio.spec.model.v0_5.ScaleMeanVarianceKwargs.eps": {"fullname": "bioimageio.spec.model.v0_5.ScaleMeanVarianceKwargs.eps", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ScaleMeanVarianceKwargs.eps", "kind": "variable", "doc": "
    Epsilon for numeric stability:\nout  = (tensor - mean) / (std + eps) * (ref_std + eps) + ref_mean.
    \n", "annotation": ": Annotated[float, Interval(gt=0, ge=None, lt=None, le=0.1)]"}, "bioimageio.spec.model.v0_5.ScaleMeanVarianceKwargs.model_config": {"fullname": "bioimageio.spec.model.v0_5.ScaleMeanVarianceKwargs.model_config", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ScaleMeanVarianceKwargs.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_5.ScaleMeanVarianceKwargs.model_fields": {"fullname": "bioimageio.spec.model.v0_5.ScaleMeanVarianceKwargs.model_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ScaleMeanVarianceKwargs.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'reference_tensor': FieldInfo(annotation=ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]], required=True), 'axes': FieldInfo(annotation=Union[Sequence[AxisId], NoneType], required=False, examples=[('batch', 'x', 'y')]), 'eps': FieldInfo(annotation=float, required=False, default=1e-06, metadata=[Interval(gt=0, ge=None, lt=None, le=0.1)])}"}, "bioimageio.spec.model.v0_5.ScaleMeanVarianceKwargs.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_5.ScaleMeanVarianceKwargs.model_computed_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ScaleMeanVarianceKwargs.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_5.ScaleMeanVarianceDescr": {"fullname": "bioimageio.spec.model.v0_5.ScaleMeanVarianceDescr", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ScaleMeanVarianceDescr", "kind": "class", "doc": "
    Scale the tensor s.t. its mean and variance match a reference tensor.
    \n", "bases": "ProcessingDescrBase"}, "bioimageio.spec.model.v0_5.ScaleMeanVarianceDescr.id": {"fullname": "bioimageio.spec.model.v0_5.ScaleMeanVarianceDescr.id", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ScaleMeanVarianceDescr.id", "kind": "variable", "doc": "
    \n", "annotation": ": Literal['scale_mean_variance']"}, "bioimageio.spec.model.v0_5.ScaleMeanVarianceDescr.kwargs": {"fullname": "bioimageio.spec.model.v0_5.ScaleMeanVarianceDescr.kwargs", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ScaleMeanVarianceDescr.kwargs", "kind": "variable", "doc": "
    \n", "annotation": ": bioimageio.spec.model.v0_5.ScaleMeanVarianceKwargs"}, "bioimageio.spec.model.v0_5.ScaleMeanVarianceDescr.model_config": {"fullname": "bioimageio.spec.model.v0_5.ScaleMeanVarianceDescr.model_config", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ScaleMeanVarianceDescr.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_5.ScaleMeanVarianceDescr.model_fields": {"fullname": "bioimageio.spec.model.v0_5.ScaleMeanVarianceDescr.model_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ScaleMeanVarianceDescr.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'id': FieldInfo(annotation=Literal['scale_mean_variance'], required=False, default='scale_mean_variance'), 'kwargs': FieldInfo(annotation=ScaleMeanVarianceKwargs, required=True)}"}, "bioimageio.spec.model.v0_5.ScaleMeanVarianceDescr.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_5.ScaleMeanVarianceDescr.model_computed_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ScaleMeanVarianceDescr.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_5.PreprocessingDescr": {"fullname": "bioimageio.spec.model.v0_5.PreprocessingDescr", "modulename": "bioimageio.spec.model.v0_5", "qualname": "PreprocessingDescr", "kind": "variable", "doc": "
    \n", "default_value": "typing.Annotated[typing.Union[bioimageio.spec.model.v0_5.BinarizeDescr, bioimageio.spec.model.v0_5.ClipDescr, bioimageio.spec.model.v0_5.EnsureDtypeDescr, bioimageio.spec.model.v0_5.ScaleLinearDescr, bioimageio.spec.model.v0_5.SigmoidDescr, bioimageio.spec.model.v0_5.FixedZeroMeanUnitVarianceDescr, bioimageio.spec.model.v0_5.ZeroMeanUnitVarianceDescr, bioimageio.spec.model.v0_5.ScaleRangeDescr], FieldInfo(annotation=NoneType, required=True, discriminator='id')]"}, "bioimageio.spec.model.v0_5.PostprocessingDescr": {"fullname": "bioimageio.spec.model.v0_5.PostprocessingDescr", "modulename": "bioimageio.spec.model.v0_5", "qualname": "PostprocessingDescr", "kind": "variable", "doc": "
    \n", "default_value": "typing.Annotated[typing.Union[bioimageio.spec.model.v0_5.BinarizeDescr, bioimageio.spec.model.v0_5.ClipDescr, bioimageio.spec.model.v0_5.EnsureDtypeDescr, bioimageio.spec.model.v0_5.ScaleLinearDescr, bioimageio.spec.model.v0_5.SigmoidDescr, bioimageio.spec.model.v0_5.FixedZeroMeanUnitVarianceDescr, bioimageio.spec.model.v0_5.ZeroMeanUnitVarianceDescr, bioimageio.spec.model.v0_5.ScaleRangeDescr, bioimageio.spec.model.v0_5.ScaleMeanVarianceDescr], FieldInfo(annotation=NoneType, required=True, discriminator='id')]"}, "bioimageio.spec.model.v0_5.TensorDescrBase": {"fullname": "bioimageio.spec.model.v0_5.TensorDescrBase", "modulename": "bioimageio.spec.model.v0_5", "qualname": "TensorDescrBase", "kind": "class", "doc": "
    Subpart of a resource description
    \n", "bases": "bioimageio.spec._internal.node.Node, typing.Generic[~IO_AxisT]"}, "bioimageio.spec.model.v0_5.TensorDescrBase.id": {"fullname": "bioimageio.spec.model.v0_5.TensorDescrBase.id", "modulename": "bioimageio.spec.model.v0_5", "qualname": "TensorDescrBase.id", "kind": "variable", "doc": "
    Tensor id. No duplicates are allowed.
    \n", "annotation": ": bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]"}, "bioimageio.spec.model.v0_5.TensorDescrBase.description": {"fullname": "bioimageio.spec.model.v0_5.TensorDescrBase.description", "modulename": "bioimageio.spec.model.v0_5", "qualname": "TensorDescrBase.description", "kind": "variable", "doc": "
    free text description
    \n", "annotation": ": Annotated[str, MaxLen(max_length=128)]"}, "bioimageio.spec.model.v0_5.TensorDescrBase.axes": {"fullname": "bioimageio.spec.model.v0_5.TensorDescrBase.axes", "modulename": "bioimageio.spec.model.v0_5", "qualname": "TensorDescrBase.axes", "kind": "variable", "doc": "
    tensor axes
    \n", "annotation": ": Annotated[Sequence[~IO_AxisT], MinLen(min_length=1)]"}, "bioimageio.spec.model.v0_5.TensorDescrBase.shape": {"fullname": "bioimageio.spec.model.v0_5.TensorDescrBase.shape", "modulename": "bioimageio.spec.model.v0_5", "qualname": "TensorDescrBase.shape", "kind": "variable", "doc": "
    \n"}, "bioimageio.spec.model.v0_5.TensorDescrBase.test_tensor": {"fullname": "bioimageio.spec.model.v0_5.TensorDescrBase.test_tensor", "modulename": "bioimageio.spec.model.v0_5", "qualname": "TensorDescrBase.test_tensor", "kind": "variable", "doc": "
    An example tensor to use for testing.\nUsing the model with the test input tensors is expected to yield the test output tensors.\nEach test tensor has be a an ndarray in the\nnumpy.lib file format.\nThe file extension must be '.npy'.
    \n", "annotation": ": bioimageio.spec._internal.io.FileDescr"}, "bioimageio.spec.model.v0_5.TensorDescrBase.sample_tensor": {"fullname": "bioimageio.spec.model.v0_5.TensorDescrBase.sample_tensor", "modulename": "bioimageio.spec.model.v0_5", "qualname": "TensorDescrBase.sample_tensor", "kind": "variable", "doc": "
    A sample tensor to illustrate a possible input/output for the model,\nThe sample image primarily serves to inform a human user about an example use case\nand is typically stored as .hdf5, .png or .tiff.\nIt has to be readable by the imageio library\n(numpy's .npy format is not supported).\nThe image dimensionality has to match the number of axes specified in this tensor description.
    \n", "annotation": ": Optional[bioimageio.spec._internal.io.FileDescr]"}, "bioimageio.spec.model.v0_5.TensorDescrBase.data": {"fullname": "bioimageio.spec.model.v0_5.TensorDescrBase.data", "modulename": "bioimageio.spec.model.v0_5", "qualname": "TensorDescrBase.data", "kind": "variable", "doc": "
    Description of the tensor's data values, optionally per channel.\nIf specified per channel, the data type needs to match across channels.
    \n", "annotation": ": Union[bioimageio.spec.model.v0_5.NominalOrOrdinalDataDescr, bioimageio.spec.model.v0_5.IntervalOrRatioDataDescr, Annotated[Sequence[Union[bioimageio.spec.model.v0_5.NominalOrOrdinalDataDescr, bioimageio.spec.model.v0_5.IntervalOrRatioDataDescr]], MinLen(min_length=1)]]"}, "bioimageio.spec.model.v0_5.TensorDescrBase.dtype": {"fullname": "bioimageio.spec.model.v0_5.TensorDescrBase.dtype", "modulename": "bioimageio.spec.model.v0_5", "qualname": "TensorDescrBase.dtype", "kind": "variable", "doc": "
    dtype as specified under data.type or data[i].type
    \n", "annotation": ": Literal['float32', 'float64', 'uint8', 'int8', 'uint16', 'int16', 'uint32', 'int32', 'uint64', 'int64', 'bool']"}, "bioimageio.spec.model.v0_5.TensorDescrBase.get_axis_sizes_for_array": {"fullname": "bioimageio.spec.model.v0_5.TensorDescrBase.get_axis_sizes_for_array", "modulename": "bioimageio.spec.model.v0_5", "qualname": "TensorDescrBase.get_axis_sizes_for_array", "kind": "function", "doc": "
    \n", "signature": "(\tself,\tarray: numpy.ndarray[typing.Any, numpy.dtype[typing.Any]]) -> Dict[bioimageio.spec.model.v0_5.AxisId, int]:", "funcdef": "def"}, "bioimageio.spec.model.v0_5.InputTensorDescr": {"fullname": "bioimageio.spec.model.v0_5.InputTensorDescr", "modulename": "bioimageio.spec.model.v0_5", "qualname": "InputTensorDescr", "kind": "class", "doc": "
    Subpart of a resource description
    \n", "bases": "bioimageio.spec._internal.node.Node, typing.Generic[~IO_AxisT]"}, "bioimageio.spec.model.v0_5.InputTensorDescr.id": {"fullname": "bioimageio.spec.model.v0_5.InputTensorDescr.id", "modulename": "bioimageio.spec.model.v0_5", "qualname": "InputTensorDescr.id", "kind": "variable", "doc": "
    Input tensor id.\nNo duplicates are allowed across all inputs and outputs.
    \n", "annotation": ": bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]"}, "bioimageio.spec.model.v0_5.InputTensorDescr.preprocessing": {"fullname": "bioimageio.spec.model.v0_5.InputTensorDescr.preprocessing", "modulename": "bioimageio.spec.model.v0_5", "qualname": "InputTensorDescr.preprocessing", "kind": "variable", "doc": "
    Description of how this input should be preprocessed.
    \n", "annotation": ": List[Annotated[Union[bioimageio.spec.model.v0_5.BinarizeDescr, bioimageio.spec.model.v0_5.ClipDescr, bioimageio.spec.model.v0_5.EnsureDtypeDescr, bioimageio.spec.model.v0_5.ScaleLinearDescr, bioimageio.spec.model.v0_5.SigmoidDescr, bioimageio.spec.model.v0_5.FixedZeroMeanUnitVarianceDescr, bioimageio.spec.model.v0_5.ZeroMeanUnitVarianceDescr, bioimageio.spec.model.v0_5.ScaleRangeDescr], FieldInfo(annotation=NoneType, required=True, discriminator='id')]]"}, "bioimageio.spec.model.v0_5.convert_axes": {"fullname": "bioimageio.spec.model.v0_5.convert_axes", "modulename": "bioimageio.spec.model.v0_5", "qualname": "convert_axes", "kind": "function", "doc": "
    \n", "signature": "(\taxes: str,\t*,\tshape: Union[Sequence[int], bioimageio.spec.model.v0_4.ParameterizedInputShape, bioimageio.spec.model.v0_4.ImplicitOutputShape],\ttensor_type: Literal['input', 'output'],\thalo: Optional[Sequence[int]],\tsize_refs: Mapping[bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate]]], Mapping[str, int]]):", "funcdef": "def"}, "bioimageio.spec.model.v0_5.OutputTensorDescr": {"fullname": "bioimageio.spec.model.v0_5.OutputTensorDescr", "modulename": "bioimageio.spec.model.v0_5", "qualname": "OutputTensorDescr", "kind": "class", "doc": "
    Subpart of a resource description
    \n", "bases": "bioimageio.spec._internal.node.Node, typing.Generic[~IO_AxisT]"}, "bioimageio.spec.model.v0_5.OutputTensorDescr.id": {"fullname": "bioimageio.spec.model.v0_5.OutputTensorDescr.id", "modulename": "bioimageio.spec.model.v0_5", "qualname": "OutputTensorDescr.id", "kind": "variable", "doc": "
    Output tensor id.\nNo duplicates are allowed across all inputs and outputs.
    \n", "annotation": ": bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]"}, "bioimageio.spec.model.v0_5.OutputTensorDescr.postprocessing": {"fullname": "bioimageio.spec.model.v0_5.OutputTensorDescr.postprocessing", "modulename": "bioimageio.spec.model.v0_5", "qualname": "OutputTensorDescr.postprocessing", "kind": "variable", "doc": "
    Description of how this output should be postprocessed.
    \n", "annotation": ": List[Annotated[Union[bioimageio.spec.model.v0_5.BinarizeDescr, bioimageio.spec.model.v0_5.ClipDescr, bioimageio.spec.model.v0_5.EnsureDtypeDescr, bioimageio.spec.model.v0_5.ScaleLinearDescr, bioimageio.spec.model.v0_5.SigmoidDescr, bioimageio.spec.model.v0_5.FixedZeroMeanUnitVarianceDescr, bioimageio.spec.model.v0_5.ZeroMeanUnitVarianceDescr, bioimageio.spec.model.v0_5.ScaleRangeDescr, bioimageio.spec.model.v0_5.ScaleMeanVarianceDescr], FieldInfo(annotation=NoneType, required=True, discriminator='id')]]"}, "bioimageio.spec.model.v0_5.TensorDescr": {"fullname": "bioimageio.spec.model.v0_5.TensorDescr", "modulename": "bioimageio.spec.model.v0_5", "qualname": "TensorDescr", "kind": "variable", "doc": "
    \n", "default_value": "typing.Union[bioimageio.spec.model.v0_5.InputTensorDescr, bioimageio.spec.model.v0_5.OutputTensorDescr]"}, "bioimageio.spec.model.v0_5.validate_tensors": {"fullname": "bioimageio.spec.model.v0_5.validate_tensors", "modulename": "bioimageio.spec.model.v0_5", "qualname": "validate_tensors", "kind": "function", "doc": "
    \n", "signature": "(\ttensors: Mapping[bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]], Tuple[Union[bioimageio.spec.model.v0_5.InputTensorDescr, bioimageio.spec.model.v0_5.OutputTensorDescr], numpy.ndarray[Any, numpy.dtype[Any]]]],\ttensor_origin: str):", "funcdef": "def"}, "bioimageio.spec.model.v0_5.EnvironmentFileDescr": {"fullname": "bioimageio.spec.model.v0_5.EnvironmentFileDescr", "modulename": "bioimageio.spec.model.v0_5", "qualname": "EnvironmentFileDescr", "kind": "class", "doc": "
    Subpart of a resource description
    \n", "bases": "bioimageio.spec._internal.io.FileDescr"}, "bioimageio.spec.model.v0_5.EnvironmentFileDescr.source": {"fullname": "bioimageio.spec.model.v0_5.EnvironmentFileDescr.source", "modulename": "bioimageio.spec.model.v0_5", "qualname": "EnvironmentFileDescr.source", "kind": "variable", "doc": "
    \u2208\ud83d\udce6 Conda environment file.\nAllows to specify custom dependencies, see conda docs:
    \n\n\n", "annotation": ": Annotated[Union[Annotated[pathlib.Path, PathType(path_type='file')], bioimageio.spec._internal.io.RelativeFilePath, bioimageio.spec._internal.url.HttpUrl, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator(func=<function wo_special_file_name at 0x7afca0d90540>), PlainSerializer(func=<function _package at 0x7afca0d91760>, return_type=PydanticUndefined, when_used='unless-none'), WithSuffix(suffix=('.yaml', '.yml'), case_sensitive=True), FieldInfo(annotation=NoneType, required=True, examples=['environment.yaml'])]"}, "bioimageio.spec.model.v0_5.EnvironmentFileDescr.model_config": {"fullname": "bioimageio.spec.model.v0_5.EnvironmentFileDescr.model_config", "modulename": "bioimageio.spec.model.v0_5", "qualname": "EnvironmentFileDescr.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_5.EnvironmentFileDescr.model_fields": {"fullname": "bioimageio.spec.model.v0_5.EnvironmentFileDescr.model_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "EnvironmentFileDescr.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'source': FieldInfo(annotation=Union[Annotated[Path, PathType], RelativeFilePath, HttpUrl, Annotated[Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], required=True, examples=['environment.yaml'], metadata=[AfterValidator(func=<function wo_special_file_name>), PlainSerializer(func=<function _package>, return_type=PydanticUndefined, when_used='unless-none'), WithSuffix(suffix=('.yaml', '.yml'), case_sensitive=True)]), 'sha256': FieldInfo(annotation=Union[Sha256, NoneType], required=False)}"}, "bioimageio.spec.model.v0_5.EnvironmentFileDescr.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_5.EnvironmentFileDescr.model_computed_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "EnvironmentFileDescr.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_5.ArchitectureFromFileDescr": {"fullname": "bioimageio.spec.model.v0_5.ArchitectureFromFileDescr", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ArchitectureFromFileDescr", "kind": "class", "doc": "
    Subpart of a resource description
    \n", "bases": "_ArchitectureCallableDescr, bioimageio.spec._internal.io.FileDescr"}, "bioimageio.spec.model.v0_5.ArchitectureFromFileDescr.model_config": {"fullname": "bioimageio.spec.model.v0_5.ArchitectureFromFileDescr.model_config", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ArchitectureFromFileDescr.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_5.ArchitectureFromFileDescr.model_fields": {"fullname": "bioimageio.spec.model.v0_5.ArchitectureFromFileDescr.model_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ArchitectureFromFileDescr.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'source': FieldInfo(annotation=Union[Annotated[Path, PathType], RelativeFilePath, HttpUrl, Annotated[Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], required=True, metadata=[AfterValidator(func=<function wo_special_file_name>), PlainSerializer(func=<function _package>, return_type=PydanticUndefined, when_used='unless-none')]), 'sha256': FieldInfo(annotation=Union[Sha256, NoneType], required=False), 'callable': FieldInfo(annotation=ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator]], required=True, examples=['MyNetworkClass', 'get_my_model']), 'kwargs': FieldInfo(annotation=Dict[str, Any], required=False, default_factory=dict)}"}, "bioimageio.spec.model.v0_5.ArchitectureFromFileDescr.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_5.ArchitectureFromFileDescr.model_computed_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ArchitectureFromFileDescr.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_5.ArchitectureFromLibraryDescr": {"fullname": "bioimageio.spec.model.v0_5.ArchitectureFromLibraryDescr", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ArchitectureFromLibraryDescr", "kind": "class", "doc": "
    Subpart of a resource description
    \n", "bases": "_ArchitectureCallableDescr"}, "bioimageio.spec.model.v0_5.ArchitectureFromLibraryDescr.import_from": {"fullname": "bioimageio.spec.model.v0_5.ArchitectureFromLibraryDescr.import_from", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ArchitectureFromLibraryDescr.import_from", "kind": "variable", "doc": "
    Where to import the callable from, i.e. from <import_from> import <callable>
    \n", "annotation": ": str"}, "bioimageio.spec.model.v0_5.ArchitectureFromLibraryDescr.model_config": {"fullname": "bioimageio.spec.model.v0_5.ArchitectureFromLibraryDescr.model_config", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ArchitectureFromLibraryDescr.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_5.ArchitectureFromLibraryDescr.model_fields": {"fullname": "bioimageio.spec.model.v0_5.ArchitectureFromLibraryDescr.model_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ArchitectureFromLibraryDescr.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'callable': FieldInfo(annotation=ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator]], required=True, examples=['MyNetworkClass', 'get_my_model']), 'kwargs': FieldInfo(annotation=Dict[str, Any], required=False, default_factory=dict), 'import_from': FieldInfo(annotation=str, required=True)}"}, "bioimageio.spec.model.v0_5.ArchitectureFromLibraryDescr.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_5.ArchitectureFromLibraryDescr.model_computed_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ArchitectureFromLibraryDescr.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_5.ArchitectureDescr": {"fullname": "bioimageio.spec.model.v0_5.ArchitectureDescr", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ArchitectureDescr", "kind": "variable", "doc": "
    \n", "default_value": "typing.Union[bioimageio.spec.model.v0_5.ArchitectureFromFileDescr, bioimageio.spec.model.v0_5.ArchitectureFromLibraryDescr]"}, "bioimageio.spec.model.v0_5.WeightsEntryDescrBase": {"fullname": "bioimageio.spec.model.v0_5.WeightsEntryDescrBase", "modulename": "bioimageio.spec.model.v0_5", "qualname": "WeightsEntryDescrBase", "kind": "class", "doc": "
    Subpart of a resource description
    \n", "bases": "bioimageio.spec._internal.io.FileDescr"}, "bioimageio.spec.model.v0_5.WeightsEntryDescrBase.type": {"fullname": "bioimageio.spec.model.v0_5.WeightsEntryDescrBase.type", "modulename": "bioimageio.spec.model.v0_5", "qualname": "WeightsEntryDescrBase.type", "kind": "variable", "doc": "
    \n", "annotation": ": ClassVar[Literal['keras_hdf5', 'onnx', 'pytorch_state_dict', 'tensorflow_js', 'tensorflow_saved_model_bundle', 'torchscript']]"}, "bioimageio.spec.model.v0_5.WeightsEntryDescrBase.weights_format_name": {"fullname": "bioimageio.spec.model.v0_5.WeightsEntryDescrBase.weights_format_name", "modulename": "bioimageio.spec.model.v0_5", "qualname": "WeightsEntryDescrBase.weights_format_name", "kind": "variable", "doc": "
    \n", "annotation": ": ClassVar[str]"}, "bioimageio.spec.model.v0_5.WeightsEntryDescrBase.source": {"fullname": "bioimageio.spec.model.v0_5.WeightsEntryDescrBase.source", "modulename": "bioimageio.spec.model.v0_5", "qualname": "WeightsEntryDescrBase.source", "kind": "variable", "doc": "
    \u2208\ud83d\udce6 The weights file.
    \n", "annotation": ": Annotated[Union[Annotated[pathlib.Path, PathType(path_type='file')], bioimageio.spec._internal.io.RelativeFilePath, bioimageio.spec._internal.url.HttpUrl, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator(func=<function wo_special_file_name at 0x7afca0d90540>), PlainSerializer(func=<function _package at 0x7afca0d91760>, return_type=PydanticUndefined, when_used='unless-none')]"}, "bioimageio.spec.model.v0_5.WeightsEntryDescrBase.authors": {"fullname": "bioimageio.spec.model.v0_5.WeightsEntryDescrBase.authors", "modulename": "bioimageio.spec.model.v0_5", "qualname": "WeightsEntryDescrBase.authors", "kind": "variable", "doc": "
    Authors\nEither the person(s) that have trained this model resulting in the original weights file.\n    (If this is the initial weights entry, i.e. it does not have a parent)\nOr the person(s) who have converted the weights to this weights format.\n    (If this is a child weight, i.e. it has a parent field)
    \n", "annotation": ": Optional[List[bioimageio.spec.generic.v0_3.Author]]"}, "bioimageio.spec.model.v0_5.WeightsEntryDescrBase.parent": {"fullname": "bioimageio.spec.model.v0_5.WeightsEntryDescrBase.parent", "modulename": "bioimageio.spec.model.v0_5", "qualname": "WeightsEntryDescrBase.parent", "kind": "variable", "doc": "
    The source weights these weights were converted from.\nFor example, if a model's weights were converted from the pytorch_state_dict format to torchscript,\nThe pytorch_state_dict weights entry has no parent and is the parent of the torchscript weights.\nAll weight entries except one (the initial set of weights resulting from training the model),\nneed to have this field.
    \n", "annotation": ": Annotated[Optional[Literal['keras_hdf5', 'onnx', 'pytorch_state_dict', 'tensorflow_js', 'tensorflow_saved_model_bundle', 'torchscript']], FieldInfo(annotation=NoneType, required=True, examples=['pytorch_state_dict'])]"}, "bioimageio.spec.model.v0_5.WeightsEntryDescrBase.check_parent_is_not_self": {"fullname": "bioimageio.spec.model.v0_5.WeightsEntryDescrBase.check_parent_is_not_self", "modulename": "bioimageio.spec.model.v0_5", "qualname": "WeightsEntryDescrBase.check_parent_is_not_self", "kind": "function", "doc": "
    \n", "signature": "(self) -> Self:", "funcdef": "def"}, "bioimageio.spec.model.v0_5.WeightsEntryDescrBase.model_config": {"fullname": "bioimageio.spec.model.v0_5.WeightsEntryDescrBase.model_config", "modulename": "bioimageio.spec.model.v0_5", "qualname": "WeightsEntryDescrBase.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_5.WeightsEntryDescrBase.model_fields": {"fullname": "bioimageio.spec.model.v0_5.WeightsEntryDescrBase.model_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "WeightsEntryDescrBase.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'source': FieldInfo(annotation=Union[Annotated[Path, PathType], RelativeFilePath, HttpUrl, Annotated[Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], required=True, metadata=[AfterValidator(func=<function wo_special_file_name>), PlainSerializer(func=<function _package>, return_type=PydanticUndefined, when_used='unless-none')]), 'sha256': FieldInfo(annotation=Union[Sha256, NoneType], required=False), 'authors': FieldInfo(annotation=Union[List[Author], NoneType], required=False), 'parent': FieldInfo(annotation=Union[Literal['keras_hdf5', 'onnx', 'pytorch_state_dict', 'tensorflow_js', 'tensorflow_saved_model_bundle', 'torchscript'], NoneType], required=False, examples=['pytorch_state_dict'])}"}, "bioimageio.spec.model.v0_5.WeightsEntryDescrBase.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_5.WeightsEntryDescrBase.model_computed_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "WeightsEntryDescrBase.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_5.KerasHdf5WeightsDescr": {"fullname": "bioimageio.spec.model.v0_5.KerasHdf5WeightsDescr", "modulename": "bioimageio.spec.model.v0_5", "qualname": "KerasHdf5WeightsDescr", "kind": "class", "doc": "
    Subpart of a resource description
    \n", "bases": "WeightsEntryDescrBase"}, "bioimageio.spec.model.v0_5.KerasHdf5WeightsDescr.type": {"fullname": "bioimageio.spec.model.v0_5.KerasHdf5WeightsDescr.type", "modulename": "bioimageio.spec.model.v0_5", "qualname": "KerasHdf5WeightsDescr.type", "kind": "variable", "doc": "
    \n", "default_value": "'keras_hdf5'"}, "bioimageio.spec.model.v0_5.KerasHdf5WeightsDescr.weights_format_name": {"fullname": "bioimageio.spec.model.v0_5.KerasHdf5WeightsDescr.weights_format_name", "modulename": "bioimageio.spec.model.v0_5", "qualname": "KerasHdf5WeightsDescr.weights_format_name", "kind": "variable", "doc": "
    \n", "annotation": ": ClassVar[str]", "default_value": "'Keras HDF5'"}, "bioimageio.spec.model.v0_5.KerasHdf5WeightsDescr.tensorflow_version": {"fullname": "bioimageio.spec.model.v0_5.KerasHdf5WeightsDescr.tensorflow_version", "modulename": "bioimageio.spec.model.v0_5", "qualname": "KerasHdf5WeightsDescr.tensorflow_version", "kind": "variable", "doc": "
    TensorFlow version used to create these weights.
    \n", "annotation": ": bioimageio.spec._internal.version_type.Version"}, "bioimageio.spec.model.v0_5.KerasHdf5WeightsDescr.model_config": {"fullname": "bioimageio.spec.model.v0_5.KerasHdf5WeightsDescr.model_config", "modulename": "bioimageio.spec.model.v0_5", "qualname": "KerasHdf5WeightsDescr.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_5.KerasHdf5WeightsDescr.model_fields": {"fullname": "bioimageio.spec.model.v0_5.KerasHdf5WeightsDescr.model_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "KerasHdf5WeightsDescr.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'source': FieldInfo(annotation=Union[Annotated[Path, PathType], RelativeFilePath, HttpUrl, Annotated[Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], required=True, metadata=[AfterValidator(func=<function wo_special_file_name>), PlainSerializer(func=<function _package>, return_type=PydanticUndefined, when_used='unless-none')]), 'sha256': FieldInfo(annotation=Union[Sha256, NoneType], required=False), 'authors': FieldInfo(annotation=Union[List[Author], NoneType], required=False), 'parent': FieldInfo(annotation=Union[Literal['keras_hdf5', 'onnx', 'pytorch_state_dict', 'tensorflow_js', 'tensorflow_saved_model_bundle', 'torchscript'], NoneType], required=False, examples=['pytorch_state_dict']), 'tensorflow_version': FieldInfo(annotation=Version, required=True)}"}, "bioimageio.spec.model.v0_5.KerasHdf5WeightsDescr.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_5.KerasHdf5WeightsDescr.model_computed_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "KerasHdf5WeightsDescr.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_5.OnnxWeightsDescr": {"fullname": "bioimageio.spec.model.v0_5.OnnxWeightsDescr", "modulename": "bioimageio.spec.model.v0_5", "qualname": "OnnxWeightsDescr", "kind": "class", "doc": "
    Subpart of a resource description
    \n", "bases": "WeightsEntryDescrBase"}, "bioimageio.spec.model.v0_5.OnnxWeightsDescr.type": {"fullname": "bioimageio.spec.model.v0_5.OnnxWeightsDescr.type", "modulename": "bioimageio.spec.model.v0_5", "qualname": "OnnxWeightsDescr.type", "kind": "variable", "doc": "
    \n", "default_value": "'onnx'"}, "bioimageio.spec.model.v0_5.OnnxWeightsDescr.weights_format_name": {"fullname": "bioimageio.spec.model.v0_5.OnnxWeightsDescr.weights_format_name", "modulename": "bioimageio.spec.model.v0_5", "qualname": "OnnxWeightsDescr.weights_format_name", "kind": "variable", "doc": "
    \n", "annotation": ": ClassVar[str]", "default_value": "'ONNX'"}, "bioimageio.spec.model.v0_5.OnnxWeightsDescr.opset_version": {"fullname": "bioimageio.spec.model.v0_5.OnnxWeightsDescr.opset_version", "modulename": "bioimageio.spec.model.v0_5", "qualname": "OnnxWeightsDescr.opset_version", "kind": "variable", "doc": "
    ONNX opset version
    \n", "annotation": ": Annotated[int, Ge(ge=7)]"}, "bioimageio.spec.model.v0_5.OnnxWeightsDescr.model_config": {"fullname": "bioimageio.spec.model.v0_5.OnnxWeightsDescr.model_config", "modulename": "bioimageio.spec.model.v0_5", "qualname": "OnnxWeightsDescr.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_5.OnnxWeightsDescr.model_fields": {"fullname": "bioimageio.spec.model.v0_5.OnnxWeightsDescr.model_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "OnnxWeightsDescr.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'source': FieldInfo(annotation=Union[Annotated[Path, PathType], RelativeFilePath, HttpUrl, Annotated[Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], required=True, metadata=[AfterValidator(func=<function wo_special_file_name>), PlainSerializer(func=<function _package>, return_type=PydanticUndefined, when_used='unless-none')]), 'sha256': FieldInfo(annotation=Union[Sha256, NoneType], required=False), 'authors': FieldInfo(annotation=Union[List[Author], NoneType], required=False), 'parent': FieldInfo(annotation=Union[Literal['keras_hdf5', 'onnx', 'pytorch_state_dict', 'tensorflow_js', 'tensorflow_saved_model_bundle', 'torchscript'], NoneType], required=False, examples=['pytorch_state_dict']), 'opset_version': FieldInfo(annotation=int, required=True, metadata=[Ge(ge=7)])}"}, "bioimageio.spec.model.v0_5.OnnxWeightsDescr.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_5.OnnxWeightsDescr.model_computed_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "OnnxWeightsDescr.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_5.PytorchStateDictWeightsDescr": {"fullname": "bioimageio.spec.model.v0_5.PytorchStateDictWeightsDescr", "modulename": "bioimageio.spec.model.v0_5", "qualname": "PytorchStateDictWeightsDescr", "kind": "class", "doc": "
    Subpart of a resource description
    \n", "bases": "WeightsEntryDescrBase"}, "bioimageio.spec.model.v0_5.PytorchStateDictWeightsDescr.type": {"fullname": "bioimageio.spec.model.v0_5.PytorchStateDictWeightsDescr.type", "modulename": "bioimageio.spec.model.v0_5", "qualname": "PytorchStateDictWeightsDescr.type", "kind": "variable", "doc": "
    \n", "default_value": "'pytorch_state_dict'"}, "bioimageio.spec.model.v0_5.PytorchStateDictWeightsDescr.weights_format_name": {"fullname": "bioimageio.spec.model.v0_5.PytorchStateDictWeightsDescr.weights_format_name", "modulename": "bioimageio.spec.model.v0_5", "qualname": "PytorchStateDictWeightsDescr.weights_format_name", "kind": "variable", "doc": "
    \n", "annotation": ": ClassVar[str]", "default_value": "'Pytorch State Dict'"}, "bioimageio.spec.model.v0_5.PytorchStateDictWeightsDescr.architecture": {"fullname": "bioimageio.spec.model.v0_5.PytorchStateDictWeightsDescr.architecture", "modulename": "bioimageio.spec.model.v0_5", "qualname": "PytorchStateDictWeightsDescr.architecture", "kind": "variable", "doc": "
    \n", "annotation": ": Union[bioimageio.spec.model.v0_5.ArchitectureFromFileDescr, bioimageio.spec.model.v0_5.ArchitectureFromLibraryDescr]"}, "bioimageio.spec.model.v0_5.PytorchStateDictWeightsDescr.pytorch_version": {"fullname": "bioimageio.spec.model.v0_5.PytorchStateDictWeightsDescr.pytorch_version", "modulename": "bioimageio.spec.model.v0_5", "qualname": "PytorchStateDictWeightsDescr.pytorch_version", "kind": "variable", "doc": "
    Version of the PyTorch library used.\nIf architecture.depencencies is specified it has to include pytorch and any version pinning has to be compatible.
    \n", "annotation": ": bioimageio.spec._internal.version_type.Version"}, "bioimageio.spec.model.v0_5.PytorchStateDictWeightsDescr.dependencies": {"fullname": "bioimageio.spec.model.v0_5.PytorchStateDictWeightsDescr.dependencies", "modulename": "bioimageio.spec.model.v0_5", "qualname": "PytorchStateDictWeightsDescr.dependencies", "kind": "variable", "doc": "
    Custom depencies beyond pytorch.\nThe conda environment file should include pytorch and any version pinning has to be compatible with\npytorch_version.
    \n", "annotation": ": Optional[bioimageio.spec.model.v0_5.EnvironmentFileDescr]"}, "bioimageio.spec.model.v0_5.PytorchStateDictWeightsDescr.model_config": {"fullname": "bioimageio.spec.model.v0_5.PytorchStateDictWeightsDescr.model_config", "modulename": "bioimageio.spec.model.v0_5", "qualname": "PytorchStateDictWeightsDescr.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_5.PytorchStateDictWeightsDescr.model_fields": {"fullname": "bioimageio.spec.model.v0_5.PytorchStateDictWeightsDescr.model_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "PytorchStateDictWeightsDescr.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'source': FieldInfo(annotation=Union[Annotated[Path, PathType], RelativeFilePath, HttpUrl, Annotated[Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], required=True, metadata=[AfterValidator(func=<function wo_special_file_name>), PlainSerializer(func=<function _package>, return_type=PydanticUndefined, when_used='unless-none')]), 'sha256': FieldInfo(annotation=Union[Sha256, NoneType], required=False), 'authors': FieldInfo(annotation=Union[List[Author], NoneType], required=False), 'parent': FieldInfo(annotation=Union[Literal['keras_hdf5', 'onnx', 'pytorch_state_dict', 'tensorflow_js', 'tensorflow_saved_model_bundle', 'torchscript'], NoneType], required=False, examples=['pytorch_state_dict']), 'architecture': FieldInfo(annotation=Union[ArchitectureFromFileDescr, ArchitectureFromLibraryDescr], required=True), 'pytorch_version': FieldInfo(annotation=Version, required=True), 'dependencies': FieldInfo(annotation=Union[EnvironmentFileDescr, NoneType], required=False)}"}, "bioimageio.spec.model.v0_5.PytorchStateDictWeightsDescr.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_5.PytorchStateDictWeightsDescr.model_computed_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "PytorchStateDictWeightsDescr.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_5.TensorflowJsWeightsDescr": {"fullname": "bioimageio.spec.model.v0_5.TensorflowJsWeightsDescr", "modulename": "bioimageio.spec.model.v0_5", "qualname": "TensorflowJsWeightsDescr", "kind": "class", "doc": "
    Subpart of a resource description
    \n", "bases": "WeightsEntryDescrBase"}, "bioimageio.spec.model.v0_5.TensorflowJsWeightsDescr.type": {"fullname": "bioimageio.spec.model.v0_5.TensorflowJsWeightsDescr.type", "modulename": "bioimageio.spec.model.v0_5", "qualname": "TensorflowJsWeightsDescr.type", "kind": "variable", "doc": "
    \n", "default_value": "'tensorflow_js'"}, "bioimageio.spec.model.v0_5.TensorflowJsWeightsDescr.weights_format_name": {"fullname": "bioimageio.spec.model.v0_5.TensorflowJsWeightsDescr.weights_format_name", "modulename": "bioimageio.spec.model.v0_5", "qualname": "TensorflowJsWeightsDescr.weights_format_name", "kind": "variable", "doc": "
    \n", "annotation": ": ClassVar[str]", "default_value": "'Tensorflow.js'"}, "bioimageio.spec.model.v0_5.TensorflowJsWeightsDescr.tensorflow_version": {"fullname": "bioimageio.spec.model.v0_5.TensorflowJsWeightsDescr.tensorflow_version", "modulename": "bioimageio.spec.model.v0_5", "qualname": "TensorflowJsWeightsDescr.tensorflow_version", "kind": "variable", "doc": "
    Version of the TensorFlow library used.
    \n", "annotation": ": bioimageio.spec._internal.version_type.Version"}, "bioimageio.spec.model.v0_5.TensorflowJsWeightsDescr.source": {"fullname": "bioimageio.spec.model.v0_5.TensorflowJsWeightsDescr.source", "modulename": "bioimageio.spec.model.v0_5", "qualname": "TensorflowJsWeightsDescr.source", "kind": "variable", "doc": "
    \u2208\ud83d\udce6 The multi-file weights.\nAll required files/folders should be a zip archive.
    \n", "annotation": ": Annotated[Union[Annotated[pathlib.Path, PathType(path_type='file')], bioimageio.spec._internal.io.RelativeFilePath, bioimageio.spec._internal.url.HttpUrl, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator(func=<function wo_special_file_name at 0x7afca0d90540>), PlainSerializer(func=<function _package at 0x7afca0d91760>, return_type=PydanticUndefined, when_used='unless-none')]"}, "bioimageio.spec.model.v0_5.TensorflowJsWeightsDescr.model_config": {"fullname": "bioimageio.spec.model.v0_5.TensorflowJsWeightsDescr.model_config", "modulename": "bioimageio.spec.model.v0_5", "qualname": "TensorflowJsWeightsDescr.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_5.TensorflowJsWeightsDescr.model_fields": {"fullname": "bioimageio.spec.model.v0_5.TensorflowJsWeightsDescr.model_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "TensorflowJsWeightsDescr.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'source': FieldInfo(annotation=Union[Annotated[Path, PathType], RelativeFilePath, HttpUrl, Annotated[Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], required=True, metadata=[AfterValidator(func=<function wo_special_file_name>), PlainSerializer(func=<function _package>, return_type=PydanticUndefined, when_used='unless-none')]), 'sha256': FieldInfo(annotation=Union[Sha256, NoneType], required=False), 'authors': FieldInfo(annotation=Union[List[Author], NoneType], required=False), 'parent': FieldInfo(annotation=Union[Literal['keras_hdf5', 'onnx', 'pytorch_state_dict', 'tensorflow_js', 'tensorflow_saved_model_bundle', 'torchscript'], NoneType], required=False, examples=['pytorch_state_dict']), 'tensorflow_version': FieldInfo(annotation=Version, required=True)}"}, "bioimageio.spec.model.v0_5.TensorflowJsWeightsDescr.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_5.TensorflowJsWeightsDescr.model_computed_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "TensorflowJsWeightsDescr.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_5.TensorflowSavedModelBundleWeightsDescr": {"fullname": "bioimageio.spec.model.v0_5.TensorflowSavedModelBundleWeightsDescr", "modulename": "bioimageio.spec.model.v0_5", "qualname": "TensorflowSavedModelBundleWeightsDescr", "kind": "class", "doc": "
    Subpart of a resource description
    \n", "bases": "WeightsEntryDescrBase"}, "bioimageio.spec.model.v0_5.TensorflowSavedModelBundleWeightsDescr.type": {"fullname": "bioimageio.spec.model.v0_5.TensorflowSavedModelBundleWeightsDescr.type", "modulename": "bioimageio.spec.model.v0_5", "qualname": "TensorflowSavedModelBundleWeightsDescr.type", "kind": "variable", "doc": "
    \n", "default_value": "'tensorflow_saved_model_bundle'"}, "bioimageio.spec.model.v0_5.TensorflowSavedModelBundleWeightsDescr.weights_format_name": {"fullname": "bioimageio.spec.model.v0_5.TensorflowSavedModelBundleWeightsDescr.weights_format_name", "modulename": "bioimageio.spec.model.v0_5", "qualname": "TensorflowSavedModelBundleWeightsDescr.weights_format_name", "kind": "variable", "doc": "
    \n", "annotation": ": ClassVar[str]", "default_value": "'Tensorflow Saved Model'"}, "bioimageio.spec.model.v0_5.TensorflowSavedModelBundleWeightsDescr.tensorflow_version": {"fullname": "bioimageio.spec.model.v0_5.TensorflowSavedModelBundleWeightsDescr.tensorflow_version", "modulename": "bioimageio.spec.model.v0_5", "qualname": "TensorflowSavedModelBundleWeightsDescr.tensorflow_version", "kind": "variable", "doc": "
    Version of the TensorFlow library used.
    \n", "annotation": ": bioimageio.spec._internal.version_type.Version"}, "bioimageio.spec.model.v0_5.TensorflowSavedModelBundleWeightsDescr.dependencies": {"fullname": "bioimageio.spec.model.v0_5.TensorflowSavedModelBundleWeightsDescr.dependencies", "modulename": "bioimageio.spec.model.v0_5", "qualname": "TensorflowSavedModelBundleWeightsDescr.dependencies", "kind": "variable", "doc": "
    Custom dependencies beyond tensorflow.\nShould include tensorflow and any version pinning has to be compatible with tensorflow_version.
    \n", "annotation": ": Optional[bioimageio.spec.model.v0_5.EnvironmentFileDescr]"}, "bioimageio.spec.model.v0_5.TensorflowSavedModelBundleWeightsDescr.source": {"fullname": "bioimageio.spec.model.v0_5.TensorflowSavedModelBundleWeightsDescr.source", "modulename": "bioimageio.spec.model.v0_5", "qualname": "TensorflowSavedModelBundleWeightsDescr.source", "kind": "variable", "doc": "
    \u2208\ud83d\udce6 The multi-file weights.\nAll required files/folders should be a zip archive.
    \n", "annotation": ": Annotated[Union[Annotated[pathlib.Path, PathType(path_type='file')], bioimageio.spec._internal.io.RelativeFilePath, bioimageio.spec._internal.url.HttpUrl, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator(func=<function wo_special_file_name at 0x7afca0d90540>), PlainSerializer(func=<function _package at 0x7afca0d91760>, return_type=PydanticUndefined, when_used='unless-none')]"}, "bioimageio.spec.model.v0_5.TensorflowSavedModelBundleWeightsDescr.model_config": {"fullname": "bioimageio.spec.model.v0_5.TensorflowSavedModelBundleWeightsDescr.model_config", "modulename": "bioimageio.spec.model.v0_5", "qualname": "TensorflowSavedModelBundleWeightsDescr.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_5.TensorflowSavedModelBundleWeightsDescr.model_fields": {"fullname": "bioimageio.spec.model.v0_5.TensorflowSavedModelBundleWeightsDescr.model_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "TensorflowSavedModelBundleWeightsDescr.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'source': FieldInfo(annotation=Union[Annotated[Path, PathType], RelativeFilePath, HttpUrl, Annotated[Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], required=True, metadata=[AfterValidator(func=<function wo_special_file_name>), PlainSerializer(func=<function _package>, return_type=PydanticUndefined, when_used='unless-none')]), 'sha256': FieldInfo(annotation=Union[Sha256, NoneType], required=False), 'authors': FieldInfo(annotation=Union[List[Author], NoneType], required=False), 'parent': FieldInfo(annotation=Union[Literal['keras_hdf5', 'onnx', 'pytorch_state_dict', 'tensorflow_js', 'tensorflow_saved_model_bundle', 'torchscript'], NoneType], required=False, examples=['pytorch_state_dict']), 'tensorflow_version': FieldInfo(annotation=Version, required=True), 'dependencies': FieldInfo(annotation=Union[EnvironmentFileDescr, NoneType], required=False)}"}, "bioimageio.spec.model.v0_5.TensorflowSavedModelBundleWeightsDescr.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_5.TensorflowSavedModelBundleWeightsDescr.model_computed_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "TensorflowSavedModelBundleWeightsDescr.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_5.TorchscriptWeightsDescr": {"fullname": "bioimageio.spec.model.v0_5.TorchscriptWeightsDescr", "modulename": "bioimageio.spec.model.v0_5", "qualname": "TorchscriptWeightsDescr", "kind": "class", "doc": "
    Subpart of a resource description
    \n", "bases": "WeightsEntryDescrBase"}, "bioimageio.spec.model.v0_5.TorchscriptWeightsDescr.type": {"fullname": "bioimageio.spec.model.v0_5.TorchscriptWeightsDescr.type", "modulename": "bioimageio.spec.model.v0_5", "qualname": "TorchscriptWeightsDescr.type", "kind": "variable", "doc": "
    \n", "default_value": "'torchscript'"}, "bioimageio.spec.model.v0_5.TorchscriptWeightsDescr.weights_format_name": {"fullname": "bioimageio.spec.model.v0_5.TorchscriptWeightsDescr.weights_format_name", "modulename": "bioimageio.spec.model.v0_5", "qualname": "TorchscriptWeightsDescr.weights_format_name", "kind": "variable", "doc": "
    \n", "annotation": ": ClassVar[str]", "default_value": "'TorchScript'"}, "bioimageio.spec.model.v0_5.TorchscriptWeightsDescr.pytorch_version": {"fullname": "bioimageio.spec.model.v0_5.TorchscriptWeightsDescr.pytorch_version", "modulename": "bioimageio.spec.model.v0_5", "qualname": "TorchscriptWeightsDescr.pytorch_version", "kind": "variable", "doc": "
    Version of the PyTorch library used.
    \n", "annotation": ": bioimageio.spec._internal.version_type.Version"}, "bioimageio.spec.model.v0_5.TorchscriptWeightsDescr.model_config": {"fullname": "bioimageio.spec.model.v0_5.TorchscriptWeightsDescr.model_config", "modulename": "bioimageio.spec.model.v0_5", "qualname": "TorchscriptWeightsDescr.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_5.TorchscriptWeightsDescr.model_fields": {"fullname": "bioimageio.spec.model.v0_5.TorchscriptWeightsDescr.model_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "TorchscriptWeightsDescr.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'source': FieldInfo(annotation=Union[Annotated[Path, PathType], RelativeFilePath, HttpUrl, Annotated[Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], required=True, metadata=[AfterValidator(func=<function wo_special_file_name>), PlainSerializer(func=<function _package>, return_type=PydanticUndefined, when_used='unless-none')]), 'sha256': FieldInfo(annotation=Union[Sha256, NoneType], required=False), 'authors': FieldInfo(annotation=Union[List[Author], NoneType], required=False), 'parent': FieldInfo(annotation=Union[Literal['keras_hdf5', 'onnx', 'pytorch_state_dict', 'tensorflow_js', 'tensorflow_saved_model_bundle', 'torchscript'], NoneType], required=False, examples=['pytorch_state_dict']), 'pytorch_version': FieldInfo(annotation=Version, required=True)}"}, "bioimageio.spec.model.v0_5.TorchscriptWeightsDescr.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_5.TorchscriptWeightsDescr.model_computed_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "TorchscriptWeightsDescr.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_5.WeightsDescr": {"fullname": "bioimageio.spec.model.v0_5.WeightsDescr", "modulename": "bioimageio.spec.model.v0_5", "qualname": "WeightsDescr", "kind": "class", "doc": "
    Subpart of a resource description
    \n", "bases": "bioimageio.spec._internal.node.Node"}, "bioimageio.spec.model.v0_5.WeightsDescr.keras_hdf5": {"fullname": "bioimageio.spec.model.v0_5.WeightsDescr.keras_hdf5", "modulename": "bioimageio.spec.model.v0_5", "qualname": "WeightsDescr.keras_hdf5", "kind": "variable", "doc": "
    \n", "annotation": ": Optional[bioimageio.spec.model.v0_5.KerasHdf5WeightsDescr]"}, "bioimageio.spec.model.v0_5.WeightsDescr.onnx": {"fullname": "bioimageio.spec.model.v0_5.WeightsDescr.onnx", "modulename": "bioimageio.spec.model.v0_5", "qualname": "WeightsDescr.onnx", "kind": "variable", "doc": "
    \n", "annotation": ": Optional[bioimageio.spec.model.v0_5.OnnxWeightsDescr]"}, "bioimageio.spec.model.v0_5.WeightsDescr.pytorch_state_dict": {"fullname": "bioimageio.spec.model.v0_5.WeightsDescr.pytorch_state_dict", "modulename": "bioimageio.spec.model.v0_5", "qualname": "WeightsDescr.pytorch_state_dict", "kind": "variable", "doc": "
    \n", "annotation": ": Optional[bioimageio.spec.model.v0_5.PytorchStateDictWeightsDescr]"}, "bioimageio.spec.model.v0_5.WeightsDescr.tensorflow_js": {"fullname": "bioimageio.spec.model.v0_5.WeightsDescr.tensorflow_js", "modulename": "bioimageio.spec.model.v0_5", "qualname": "WeightsDescr.tensorflow_js", "kind": "variable", "doc": "
    \n", "annotation": ": Optional[bioimageio.spec.model.v0_5.TensorflowJsWeightsDescr]"}, "bioimageio.spec.model.v0_5.WeightsDescr.tensorflow_saved_model_bundle": {"fullname": "bioimageio.spec.model.v0_5.WeightsDescr.tensorflow_saved_model_bundle", "modulename": "bioimageio.spec.model.v0_5", "qualname": "WeightsDescr.tensorflow_saved_model_bundle", "kind": "variable", "doc": "
    \n", "annotation": ": Optional[bioimageio.spec.model.v0_5.TensorflowSavedModelBundleWeightsDescr]"}, "bioimageio.spec.model.v0_5.WeightsDescr.torchscript": {"fullname": "bioimageio.spec.model.v0_5.WeightsDescr.torchscript", "modulename": "bioimageio.spec.model.v0_5", "qualname": "WeightsDescr.torchscript", "kind": "variable", "doc": "
    \n", "annotation": ": Optional[bioimageio.spec.model.v0_5.TorchscriptWeightsDescr]"}, "bioimageio.spec.model.v0_5.WeightsDescr.check_entries": {"fullname": "bioimageio.spec.model.v0_5.WeightsDescr.check_entries", "modulename": "bioimageio.spec.model.v0_5", "qualname": "WeightsDescr.check_entries", "kind": "function", "doc": "
    \n", "signature": "(self) -> Self:", "funcdef": "def"}, "bioimageio.spec.model.v0_5.WeightsDescr.model_config": {"fullname": "bioimageio.spec.model.v0_5.WeightsDescr.model_config", "modulename": "bioimageio.spec.model.v0_5", "qualname": "WeightsDescr.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_5.WeightsDescr.model_fields": {"fullname": "bioimageio.spec.model.v0_5.WeightsDescr.model_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "WeightsDescr.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'keras_hdf5': FieldInfo(annotation=Union[KerasHdf5WeightsDescr, NoneType], required=False), 'onnx': FieldInfo(annotation=Union[OnnxWeightsDescr, NoneType], required=False), 'pytorch_state_dict': FieldInfo(annotation=Union[PytorchStateDictWeightsDescr, NoneType], required=False), 'tensorflow_js': FieldInfo(annotation=Union[TensorflowJsWeightsDescr, NoneType], required=False), 'tensorflow_saved_model_bundle': FieldInfo(annotation=Union[TensorflowSavedModelBundleWeightsDescr, NoneType], required=False), 'torchscript': FieldInfo(annotation=Union[TorchscriptWeightsDescr, NoneType], required=False)}"}, "bioimageio.spec.model.v0_5.WeightsDescr.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_5.WeightsDescr.model_computed_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "WeightsDescr.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_5.LinkedModel": {"fullname": "bioimageio.spec.model.v0_5.LinkedModel", "modulename": "bioimageio.spec.model.v0_5", "qualname": "LinkedModel", "kind": "class", "doc": "
    Reference to a bioimage.io model.
    \n", "bases": "bioimageio.spec._internal.node.Node"}, "bioimageio.spec.model.v0_5.LinkedModel.id": {"fullname": "bioimageio.spec.model.v0_5.LinkedModel.id", "modulename": "bioimageio.spec.model.v0_5", "qualname": "LinkedModel.id", "kind": "variable", "doc": "
    A valid model id from the bioimage.io collection.
    \n", "annotation": ": bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]]"}, "bioimageio.spec.model.v0_5.LinkedModel.version_number": {"fullname": "bioimageio.spec.model.v0_5.LinkedModel.version_number", "modulename": "bioimageio.spec.model.v0_5", "qualname": "LinkedModel.version_number", "kind": "variable", "doc": "
    version number (n-th published version, not the semantic version) of linked model
    \n", "annotation": ": int"}, "bioimageio.spec.model.v0_5.LinkedModel.model_config": {"fullname": "bioimageio.spec.model.v0_5.LinkedModel.model_config", "modulename": "bioimageio.spec.model.v0_5", "qualname": "LinkedModel.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.model.v0_5.LinkedModel.model_fields": {"fullname": "bioimageio.spec.model.v0_5.LinkedModel.model_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "LinkedModel.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'id': FieldInfo(annotation=ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]], required=True), 'version_number': FieldInfo(annotation=int, required=True)}"}, "bioimageio.spec.model.v0_5.LinkedModel.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_5.LinkedModel.model_computed_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "LinkedModel.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_5.ModelDescr": {"fullname": "bioimageio.spec.model.v0_5.ModelDescr", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ModelDescr", "kind": "class", "doc": "
    Specification of the fields used in a bioimage.io-compliant RDF to describe AI models with pretrained weights.\nThese fields are typically stored in a YAML file which we call a model resource description file (model RDF).
    \n", "bases": "bioimageio.spec.generic.v0_3.GenericModelDescrBase"}, "bioimageio.spec.model.v0_5.ModelDescr.format_version": {"fullname": "bioimageio.spec.model.v0_5.ModelDescr.format_version", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ModelDescr.format_version", "kind": "variable", "doc": "
    Version of the bioimage.io model description specification used.\nWhen creating a new model always use the latest micro/patch version described here.\nThe format_version is important for any consumer software to understand how to parse the fields.
    \n", "annotation": ": Literal['0.5.0']"}, "bioimageio.spec.model.v0_5.ModelDescr.type": {"fullname": "bioimageio.spec.model.v0_5.ModelDescr.type", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ModelDescr.type", "kind": "variable", "doc": "
    Specialized resource type 'model'
    \n", "annotation": ": Literal['model']"}, "bioimageio.spec.model.v0_5.ModelDescr.id": {"fullname": "bioimageio.spec.model.v0_5.ModelDescr.id", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ModelDescr.id", "kind": "variable", "doc": "
    Model zoo (bioimage.io) wide, unique identifier (assigned by bioimage.io)
    \n", "annotation": ": Optional[bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]]]"}, "bioimageio.spec.model.v0_5.ModelDescr.authors": {"fullname": "bioimageio.spec.model.v0_5.ModelDescr.authors", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ModelDescr.authors", "kind": "variable", "doc": "
    The authors are the creators of the model RDF and the primary points of contact.
    \n", "annotation": ": Annotated[List[bioimageio.spec.generic.v0_3.Author], MinLen(min_length=1)]"}, "bioimageio.spec.model.v0_5.ModelDescr.documentation": {"fullname": "bioimageio.spec.model.v0_5.ModelDescr.documentation", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ModelDescr.documentation", "kind": "variable", "doc": "
    \u2208\ud83d\udce6 URL or relative path to a markdown file with additional documentation.\nThe recommended documentation file name is README.md. An .md suffix is mandatory.\nThe documentation should include a '#[#] Validation' (sub)section\nwith details on how to quantitatively validate the model on unseen data.
    \n", "annotation": ": Annotated[Union[Annotated[pathlib.Path, PathType(path_type='file'), Predicate(func=<function PurePath.is_absolute at 0x7afca4145940>)], bioimageio.spec._internal.io.RelativeFilePath, bioimageio.spec._internal.url.HttpUrl], AfterValidator(func=<function _validate_md_suffix at 0x7afca0c06ca0>), PlainSerializer(func=<function _package at 0x7afca0d91760>, return_type=PydanticUndefined, when_used='unless-none'), FieldInfo(annotation=NoneType, required=True, examples=['https://raw.githubusercontent.com/bioimage-io/spec-bioimage-io/main/example_descriptions/models/unet2d_nuclei_broad/README.md', 'README.md'])]"}, "bioimageio.spec.model.v0_5.ModelDescr.inputs": {"fullname": "bioimageio.spec.model.v0_5.ModelDescr.inputs", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ModelDescr.inputs", "kind": "variable", "doc": "
    Describes the input tensors expected by this model.
    \n", "annotation": ": Annotated[Sequence[bioimageio.spec.model.v0_5.InputTensorDescr], MinLen(min_length=1)]"}, "bioimageio.spec.model.v0_5.ModelDescr.name": {"fullname": "bioimageio.spec.model.v0_5.ModelDescr.name", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ModelDescr.name", "kind": "variable", "doc": "
    A human-readable name of this model.\nIt should be no longer than 64 characters\nand may only contain letter, number, underscore, minus or space characters.\nWe recommend to chose a name that refers to the model's task and image modality.
    \n", "annotation": ": Annotated[str, MinLen(min_length=5), AfterWarner(func=<function as_warning.<locals>.wrapper at 0x7afc93e7bf60>, severity=20, msg='Name longer than 64 characters.', context={'typ': Annotated[Any, MaxLen(max_length=64)]})]"}, "bioimageio.spec.model.v0_5.ModelDescr.outputs": {"fullname": "bioimageio.spec.model.v0_5.ModelDescr.outputs", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ModelDescr.outputs", "kind": "variable", "doc": "
    Describes the output tensors.
    \n", "annotation": ": Annotated[Sequence[bioimageio.spec.model.v0_5.OutputTensorDescr], MinLen(min_length=1)]"}, "bioimageio.spec.model.v0_5.ModelDescr.packaged_by": {"fullname": "bioimageio.spec.model.v0_5.ModelDescr.packaged_by", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ModelDescr.packaged_by", "kind": "variable", "doc": "
    The persons that have packaged and uploaded this model.\nOnly required if those persons differ from the authors.
    \n", "annotation": ": List[bioimageio.spec.generic.v0_3.Author]"}, "bioimageio.spec.model.v0_5.ModelDescr.parent": {"fullname": "bioimageio.spec.model.v0_5.ModelDescr.parent", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ModelDescr.parent", "kind": "variable", "doc": "
    The model from which this model is derived, e.g. by fine-tuning the weights.
    \n", "annotation": ": Optional[bioimageio.spec.model.v0_5.LinkedModel]"}, "bioimageio.spec.model.v0_5.ModelDescr.run_mode": {"fullname": "bioimageio.spec.model.v0_5.ModelDescr.run_mode", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ModelDescr.run_mode", "kind": "variable", "doc": "
    Custom run mode for this model: for more complex prediction procedures like test time\ndata augmentation that currently cannot be expressed in the specification.\nNo standard run modes are defined yet.
    \n", "annotation": ": Annotated[Optional[bioimageio.spec.model.v0_4.RunMode], AfterWarner(func=<function as_warning.<locals>.wrapper at 0x7afc91dd7a60>, severity=30, msg="Run mode '{value}' has limited support across consumer softwares.", context={'typ': None})]"}, "bioimageio.spec.model.v0_5.ModelDescr.timestamp": {"fullname": "bioimageio.spec.model.v0_5.ModelDescr.timestamp", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ModelDescr.timestamp", "kind": "variable", "doc": "
    Timestamp in ISO 8601 format\nwith a few restrictions listed here.\n(In Python a datetime object is valid, too).
    \n", "annotation": ": bioimageio.spec._internal.types.Datetime"}, "bioimageio.spec.model.v0_5.ModelDescr.training_data": {"fullname": "bioimageio.spec.model.v0_5.ModelDescr.training_data", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ModelDescr.training_data", "kind": "variable", "doc": "
    The dataset used to train this model
    \n", "annotation": ": Union[bioimageio.spec.dataset.v0_3.LinkedDataset, bioimageio.spec.dataset.v0_3.DatasetDescr, NoneType]"}, "bioimageio.spec.model.v0_5.ModelDescr.weights": {"fullname": "bioimageio.spec.model.v0_5.ModelDescr.weights", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ModelDescr.weights", "kind": "variable", "doc": "
    The weights for this model.\nWeights can be given for different formats, but should otherwise be equivalent.\nThe available weight formats determine which consumers can use this model.
    \n", "annotation": ": bioimageio.spec.model.v0_5.WeightsDescr"}, "bioimageio.spec.model.v0_5.ModelDescr.get_input_test_arrays": {"fullname": "bioimageio.spec.model.v0_5.ModelDescr.get_input_test_arrays", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ModelDescr.get_input_test_arrays", "kind": "function", "doc": "
    \n", "signature": "(self) -> List[numpy.ndarray[Any, numpy.dtype[Any]]]:", "funcdef": "def"}, "bioimageio.spec.model.v0_5.ModelDescr.get_output_test_arrays": {"fullname": "bioimageio.spec.model.v0_5.ModelDescr.get_output_test_arrays", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ModelDescr.get_output_test_arrays", "kind": "function", "doc": "
    \n", "signature": "(self) -> List[numpy.ndarray[Any, numpy.dtype[Any]]]:", "funcdef": "def"}, "bioimageio.spec.model.v0_5.ModelDescr.get_tensor_sizes": {"fullname": "bioimageio.spec.model.v0_5.ModelDescr.get_tensor_sizes", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ModelDescr.get_tensor_sizes", "kind": "function", "doc": "
    \n", "signature": "(\tself,\tn: int,\tbatch_size: int) -> Dict[bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]], Dict[bioimageio.spec.model.v0_5.AxisId, int]]:", "funcdef": "def"}, "bioimageio.spec.model.v0_5.ModelDescr.implemented_format_version": {"fullname": "bioimageio.spec.model.v0_5.ModelDescr.implemented_format_version", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ModelDescr.implemented_format_version", "kind": "variable", "doc": "
    \n", "annotation": ": ClassVar[str]", "default_value": "'0.5.0'"}, "bioimageio.spec.model.v0_5.ModelDescr.implemented_format_version_tuple": {"fullname": "bioimageio.spec.model.v0_5.ModelDescr.implemented_format_version_tuple", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ModelDescr.implemented_format_version_tuple", "kind": "variable", "doc": "
    \n", "annotation": ": ClassVar[Tuple[int, int, int]]", "default_value": "(0, 5, 0)"}, "bioimageio.spec.model.v0_5.ModelDescr.model_config": {"fullname": "bioimageio.spec.model.v0_5.ModelDescr.model_config", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ModelDescr.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True, 'title': 'bioimage.io model specification'}"}, "bioimageio.spec.model.v0_5.ModelDescr.model_fields": {"fullname": "bioimageio.spec.model.v0_5.ModelDescr.model_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ModelDescr.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'name': FieldInfo(annotation=str, required=True, metadata=[MinLen(min_length=5), AfterWarner(func=<function as_warning.<locals>.wrapper>, severity=20, msg='Name longer than 64 characters.', context={'typ': typing.Annotated[typing.Any, MaxLen(max_length=64)]})]), 'description': FieldInfo(annotation=str, required=True, metadata=[MaxLen(max_length=1024), AfterWarner(func=<function as_warning.<locals>.wrapper>, severity=30, msg='Description longer than 512 characters.', context={'typ': typing.Annotated[typing.Any, MaxLen(max_length=512)]})]), 'covers': FieldInfo(annotation=List[Annotated[Union[HttpUrl, Annotated[Path, PathType, Predicate], RelativeFilePath], WithSuffix, PlainSerializer]], required=False, default_factory=list, description="Cover images. Please use an image smaller than 500KB and an aspect ratio width to height of 2:1 or 1:1.\\nThe supported image formats are: ('.gif', '.jpeg', '.jpg', '.png', '.svg')", examples=[]), 'id_emoji': FieldInfo(annotation=Union[Annotated[str, Len], NoneType], required=False), 'authors': FieldInfo(annotation=List[Author], required=True, metadata=[MinLen(min_length=1)]), 'attachments': FieldInfo(annotation=List[FileDescr], required=False, default_factory=list), 'cite': FieldInfo(annotation=List[CiteEntry], required=True, metadata=[MinLen(min_length=1)]), 'license': FieldInfo(annotation=Union[LicenseId, DeprecatedLicenseId], required=True, examples=['CC-BY-4.0', 'MIT', 'BSD-2-Clause'], metadata=[AfterWarner(func=<function as_warning.<locals>.wrapper>, severity=30, msg='{value} is deprecated, see https://spdx.org/licenses/{value}.html', context={'typ': <class 'bioimageio.spec._internal.license_id.LicenseId'>})]), 'config': FieldInfo(annotation=Dict[str, YamlValue], required=False, default_factory=dict, examples=[{'bioimageio': {'my_custom_key': 3837283, 'another_key': {'nested': 'value'}}, 'imagej': {'macro_dir': 'path/to/macro/file'}}]), 'git_repo': FieldInfo(annotation=Union[HttpUrl, NoneType], required=False, examples=['https://github.com/bioimage-io/spec-bioimage-io/tree/main/example_descriptions/models/unet2d_nuclei_broad']), 'icon': FieldInfo(annotation=Union[Annotated[Union[Annotated[Path, PathType], RelativeFilePath, HttpUrl, Annotated[Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator, PlainSerializer], Annotated[str, Len], NoneType], required=False), 'links': FieldInfo(annotation=List[str], required=False, default_factory=list, examples=[('ilastik/ilastik', 'deepimagej/deepimagej', 'zero/notebook_u-net_3d_zerocostdl4mic')]), 'uploader': FieldInfo(annotation=Union[Uploader, NoneType], required=False), 'maintainers': FieldInfo(annotation=List[Maintainer], required=False, default_factory=list), 'tags': FieldInfo(annotation=List[str], required=False, default_factory=list, examples=[('unet2d', 'pytorch', 'nucleus', 'segmentation', 'dsb2018')]), 'version': FieldInfo(annotation=Union[Version, NoneType], required=False), 'version_number': FieldInfo(annotation=Union[int, NoneType], required=False), 'format_version': FieldInfo(annotation=Literal['0.5.0'], required=False, default='0.5.0'), 'type': FieldInfo(annotation=Literal['model'], required=False, default='model'), 'id': FieldInfo(annotation=Union[ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]], NoneType], required=False), 'documentation': FieldInfo(annotation=Union[Annotated[Path, PathType, Predicate], RelativeFilePath, HttpUrl], required=True, examples=['https://raw.githubusercontent.com/bioimage-io/spec-bioimage-io/main/example_descriptions/models/unet2d_nuclei_broad/README.md', 'README.md'], metadata=[AfterValidator(func=<function _validate_md_suffix>), PlainSerializer(func=<function _package>, return_type=PydanticUndefined, when_used='unless-none')]), 'inputs': FieldInfo(annotation=Sequence[InputTensorDescr], required=True, metadata=[MinLen(min_length=1)]), 'outputs': FieldInfo(annotation=Sequence[OutputTensorDescr], required=True, metadata=[MinLen(min_length=1)]), 'packaged_by': FieldInfo(annotation=List[Author], required=False, default_factory=list), 'parent': FieldInfo(annotation=Union[LinkedModel, NoneType], required=False), 'run_mode': FieldInfo(annotation=Union[RunMode, NoneType], required=False, metadata=[AfterWarner(func=<function as_warning.<locals>.wrapper>, severity=30, msg="Run mode '{value}' has limited support across consumer softwares.", context={'typ': None})]), 'timestamp': FieldInfo(annotation=Datetime, required=False, default=Datetime(root=datetime.datetime(2024, 3, 14, 14, 46, 42, 87090))), 'training_data': FieldInfo(annotation=Union[LinkedDataset, DatasetDescr, NoneType], required=False), 'weights': FieldInfo(annotation=WeightsDescr, required=True)}"}, "bioimageio.spec.model.v0_5.ModelDescr.model_computed_fields": {"fullname": "bioimageio.spec.model.v0_5.ModelDescr.model_computed_fields", "modulename": "bioimageio.spec.model.v0_5", "qualname": "ModelDescr.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.model.v0_5.generate_covers": {"fullname": "bioimageio.spec.model.v0_5.generate_covers", "modulename": "bioimageio.spec.model.v0_5", "qualname": "generate_covers", "kind": "function", "doc": "
    \n", "signature": "(\tinputs: Sequence[Tuple[bioimageio.spec.model.v0_5.InputTensorDescr, numpy.ndarray[Any, numpy.dtype[Any]]]],\toutputs: Sequence[Tuple[bioimageio.spec.model.v0_5.OutputTensorDescr, numpy.ndarray[Any, numpy.dtype[Any]]]]) -> List[pathlib.Path]:", "funcdef": "def"}, "bioimageio.spec.model.v0_5.TensorDescrBase[Annotated[Union[BatchAxis, ChannelAxis, IndexAxis, TimeInputAxis, SpaceInputAxis], FieldInfo(annotation=NoneType, required=True, discriminator='type')]]": {"fullname": "bioimageio.spec.model.v0_5.TensorDescrBase[Annotated[Union[BatchAxis, ChannelAxis, IndexAxis, TimeInputAxis, SpaceInputAxis], FieldInfo(annotation=NoneType, required=True, discriminator='type')]]", "modulename": "bioimageio.spec.model.v0_5", "qualname": "TensorDescrBase[Annotated[Union[BatchAxis, ChannelAxis, IndexAxis, TimeInputAxis, SpaceInputAxis], FieldInfo(annotation=NoneType, required=True, discriminator='type')]]", "kind": "class", "doc": "
    Subpart of a resource description
    \n", "bases": "bioimageio.spec._internal.node.Node, typing.Generic[~IO_AxisT]"}, "bioimageio.spec.model.v0_5.TensorDescrBase[Annotated[Union[BatchAxis, ChannelAxis, IndexAxis, TimeOutputAxis, SpaceOutputAxis], FieldInfo(annotation=NoneType, required=True, discriminator='type')]]": {"fullname": "bioimageio.spec.model.v0_5.TensorDescrBase[Annotated[Union[BatchAxis, ChannelAxis, IndexAxis, TimeOutputAxis, SpaceOutputAxis], FieldInfo(annotation=NoneType, required=True, discriminator='type')]]", "modulename": "bioimageio.spec.model.v0_5", "qualname": "TensorDescrBase[Annotated[Union[BatchAxis, ChannelAxis, IndexAxis, TimeOutputAxis, SpaceOutputAxis], FieldInfo(annotation=NoneType, required=True, discriminator='type')]]", "kind": "class", "doc": "
    Subpart of a resource description
    \n", "bases": "bioimageio.spec._internal.node.Node, typing.Generic[~IO_AxisT]"}, "bioimageio.spec.notebook": {"fullname": "bioimageio.spec.notebook", "modulename": "bioimageio.spec.notebook", "kind": "module", "doc": "
    implementaions of all released minor versions are available in submodules:
    \n\n\n"}, "bioimageio.spec.notebook.AnyNotebookDescr": {"fullname": "bioimageio.spec.notebook.AnyNotebookDescr", "modulename": "bioimageio.spec.notebook", "qualname": "AnyNotebookDescr", "kind": "variable", "doc": "
    Union of any released notebook desription
    \n", "default_value": "typing.Annotated[typing.Union[bioimageio.spec.notebook.v0_2.NotebookDescr, bioimageio.spec.notebook.v0_3.NotebookDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)]"}, "bioimageio.spec.notebook.v0_2": {"fullname": "bioimageio.spec.notebook.v0_2", "modulename": "bioimageio.spec.notebook.v0_2", "kind": "module", "doc": "
    \n"}, "bioimageio.spec.notebook.v0_2.NotebookSource": {"fullname": "bioimageio.spec.notebook.v0_2.NotebookSource", "modulename": "bioimageio.spec.notebook.v0_2", "qualname": "NotebookSource", "kind": "variable", "doc": "
    \n", "default_value": "typing.Union[typing.Annotated[bioimageio.spec._internal.url.HttpUrl, WithSuffix(suffix='.ipynb', case_sensitive=True)], typing.Annotated[pathlib.Path, PathType(path_type='file'), Predicate(func=<function PurePath.is_absolute>), WithSuffix(suffix='.ipynb', case_sensitive=True)], typing.Annotated[bioimageio.spec._internal.io.RelativeFilePath, WithSuffix(suffix='.ipynb', case_sensitive=True)]]"}, "bioimageio.spec.notebook.v0_2.NotebookDescr": {"fullname": "bioimageio.spec.notebook.v0_2.NotebookDescr", "modulename": "bioimageio.spec.notebook.v0_2", "qualname": "NotebookDescr", "kind": "class", "doc": "
    Bioimage.io description of a Jupyter Notebook.
    \n", "bases": "bioimageio.spec.generic.v0_2.GenericDescrBase"}, "bioimageio.spec.notebook.v0_2.NotebookDescr.type": {"fullname": "bioimageio.spec.notebook.v0_2.NotebookDescr.type", "modulename": "bioimageio.spec.notebook.v0_2", "qualname": "NotebookDescr.type", "kind": "variable", "doc": "
    \n", "annotation": ": Literal['notebook']"}, "bioimageio.spec.notebook.v0_2.NotebookDescr.id": {"fullname": "bioimageio.spec.notebook.v0_2.NotebookDescr.id", "modulename": "bioimageio.spec.notebook.v0_2", "qualname": "NotebookDescr.id", "kind": "variable", "doc": "
    Model zoo (bioimage.io) wide, unique identifier (assigned by bioimage.io)
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    The Jupyter notebook
    \n", "annotation": ": Union[Annotated[bioimageio.spec._internal.url.HttpUrl, WithSuffix(suffix='.ipynb', case_sensitive=True)], Annotated[pathlib.Path, PathType(path_type='file'), Predicate(func=<function PurePath.is_absolute at 0x7afca4145940>), WithSuffix(suffix='.ipynb', case_sensitive=True)], Annotated[bioimageio.spec._internal.io.RelativeFilePath, WithSuffix(suffix='.ipynb', case_sensitive=True)]]"}, "bioimageio.spec.notebook.v0_2.NotebookDescr.implemented_format_version": {"fullname": "bioimageio.spec.notebook.v0_2.NotebookDescr.implemented_format_version", "modulename": "bioimageio.spec.notebook.v0_2", "qualname": "NotebookDescr.implemented_format_version", "kind": "variable", "doc": "
    \n", "annotation": ": ClassVar[str]", "default_value": "'0.2.4'"}, "bioimageio.spec.notebook.v0_2.NotebookDescr.implemented_format_version_tuple": {"fullname": "bioimageio.spec.notebook.v0_2.NotebookDescr.implemented_format_version_tuple", "modulename": "bioimageio.spec.notebook.v0_2", "qualname": "NotebookDescr.implemented_format_version_tuple", "kind": "variable", "doc": "
    \n", "annotation": ": ClassVar[Tuple[int, int, int]]", "default_value": "(0, 2, 4)"}, "bioimageio.spec.notebook.v0_2.NotebookDescr.model_config": {"fullname": "bioimageio.spec.notebook.v0_2.NotebookDescr.model_config", "modulename": "bioimageio.spec.notebook.v0_2", "qualname": "NotebookDescr.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True, 'title': 'bioimage.io notebook specification'}"}, "bioimageio.spec.notebook.v0_2.NotebookDescr.model_fields": {"fullname": "bioimageio.spec.notebook.v0_2.NotebookDescr.model_fields", "modulename": "bioimageio.spec.notebook.v0_2", "qualname": "NotebookDescr.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'name': FieldInfo(annotation=str, required=True, metadata=[MinLen(min_length=1), AfterWarner(func=<function as_warning.<locals>.wrapper>, severity=30, msg='Longer than 128 characters.', context={'typ': typing.Annotated[typing.Any, MaxLen(max_length=128)]})]), 'description': FieldInfo(annotation=str, required=True), 'covers': FieldInfo(annotation=List[Annotated[Union[HttpUrl, Annotated[Path, PathType, Predicate], RelativeFilePath], WithSuffix, PlainSerializer]], required=False, default_factory=list, description="Cover images. Please use an image smaller than 500KB and an aspect ratio width to height of 2:1.\\nThe supported image formats are: ('.gif', '.jpeg', '.jpg', '.png', '.svg')", examples=['cover.png']), 'id_emoji': FieldInfo(annotation=Union[Annotated[str, Len], NoneType], required=False), 'authors': FieldInfo(annotation=List[Author], required=False, default_factory=list), 'attachments': FieldInfo(annotation=Union[AttachmentsDescr, NoneType], required=False), 'cite': FieldInfo(annotation=List[CiteEntry], required=False, default_factory=list), 'config': FieldInfo(annotation=Dict[str, YamlValue], required=False, default_factory=dict, examples=[{'bioimageio': {'my_custom_key': 3837283, 'another_key': {'nested': 'value'}}, 'imagej': {'macro_dir': 'path/to/macro/file'}}]), 'download_url': FieldInfo(annotation=Union[HttpUrl, NoneType], required=False), 'git_repo': FieldInfo(annotation=Union[str, NoneType], required=False, examples=['https://github.com/bioimage-io/spec-bioimage-io/tree/main/example_descriptions/models/unet2d_nuclei_broad']), 'icon': FieldInfo(annotation=Union[Annotated[Union[Annotated[Path, PathType], RelativeFilePath, HttpUrl, Annotated[Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator, PlainSerializer], Annotated[str, Len], NoneType], required=False), 'links': FieldInfo(annotation=List[str], required=False, default_factory=list, examples=[('ilastik/ilastik', 'deepimagej/deepimagej', 'zero/notebook_u-net_3d_zerocostdl4mic')]), 'uploader': FieldInfo(annotation=Union[Uploader, NoneType], required=False), 'maintainers': FieldInfo(annotation=List[Maintainer], required=False, default_factory=list), 'rdf_source': FieldInfo(annotation=Union[Annotated[Path, PathType], RelativeFilePath, HttpUrl, Annotated[Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)], NoneType], required=False), 'tags': FieldInfo(annotation=List[str], required=False, default_factory=list, examples=[('unet2d', 'pytorch', 'nucleus', 'segmentation', 'dsb2018')]), 'version': FieldInfo(annotation=Union[Version, NoneType], required=False), 'version_number': FieldInfo(annotation=Union[int, NoneType], required=False), 'format_version': FieldInfo(annotation=Literal['0.2.4'], required=False, default='0.2.4'), 'badges': FieldInfo(annotation=List[BadgeDescr], required=False, default_factory=list), 'documentation': FieldInfo(annotation=Union[Annotated[Union[Annotated[Path, PathType], RelativeFilePath, HttpUrl, Annotated[Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator, PlainSerializer], NoneType], required=False, examples=['https://raw.githubusercontent.com/bioimage-io/spec-bioimage-io/main/example_descriptions/models/unet2d_nuclei_broad/README.md', 'README.md']), 'license': FieldInfo(annotation=Union[LicenseId, DeprecatedLicenseId, str, NoneType], required=False, examples=['CC-BY-4.0', 'MIT', 'BSD-2-Clause']), 'type': FieldInfo(annotation=Literal['notebook'], required=False, default='notebook'), 'id': FieldInfo(annotation=Union[ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]], NoneType], required=False), 'source': FieldInfo(annotation=Union[Annotated[HttpUrl, WithSuffix], Annotated[Path, PathType, Predicate, WithSuffix], Annotated[RelativeFilePath, WithSuffix]], required=True)}"}, "bioimageio.spec.notebook.v0_2.NotebookDescr.model_computed_fields": {"fullname": "bioimageio.spec.notebook.v0_2.NotebookDescr.model_computed_fields", "modulename": "bioimageio.spec.notebook.v0_2", "qualname": "NotebookDescr.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.notebook.v0_2.LinkedNotebook": {"fullname": "bioimageio.spec.notebook.v0_2.LinkedNotebook", "modulename": "bioimageio.spec.notebook.v0_2", "qualname": "LinkedNotebook", "kind": "class", "doc": "
    Reference to a bioimage.io notebook.
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    A valid notebook id from the bioimage.io collection.
    \n", "annotation": ": bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]]"}, "bioimageio.spec.notebook.v0_2.LinkedNotebook.version_number": {"fullname": "bioimageio.spec.notebook.v0_2.LinkedNotebook.version_number", "modulename": "bioimageio.spec.notebook.v0_2", "qualname": "LinkedNotebook.version_number", "kind": "variable", "doc": "
    version number (n-th published version, not the semantic version) of linked notebook
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    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.notebook.v0_2.LinkedNotebook.model_fields": {"fullname": "bioimageio.spec.notebook.v0_2.LinkedNotebook.model_fields", "modulename": "bioimageio.spec.notebook.v0_2", "qualname": "LinkedNotebook.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'id': FieldInfo(annotation=ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]], required=True), 'version_number': FieldInfo(annotation=Union[int, NoneType], required=False)}"}, "bioimageio.spec.notebook.v0_2.LinkedNotebook.model_computed_fields": {"fullname": "bioimageio.spec.notebook.v0_2.LinkedNotebook.model_computed_fields", "modulename": "bioimageio.spec.notebook.v0_2", "qualname": "LinkedNotebook.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.notebook.v0_3": {"fullname": "bioimageio.spec.notebook.v0_3", "modulename": "bioimageio.spec.notebook.v0_3", "kind": "module", "doc": "
    \n"}, "bioimageio.spec.notebook.v0_3.NotebookDescr": {"fullname": "bioimageio.spec.notebook.v0_3.NotebookDescr", "modulename": "bioimageio.spec.notebook.v0_3", "qualname": "NotebookDescr", "kind": "class", "doc": "
    Bioimage.io description of a Jupyter notebook.
    \n", "bases": "bioimageio.spec.generic.v0_3.GenericDescrBase"}, "bioimageio.spec.notebook.v0_3.NotebookDescr.type": {"fullname": "bioimageio.spec.notebook.v0_3.NotebookDescr.type", "modulename": "bioimageio.spec.notebook.v0_3", "qualname": "NotebookDescr.type", "kind": "variable", "doc": "
    \n", "annotation": ": Literal['notebook']"}, "bioimageio.spec.notebook.v0_3.NotebookDescr.id": {"fullname": "bioimageio.spec.notebook.v0_3.NotebookDescr.id", "modulename": "bioimageio.spec.notebook.v0_3", "qualname": "NotebookDescr.id", "kind": "variable", "doc": "
    Model zoo (bioimage.io) wide, unique identifier (assigned by bioimage.io)
    \n", "annotation": ": Optional[bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]]]"}, "bioimageio.spec.notebook.v0_3.NotebookDescr.parent": {"fullname": "bioimageio.spec.notebook.v0_3.NotebookDescr.parent", "modulename": "bioimageio.spec.notebook.v0_3", "qualname": "NotebookDescr.parent", "kind": "variable", "doc": "
    The description from which this one is derived
    \n", "annotation": ": Optional[bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]]]"}, "bioimageio.spec.notebook.v0_3.NotebookDescr.source": {"fullname": "bioimageio.spec.notebook.v0_3.NotebookDescr.source", "modulename": "bioimageio.spec.notebook.v0_3", "qualname": "NotebookDescr.source", "kind": "variable", "doc": "
    The Jupyter notebook
    \n", "annotation": ": Union[Annotated[bioimageio.spec._internal.url.HttpUrl, WithSuffix(suffix='.ipynb', case_sensitive=True)], Annotated[pathlib.Path, PathType(path_type='file'), Predicate(func=<function PurePath.is_absolute at 0x7afca4145940>), WithSuffix(suffix='.ipynb', case_sensitive=True)], Annotated[bioimageio.spec._internal.io.RelativeFilePath, WithSuffix(suffix='.ipynb', case_sensitive=True)]]"}, "bioimageio.spec.notebook.v0_3.NotebookDescr.implemented_format_version": {"fullname": "bioimageio.spec.notebook.v0_3.NotebookDescr.implemented_format_version", "modulename": "bioimageio.spec.notebook.v0_3", "qualname": "NotebookDescr.implemented_format_version", "kind": "variable", "doc": "
    \n", "annotation": ": ClassVar[str]", "default_value": "'0.3.0'"}, "bioimageio.spec.notebook.v0_3.NotebookDescr.implemented_format_version_tuple": {"fullname": "bioimageio.spec.notebook.v0_3.NotebookDescr.implemented_format_version_tuple", "modulename": "bioimageio.spec.notebook.v0_3", "qualname": "NotebookDescr.implemented_format_version_tuple", "kind": "variable", "doc": "
    \n", "annotation": ": ClassVar[Tuple[int, int, int]]", "default_value": "(0, 3, 0)"}, "bioimageio.spec.notebook.v0_3.NotebookDescr.model_config": {"fullname": "bioimageio.spec.notebook.v0_3.NotebookDescr.model_config", "modulename": "bioimageio.spec.notebook.v0_3", "qualname": "NotebookDescr.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True, 'title': 'bioimage.io notebook specification'}"}, "bioimageio.spec.notebook.v0_3.NotebookDescr.model_fields": {"fullname": "bioimageio.spec.notebook.v0_3.NotebookDescr.model_fields", "modulename": "bioimageio.spec.notebook.v0_3", "qualname": "NotebookDescr.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'name': FieldInfo(annotation=str, required=True, metadata=[MinLen(min_length=1), MaxLen(max_length=128)]), 'description': FieldInfo(annotation=str, required=True, metadata=[MaxLen(max_length=1024), AfterWarner(func=<function as_warning.<locals>.wrapper>, severity=30, msg='Description longer than 512 characters.', context={'typ': typing.Annotated[typing.Any, MaxLen(max_length=512)]})]), 'covers': FieldInfo(annotation=List[Annotated[Union[HttpUrl, Annotated[Path, PathType, Predicate], RelativeFilePath], WithSuffix, PlainSerializer]], required=False, default_factory=list, description="Cover images. Please use an image smaller than 500KB and an aspect ratio width to height of 2:1 or 1:1.\\nThe supported image formats are: ('.gif', '.jpeg', '.jpg', '.png', '.svg')", examples=[]), 'id_emoji': FieldInfo(annotation=Union[Annotated[str, Len], NoneType], required=False), 'authors': FieldInfo(annotation=List[Author], required=True, metadata=[MinLen(min_length=1)]), 'attachments': FieldInfo(annotation=List[FileDescr], required=False, default_factory=list), 'cite': FieldInfo(annotation=List[CiteEntry], required=True, metadata=[MinLen(min_length=1)]), 'license': FieldInfo(annotation=Union[LicenseId, DeprecatedLicenseId], required=True, examples=['CC-BY-4.0', 'MIT', 'BSD-2-Clause'], metadata=[AfterWarner(func=<function as_warning.<locals>.wrapper>, severity=30, msg='{value} is deprecated, see https://spdx.org/licenses/{value}.html', context={'typ': <class 'bioimageio.spec._internal.license_id.LicenseId'>})]), 'config': FieldInfo(annotation=Dict[str, YamlValue], required=False, default_factory=dict, examples=[{'bioimageio': {'my_custom_key': 3837283, 'another_key': {'nested': 'value'}}, 'imagej': {'macro_dir': 'path/to/macro/file'}}]), 'git_repo': FieldInfo(annotation=Union[HttpUrl, NoneType], required=False, examples=['https://github.com/bioimage-io/spec-bioimage-io/tree/main/example_descriptions/models/unet2d_nuclei_broad']), 'icon': FieldInfo(annotation=Union[Annotated[Union[Annotated[Path, PathType], RelativeFilePath, HttpUrl, Annotated[Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], AfterValidator, PlainSerializer], Annotated[str, Len], NoneType], required=False), 'links': FieldInfo(annotation=List[str], required=False, default_factory=list, examples=[('ilastik/ilastik', 'deepimagej/deepimagej', 'zero/notebook_u-net_3d_zerocostdl4mic')]), 'uploader': FieldInfo(annotation=Union[Uploader, NoneType], required=False), 'maintainers': FieldInfo(annotation=List[Maintainer], required=False, default_factory=list), 'tags': FieldInfo(annotation=List[str], required=False, default_factory=list, examples=[('unet2d', 'pytorch', 'nucleus', 'segmentation', 'dsb2018')]), 'version': FieldInfo(annotation=Union[Version, NoneType], required=False), 'version_number': FieldInfo(annotation=Union[int, NoneType], required=False), 'format_version': FieldInfo(annotation=Literal['0.3.0'], required=False, default='0.3.0'), 'documentation': FieldInfo(annotation=Union[Annotated[Union[Annotated[Path, PathType, Predicate], RelativeFilePath, HttpUrl], AfterValidator, PlainSerializer], NoneType], required=False, examples=['https://raw.githubusercontent.com/bioimage-io/spec-bioimage-io/main/example_descriptions/models/unet2d_nuclei_broad/README.md', 'README.md']), 'badges': FieldInfo(annotation=List[BadgeDescr], required=False, default_factory=list), 'type': FieldInfo(annotation=Literal['notebook'], required=False, default='notebook'), 'id': FieldInfo(annotation=Union[ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]], NoneType], required=False), 'parent': FieldInfo(annotation=Union[ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]], NoneType], required=False), 'source': FieldInfo(annotation=Union[Annotated[HttpUrl, WithSuffix], Annotated[Path, PathType, Predicate, WithSuffix], Annotated[RelativeFilePath, WithSuffix]], required=True)}"}, "bioimageio.spec.notebook.v0_3.NotebookDescr.model_computed_fields": {"fullname": "bioimageio.spec.notebook.v0_3.NotebookDescr.model_computed_fields", "modulename": "bioimageio.spec.notebook.v0_3", "qualname": "NotebookDescr.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.notebook.v0_3.LinkedNotebook": {"fullname": "bioimageio.spec.notebook.v0_3.LinkedNotebook", "modulename": "bioimageio.spec.notebook.v0_3", "qualname": "LinkedNotebook", "kind": "class", "doc": "
    Reference to a bioimage.io notebook.
    \n", "bases": "bioimageio.spec._internal.node.Node"}, "bioimageio.spec.notebook.v0_3.LinkedNotebook.id": {"fullname": "bioimageio.spec.notebook.v0_3.LinkedNotebook.id", "modulename": "bioimageio.spec.notebook.v0_3", "qualname": "LinkedNotebook.id", "kind": "variable", "doc": "
    A valid notebook id from the bioimage.io collection.
    \n", "annotation": ": bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]]"}, "bioimageio.spec.notebook.v0_3.LinkedNotebook.version_number": {"fullname": "bioimageio.spec.notebook.v0_3.LinkedNotebook.version_number", "modulename": "bioimageio.spec.notebook.v0_3", "qualname": "LinkedNotebook.version_number", "kind": "variable", "doc": "
    version number (n-th published version, not the semantic version) of linked notebook
    \n", "annotation": ": int"}, "bioimageio.spec.notebook.v0_3.LinkedNotebook.model_config": {"fullname": "bioimageio.spec.notebook.v0_3.LinkedNotebook.model_config", "modulename": "bioimageio.spec.notebook.v0_3", "qualname": "LinkedNotebook.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{'extra': 'forbid', 'frozen': False, 'populate_by_name': True, 'revalidate_instances': 'never', 'validate_assignment': True, 'validate_default': False, 'validate_return': True}"}, "bioimageio.spec.notebook.v0_3.LinkedNotebook.model_fields": {"fullname": "bioimageio.spec.notebook.v0_3.LinkedNotebook.model_fields", "modulename": "bioimageio.spec.notebook.v0_3", "qualname": "LinkedNotebook.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'id': FieldInfo(annotation=ValidatedString[Annotated[str, MinLen, Annotated[TypeVar, Predicate], Predicate]], required=True), 'version_number': FieldInfo(annotation=int, required=True)}"}, "bioimageio.spec.notebook.v0_3.LinkedNotebook.model_computed_fields": {"fullname": "bioimageio.spec.notebook.v0_3.LinkedNotebook.model_computed_fields", "modulename": "bioimageio.spec.notebook.v0_3", "qualname": "LinkedNotebook.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.partner_utils": {"fullname": "bioimageio.spec.partner_utils", "modulename": "bioimageio.spec.partner_utils", "kind": "module", "doc": "
    bioimageio.spec extensions for bioimage.io community partners
    \n"}, "bioimageio.spec.partner_utils.imjoy": {"fullname": "bioimageio.spec.partner_utils.imjoy", "modulename": "bioimageio.spec.partner_utils.imjoy", "kind": "module", "doc": "
    \n"}, "bioimageio.spec.partner_utils.imjoy.enrich_partial_rdf_with_imjoy_plugin": {"fullname": "bioimageio.spec.partner_utils.imjoy.enrich_partial_rdf_with_imjoy_plugin", "modulename": "bioimageio.spec.partner_utils.imjoy", "qualname": "enrich_partial_rdf_with_imjoy_plugin", "kind": "function", "doc": "
    a (partial) rdf may have 'rdf_source' or 'source' which resolve to rdf data that may be overwritten.\nDue to resolving imjoy plugins this is not done in bioimageio.spec.collection atm
    \n", "signature": "(\tpartial_rdf: Dict[str, Any],\troot: Union[Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)], Annotated[pathlib.Path, PathType(path_type='dir')]],\tresolve_rdf_source: Callable[[Union[Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)], Annotated[pathlib.Path, PathType(path_type='file')], str]], Tuple[Dict[str, Any], str, Union[Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)], Annotated[pathlib.Path, PathType(path_type='dir')]]]]) -> Dict[str, Any]:", "funcdef": "def"}, "bioimageio.spec.partner_utils.imjoy.get_plugin_as_rdf": {"fullname": "bioimageio.spec.partner_utils.imjoy.get_plugin_as_rdf", "modulename": "bioimageio.spec.partner_utils.imjoy", "qualname": "get_plugin_as_rdf", "kind": "function", "doc": "
    Get imjoy plugin config in RDF format.
    \n", "signature": "(source_url: str) -> Dict[Any, Any]:", "funcdef": "def"}, "bioimageio.spec.pretty_validation_errors": {"fullname": "bioimageio.spec.pretty_validation_errors", "modulename": "bioimageio.spec.pretty_validation_errors", "kind": "module", "doc": "
    \n"}, "bioimageio.spec.pretty_validation_errors.PrettyValidationError": {"fullname": "bioimageio.spec.pretty_validation_errors.PrettyValidationError", "modulename": "bioimageio.spec.pretty_validation_errors", "qualname": "PrettyValidationError", "kind": "class", "doc": "
    Wrap a pydantic.ValidationError to custumize formatting.
    \n", "bases": "builtins.ValueError"}, "bioimageio.spec.pretty_validation_errors.PrettyValidationError.__init__": {"fullname": "bioimageio.spec.pretty_validation_errors.PrettyValidationError.__init__", "modulename": "bioimageio.spec.pretty_validation_errors", "qualname": "PrettyValidationError.__init__", "kind": "function", "doc": "
    \n", "signature": "(validation_error: pydantic_core._pydantic_core.ValidationError)"}, "bioimageio.spec.pretty_validation_errors.PrettyValidationError.error": {"fullname": "bioimageio.spec.pretty_validation_errors.PrettyValidationError.error", "modulename": "bioimageio.spec.pretty_validation_errors", "qualname": "PrettyValidationError.error", "kind": "variable", "doc": "
    \n"}, "bioimageio.spec.pretty_validation_errors.enable_pretty_validation_errors_in_ipynb": {"fullname": "bioimageio.spec.pretty_validation_errors.enable_pretty_validation_errors_in_ipynb", "modulename": "bioimageio.spec.pretty_validation_errors", "qualname": "enable_pretty_validation_errors_in_ipynb", "kind": "function", "doc": "
    A modestly hacky way to display prettified validaiton error messages and traceback\nin interactive Python notebooks
    \n", "signature": "():", "funcdef": "def"}, "bioimageio.spec.summary": {"fullname": "bioimageio.spec.summary", "modulename": "bioimageio.spec.summary", "kind": "module", "doc": "
    \n"}, "bioimageio.spec.summary.Loc": {"fullname": "bioimageio.spec.summary.Loc", "modulename": "bioimageio.spec.summary", "qualname": "Loc", "kind": "variable", "doc": "
    location of error/warning in a nested data structure
    \n", "default_value": "typing.Tuple[typing.Union[int, str], ...]"}, "bioimageio.spec.summary.WarningSeverityName": {"fullname": "bioimageio.spec.summary.WarningSeverityName", "modulename": "bioimageio.spec.summary", "qualname": "WarningSeverityName", "kind": "variable", "doc": "
    \n", "default_value": "typing.Literal['info', 'warning', 'alert']"}, "bioimageio.spec.summary.WarningLevelName": {"fullname": "bioimageio.spec.summary.WarningLevelName", "modulename": "bioimageio.spec.summary", "qualname": "WarningLevelName", "kind": "variable", "doc": "
    \n", "default_value": "typing.Literal['info', 'warning', 'alert', 'error']"}, "bioimageio.spec.summary.WARNING_SEVERITY_TO_NAME": {"fullname": "bioimageio.spec.summary.WARNING_SEVERITY_TO_NAME", "modulename": "bioimageio.spec.summary", "qualname": "WARNING_SEVERITY_TO_NAME", "kind": "variable", "doc": "
    \n", "annotation": ": Mapping[Literal[20, 30, 35], Literal['info', 'warning', 'alert']]", "default_value": "mappingproxy({20: 'info', 30: 'warning', 35: 'alert'})"}, "bioimageio.spec.summary.WARNING_LEVEL_TO_NAME": {"fullname": "bioimageio.spec.summary.WARNING_LEVEL_TO_NAME", "modulename": "bioimageio.spec.summary", "qualname": "WARNING_LEVEL_TO_NAME", "kind": "variable", "doc": "
    \n", "annotation": ": Mapping[Literal[20, 30, 35, 50], Literal['info', 'warning', 'alert', 'error']]", "default_value": "mappingproxy({20: 'info', 30: 'warning', 35: 'alert', 50: 'error'})"}, "bioimageio.spec.summary.WARNING_NAME_TO_LEVEL": {"fullname": "bioimageio.spec.summary.WARNING_NAME_TO_LEVEL", "modulename": "bioimageio.spec.summary", "qualname": "WARNING_NAME_TO_LEVEL", "kind": "variable", "doc": "
    \n", "annotation": ": Mapping[Literal['info', 'warning', 'alert', 'error'], Literal[20, 30, 35, 50]]", "default_value": "mappingproxy({'info': 20, 'warning': 30, 'alert': 35, 'error': 50})"}, "bioimageio.spec.summary.ValidationEntry": {"fullname": "bioimageio.spec.summary.ValidationEntry", "modulename": "bioimageio.spec.summary", "qualname": "ValidationEntry", "kind": "class", "doc": "
    Usage docs: https://docs.pydantic.dev/2.6/concepts/models/
    \n\n
    A base class for creating Pydantic models.
    \n\n
    Attributes:\n    __class_vars__: The names of classvars defined on the model.\n    __private_attributes__: Metadata about the private attributes of the model.\n    __signature__: The signature for instantiating the model.
    \n\n
    __pydantic_complete__: Whether model building is completed, or if there are still undefined fields.\n__pydantic_core_schema__: The pydantic-core schema used to build the SchemaValidator and SchemaSerializer.\n__pydantic_custom_init__: Whether the model has a custom `__init__` function.\n__pydantic_decorators__: Metadata containing the decorators defined on the model.\n    This replaces `Model.__validators__` and `Model.__root_validators__` from Pydantic V1.\n__pydantic_generic_metadata__: Metadata for generic models; contains data used for a similar purpose to\n    __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.\n__pydantic_parent_namespace__: Parent namespace of the model, used for automatic rebuilding of models.\n__pydantic_post_init__: The name of the post-init method for the model, if defined.\n__pydantic_root_model__: Whether the model is a `RootModel`.\n__pydantic_serializer__: The pydantic-core SchemaSerializer used to dump instances of the model.\n__pydantic_validator__: The pydantic-core SchemaValidator used to validate instances of the model.\n\n__pydantic_extra__: An instance attribute with the values of extra fields from validation when\n    `model_config['extra'] == 'allow'`.\n__pydantic_fields_set__: An instance attribute with the names of fields explicitly set.\n__pydantic_private__: Instance attribute with the values of private attributes set on the model instance.\n
    \n", "bases": "pydantic.main.BaseModel"}, "bioimageio.spec.summary.ValidationEntry.loc": {"fullname": "bioimageio.spec.summary.ValidationEntry.loc", "modulename": "bioimageio.spec.summary", "qualname": "ValidationEntry.loc", "kind": "variable", "doc": "
    \n", "annotation": ": Tuple[Union[int, str], ...]"}, "bioimageio.spec.summary.ValidationEntry.msg": {"fullname": "bioimageio.spec.summary.ValidationEntry.msg", "modulename": "bioimageio.spec.summary", "qualname": "ValidationEntry.msg", "kind": "variable", "doc": "
    \n", "annotation": ": str"}, "bioimageio.spec.summary.ValidationEntry.type": {"fullname": "bioimageio.spec.summary.ValidationEntry.type", "modulename": "bioimageio.spec.summary", "qualname": "ValidationEntry.type", "kind": "variable", "doc": "
    \n", "annotation": ": Union[Literal['no_such_attribute', 'json_invalid', 'json_type', 'recursion_loop', 'missing', 'frozen_field', 'frozen_instance', 'extra_forbidden', 'invalid_key', 'get_attribute_error', 'model_type', 'model_attributes_type', 'dataclass_type', 'dataclass_exact_type', 'none_required', 'greater_than', 'greater_than_equal', 'less_than', 'less_than_equal', 'multiple_of', 'finite_number', 'too_short', 'too_long', 'iterable_type', 'iteration_error', 'string_type', 'string_sub_type', 'string_unicode', 'string_too_short', 'string_too_long', 'string_pattern_mismatch', 'enum', 'dict_type', 'mapping_type', 'list_type', 'tuple_type', 'set_type', 'bool_type', 'bool_parsing', 'int_type', 'int_parsing', 'int_parsing_size', 'int_from_float', 'float_type', 'float_parsing', 'bytes_type', 'bytes_too_short', 'bytes_too_long', 'value_error', 'assertion_error', 'literal_error', 'date_type', 'date_parsing', 'date_from_datetime_parsing', 'date_from_datetime_inexact', 'date_past', 'date_future', 'time_type', 'time_parsing', 'datetime_type', 'datetime_parsing', 'datetime_object_invalid', 'datetime_from_date_parsing', 'datetime_past', 'datetime_future', 'timezone_naive', 'timezone_aware', 'timezone_offset', 'time_delta_type', 'time_delta_parsing', 'frozen_set_type', 'is_instance_of', 'is_subclass_of', 'callable_type', 'union_tag_invalid', 'union_tag_not_found', 'arguments_type', 'missing_argument', 'unexpected_keyword_argument', 'missing_keyword_only_argument', 'unexpected_positional_argument', 'missing_positional_only_argument', 'multiple_argument_values', 'url_type', 'url_parsing', 'url_syntax_violation', 'url_too_long', 'url_scheme', 'uuid_type', 'uuid_parsing', 'uuid_version', 'decimal_type', 'decimal_parsing', 'decimal_max_digits', 'decimal_max_places', 'decimal_whole_digits'], str]"}, "bioimageio.spec.summary.ValidationEntry.model_config": {"fullname": "bioimageio.spec.summary.ValidationEntry.model_config", "modulename": "bioimageio.spec.summary", "qualname": "ValidationEntry.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.summary.ValidationEntry.model_fields": {"fullname": "bioimageio.spec.summary.ValidationEntry.model_fields", "modulename": "bioimageio.spec.summary", "qualname": "ValidationEntry.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'loc': FieldInfo(annotation=Tuple[Union[int, str], ...], required=True), 'msg': FieldInfo(annotation=str, required=True), 'type': FieldInfo(annotation=Union[Literal['no_such_attribute', 'json_invalid', 'json_type', 'recursion_loop', 'missing', 'frozen_field', 'frozen_instance', 'extra_forbidden', 'invalid_key', 'get_attribute_error', 'model_type', 'model_attributes_type', 'dataclass_type', 'dataclass_exact_type', 'none_required', 'greater_than', 'greater_than_equal', 'less_than', 'less_than_equal', 'multiple_of', 'finite_number', 'too_short', 'too_long', 'iterable_type', 'iteration_error', 'string_type', 'string_sub_type', 'string_unicode', 'string_too_short', 'string_too_long', 'string_pattern_mismatch', 'enum', 'dict_type', 'mapping_type', 'list_type', 'tuple_type', 'set_type', 'bool_type', 'bool_parsing', 'int_type', 'int_parsing', 'int_parsing_size', 'int_from_float', 'float_type', 'float_parsing', 'bytes_type', 'bytes_too_short', 'bytes_too_long', 'value_error', 'assertion_error', 'literal_error', 'date_type', 'date_parsing', 'date_from_datetime_parsing', 'date_from_datetime_inexact', 'date_past', 'date_future', 'time_type', 'time_parsing', 'datetime_type', 'datetime_parsing', 'datetime_object_invalid', 'datetime_from_date_parsing', 'datetime_past', 'datetime_future', 'timezone_naive', 'timezone_aware', 'timezone_offset', 'time_delta_type', 'time_delta_parsing', 'frozen_set_type', 'is_instance_of', 'is_subclass_of', 'callable_type', 'union_tag_invalid', 'union_tag_not_found', 'arguments_type', 'missing_argument', 'unexpected_keyword_argument', 'missing_keyword_only_argument', 'unexpected_positional_argument', 'missing_positional_only_argument', 'multiple_argument_values', 'url_type', 'url_parsing', 'url_syntax_violation', 'url_too_long', 'url_scheme', 'uuid_type', 'uuid_parsing', 'uuid_version', 'decimal_type', 'decimal_parsing', 'decimal_max_digits', 'decimal_max_places', 'decimal_whole_digits'], str], required=True)}"}, "bioimageio.spec.summary.ValidationEntry.model_computed_fields": {"fullname": "bioimageio.spec.summary.ValidationEntry.model_computed_fields", "modulename": "bioimageio.spec.summary", "qualname": "ValidationEntry.model_computed_fields", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.summary.ErrorEntry": {"fullname": "bioimageio.spec.summary.ErrorEntry", "modulename": "bioimageio.spec.summary", "qualname": "ErrorEntry", "kind": "class", "doc": "
    Usage docs: https://docs.pydantic.dev/2.6/concepts/models/
    \n\n
    A base class for creating Pydantic models.
    \n\n
    Attributes:\n    __class_vars__: The names of classvars defined on the model.\n    __private_attributes__: Metadata about the private attributes of the model.\n    __signature__: The signature for instantiating the model.
    \n\n
    __pydantic_complete__: Whether model building is completed, or if there are still undefined fields.\n__pydantic_core_schema__: The pydantic-core schema used to build the SchemaValidator and SchemaSerializer.\n__pydantic_custom_init__: Whether the model has a custom `__init__` function.\n__pydantic_decorators__: Metadata containing the decorators defined on the model.\n    This replaces `Model.__validators__` and `Model.__root_validators__` from Pydantic V1.\n__pydantic_generic_metadata__: Metadata for generic models; contains data used for a similar purpose to\n    __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.\n__pydantic_parent_namespace__: Parent namespace of the model, used for automatic rebuilding of models.\n__pydantic_post_init__: The name of the post-init method for the model, if defined.\n__pydantic_root_model__: Whether the model is a `RootModel`.\n__pydantic_serializer__: The pydantic-core SchemaSerializer used to dump instances of the model.\n__pydantic_validator__: The pydantic-core SchemaValidator used to validate instances of the model.\n\n__pydantic_extra__: An instance attribute with the values of extra fields from validation when\n    `model_config['extra'] == 'allow'`.\n__pydantic_fields_set__: An instance attribute with the names of fields explicitly set.\n__pydantic_private__: Instance attribute with the values of private attributes set on the model instance.\n
    \n", "bases": "ValidationEntry"}, "bioimageio.spec.summary.ErrorEntry.traceback": {"fullname": "bioimageio.spec.summary.ErrorEntry.traceback", "modulename": "bioimageio.spec.summary", "qualname": "ErrorEntry.traceback", "kind": "variable", "doc": "
    \n", "annotation": ": List[str]"}, "bioimageio.spec.summary.ErrorEntry.model_config": {"fullname": "bioimageio.spec.summary.ErrorEntry.model_config", "modulename": "bioimageio.spec.summary", "qualname": "ErrorEntry.model_config", "kind": "variable", "doc": "
    \n", "default_value": "{}"}, "bioimageio.spec.summary.ErrorEntry.model_fields": {"fullname": "bioimageio.spec.summary.ErrorEntry.model_fields", "modulename": "bioimageio.spec.summary", "qualname": "ErrorEntry.model_fields", "kind": "variable", "doc": "
    \n", "default_value": "{'loc': FieldInfo(annotation=Tuple[Union[int, str], ...], required=True), 'msg': FieldInfo(annotation=str, required=True), 'type': FieldInfo(annotation=Union[Literal['no_such_attribute', 'json_invalid', 'json_type', 'recursion_loop', 'missing', 'frozen_field', 'frozen_instance', 'extra_forbidden', 'invalid_key', 'get_attribute_error', 'model_type', 'model_attributes_type', 'dataclass_type', 'dataclass_exact_type', 'none_required', 'greater_than', 'greater_than_equal', 'less_than', 'less_than_equal', 'multiple_of', 'finite_number', 'too_short', 'too_long', 'iterable_type', 'iteration_error', 'string_type', 'string_sub_type', 'string_unicode', 'string_too_short', 'string_too_long', 'string_pattern_mismatch', 'enum', 'dict_type', 'mapping_type', 'list_type', 'tuple_type', 'set_type', 'bool_type', 'bool_parsing', 'int_type', 'int_parsing', 'int_parsing_size', 'int_from_float', 'float_type', 'float_parsing', 'bytes_type', 'bytes_too_short', 'bytes_too_long', 'value_error', 'assertion_error', 'literal_error', 'date_type', 'date_parsing', 'date_from_datetime_parsing', 'date_from_datetime_inexact', 'date_past', 'date_future', 'time_type', 'time_parsing', 'datetime_type', 'datetime_parsing', 'datetime_object_invalid', 'datetime_from_date_parsing', 'datetime_past', 'datetime_future', 'timezone_naive', 'timezone_aware', 'timezone_offset', 'time_delta_type', 'time_delta_parsing', 'frozen_set_type', 'is_instance_of', 'is_subclass_of', 'callable_type', 'union_tag_invalid', 'union_tag_not_found', 'arguments_type', 'missing_argument', 'unexpected_keyword_argument', 'missing_keyword_only_argument', 'unexpected_positional_argument', 'missing_positional_only_argument', 'multiple_argument_values', 'url_type', 'url_parsing', 'url_syntax_violation', 'url_too_long', 'url_scheme', 'uuid_type', 'uuid_parsing', 'uuid_version', 'decimal_type', 'decimal_parsing', 'decimal_max_digits', 'decimal_max_places', 'decimal_whole_digits'], str], required=True), 'traceback': FieldInfo(annotation=List[str], required=False, default_factory=list)}"}, "bioimageio.spec.summary.ErrorEntry.model_computed_fields": {"fullname": "bioimageio.spec.summary.ErrorEntry.model_computed_fields", "modulename": "bioimageio.spec.summary", "qualname": "ErrorEntry.model_computed_fields", "kind": "variable", "doc": "
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    Attributes:\n    __class_vars__: The names of classvars defined on the model.\n    __private_attributes__: Metadata about the private attributes of the model.\n    __signature__: The signature for instantiating the model.
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    \n", "bases": "ValidationEntry"}, "bioimageio.spec.summary.WarningEntry.severity": {"fullname": "bioimageio.spec.summary.WarningEntry.severity", "modulename": "bioimageio.spec.summary", "qualname": "WarningEntry.severity", "kind": "variable", "doc": "
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    \n", "signature": "(cls, data: Union[Mapping[Any, Any], Any]) -> Any:", "funcdef": "def"}, "bioimageio.spec.summary.WarningEntry.model_config": {"fullname": "bioimageio.spec.summary.WarningEntry.model_config", "modulename": "bioimageio.spec.summary", "qualname": "WarningEntry.model_config", "kind": "variable", "doc": "
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    Usage docs: https://docs.pydantic.dev/2.6/concepts/models/
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    A base class for creating Pydantic models.
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    Attributes:\n    __class_vars__: The names of classvars defined on the model.\n    __private_attributes__: Metadata about the private attributes of the model.\n    __signature__: The signature for instantiating the model.
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    \n", "bases": "pydantic.main.BaseModel"}, "bioimageio.spec.summary.ValidationDetail.name": {"fullname": "bioimageio.spec.summary.ValidationDetail.name", "modulename": "bioimageio.spec.summary", "qualname": "ValidationDetail.name", "kind": "variable", "doc": "
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    Usage docs: https://docs.pydantic.dev/2.6/concepts/models/
    \n\n
    A base class for creating Pydantic models.
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{"docs": {}, "df": 0, "r": {"docs": {"bioimageio.spec.notebook.v0_2.NotebookDescr": {"tf": 1}, "bioimageio.spec.notebook.v0_2.NotebookDescr.source": {"tf": 1}, "bioimageio.spec.notebook.v0_3.NotebookDescr": {"tf": 1}, "bioimageio.spec.notebook.v0_3.NotebookDescr.source": {"tf": 1}}, "df": 4}}}}}}}, "z": {"docs": {"bioimageio.spec.model.v0_4.TensorDescrBase.axes": {"tf": 1.4142135623730951}}, "df": 1, "e": {"docs": {}, "df": 0, "n": {"docs": {}, "df": 0, "o": {"docs": {}, "df": 0, "d": {"docs": {}, "df": 0, "o": {"docs": {"bioimageio.spec": {"tf": 1}}, "df": 1}}}}, "r": {"docs": {}, "df": 0, "o": {"docs": {"bioimageio.spec": {"tf": 1.4142135623730951}, "bioimageio.spec.model.v0_4.BinarizeDescr": {"tf": 1}, "bioimageio.spec.model.v0_5.BinarizeDescr": {"tf": 1}, "bioimageio.spec.model.v0_5.FixedZeroMeanUnitVarianceKwargs": {"tf": 1}}, "df": 4, "e": {"docs": {}, "df": 0, "s": {"docs": {"bioimageio.spec._internal.version_type.Version.release": {"tf": 1}}, "df": 1}}}}}, "i": {"docs": {}, "df": 0, "p": {"docs": {"bioimageio.spec._internal.io_utils.write_zip": {"tf": 1}, "bioimageio.spec.generic.v0_2.GenericModelDescrBase.config": {"tf": 1}, "bioimageio.spec.generic.v0_3.GenericModelDescrBase.config": {"tf": 1}, "bioimageio.spec.model.v0_4.TensorflowJsWeightsDescr.source": {"tf": 1}, "bioimageio.spec.model.v0_5.TensorflowJsWeightsDescr.source": {"tf": 1}, "bioimageio.spec.model.v0_5.TensorflowSavedModelBundleWeightsDescr.source": {"tf": 1}}, "df": 6, "f": {"docs": {}, "df": 0, "i": {"docs": {}, "df": 0, "l": {"docs": {}, "df": 0, "e": {"docs": {"bioimageio.spec._internal.io_utils.write_zip": {"tf": 1}}, "df": 1}}}}}}, "o": {"docs": {}, "df": 0, "o": {"docs": {"bioimageio.spec.application.v0_2.ApplicationDescr.id": {"tf": 1}, "bioimageio.spec.application.v0_3.ApplicationDescr.id": {"tf": 1}, "bioimageio.spec.collection.v0_2.CollectionDescr.id": {"tf": 1}, "bioimageio.spec.collection.v0_3.CollectionDescr.id": {"tf": 1}, "bioimageio.spec.dataset.v0_2.DatasetDescr.id": {"tf": 1}, "bioimageio.spec.dataset.v0_3.DatasetDescr.id": {"tf": 1}, "bioimageio.spec.generic.v0_2.GenericDescr.id": {"tf": 1}, "bioimageio.spec.generic.v0_3.GenericDescr.id": {"tf": 1}, "bioimageio.spec.model.v0_4.ModelDescr.id": {"tf": 1}, "bioimageio.spec.model.v0_5.ModelDescr.id": {"tf": 1}, "bioimageio.spec.notebook.v0_2.NotebookDescr.id": {"tf": 1}, "bioimageio.spec.notebook.v0_3.NotebookDescr.id": {"tf": 1}}, "df": 12}}}, "k": {"docs": {"bioimageio.spec.model.v0_4.ParameterizedInputShape": {"tf": 1.7320508075688772}, "bioimageio.spec.model.v0_4.SigmoidDescr": {"tf": 1}, "bioimageio.spec.model.v0_5.SigmoidDescr": {"tf": 1}}, "df": 3, "e": {"docs": {}, "df": 0, "e": {"docs": {}, "df": 0, "p": {"docs": {"bioimageio.spec": {"tf": 1.7320508075688772}, "bioimageio.spec.generic.v0_2.GenericModelDescrBase.rdf_source": {"tf": 1}}, "df": 2, "s": {"docs": {"bioimageio.spec": {"tf": 1}}, "df": 1}}}, "y": {"docs": {"bioimageio.spec._internal.common_nodes.Converter": {"tf": 1.4142135623730951}, "bioimageio.spec.generic.v0_2.GenericModelDescrBase.config": {"tf": 1.4142135623730951}, "bioimageio.spec.generic.v0_3.GenericModelDescrBase.config": {"tf": 1.4142135623730951}, "bioimageio.spec.model.v0_4.PytorchStateDictWeightsDescr.kwargs": {"tf": 1}, "bioimageio.spec.model.v0_4.ProcessingKwargs": {"tf": 1}, "bioimageio.spec.model.v0_4.BinarizeKwargs": {"tf": 1}, "bioimageio.spec.model.v0_4.ClipKwargs": {"tf": 1}, "bioimageio.spec.model.v0_4.ScaleLinearKwargs": {"tf": 1}, "bioimageio.spec.model.v0_4.ZeroMeanUnitVarianceKwargs": {"tf": 1}, "bioimageio.spec.model.v0_4.ScaleRangeKwargs": {"tf": 1}, "bioimageio.spec.model.v0_4.ScaleMeanVarianceKwargs": {"tf": 1}, "bioimageio.spec.model.v0_4.RunMode.kwargs": {"tf": 1}, "bioimageio.spec.model.v0_5.EnsureDtypeKwargs": {"tf": 1}, "bioimageio.spec.model.v0_5.ScaleLinearKwargs": {"tf": 1}, "bioimageio.spec.model.v0_5.ZeroMeanUnitVarianceKwargs": {"tf": 1}, "bioimageio.spec.model.v0_5.ScaleRangeKwargs": {"tf": 1}}, "df": 16, "s": {"docs": {"bioimageio.spec": {"tf": 1}, "bioimageio.spec._internal.utils.nest_dict_with_narrow_first_key": {"tf": 1.4142135623730951}, "bioimageio.spec.generic.v0_2.AttachmentsDescr.model_config": {"tf": 1}, "bioimageio.spec.generic.v0_2.GenericModelDescrBase.config": {"tf": 1.7320508075688772}, "bioimageio.spec.generic.v0_3.GenericModelDescrBase.config": {"tf": 1.7320508075688772}}, "df": 5}, "e": {"docs": {}, "df": 0, "r": {"docs": {}, "df": 0, "r": {"docs": {}, "df": 0, "o": {"docs": {}, "df": 0, "r": {"docs": {"bioimageio.spec._internal.common_nodes.Converter": {"tf": 1}}, "df": 1}}}}}}}, "n": {"docs": {}, "df": 0, "o": {"docs": {}, "df": 0, "w": {"docs": {}, "df": 0, "n": {"docs": {"bioimageio.spec": {"tf": 1}, "bioimageio.spec.generic.v0_2.GenericDescr": {"tf": 1}, "bioimageio.spec.generic.v0_3.GenericDescr": {"tf": 1}}, "df": 3}}}}, "w": {"docs": {}, "df": 0, "a": {"docs": {}, "df": 0, "r": {"docs": {}, "df": 0, "g": {"docs": {"bioimageio.spec": {"tf": 1.7320508075688772}}, "df": 1, "s": {"docs": {"bioimageio.spec": {"tf": 1.4142135623730951}, "bioimageio.spec.model.v0_4.SigmoidDescr.kwargs": {"tf": 1}, "bioimageio.spec.model.v0_5.SigmoidDescr.kwargs": {"tf": 1}}, "df": 3}}}}}, "t": {"docs": {"bioimageio.spec._internal.common_nodes.Converter": {"tf": 1.4142135623730951}}, "df": 1}}, "q": {"docs": {}, "df": 0, "u": {"docs": {}, "df": 0, "o": {"docs": {}, "df": 0, "t": {"docs": {"bioimageio.spec._internal.docs_utils.get_ref_url": {"tf": 2.449489742783178}, "bioimageio.spec._internal.version_type.Version.epoch": {"tf": 2}, "bioimageio.spec._internal.version_type.Version.release": {"tf": 2.449489742783178}, "bioimageio.spec._internal.version_type.Version.pre": {"tf": 2.8284271247461903}, "bioimageio.spec._internal.version_type.Version.post": {"tf": 2}, "bioimageio.spec._internal.version_type.Version.dev": {"tf": 2}, "bioimageio.spec._internal.version_type.Version.local": {"tf": 2}, "bioimageio.spec._internal.version_type.Version.public": {"tf": 2.449489742783178}, "bioimageio.spec._internal.version_type.Version.base_version": {"tf": 2.449489742783178}, "bioimageio.spec._internal.version_type.Version.is_prerelease": {"tf": 3.1622776601683795}, "bioimageio.spec._internal.version_type.Version.is_postrelease": {"tf": 2}, "bioimageio.spec._internal.version_type.Version.is_devrelease": {"tf": 2}, "bioimageio.spec._internal.version_type.Version.major": {"tf": 1.4142135623730951}, "bioimageio.spec._internal.version_type.Version.minor": {"tf": 2}, "bioimageio.spec._internal.version_type.Version.micro": {"tf": 2}, "bioimageio.spec.model.v0_5.SizeReference": {"tf": 3.4641016151377544}}, "df": 16}}, "a": {"docs": {}, "df": 0, "n": {"docs": {}, "df": 0, "t": {"docs": {}, "df": 0, "i": {"docs": {}, "df": 0, "t": {"docs": {}, "df": 0, "a": {"docs": {}, "df": 0, "t": {"docs": {}, "df": 0, "i": {"docs": {}, "df": 0, "v": {"docs": {}, "df": 0, "e": {"docs": {}, "df": 0, "l": {"docs": {}, "df": 0, "y": {"docs": {"bioimageio.spec.model.v0_4.ModelDescr.documentation": {"tf": 1}, "bioimageio.spec.model.v0_5.ModelDescr.documentation": {"tf": 1}}, "df": 2}}}}}}}}}}}}}}, "x": {"docs": {"bioimageio.spec._internal.warning_levels.WarningLevel": {"tf": 1.4142135623730951}, "bioimageio.spec.model.v0_4.TensorDescrBase.axes": {"tf": 1.4142135623730951}, "bioimageio.spec.model.v0_5.ZeroMeanUnitVarianceKwargs.axes": {"tf": 1.7320508075688772}, "bioimageio.spec.model.v0_5.ScaleRangeKwargs.axes": {"tf": 1.7320508075688772}, "bioimageio.spec.model.v0_5.ScaleMeanVarianceKwargs.axes": {"tf": 1.7320508075688772}}, "df": 5, "y": {"docs": {"bioimageio.spec.model.v0_4.ScaleLinearKwargs.axes": {"tf": 1}, "bioimageio.spec.model.v0_4.ZeroMeanUnitVarianceKwargs.axes": {"tf": 1}, "bioimageio.spec.model.v0_4.ZeroMeanUnitVarianceKwargs.mean": {"tf": 1}, "bioimageio.spec.model.v0_4.ScaleRangeKwargs.axes": {"tf": 1}, "bioimageio.spec.model.v0_4.ScaleMeanVarianceKwargs.axes": {"tf": 1}}, "df": 5}}}}}, "pipeline": ["trimmer"], "_isPrebuiltIndex": true};
 
     // mirrored in build-search-index.js (part 1)
     // Also split on html tags. this is a cheap heuristic, but good enough.
diff --git a/user_docs/application_descr_latest.md b/user_docs/application_descr_latest.md
index b82f3d008..9677f7e0e 100644
--- a/user_docs/application_descr_latest.md
+++ b/user_docs/application_descr_latest.md
@@ -181,10 +181,10 @@ The supported image formats are: ('.gif', '.jpeg', '.jpg', '.png', '.svg')
 
 Sequence of Union of
 - _internal.url.HttpUrl
-- Path (PathType(path_type='file'); Predicate(func=))
+- Path (PathType(path_type='file'); Predicate(func=))
 - _internal.io.RelativeFilePath
 
-(WithSuffix(suffix=('.gif', '.jpeg', '.jpg', '.png', '.svg'), case_sensitive=False); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
+(WithSuffix(suffix=('.gif', '.jpeg', '.jpg', '.png', '.svg'), case_sensitive=False); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
 
 
 
@@ -197,11 +197,11 @@ Sequence of Union of
 
 
 Optional[Union of
-- Path (PathType(path_type='file'); Predicate(func=))
+- Path (PathType(path_type='file'); Predicate(func=))
 - _internal.io.RelativeFilePath
 - _internal.url.HttpUrl
 
-(AfterValidator(_validate_md_suffix); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))]
+(AfterValidator(_validate_md_suffix); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))]
 
 
 
@@ -225,7 +225,7 @@ Union of
   - _internal.url.HttpUrl
   - Url (max_length=2083 allowed_schemes=['http', 'https'])
 
-  (AfterValidator(func=); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
+  (AfterValidator(wo_special_file_name); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
 - str (Len(min_length=1, max_length=2))
 - None
 
@@ -308,7 +308,7 @@ Optional[Union of
 - _internal.url.HttpUrl
 - Url (max_length=2083 allowed_schemes=['http', 'https'])
 
-(AfterValidator(func=); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))]
+(AfterValidator(wo_special_file_name); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))]
 
 
 
diff --git a/user_docs/application_descr_v0-2-4.md b/user_docs/application_descr_v0-2-4.md
index 28a5b66dd..ea41e896a 100644
--- a/user_docs/application_descr_v0-2-4.md
+++ b/user_docs/application_descr_v0-2-4.md
@@ -54,7 +54,7 @@ Sequence of Union of
 - _internal.url.HttpUrl
 - Url (max_length=2083 allowed_schemes=['http', 'https'])
 
-(AfterValidator(func=); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
+(AfterValidator(wo_special_file_name); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
 
 
 
@@ -171,10 +171,10 @@ The supported image formats are: ('.gif', '.jpeg', '.jpg', '.png', '.svg')
 
 Sequence of Union of
 - _internal.url.HttpUrl
-- Path (PathType(path_type='file'); Predicate(func=))
+- Path (PathType(path_type='file'); Predicate(func=))
 - _internal.io.RelativeFilePath
 
-(WithSuffix(suffix=('.gif', '.jpeg', '.jpg', '.png', '.svg'), case_sensitive=False); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
+(WithSuffix(suffix=('.gif', '.jpeg', '.jpg', '.png', '.svg'), case_sensitive=False); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
 
 
 
@@ -192,7 +192,7 @@ Optional[Union of
 - _internal.url.HttpUrl
 - Url (max_length=2083 allowed_schemes=['http', 'https'])
 
-(AfterValidator(func=); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))]
+(AfterValidator(wo_special_file_name); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))]
 
 
 
@@ -221,7 +221,7 @@ Union of
   - _internal.url.HttpUrl
   - Url (max_length=2083 allowed_schemes=['http', 'https'])
 
-  (AfterValidator(func=); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
+  (AfterValidator(wo_special_file_name); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
 - str (Len(min_length=1, max_length=2))
 - None
 
@@ -322,7 +322,7 @@ Optional[Union of
 - _internal.url.HttpUrl
 - Url (max_length=2083 allowed_schemes=['http', 'https'])
 
-(AfterValidator(func=); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))]
+(AfterValidator(wo_special_file_name); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))]
 
 
 
diff --git a/user_docs/application_descr_v0-2.md b/user_docs/application_descr_v0-2.md
index 28a5b66dd..ea41e896a 100644
--- a/user_docs/application_descr_v0-2.md
+++ b/user_docs/application_descr_v0-2.md
@@ -54,7 +54,7 @@ Sequence of Union of
 - _internal.url.HttpUrl
 - Url (max_length=2083 allowed_schemes=['http', 'https'])
 
-(AfterValidator(func=); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
+(AfterValidator(wo_special_file_name); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
 
 
 
@@ -171,10 +171,10 @@ The supported image formats are: ('.gif', '.jpeg', '.jpg', '.png', '.svg')
 
 Sequence of Union of
 - _internal.url.HttpUrl
-- Path (PathType(path_type='file'); Predicate(func=))
+- Path (PathType(path_type='file'); Predicate(func=))
 - _internal.io.RelativeFilePath
 
-(WithSuffix(suffix=('.gif', '.jpeg', '.jpg', '.png', '.svg'), case_sensitive=False); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
+(WithSuffix(suffix=('.gif', '.jpeg', '.jpg', '.png', '.svg'), case_sensitive=False); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
 
 
 
@@ -192,7 +192,7 @@ Optional[Union of
 - _internal.url.HttpUrl
 - Url (max_length=2083 allowed_schemes=['http', 'https'])
 
-(AfterValidator(func=); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))]
+(AfterValidator(wo_special_file_name); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))]
 
 
 
@@ -221,7 +221,7 @@ Union of
   - _internal.url.HttpUrl
   - Url (max_length=2083 allowed_schemes=['http', 'https'])
 
-  (AfterValidator(func=); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
+  (AfterValidator(wo_special_file_name); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
 - str (Len(min_length=1, max_length=2))
 - None
 
@@ -322,7 +322,7 @@ Optional[Union of
 - _internal.url.HttpUrl
 - Url (max_length=2083 allowed_schemes=['http', 'https'])
 
-(AfterValidator(func=); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))]
+(AfterValidator(wo_special_file_name); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))]
 
 
 
diff --git a/user_docs/application_descr_v0-3-0.md b/user_docs/application_descr_v0-3-0.md
index b82f3d008..9677f7e0e 100644
--- a/user_docs/application_descr_v0-3-0.md
+++ b/user_docs/application_descr_v0-3-0.md
@@ -181,10 +181,10 @@ The supported image formats are: ('.gif', '.jpeg', '.jpg', '.png', '.svg')
 
 Sequence of Union of
 - _internal.url.HttpUrl
-- Path (PathType(path_type='file'); Predicate(func=))
+- Path (PathType(path_type='file'); Predicate(func=))
 - _internal.io.RelativeFilePath
 
-(WithSuffix(suffix=('.gif', '.jpeg', '.jpg', '.png', '.svg'), case_sensitive=False); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
+(WithSuffix(suffix=('.gif', '.jpeg', '.jpg', '.png', '.svg'), case_sensitive=False); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
 
 
 
@@ -197,11 +197,11 @@ Sequence of Union of
 
 
 Optional[Union of
-- Path (PathType(path_type='file'); Predicate(func=))
+- Path (PathType(path_type='file'); Predicate(func=))
 - _internal.io.RelativeFilePath
 - _internal.url.HttpUrl
 
-(AfterValidator(_validate_md_suffix); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))]
+(AfterValidator(_validate_md_suffix); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))]
 
 
 
@@ -225,7 +225,7 @@ Union of
   - _internal.url.HttpUrl
   - Url (max_length=2083 allowed_schemes=['http', 'https'])
 
-  (AfterValidator(func=); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
+  (AfterValidator(wo_special_file_name); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
 - str (Len(min_length=1, max_length=2))
 - None
 
@@ -308,7 +308,7 @@ Optional[Union of
 - _internal.url.HttpUrl
 - Url (max_length=2083 allowed_schemes=['http', 'https'])
 
-(AfterValidator(func=); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))]
+(AfterValidator(wo_special_file_name); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))]
 
 
 
diff --git a/user_docs/application_descr_v0-3.md b/user_docs/application_descr_v0-3.md
index b82f3d008..9677f7e0e 100644
--- a/user_docs/application_descr_v0-3.md
+++ b/user_docs/application_descr_v0-3.md
@@ -181,10 +181,10 @@ The supported image formats are: ('.gif', '.jpeg', '.jpg', '.png', '.svg')
 
 Sequence of Union of
 - _internal.url.HttpUrl
-- Path (PathType(path_type='file'); Predicate(func=))
+- Path (PathType(path_type='file'); Predicate(func=))
 - _internal.io.RelativeFilePath
 
-(WithSuffix(suffix=('.gif', '.jpeg', '.jpg', '.png', '.svg'), case_sensitive=False); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
+(WithSuffix(suffix=('.gif', '.jpeg', '.jpg', '.png', '.svg'), case_sensitive=False); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
 
 
 
@@ -197,11 +197,11 @@ Sequence of Union of
 
 
 Optional[Union of
-- Path (PathType(path_type='file'); Predicate(func=))
+- Path (PathType(path_type='file'); Predicate(func=))
 - _internal.io.RelativeFilePath
 - _internal.url.HttpUrl
 
-(AfterValidator(_validate_md_suffix); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))]
+(AfterValidator(_validate_md_suffix); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))]
 
 
 
@@ -225,7 +225,7 @@ Union of
   - _internal.url.HttpUrl
   - Url (max_length=2083 allowed_schemes=['http', 'https'])
 
-  (AfterValidator(func=); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
+  (AfterValidator(wo_special_file_name); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
 - str (Len(min_length=1, max_length=2))
 - None
 
@@ -308,7 +308,7 @@ Optional[Union of
 - _internal.url.HttpUrl
 - Url (max_length=2083 allowed_schemes=['http', 'https'])
 
-(AfterValidator(func=); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))]
+(AfterValidator(wo_special_file_name); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))]
 
 
 
diff --git a/user_docs/collection_descr_latest.md b/user_docs/collection_descr_latest.md
index dff177ba1..44715cdba 100644
--- a/user_docs/collection_descr_latest.md
+++ b/user_docs/collection_descr_latest.md
@@ -218,10 +218,10 @@ The supported image formats are: ('.gif', '.jpeg', '.jpg', '.png', '.svg')
 
 Sequence of Union of
 - _internal.url.HttpUrl
-- Path (PathType(path_type='file'); Predicate(func=))
+- Path (PathType(path_type='file'); Predicate(func=))
 - _internal.io.RelativeFilePath
 
-(WithSuffix(suffix=('.gif', '.jpeg', '.jpg', '.png', '.svg'), case_sensitive=False); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
+(WithSuffix(suffix=('.gif', '.jpeg', '.jpg', '.png', '.svg'), case_sensitive=False); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
 
 
 
@@ -234,11 +234,11 @@ Sequence of Union of
 
 
 Optional[Union of
-- Path (PathType(path_type='file'); Predicate(func=))
+- Path (PathType(path_type='file'); Predicate(func=))
 - _internal.io.RelativeFilePath
 - _internal.url.HttpUrl
 
-(AfterValidator(_validate_md_suffix); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))]
+(AfterValidator(_validate_md_suffix); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))]
 
 
 
@@ -262,7 +262,7 @@ Union of
   - _internal.url.HttpUrl
   - Url (max_length=2083 allowed_schemes=['http', 'https'])
 
-  (AfterValidator(func=); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
+  (AfterValidator(wo_special_file_name); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
 - str (Len(min_length=1, max_length=2))
 - None
 
diff --git a/user_docs/collection_descr_v0-2-4.md b/user_docs/collection_descr_v0-2-4.md
index cf1db476b..eb49a84da 100644
--- a/user_docs/collection_descr_v0-2-4.md
+++ b/user_docs/collection_descr_v0-2-4.md
@@ -90,7 +90,7 @@ Sequence of Union of
 - _internal.url.HttpUrl
 - Url (max_length=2083 allowed_schemes=['http', 'https'])
 
-(AfterValidator(func=); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
+(AfterValidator(wo_special_file_name); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
 
 
 
@@ -207,10 +207,10 @@ The supported image formats are: ('.gif', '.jpeg', '.jpg', '.png', '.svg')
 
 Sequence of Union of
 - _internal.url.HttpUrl
-- Path (PathType(path_type='file'); Predicate(func=))
+- Path (PathType(path_type='file'); Predicate(func=))
 - _internal.io.RelativeFilePath
 
-(WithSuffix(suffix=('.gif', '.jpeg', '.jpg', '.png', '.svg'), case_sensitive=False); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
+(WithSuffix(suffix=('.gif', '.jpeg', '.jpg', '.png', '.svg'), case_sensitive=False); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
 
 
 
@@ -228,7 +228,7 @@ Optional[Union of
 - _internal.url.HttpUrl
 - Url (max_length=2083 allowed_schemes=['http', 'https'])
 
-(AfterValidator(func=); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))]
+(AfterValidator(wo_special_file_name); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))]
 
 
 
@@ -257,7 +257,7 @@ Union of
   - _internal.url.HttpUrl
   - Url (max_length=2083 allowed_schemes=['http', 'https'])
 
-  (AfterValidator(func=); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
+  (AfterValidator(wo_special_file_name); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
 - str (Len(min_length=1, max_length=2))
 - None
 
diff --git a/user_docs/collection_descr_v0-2.md b/user_docs/collection_descr_v0-2.md
index cf1db476b..eb49a84da 100644
--- a/user_docs/collection_descr_v0-2.md
+++ b/user_docs/collection_descr_v0-2.md
@@ -90,7 +90,7 @@ Sequence of Union of
 - _internal.url.HttpUrl
 - Url (max_length=2083 allowed_schemes=['http', 'https'])
 
-(AfterValidator(func=); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
+(AfterValidator(wo_special_file_name); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
 
 
 
@@ -207,10 +207,10 @@ The supported image formats are: ('.gif', '.jpeg', '.jpg', '.png', '.svg')
 
 Sequence of Union of
 - _internal.url.HttpUrl
-- Path (PathType(path_type='file'); Predicate(func=))
+- Path (PathType(path_type='file'); Predicate(func=))
 - _internal.io.RelativeFilePath
 
-(WithSuffix(suffix=('.gif', '.jpeg', '.jpg', '.png', '.svg'), case_sensitive=False); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
+(WithSuffix(suffix=('.gif', '.jpeg', '.jpg', '.png', '.svg'), case_sensitive=False); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
 
 
 
@@ -228,7 +228,7 @@ Optional[Union of
 - _internal.url.HttpUrl
 - Url (max_length=2083 allowed_schemes=['http', 'https'])
 
-(AfterValidator(func=); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))]
+(AfterValidator(wo_special_file_name); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))]
 
 
 
@@ -257,7 +257,7 @@ Union of
   - _internal.url.HttpUrl
   - Url (max_length=2083 allowed_schemes=['http', 'https'])
 
-  (AfterValidator(func=); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
+  (AfterValidator(wo_special_file_name); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
 - str (Len(min_length=1, max_length=2))
 - None
 
diff --git a/user_docs/collection_descr_v0-3-0.md b/user_docs/collection_descr_v0-3-0.md
index dff177ba1..44715cdba 100644
--- a/user_docs/collection_descr_v0-3-0.md
+++ b/user_docs/collection_descr_v0-3-0.md
@@ -218,10 +218,10 @@ The supported image formats are: ('.gif', '.jpeg', '.jpg', '.png', '.svg')
 
 Sequence of Union of
 - _internal.url.HttpUrl
-- Path (PathType(path_type='file'); Predicate(func=))
+- Path (PathType(path_type='file'); Predicate(func=))
 - _internal.io.RelativeFilePath
 
-(WithSuffix(suffix=('.gif', '.jpeg', '.jpg', '.png', '.svg'), case_sensitive=False); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
+(WithSuffix(suffix=('.gif', '.jpeg', '.jpg', '.png', '.svg'), case_sensitive=False); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
 
 
 
@@ -234,11 +234,11 @@ Sequence of Union of
 
 
 Optional[Union of
-- Path (PathType(path_type='file'); Predicate(func=))
+- Path (PathType(path_type='file'); Predicate(func=))
 - _internal.io.RelativeFilePath
 - _internal.url.HttpUrl
 
-(AfterValidator(_validate_md_suffix); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))]
+(AfterValidator(_validate_md_suffix); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))]
 
 
 
@@ -262,7 +262,7 @@ Union of
   - _internal.url.HttpUrl
   - Url (max_length=2083 allowed_schemes=['http', 'https'])
 
-  (AfterValidator(func=); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
+  (AfterValidator(wo_special_file_name); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
 - str (Len(min_length=1, max_length=2))
 - None
 
diff --git a/user_docs/collection_descr_v0-3.md b/user_docs/collection_descr_v0-3.md
index dff177ba1..44715cdba 100644
--- a/user_docs/collection_descr_v0-3.md
+++ b/user_docs/collection_descr_v0-3.md
@@ -218,10 +218,10 @@ The supported image formats are: ('.gif', '.jpeg', '.jpg', '.png', '.svg')
 
 Sequence of Union of
 - _internal.url.HttpUrl
-- Path (PathType(path_type='file'); Predicate(func=))
+- Path (PathType(path_type='file'); Predicate(func=))
 - _internal.io.RelativeFilePath
 
-(WithSuffix(suffix=('.gif', '.jpeg', '.jpg', '.png', '.svg'), case_sensitive=False); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
+(WithSuffix(suffix=('.gif', '.jpeg', '.jpg', '.png', '.svg'), case_sensitive=False); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
 
 
 
@@ -234,11 +234,11 @@ Sequence of Union of
 
 
 Optional[Union of
-- Path (PathType(path_type='file'); Predicate(func=))
+- Path (PathType(path_type='file'); Predicate(func=))
 - _internal.io.RelativeFilePath
 - _internal.url.HttpUrl
 
-(AfterValidator(_validate_md_suffix); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))]
+(AfterValidator(_validate_md_suffix); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))]
 
 
 
@@ -262,7 +262,7 @@ Union of
   - _internal.url.HttpUrl
   - Url (max_length=2083 allowed_schemes=['http', 'https'])
 
-  (AfterValidator(func=); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
+  (AfterValidator(wo_special_file_name); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
 - str (Len(min_length=1, max_length=2))
 - None
 
diff --git a/user_docs/dataset_descr_latest.md b/user_docs/dataset_descr_latest.md
index 8f17888a3..1762d0318 100644
--- a/user_docs/dataset_descr_latest.md
+++ b/user_docs/dataset_descr_latest.md
@@ -183,10 +183,10 @@ The supported image formats are: ('.gif', '.jpeg', '.jpg', '.png', '.svg')
 
 Sequence of Union of
 - _internal.url.HttpUrl
-- Path (PathType(path_type='file'); Predicate(func=))
+- Path (PathType(path_type='file'); Predicate(func=))
 - _internal.io.RelativeFilePath
 
-(WithSuffix(suffix=('.gif', '.jpeg', '.jpg', '.png', '.svg'), case_sensitive=False); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
+(WithSuffix(suffix=('.gif', '.jpeg', '.jpg', '.png', '.svg'), case_sensitive=False); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
 
 
 
@@ -199,11 +199,11 @@ Sequence of Union of
 
 
 Optional[Union of
-- Path (PathType(path_type='file'); Predicate(func=))
+- Path (PathType(path_type='file'); Predicate(func=))
 - _internal.io.RelativeFilePath
 - _internal.url.HttpUrl
 
-(AfterValidator(_validate_md_suffix); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))]
+(AfterValidator(_validate_md_suffix); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))]
 
 
 
@@ -227,7 +227,7 @@ Union of
   - _internal.url.HttpUrl
   - Url (max_length=2083 allowed_schemes=['http', 'https'])
 
-  (AfterValidator(func=); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
+  (AfterValidator(wo_special_file_name); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
 - str (Len(min_length=1, max_length=2))
 - None
 
diff --git a/user_docs/dataset_descr_v0-2-4.md b/user_docs/dataset_descr_v0-2-4.md
index 001d7f48f..7e8e87812 100644
--- a/user_docs/dataset_descr_v0-2-4.md
+++ b/user_docs/dataset_descr_v0-2-4.md
@@ -56,7 +56,7 @@ Sequence of Union of
 - _internal.url.HttpUrl
 - Url (max_length=2083 allowed_schemes=['http', 'https'])
 
-(AfterValidator(func=); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
+(AfterValidator(wo_special_file_name); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
 
 
 
@@ -173,10 +173,10 @@ The supported image formats are: ('.gif', '.jpeg', '.jpg', '.png', '.svg')
 
 Sequence of Union of
 - _internal.url.HttpUrl
-- Path (PathType(path_type='file'); Predicate(func=))
+- Path (PathType(path_type='file'); Predicate(func=))
 - _internal.io.RelativeFilePath
 
-(WithSuffix(suffix=('.gif', '.jpeg', '.jpg', '.png', '.svg'), case_sensitive=False); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
+(WithSuffix(suffix=('.gif', '.jpeg', '.jpg', '.png', '.svg'), case_sensitive=False); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
 
 
 
@@ -194,7 +194,7 @@ Optional[Union of
 - _internal.url.HttpUrl
 - Url (max_length=2083 allowed_schemes=['http', 'https'])
 
-(AfterValidator(func=); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))]
+(AfterValidator(wo_special_file_name); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))]
 
 
 
@@ -223,7 +223,7 @@ Union of
   - _internal.url.HttpUrl
   - Url (max_length=2083 allowed_schemes=['http', 'https'])
 
-  (AfterValidator(func=); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
+  (AfterValidator(wo_special_file_name); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
 - str (Len(min_length=1, max_length=2))
 - None
 
diff --git a/user_docs/dataset_descr_v0-2.md b/user_docs/dataset_descr_v0-2.md
index 001d7f48f..7e8e87812 100644
--- a/user_docs/dataset_descr_v0-2.md
+++ b/user_docs/dataset_descr_v0-2.md
@@ -56,7 +56,7 @@ Sequence of Union of
 - _internal.url.HttpUrl
 - Url (max_length=2083 allowed_schemes=['http', 'https'])
 
-(AfterValidator(func=); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
+(AfterValidator(wo_special_file_name); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
 
 
 
@@ -173,10 +173,10 @@ The supported image formats are: ('.gif', '.jpeg', '.jpg', '.png', '.svg')
 
 Sequence of Union of
 - _internal.url.HttpUrl
-- Path (PathType(path_type='file'); Predicate(func=))
+- Path (PathType(path_type='file'); Predicate(func=))
 - _internal.io.RelativeFilePath
 
-(WithSuffix(suffix=('.gif', '.jpeg', '.jpg', '.png', '.svg'), case_sensitive=False); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
+(WithSuffix(suffix=('.gif', '.jpeg', '.jpg', '.png', '.svg'), case_sensitive=False); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
 
 
 
@@ -194,7 +194,7 @@ Optional[Union of
 - _internal.url.HttpUrl
 - Url (max_length=2083 allowed_schemes=['http', 'https'])
 
-(AfterValidator(func=); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))]
+(AfterValidator(wo_special_file_name); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))]
 
 
 
@@ -223,7 +223,7 @@ Union of
   - _internal.url.HttpUrl
   - Url (max_length=2083 allowed_schemes=['http', 'https'])
 
-  (AfterValidator(func=); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
+  (AfterValidator(wo_special_file_name); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
 - str (Len(min_length=1, max_length=2))
 - None
 
diff --git a/user_docs/dataset_descr_v0-3-0.md b/user_docs/dataset_descr_v0-3-0.md
index 8f17888a3..1762d0318 100644
--- a/user_docs/dataset_descr_v0-3-0.md
+++ b/user_docs/dataset_descr_v0-3-0.md
@@ -183,10 +183,10 @@ The supported image formats are: ('.gif', '.jpeg', '.jpg', '.png', '.svg')
 
 Sequence of Union of
 - _internal.url.HttpUrl
-- Path (PathType(path_type='file'); Predicate(func=))
+- Path (PathType(path_type='file'); Predicate(func=))
 - _internal.io.RelativeFilePath
 
-(WithSuffix(suffix=('.gif', '.jpeg', '.jpg', '.png', '.svg'), case_sensitive=False); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
+(WithSuffix(suffix=('.gif', '.jpeg', '.jpg', '.png', '.svg'), case_sensitive=False); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
 
 
 
@@ -199,11 +199,11 @@ Sequence of Union of
 
 
 Optional[Union of
-- Path (PathType(path_type='file'); Predicate(func=))
+- Path (PathType(path_type='file'); Predicate(func=))
 - _internal.io.RelativeFilePath
 - _internal.url.HttpUrl
 
-(AfterValidator(_validate_md_suffix); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))]
+(AfterValidator(_validate_md_suffix); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))]
 
 
 
@@ -227,7 +227,7 @@ Union of
   - _internal.url.HttpUrl
   - Url (max_length=2083 allowed_schemes=['http', 'https'])
 
-  (AfterValidator(func=); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
+  (AfterValidator(wo_special_file_name); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
 - str (Len(min_length=1, max_length=2))
 - None
 
diff --git a/user_docs/dataset_descr_v0-3.md b/user_docs/dataset_descr_v0-3.md
index 8f17888a3..1762d0318 100644
--- a/user_docs/dataset_descr_v0-3.md
+++ b/user_docs/dataset_descr_v0-3.md
@@ -183,10 +183,10 @@ The supported image formats are: ('.gif', '.jpeg', '.jpg', '.png', '.svg')
 
 Sequence of Union of
 - _internal.url.HttpUrl
-- Path (PathType(path_type='file'); Predicate(func=))
+- Path (PathType(path_type='file'); Predicate(func=))
 - _internal.io.RelativeFilePath
 
-(WithSuffix(suffix=('.gif', '.jpeg', '.jpg', '.png', '.svg'), case_sensitive=False); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
+(WithSuffix(suffix=('.gif', '.jpeg', '.jpg', '.png', '.svg'), case_sensitive=False); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
 
 
 
@@ -199,11 +199,11 @@ Sequence of Union of
 
 
 Optional[Union of
-- Path (PathType(path_type='file'); Predicate(func=))
+- Path (PathType(path_type='file'); Predicate(func=))
 - _internal.io.RelativeFilePath
 - _internal.url.HttpUrl
 
-(AfterValidator(_validate_md_suffix); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))]
+(AfterValidator(_validate_md_suffix); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))]
 
 
 
@@ -227,7 +227,7 @@ Union of
   - _internal.url.HttpUrl
   - Url (max_length=2083 allowed_schemes=['http', 'https'])
 
-  (AfterValidator(func=); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
+  (AfterValidator(wo_special_file_name); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
 - str (Len(min_length=1, max_length=2))
 - None
 
diff --git a/user_docs/generic_descr_latest.md b/user_docs/generic_descr_latest.md
index 5c544a589..21d08d078 100644
--- a/user_docs/generic_descr_latest.md
+++ b/user_docs/generic_descr_latest.md
@@ -186,10 +186,10 @@ The supported image formats are: ('.gif', '.jpeg', '.jpg', '.png', '.svg')
 
 Sequence of Union of
 - _internal.url.HttpUrl
-- Path (PathType(path_type='file'); Predicate(func=))
+- Path (PathType(path_type='file'); Predicate(func=))
 - _internal.io.RelativeFilePath
 
-(WithSuffix(suffix=('.gif', '.jpeg', '.jpg', '.png', '.svg'), case_sensitive=False); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
+(WithSuffix(suffix=('.gif', '.jpeg', '.jpg', '.png', '.svg'), case_sensitive=False); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
 
 
 
@@ -202,11 +202,11 @@ Sequence of Union of
 
 
 Optional[Union of
-- Path (PathType(path_type='file'); Predicate(func=))
+- Path (PathType(path_type='file'); Predicate(func=))
 - _internal.io.RelativeFilePath
 - _internal.url.HttpUrl
 
-(AfterValidator(_validate_md_suffix); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))]
+(AfterValidator(_validate_md_suffix); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))]
 
 
 
@@ -230,7 +230,7 @@ Union of
   - _internal.url.HttpUrl
   - Url (max_length=2083 allowed_schemes=['http', 'https'])
 
-  (AfterValidator(func=); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
+  (AfterValidator(wo_special_file_name); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
 - str (Len(min_length=1, max_length=2))
 - None
 
diff --git a/user_docs/generic_descr_v0-2-4.md b/user_docs/generic_descr_v0-2-4.md
index 03bb506b7..489202140 100644
--- a/user_docs/generic_descr_v0-2-4.md
+++ b/user_docs/generic_descr_v0-2-4.md
@@ -59,7 +59,7 @@ Sequence of Union of
 - _internal.url.HttpUrl
 - Url (max_length=2083 allowed_schemes=['http', 'https'])
 
-(AfterValidator(func=); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
+(AfterValidator(wo_special_file_name); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
 
 
 
@@ -176,10 +176,10 @@ The supported image formats are: ('.gif', '.jpeg', '.jpg', '.png', '.svg')
 
 Sequence of Union of
 - _internal.url.HttpUrl
-- Path (PathType(path_type='file'); Predicate(func=))
+- Path (PathType(path_type='file'); Predicate(func=))
 - _internal.io.RelativeFilePath
 
-(WithSuffix(suffix=('.gif', '.jpeg', '.jpg', '.png', '.svg'), case_sensitive=False); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
+(WithSuffix(suffix=('.gif', '.jpeg', '.jpg', '.png', '.svg'), case_sensitive=False); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
 
 
 
@@ -197,7 +197,7 @@ Optional[Union of
 - _internal.url.HttpUrl
 - Url (max_length=2083 allowed_schemes=['http', 'https'])
 
-(AfterValidator(func=); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))]
+(AfterValidator(wo_special_file_name); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))]
 
 
 
@@ -226,7 +226,7 @@ Union of
   - _internal.url.HttpUrl
   - Url (max_length=2083 allowed_schemes=['http', 'https'])
 
-  (AfterValidator(func=); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
+  (AfterValidator(wo_special_file_name); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
 - str (Len(min_length=1, max_length=2))
 - None
 
diff --git a/user_docs/generic_descr_v0-2.md b/user_docs/generic_descr_v0-2.md
index 03bb506b7..489202140 100644
--- a/user_docs/generic_descr_v0-2.md
+++ b/user_docs/generic_descr_v0-2.md
@@ -59,7 +59,7 @@ Sequence of Union of
 - _internal.url.HttpUrl
 - Url (max_length=2083 allowed_schemes=['http', 'https'])
 
-(AfterValidator(func=); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
+(AfterValidator(wo_special_file_name); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
 
 
 
@@ -176,10 +176,10 @@ The supported image formats are: ('.gif', '.jpeg', '.jpg', '.png', '.svg')
 
 Sequence of Union of
 - _internal.url.HttpUrl
-- Path (PathType(path_type='file'); Predicate(func=))
+- Path (PathType(path_type='file'); Predicate(func=))
 - _internal.io.RelativeFilePath
 
-(WithSuffix(suffix=('.gif', '.jpeg', '.jpg', '.png', '.svg'), case_sensitive=False); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
+(WithSuffix(suffix=('.gif', '.jpeg', '.jpg', '.png', '.svg'), case_sensitive=False); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
 
 
 
@@ -197,7 +197,7 @@ Optional[Union of
 - _internal.url.HttpUrl
 - Url (max_length=2083 allowed_schemes=['http', 'https'])
 
-(AfterValidator(func=); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))]
+(AfterValidator(wo_special_file_name); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))]
 
 
 
@@ -226,7 +226,7 @@ Union of
   - _internal.url.HttpUrl
   - Url (max_length=2083 allowed_schemes=['http', 'https'])
 
-  (AfterValidator(func=); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
+  (AfterValidator(wo_special_file_name); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
 - str (Len(min_length=1, max_length=2))
 - None
 
diff --git a/user_docs/generic_descr_v0-3-0.md b/user_docs/generic_descr_v0-3-0.md
index 5c544a589..21d08d078 100644
--- a/user_docs/generic_descr_v0-3-0.md
+++ b/user_docs/generic_descr_v0-3-0.md
@@ -186,10 +186,10 @@ The supported image formats are: ('.gif', '.jpeg', '.jpg', '.png', '.svg')
 
 Sequence of Union of
 - _internal.url.HttpUrl
-- Path (PathType(path_type='file'); Predicate(func=))
+- Path (PathType(path_type='file'); Predicate(func=))
 - _internal.io.RelativeFilePath
 
-(WithSuffix(suffix=('.gif', '.jpeg', '.jpg', '.png', '.svg'), case_sensitive=False); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
+(WithSuffix(suffix=('.gif', '.jpeg', '.jpg', '.png', '.svg'), case_sensitive=False); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
 
 
 
@@ -202,11 +202,11 @@ Sequence of Union of
 
 
 Optional[Union of
-- Path (PathType(path_type='file'); Predicate(func=))
+- Path (PathType(path_type='file'); Predicate(func=))
 - _internal.io.RelativeFilePath
 - _internal.url.HttpUrl
 
-(AfterValidator(_validate_md_suffix); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))]
+(AfterValidator(_validate_md_suffix); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))]
 
 
 
@@ -230,7 +230,7 @@ Union of
   - _internal.url.HttpUrl
   - Url (max_length=2083 allowed_schemes=['http', 'https'])
 
-  (AfterValidator(func=); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
+  (AfterValidator(wo_special_file_name); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
 - str (Len(min_length=1, max_length=2))
 - None
 
diff --git a/user_docs/generic_descr_v0-3.md b/user_docs/generic_descr_v0-3.md
index 5c544a589..21d08d078 100644
--- a/user_docs/generic_descr_v0-3.md
+++ b/user_docs/generic_descr_v0-3.md
@@ -186,10 +186,10 @@ The supported image formats are: ('.gif', '.jpeg', '.jpg', '.png', '.svg')
 
 Sequence of Union of
 - _internal.url.HttpUrl
-- Path (PathType(path_type='file'); Predicate(func=))
+- Path (PathType(path_type='file'); Predicate(func=))
 - _internal.io.RelativeFilePath
 
-(WithSuffix(suffix=('.gif', '.jpeg', '.jpg', '.png', '.svg'), case_sensitive=False); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
+(WithSuffix(suffix=('.gif', '.jpeg', '.jpg', '.png', '.svg'), case_sensitive=False); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
 
 
 
@@ -202,11 +202,11 @@ Sequence of Union of
 
 
 Optional[Union of
-- Path (PathType(path_type='file'); Predicate(func=))
+- Path (PathType(path_type='file'); Predicate(func=))
 - _internal.io.RelativeFilePath
 - _internal.url.HttpUrl
 
-(AfterValidator(_validate_md_suffix); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))]
+(AfterValidator(_validate_md_suffix); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))]
 
 
 
@@ -230,7 +230,7 @@ Union of
   - _internal.url.HttpUrl
   - Url (max_length=2083 allowed_schemes=['http', 'https'])
 
-  (AfterValidator(func=); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
+  (AfterValidator(wo_special_file_name); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
 - str (Len(min_length=1, max_length=2))
 - None
 
diff --git a/user_docs/model_descr_latest.md b/user_docs/model_descr_latest.md
index 4ac88e35f..38810c17a 100644
--- a/user_docs/model_descr_latest.md
+++ b/user_docs/model_descr_latest.md
@@ -103,7 +103,7 @@ Optional[_internal.validated_string.ValidatedString[Annotated[str, StringConstra
 
 
 Union of
-- Path (PathType(path_type='file'); Predicate(func=))
+- Path (PathType(path_type='file'); Predicate(func=))
 - _internal.io.RelativeFilePath
 - _internal.url.HttpUrl
 
@@ -145,16 +145,10 @@ _internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator
 Sequence[typing.Annotated[typing.Union[bioimageio.spec.model.v0_5.BatchAxis, bioimageio.spec.model.v0_5.ChannelAxis, bioimageio.spec.model.v0_5.IndexAxis, bioimageio.spec.model.v0_5.TimeInputAxis, bioimageio.spec.model.v0_5.SpaceInputAxis], FieldInfo(annotation=NoneType, required=True, discriminator='type')]]
 
 **BatchAxis:**
-#### `inputs.axes.id` _internal.validated_string.Valid ≝ `batch`
+#### `inputs.axes.id` AxisId ≝ `batch`
 
 
-
    _internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]
 
-
-
-_internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]
-
-
    
 
 #### `inputs.axes.description` str ≝ ``
 
@@ -172,16 +166,10 @@ _internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator
 
 
 **ChannelAxis:**
-#### `inputs.axes.id` _internal.validated_string.Valid ≝ `channel`
+#### `inputs.axes.id` AxisId ≝ `channel`
 
 
-
    _internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]
 
-
-
-_internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]
-
-
    
 
 #### `inputs.axes.description` str ≝ ``
 
@@ -200,16 +188,10 @@ _internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator
 Sequence[_internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator]]]
 
 **IndexAxis:**
-#### `inputs.axes.id` _internal.validated_string.Valid ≝ `index`
-
+#### `inputs.axes.id` AxisId ≝ `index`
 
-
    _internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]
 
-
 
-_internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]
-
-
    
 
 #### `inputs.axes.description` str ≝ ``
 
@@ -248,16 +230,10 @@ _internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator
 
 
 
-##### `inputs.axes.size.axis_id` _internal.validated_string.Valid
-
-
-
    _internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]
+##### `inputs.axes.size.axis_id` AxisId
 
-
 
-_internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]
 
-
    
 
 ##### `inputs.axes.size.offset` int ≝ `0`
 
@@ -272,16 +248,10 @@ _internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator
 
 
 **TimeInputAxis:**
-#### `inputs.axes.id` _internal.validated_string.Valid ≝ `time`
-
+#### `inputs.axes.id` AxisId ≝ `time`
 
-
    _internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]
-
-
 
-_internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]
 
-
    
 
 #### `inputs.axes.description` str ≝ ``
 
@@ -320,16 +290,10 @@ _internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator
 
 
 
-##### `inputs.axes.size.axis_id` _internal.validated_string.Valid
-
-
-
    _internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]
+##### `inputs.axes.size.axis_id` AxisId
 
-
 
-_internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]
 
-
    
 
 ##### `inputs.axes.size.offset` int ≝ `0`
 
@@ -384,17 +348,11 @@ Optional[Literal of
 
 
 **SpaceInputAxis:**
-#### `inputs.axes.id` _internal.validated_string.Valid ≝ `x`
+#### `inputs.axes.id` AxisId ≝ `x`
 
 [*Examples:*](#inputsaxesid) ['x', 'y', 'z']
 
-
    _internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]
 
-
-
-_internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]
-
-
    
 
 #### `inputs.axes.description` str ≝ ``
 
@@ -433,16 +391,10 @@ _internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator
 
 
 
-##### `inputs.axes.size.axis_id` _internal.validated_string.Valid
+##### `inputs.axes.size.axis_id` AxisId
 
 
-
    _internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]
-
-
-
-_internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]
 
-
    
 
 ##### `inputs.axes.size.offset` int ≝ `0`
 
@@ -844,14 +796,8 @@ Sequence of Union of
 
 [*Example:*](#inputspreprocessingikwargsaxis) 'channel'
 
-
    Optional[_internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]*]
-
-
 
-Optional[_internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]
-(Predicate(func= at 0x7f3030c36160>))]
-
-
    
+Optional[AxisId (Predicate(func= at 0x7bb25d470ea0>))]
 
 ##### `inputs.preprocessing.i.kwargs.gain` Union ≝ `1.0`
 
@@ -907,14 +853,8 @@ Union[float (Ge(ge=1e-06)), Sequence[float (Ge(ge=1e-06))] (MinLen(min_length=1)
 
 [*Examples:*](#inputspreprocessingikwargsaxis) ['channel', 'index']
 
-
    Optional[_internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]*]
-
-
-
-Optional[_internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]
-(Predicate(func= at 0x7f3030c36160>))]
 
-
    
+Optional[AxisId (Predicate(func= at 0x7bb25d470ea0>))]
 
 
 
@@ -937,13 +877,8 @@ Optional[_internal.validated_string.ValidatedString[Annotated[str, MinLen, After
 
 [*Example:*](#inputspreprocessingikwargsaxes) ('batch', 'x', 'y')
 
-
    Optional[Sequence[bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]]]
-
-
-
-Optional[Sequence[bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]]]
 
-
    
+Optional[Sequence[bioimageio.spec.model.v0_5.AxisId]]
 
 ##### `inputs.preprocessing.i.kwargs.eps` float ≝ `1e-06`
 
@@ -971,13 +906,8 @@ Optional[Sequence[bioimageio.spec._internal.validated_string.ValidatedString[Ann
 
 [*Example:*](#inputspreprocessingikwargsaxes) ('batch', 'x', 'y')
 
-
    Optional[Sequence[bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]]]
-
-
-
-Optional[Sequence[bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]]]
 
-
    
+Optional[Sequence[bioimageio.spec.model.v0_5.AxisId]]
 
 ##### `inputs.preprocessing.i.kwargs.min_percentile` float ≝ `0.0`
 
@@ -1058,16 +988,10 @@ _internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator
 Sequence[typing.Annotated[typing.Union[bioimageio.spec.model.v0_5.BatchAxis, bioimageio.spec.model.v0_5.ChannelAxis, bioimageio.spec.model.v0_5.IndexAxis, bioimageio.spec.model.v0_5.TimeOutputAxis, bioimageio.spec.model.v0_5.SpaceOutputAxis], FieldInfo(annotation=NoneType, required=True, discriminator='type')]]
 
 **BatchAxis:**
-#### `outputs.axes.id` _internal.validated_string.Valid ≝ `batch`
-
-
-
    _internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]
+#### `outputs.axes.id` AxisId ≝ `batch`
 
-
 
-_internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]
 
-
    
 
 #### `outputs.axes.description` str ≝ ``
 
@@ -1085,16 +1009,10 @@ _internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator
 
 
 **ChannelAxis:**
-#### `outputs.axes.id` _internal.validated_string.Valid ≝ `channel`
+#### `outputs.axes.id` AxisId ≝ `channel`
 
 
-
    _internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]
 
-
-
-_internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]
-
-
    
 
 #### `outputs.axes.description` str ≝ ``
 
@@ -1113,16 +1031,10 @@ _internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator
 Sequence[_internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator]]]
 
 **IndexAxis:**
-#### `outputs.axes.id` _internal.validated_string.Valid ≝ `index`
-
-
-
    _internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]
+#### `outputs.axes.id` AxisId ≝ `index`
 
-
 
-_internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]
 
-
    
 
 #### `outputs.axes.description` str ≝ ``
 
@@ -1161,16 +1073,10 @@ _internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator
 
 
 
-##### `outputs.axes.size.axis_id` _internal.validated_string.Valid
+##### `outputs.axes.size.axis_id` AxisId
 
 
-
    _internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]
 
-
-
-_internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]
-
-
    
 
 ##### `outputs.axes.size.offset` int ≝ `0`
 
@@ -1190,16 +1096,10 @@ _internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator
 
 
 
-#### `outputs.axes.id` _internal.validated_string.Valid ≝ `time`
-
-
-
    _internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]
+#### `outputs.axes.id` AxisId ≝ `time`
 
-
 
-_internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]
 
-
    
 
 #### `outputs.axes.description` str ≝ ``
 
@@ -1238,16 +1138,10 @@ _internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator
 
 
 
-##### `outputs.axes.size.axis_id` _internal.validated_string.Valid
-
+##### `outputs.axes.size.axis_id` AxisId
 
-
    _internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]
-
-
 
-_internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]
 
-
    
 
 ##### `outputs.axes.size.offset` int ≝ `0`
 
@@ -1307,17 +1201,11 @@ Optional[Literal of
 
 
 
-#### `outputs.axes.id` _internal.validated_string.Valid ≝ `x`
+#### `outputs.axes.id` AxisId ≝ `x`
 
 [*Examples:*](#outputsaxesid) ['x', 'y', 'z']
 
-
    _internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]
 
-
-
-_internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]
-
-
    
 
 #### `outputs.axes.description` str ≝ ``
 
@@ -1356,16 +1244,10 @@ _internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator
 
 
 
-##### `outputs.axes.size.axis_id` _internal.validated_string.Valid
+##### `outputs.axes.size.axis_id` AxisId
 
 
-
    _internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]
 
-
-
-_internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]
-
-
    
 
 ##### `outputs.axes.size.offset` int ≝ `0`
 
@@ -1768,14 +1650,8 @@ Sequence of Union of
 
 [*Example:*](#outputspostprocessingikwargsaxis) 'channel'
 
-
    Optional[_internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]*]
 
-
-
-Optional[_internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]
-(Predicate(func= at 0x7f3030c36160>))]
-
-
    
+Optional[AxisId (Predicate(func= at 0x7bb25d470ea0>))]
 
 ##### `outputs.postprocessing.i.kwargs.gain` Union ≝ `1.0`
 
@@ -1831,14 +1707,8 @@ Union[float (Ge(ge=1e-06)), Sequence[float (Ge(ge=1e-06))] (MinLen(min_length=1)
 
 [*Examples:*](#outputspostprocessingikwargsaxis) ['channel', 'index']
 
-
    Optional[_internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]*]
 
-
-
-Optional[_internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]
-(Predicate(func= at 0x7f3030c36160>))]
-
-
    
+Optional[AxisId (Predicate(func= at 0x7bb25d470ea0>))]
 
 
 
@@ -1861,13 +1731,8 @@ Optional[_internal.validated_string.ValidatedString[Annotated[str, MinLen, After
 
 [*Example:*](#outputspostprocessingikwargsaxes) ('batch', 'x', 'y')
 
-
    Optional[Sequence[bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]]]
 
-
-
-Optional[Sequence[bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]]]
-
-
    
+Optional[Sequence[bioimageio.spec.model.v0_5.AxisId]]
 
 ##### `outputs.postprocessing.i.kwargs.eps` float ≝ `1e-06`
 
@@ -1895,13 +1760,8 @@ Optional[Sequence[bioimageio.spec._internal.validated_string.ValidatedString[Ann
 
 [*Example:*](#outputspostprocessingikwargsaxes) ('batch', 'x', 'y')
 
-
    Optional[Sequence[bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]]]
 
-
-
-Optional[Sequence[bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]]]
-
-
    
+Optional[Sequence[bioimageio.spec.model.v0_5.AxisId]]
 
 ##### `outputs.postprocessing.i.kwargs.min_percentile` float ≝ `0.0`
 
@@ -1961,13 +1821,8 @@ _internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator
 
 [*Example:*](#outputspostprocessingikwargsaxes) ('batch', 'x', 'y')
 
-
    Optional[Sequence[bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]]]
 
-
-
-Optional[Sequence[bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]]]
-
-
    
+Optional[Sequence[bioimageio.spec.model.v0_5.AxisId]]
 
 ##### `outputs.postprocessing.i.kwargs.eps` float ≝ `1e-06`
 
@@ -2659,10 +2514,10 @@ The supported image formats are: ('.gif', '.jpeg', '.jpg', '.png', '.svg')
 
 Sequence of Union of
 - _internal.url.HttpUrl
-- Path (PathType(path_type='file'); Predicate(func=))
+- Path (PathType(path_type='file'); Predicate(func=))
 - _internal.io.RelativeFilePath
 
-(WithSuffix(suffix=('.gif', '.jpeg', '.jpg', '.png', '.svg'), case_sensitive=False); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
+(WithSuffix(suffix=('.gif', '.jpeg', '.jpg', '.png', '.svg'), case_sensitive=False); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
 
 
 
@@ -2686,7 +2541,7 @@ Union of
   - _internal.url.HttpUrl
   - Url (max_length=2083 allowed_schemes=['http', 'https'])
 
-  (AfterValidator(func=); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
+  (AfterValidator(wo_special_file_name); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
 - str (Len(min_length=1, max_length=2))
 - None
 
@@ -2837,7 +2692,7 @@ _internal.validated_string.ValidatedString[Annotated[str, MinLen, Annotated[Type
 
 
 
-## `timestamp` _internal.types.Datetime ≝ `root=datetime.datetime(2024, 3, 13, 14, 32, 39, 909186)`
+## `timestamp` _internal.types.Datetime ≝ `root=datetime.datetime(2024, 3, 14, 14, 46, 38, 123308)`
 
 
 
@@ -2883,10 +2738,10 @@ The supported image formats are: ('.gif', '.jpeg', '.jpg', '.png', '.svg')
 
 Sequence of Union of
 - _internal.url.HttpUrl
-- Path (PathType(path_type='file'); Predicate(func=))
+- Path (PathType(path_type='file'); Predicate(func=))
 - _internal.io.RelativeFilePath
 
-(WithSuffix(suffix=('.gif', '.jpeg', '.jpg', '.png', '.svg'), case_sensitive=False); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
+(WithSuffix(suffix=('.gif', '.jpeg', '.jpg', '.png', '.svg'), case_sensitive=False); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
 
 
 
@@ -3026,7 +2881,7 @@ Union of
   - _internal.url.HttpUrl
   - Url (max_length=2083 allowed_schemes=['http', 'https'])
 
-  (AfterValidator(func=); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
+  (AfterValidator(wo_special_file_name); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
 - str (Len(min_length=1, max_length=2))
 - None
 
@@ -3131,11 +2986,11 @@ Optional[_internal.version_type.Version]
 
 
 Optional[Union of
-- Path (PathType(path_type='file'); Predicate(func=))
+- Path (PathType(path_type='file'); Predicate(func=))
 - _internal.io.RelativeFilePath
 - _internal.url.HttpUrl
 
-(AfterValidator(_validate_md_suffix); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))]
+(AfterValidator(_validate_md_suffix); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))]
 
 
 
diff --git a/user_docs/model_descr_v0-4-10.md b/user_docs/model_descr_v0-4-10.md
index b70e7b600..8580f0801 100644
--- a/user_docs/model_descr_v0-4-10.md
+++ b/user_docs/model_descr_v0-4-10.md
@@ -716,7 +716,7 @@ Sequence of Union of
 - _internal.url.HttpUrl
 - Url (max_length=2083 allowed_schemes=['http', 'https'])
 
-(AfterValidator(func=); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'); WithSuffix(suffix='.npy', case_sensitive=True))
+(AfterValidator(wo_special_file_name); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'); WithSuffix(suffix='.npy', case_sensitive=True))
 
 
 
@@ -733,7 +733,7 @@ Sequence of Union of
 - _internal.url.HttpUrl
 - Url (max_length=2083 allowed_schemes=['http', 'https'])
 
-(AfterValidator(func=); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'); WithSuffix(suffix='.npy', case_sensitive=True))
+(AfterValidator(wo_special_file_name); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'); WithSuffix(suffix='.npy', case_sensitive=True))
 
 
 
@@ -803,7 +803,7 @@ Sequence of Union of
 - _internal.url.HttpUrl
 - Url (max_length=2083 allowed_schemes=['http', 'https'])
 
-(AfterValidator(func=); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
+(AfterValidator(wo_special_file_name); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
 
 
 
@@ -920,7 +920,7 @@ Sequence of Union of
 - _internal.url.HttpUrl
 - Url (max_length=2083 allowed_schemes=['http', 'https'])
 
-(AfterValidator(func=); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
+(AfterValidator(wo_special_file_name); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
 
 
 
@@ -1036,7 +1036,7 @@ Sequence of Union of
 - _internal.url.HttpUrl
 - Url (max_length=2083 allowed_schemes=['http', 'https'])
 
-(AfterValidator(func=); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
+(AfterValidator(wo_special_file_name); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
 
 
 
@@ -1174,7 +1174,7 @@ Sequence of Union of
 - _internal.url.HttpUrl
 - Url (max_length=2083 allowed_schemes=['http', 'https'])
 
-(AfterValidator(func=); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
+(AfterValidator(wo_special_file_name); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
 
 
 
@@ -1291,7 +1291,7 @@ Sequence of Union of
 - _internal.url.HttpUrl
 - Url (max_length=2083 allowed_schemes=['http', 'https'])
 
-(AfterValidator(func=); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
+(AfterValidator(wo_special_file_name); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
 
 
 
@@ -1408,7 +1408,7 @@ Sequence of Union of
 - _internal.url.HttpUrl
 - Url (max_length=2083 allowed_schemes=['http', 'https'])
 
-(AfterValidator(func=); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
+(AfterValidator(wo_special_file_name); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
 
 
 
@@ -1497,7 +1497,7 @@ Sequence of Union of
 - _internal.url.HttpUrl
 - Url (max_length=2083 allowed_schemes=['http', 'https'])
 
-(AfterValidator(func=); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
+(AfterValidator(wo_special_file_name); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
 
 
 
@@ -1547,10 +1547,10 @@ The supported image formats are: ('.gif', '.jpeg', '.jpg', '.png', '.svg')
 
 Sequence of Union of
 - _internal.url.HttpUrl
-- Path (PathType(path_type='file'); Predicate(func=))
+- Path (PathType(path_type='file'); Predicate(func=))
 - _internal.io.RelativeFilePath
 
-(WithSuffix(suffix=('.gif', '.jpeg', '.jpg', '.png', '.svg'), case_sensitive=False); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
+(WithSuffix(suffix=('.gif', '.jpeg', '.jpg', '.png', '.svg'), case_sensitive=False); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
 
 
 
@@ -1579,7 +1579,7 @@ Union of
   - _internal.url.HttpUrl
   - Url (max_length=2083 allowed_schemes=['http', 'https'])
 
-  (AfterValidator(func=); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
+  (AfterValidator(wo_special_file_name); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
 - str (Len(min_length=1, max_length=2))
 - None
 
@@ -1754,7 +1754,7 @@ Sequence of Union of
 - _internal.url.HttpUrl
 - Url (max_length=2083 allowed_schemes=['http', 'https'])
 
-(AfterValidator(func=); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
+(AfterValidator(wo_special_file_name); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
 
 
 
@@ -1771,7 +1771,7 @@ Sequence of Union of
 - _internal.url.HttpUrl
 - Url (max_length=2083 allowed_schemes=['http', 'https'])
 
-(AfterValidator(func=); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
+(AfterValidator(wo_special_file_name); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
 
 
 
@@ -1823,10 +1823,10 @@ The supported image formats are: ('.gif', '.jpeg', '.jpg', '.png', '.svg')
 
 Sequence of Union of
 - _internal.url.HttpUrl
-- Path (PathType(path_type='file'); Predicate(func=))
+- Path (PathType(path_type='file'); Predicate(func=))
 - _internal.io.RelativeFilePath
 
-(WithSuffix(suffix=('.gif', '.jpeg', '.jpg', '.png', '.svg'), case_sensitive=False); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
+(WithSuffix(suffix=('.gif', '.jpeg', '.jpg', '.png', '.svg'), case_sensitive=False); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
 
 
 
@@ -1896,7 +1896,7 @@ Sequence of Union of
 - _internal.url.HttpUrl
 - Url (max_length=2083 allowed_schemes=['http', 'https'])
 
-(AfterValidator(func=); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
+(AfterValidator(wo_special_file_name); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
 
 
 
@@ -1960,7 +1960,7 @@ Union of
   - _internal.url.HttpUrl
   - Url (max_length=2083 allowed_schemes=['http', 'https'])
 
-  (AfterValidator(func=); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
+  (AfterValidator(wo_special_file_name); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
 - str (Len(min_length=1, max_length=2))
 - None
 
@@ -2116,7 +2116,7 @@ Optional[Union of
 - _internal.url.HttpUrl
 - Url (max_length=2083 allowed_schemes=['http', 'https'])
 
-(AfterValidator(func=); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))]
+(AfterValidator(wo_special_file_name); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))]
 
 
 
diff --git a/user_docs/model_descr_v0-4.md b/user_docs/model_descr_v0-4.md
index b70e7b600..8580f0801 100644
--- a/user_docs/model_descr_v0-4.md
+++ b/user_docs/model_descr_v0-4.md
@@ -716,7 +716,7 @@ Sequence of Union of
 - _internal.url.HttpUrl
 - Url (max_length=2083 allowed_schemes=['http', 'https'])
 
-(AfterValidator(func=); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'); WithSuffix(suffix='.npy', case_sensitive=True))
+(AfterValidator(wo_special_file_name); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'); WithSuffix(suffix='.npy', case_sensitive=True))
 
 
 
@@ -733,7 +733,7 @@ Sequence of Union of
 - _internal.url.HttpUrl
 - Url (max_length=2083 allowed_schemes=['http', 'https'])
 
-(AfterValidator(func=); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'); WithSuffix(suffix='.npy', case_sensitive=True))
+(AfterValidator(wo_special_file_name); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'); WithSuffix(suffix='.npy', case_sensitive=True))
 
 
 
@@ -803,7 +803,7 @@ Sequence of Union of
 - _internal.url.HttpUrl
 - Url (max_length=2083 allowed_schemes=['http', 'https'])
 
-(AfterValidator(func=); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
+(AfterValidator(wo_special_file_name); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
 
 
 
@@ -920,7 +920,7 @@ Sequence of Union of
 - _internal.url.HttpUrl
 - Url (max_length=2083 allowed_schemes=['http', 'https'])
 
-(AfterValidator(func=); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
+(AfterValidator(wo_special_file_name); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
 
 
 
@@ -1036,7 +1036,7 @@ Sequence of Union of
 - _internal.url.HttpUrl
 - Url (max_length=2083 allowed_schemes=['http', 'https'])
 
-(AfterValidator(func=); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
+(AfterValidator(wo_special_file_name); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
 
 
 
@@ -1174,7 +1174,7 @@ Sequence of Union of
 - _internal.url.HttpUrl
 - Url (max_length=2083 allowed_schemes=['http', 'https'])
 
-(AfterValidator(func=); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
+(AfterValidator(wo_special_file_name); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
 
 
 
@@ -1291,7 +1291,7 @@ Sequence of Union of
 - _internal.url.HttpUrl
 - Url (max_length=2083 allowed_schemes=['http', 'https'])
 
-(AfterValidator(func=); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
+(AfterValidator(wo_special_file_name); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
 
 
 
@@ -1408,7 +1408,7 @@ Sequence of Union of
 - _internal.url.HttpUrl
 - Url (max_length=2083 allowed_schemes=['http', 'https'])
 
-(AfterValidator(func=); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
+(AfterValidator(wo_special_file_name); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
 
 
 
@@ -1497,7 +1497,7 @@ Sequence of Union of
 - _internal.url.HttpUrl
 - Url (max_length=2083 allowed_schemes=['http', 'https'])
 
-(AfterValidator(func=); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
+(AfterValidator(wo_special_file_name); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
 
 
 
@@ -1547,10 +1547,10 @@ The supported image formats are: ('.gif', '.jpeg', '.jpg', '.png', '.svg')
 
 Sequence of Union of
 - _internal.url.HttpUrl
-- Path (PathType(path_type='file'); Predicate(func=))
+- Path (PathType(path_type='file'); Predicate(func=))
 - _internal.io.RelativeFilePath
 
-(WithSuffix(suffix=('.gif', '.jpeg', '.jpg', '.png', '.svg'), case_sensitive=False); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
+(WithSuffix(suffix=('.gif', '.jpeg', '.jpg', '.png', '.svg'), case_sensitive=False); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
 
 
 
@@ -1579,7 +1579,7 @@ Union of
   - _internal.url.HttpUrl
   - Url (max_length=2083 allowed_schemes=['http', 'https'])
 
-  (AfterValidator(func=); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
+  (AfterValidator(wo_special_file_name); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
 - str (Len(min_length=1, max_length=2))
 - None
 
@@ -1754,7 +1754,7 @@ Sequence of Union of
 - _internal.url.HttpUrl
 - Url (max_length=2083 allowed_schemes=['http', 'https'])
 
-(AfterValidator(func=); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
+(AfterValidator(wo_special_file_name); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
 
 
 
@@ -1771,7 +1771,7 @@ Sequence of Union of
 - _internal.url.HttpUrl
 - Url (max_length=2083 allowed_schemes=['http', 'https'])
 
-(AfterValidator(func=); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
+(AfterValidator(wo_special_file_name); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
 
 
 
@@ -1823,10 +1823,10 @@ The supported image formats are: ('.gif', '.jpeg', '.jpg', '.png', '.svg')
 
 Sequence of Union of
 - _internal.url.HttpUrl
-- Path (PathType(path_type='file'); Predicate(func=))
+- Path (PathType(path_type='file'); Predicate(func=))
 - _internal.io.RelativeFilePath
 
-(WithSuffix(suffix=('.gif', '.jpeg', '.jpg', '.png', '.svg'), case_sensitive=False); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
+(WithSuffix(suffix=('.gif', '.jpeg', '.jpg', '.png', '.svg'), case_sensitive=False); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
 
 
 
@@ -1896,7 +1896,7 @@ Sequence of Union of
 - _internal.url.HttpUrl
 - Url (max_length=2083 allowed_schemes=['http', 'https'])
 
-(AfterValidator(func=); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
+(AfterValidator(wo_special_file_name); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
 
 
 
@@ -1960,7 +1960,7 @@ Union of
   - _internal.url.HttpUrl
   - Url (max_length=2083 allowed_schemes=['http', 'https'])
 
-  (AfterValidator(func=); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
+  (AfterValidator(wo_special_file_name); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
 - str (Len(min_length=1, max_length=2))
 - None
 
@@ -2116,7 +2116,7 @@ Optional[Union of
 - _internal.url.HttpUrl
 - Url (max_length=2083 allowed_schemes=['http', 'https'])
 
-(AfterValidator(func=); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))]
+(AfterValidator(wo_special_file_name); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))]
 
 
 
diff --git a/user_docs/model_descr_v0-5-0.md b/user_docs/model_descr_v0-5-0.md
index 4ac88e35f..38810c17a 100644
--- a/user_docs/model_descr_v0-5-0.md
+++ b/user_docs/model_descr_v0-5-0.md
@@ -103,7 +103,7 @@ Optional[_internal.validated_string.ValidatedString[Annotated[str, StringConstra
 
 
 Union of
-- Path (PathType(path_type='file'); Predicate(func=))
+- Path (PathType(path_type='file'); Predicate(func=))
 - _internal.io.RelativeFilePath
 - _internal.url.HttpUrl
 
@@ -145,16 +145,10 @@ _internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator
 Sequence[typing.Annotated[typing.Union[bioimageio.spec.model.v0_5.BatchAxis, bioimageio.spec.model.v0_5.ChannelAxis, bioimageio.spec.model.v0_5.IndexAxis, bioimageio.spec.model.v0_5.TimeInputAxis, bioimageio.spec.model.v0_5.SpaceInputAxis], FieldInfo(annotation=NoneType, required=True, discriminator='type')]]
 
 **BatchAxis:**
-#### `inputs.axes.id` _internal.validated_string.Valid ≝ `batch`
+#### `inputs.axes.id` AxisId ≝ `batch`
 
 
-
    _internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]
 
-
-
-_internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]
-
-
    
 
 #### `inputs.axes.description` str ≝ ``
 
@@ -172,16 +166,10 @@ _internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator
 
 
 **ChannelAxis:**
-#### `inputs.axes.id` _internal.validated_string.Valid ≝ `channel`
+#### `inputs.axes.id` AxisId ≝ `channel`
 
 
-
    _internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]
 
-
-
-_internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]
-
-
    
 
 #### `inputs.axes.description` str ≝ ``
 
@@ -200,16 +188,10 @@ _internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator
 Sequence[_internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator]]]
 
 **IndexAxis:**
-#### `inputs.axes.id` _internal.validated_string.Valid ≝ `index`
-
+#### `inputs.axes.id` AxisId ≝ `index`
 
-
    _internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]
 
-
 
-_internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]
-
-
    
 
 #### `inputs.axes.description` str ≝ ``
 
@@ -248,16 +230,10 @@ _internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator
 
 
 
-##### `inputs.axes.size.axis_id` _internal.validated_string.Valid
-
-
-
    _internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]
+##### `inputs.axes.size.axis_id` AxisId
 
-
 
-_internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]
 
-
    
 
 ##### `inputs.axes.size.offset` int ≝ `0`
 
@@ -272,16 +248,10 @@ _internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator
 
 
 **TimeInputAxis:**
-#### `inputs.axes.id` _internal.validated_string.Valid ≝ `time`
-
+#### `inputs.axes.id` AxisId ≝ `time`
 
-
    _internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]
-
-
 
-_internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]
 
-
    
 
 #### `inputs.axes.description` str ≝ ``
 
@@ -320,16 +290,10 @@ _internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator
 
 
 
-##### `inputs.axes.size.axis_id` _internal.validated_string.Valid
-
-
-
    _internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]
+##### `inputs.axes.size.axis_id` AxisId
 
-
 
-_internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]
 
-
    
 
 ##### `inputs.axes.size.offset` int ≝ `0`
 
@@ -384,17 +348,11 @@ Optional[Literal of
 
 
 **SpaceInputAxis:**
-#### `inputs.axes.id` _internal.validated_string.Valid ≝ `x`
+#### `inputs.axes.id` AxisId ≝ `x`
 
 [*Examples:*](#inputsaxesid) ['x', 'y', 'z']
 
-
    _internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]
 
-
-
-_internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]
-
-
    
 
 #### `inputs.axes.description` str ≝ ``
 
@@ -433,16 +391,10 @@ _internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator
 
 
 
-##### `inputs.axes.size.axis_id` _internal.validated_string.Valid
+##### `inputs.axes.size.axis_id` AxisId
 
 
-
    _internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]
-
-
-
-_internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]
 
-
    
 
 ##### `inputs.axes.size.offset` int ≝ `0`
 
@@ -844,14 +796,8 @@ Sequence of Union of
 
 [*Example:*](#inputspreprocessingikwargsaxis) 'channel'
 
-
    Optional[_internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]*]
-
-
 
-Optional[_internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]
-(Predicate(func= at 0x7f3030c36160>))]
-
-
    
+Optional[AxisId (Predicate(func= at 0x7bb25d470ea0>))]
 
 ##### `inputs.preprocessing.i.kwargs.gain` Union ≝ `1.0`
 
@@ -907,14 +853,8 @@ Union[float (Ge(ge=1e-06)), Sequence[float (Ge(ge=1e-06))] (MinLen(min_length=1)
 
 [*Examples:*](#inputspreprocessingikwargsaxis) ['channel', 'index']
 
-
    Optional[_internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]*]
-
-
-
-Optional[_internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]
-(Predicate(func= at 0x7f3030c36160>))]
 
-
    
+Optional[AxisId (Predicate(func= at 0x7bb25d470ea0>))]
 
 
 
@@ -937,13 +877,8 @@ Optional[_internal.validated_string.ValidatedString[Annotated[str, MinLen, After
 
 [*Example:*](#inputspreprocessingikwargsaxes) ('batch', 'x', 'y')
 
-
    Optional[Sequence[bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]]]
-
-
-
-Optional[Sequence[bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]]]
 
-
    
+Optional[Sequence[bioimageio.spec.model.v0_5.AxisId]]
 
 ##### `inputs.preprocessing.i.kwargs.eps` float ≝ `1e-06`
 
@@ -971,13 +906,8 @@ Optional[Sequence[bioimageio.spec._internal.validated_string.ValidatedString[Ann
 
 [*Example:*](#inputspreprocessingikwargsaxes) ('batch', 'x', 'y')
 
-
    Optional[Sequence[bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]]]
-
-
-
-Optional[Sequence[bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]]]
 
-
    
+Optional[Sequence[bioimageio.spec.model.v0_5.AxisId]]
 
 ##### `inputs.preprocessing.i.kwargs.min_percentile` float ≝ `0.0`
 
@@ -1058,16 +988,10 @@ _internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator
 Sequence[typing.Annotated[typing.Union[bioimageio.spec.model.v0_5.BatchAxis, bioimageio.spec.model.v0_5.ChannelAxis, bioimageio.spec.model.v0_5.IndexAxis, bioimageio.spec.model.v0_5.TimeOutputAxis, bioimageio.spec.model.v0_5.SpaceOutputAxis], FieldInfo(annotation=NoneType, required=True, discriminator='type')]]
 
 **BatchAxis:**
-#### `outputs.axes.id` _internal.validated_string.Valid ≝ `batch`
-
-
-
    _internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]
+#### `outputs.axes.id` AxisId ≝ `batch`
 
-
 
-_internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]
 
-
    
 
 #### `outputs.axes.description` str ≝ ``
 
@@ -1085,16 +1009,10 @@ _internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator
 
 
 **ChannelAxis:**
-#### `outputs.axes.id` _internal.validated_string.Valid ≝ `channel`
+#### `outputs.axes.id` AxisId ≝ `channel`
 
 
-
    _internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]
 
-
-
-_internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]
-
-
    
 
 #### `outputs.axes.description` str ≝ ``
 
@@ -1113,16 +1031,10 @@ _internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator
 Sequence[_internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator]]]
 
 **IndexAxis:**
-#### `outputs.axes.id` _internal.validated_string.Valid ≝ `index`
-
-
-
    _internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]
+#### `outputs.axes.id` AxisId ≝ `index`
 
-
 
-_internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]
 
-
    
 
 #### `outputs.axes.description` str ≝ ``
 
@@ -1161,16 +1073,10 @@ _internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator
 
 
 
-##### `outputs.axes.size.axis_id` _internal.validated_string.Valid
+##### `outputs.axes.size.axis_id` AxisId
 
 
-
    _internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]
 
-
-
-_internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]
-
-
    
 
 ##### `outputs.axes.size.offset` int ≝ `0`
 
@@ -1190,16 +1096,10 @@ _internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator
 
 
 
-#### `outputs.axes.id` _internal.validated_string.Valid ≝ `time`
-
-
-
    _internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]
+#### `outputs.axes.id` AxisId ≝ `time`
 
-
 
-_internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]
 
-
    
 
 #### `outputs.axes.description` str ≝ ``
 
@@ -1238,16 +1138,10 @@ _internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator
 
 
 
-##### `outputs.axes.size.axis_id` _internal.validated_string.Valid
-
+##### `outputs.axes.size.axis_id` AxisId
 
-
    _internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]
-
-
 
-_internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]
 
-
    
 
 ##### `outputs.axes.size.offset` int ≝ `0`
 
@@ -1307,17 +1201,11 @@ Optional[Literal of
 
 
 
-#### `outputs.axes.id` _internal.validated_string.Valid ≝ `x`
+#### `outputs.axes.id` AxisId ≝ `x`
 
 [*Examples:*](#outputsaxesid) ['x', 'y', 'z']
 
-
    _internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]
 
-
-
-_internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]
-
-
    
 
 #### `outputs.axes.description` str ≝ ``
 
@@ -1356,16 +1244,10 @@ _internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator
 
 
 
-##### `outputs.axes.size.axis_id` _internal.validated_string.Valid
+##### `outputs.axes.size.axis_id` AxisId
 
 
-
    _internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]
 
-
-
-_internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]
-
-
    
 
 ##### `outputs.axes.size.offset` int ≝ `0`
 
@@ -1768,14 +1650,8 @@ Sequence of Union of
 
 [*Example:*](#outputspostprocessingikwargsaxis) 'channel'
 
-
    Optional[_internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]*]
 
-
-
-Optional[_internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]
-(Predicate(func= at 0x7f3030c36160>))]
-
-
    
+Optional[AxisId (Predicate(func= at 0x7bb25d470ea0>))]
 
 ##### `outputs.postprocessing.i.kwargs.gain` Union ≝ `1.0`
 
@@ -1831,14 +1707,8 @@ Union[float (Ge(ge=1e-06)), Sequence[float (Ge(ge=1e-06))] (MinLen(min_length=1)
 
 [*Examples:*](#outputspostprocessingikwargsaxis) ['channel', 'index']
 
-
    Optional[_internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]*]
 
-
-
-Optional[_internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]
-(Predicate(func= at 0x7f3030c36160>))]
-
-
    
+Optional[AxisId (Predicate(func= at 0x7bb25d470ea0>))]
 
 
 
@@ -1861,13 +1731,8 @@ Optional[_internal.validated_string.ValidatedString[Annotated[str, MinLen, After
 
 [*Example:*](#outputspostprocessingikwargsaxes) ('batch', 'x', 'y')
 
-
    Optional[Sequence[bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]]]
 
-
-
-Optional[Sequence[bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]]]
-
-
    
+Optional[Sequence[bioimageio.spec.model.v0_5.AxisId]]
 
 ##### `outputs.postprocessing.i.kwargs.eps` float ≝ `1e-06`
 
@@ -1895,13 +1760,8 @@ Optional[Sequence[bioimageio.spec._internal.validated_string.ValidatedString[Ann
 
 [*Example:*](#outputspostprocessingikwargsaxes) ('batch', 'x', 'y')
 
-
    Optional[Sequence[bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]]]
 
-
-
-Optional[Sequence[bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]]]
-
-
    
+Optional[Sequence[bioimageio.spec.model.v0_5.AxisId]]
 
 ##### `outputs.postprocessing.i.kwargs.min_percentile` float ≝ `0.0`
 
@@ -1961,13 +1821,8 @@ _internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator
 
 [*Example:*](#outputspostprocessingikwargsaxes) ('batch', 'x', 'y')
 
-
    Optional[Sequence[bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]]]
 
-
-
-Optional[Sequence[bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]]]
-
-
    
+Optional[Sequence[bioimageio.spec.model.v0_5.AxisId]]
 
 ##### `outputs.postprocessing.i.kwargs.eps` float ≝ `1e-06`
 
@@ -2659,10 +2514,10 @@ The supported image formats are: ('.gif', '.jpeg', '.jpg', '.png', '.svg')
 
 Sequence of Union of
 - _internal.url.HttpUrl
-- Path (PathType(path_type='file'); Predicate(func=))
+- Path (PathType(path_type='file'); Predicate(func=))
 - _internal.io.RelativeFilePath
 
-(WithSuffix(suffix=('.gif', '.jpeg', '.jpg', '.png', '.svg'), case_sensitive=False); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
+(WithSuffix(suffix=('.gif', '.jpeg', '.jpg', '.png', '.svg'), case_sensitive=False); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
 
 
 
@@ -2686,7 +2541,7 @@ Union of
   - _internal.url.HttpUrl
   - Url (max_length=2083 allowed_schemes=['http', 'https'])
 
-  (AfterValidator(func=); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
+  (AfterValidator(wo_special_file_name); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
 - str (Len(min_length=1, max_length=2))
 - None
 
@@ -2837,7 +2692,7 @@ _internal.validated_string.ValidatedString[Annotated[str, MinLen, Annotated[Type
 
 
 
-## `timestamp` _internal.types.Datetime ≝ `root=datetime.datetime(2024, 3, 13, 14, 32, 39, 909186)`
+## `timestamp` _internal.types.Datetime ≝ `root=datetime.datetime(2024, 3, 14, 14, 46, 38, 123308)`
 
 
 
@@ -2883,10 +2738,10 @@ The supported image formats are: ('.gif', '.jpeg', '.jpg', '.png', '.svg')
 
 Sequence of Union of
 - _internal.url.HttpUrl
-- Path (PathType(path_type='file'); Predicate(func=))
+- Path (PathType(path_type='file'); Predicate(func=))
 - _internal.io.RelativeFilePath
 
-(WithSuffix(suffix=('.gif', '.jpeg', '.jpg', '.png', '.svg'), case_sensitive=False); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
+(WithSuffix(suffix=('.gif', '.jpeg', '.jpg', '.png', '.svg'), case_sensitive=False); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
 
 
 
@@ -3026,7 +2881,7 @@ Union of
   - _internal.url.HttpUrl
   - Url (max_length=2083 allowed_schemes=['http', 'https'])
 
-  (AfterValidator(func=); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
+  (AfterValidator(wo_special_file_name); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
 - str (Len(min_length=1, max_length=2))
 - None
 
@@ -3131,11 +2986,11 @@ Optional[_internal.version_type.Version]
 
 
 Optional[Union of
-- Path (PathType(path_type='file'); Predicate(func=))
+- Path (PathType(path_type='file'); Predicate(func=))
 - _internal.io.RelativeFilePath
 - _internal.url.HttpUrl
 
-(AfterValidator(_validate_md_suffix); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))]
+(AfterValidator(_validate_md_suffix); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))]
 
 
 
diff --git a/user_docs/model_descr_v0-5.md b/user_docs/model_descr_v0-5.md
index 4ac88e35f..38810c17a 100644
--- a/user_docs/model_descr_v0-5.md
+++ b/user_docs/model_descr_v0-5.md
@@ -103,7 +103,7 @@ Optional[_internal.validated_string.ValidatedString[Annotated[str, StringConstra
 
 
 Union of
-- Path (PathType(path_type='file'); Predicate(func=))
+- Path (PathType(path_type='file'); Predicate(func=))
 - _internal.io.RelativeFilePath
 - _internal.url.HttpUrl
 
@@ -145,16 +145,10 @@ _internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator
 Sequence[typing.Annotated[typing.Union[bioimageio.spec.model.v0_5.BatchAxis, bioimageio.spec.model.v0_5.ChannelAxis, bioimageio.spec.model.v0_5.IndexAxis, bioimageio.spec.model.v0_5.TimeInputAxis, bioimageio.spec.model.v0_5.SpaceInputAxis], FieldInfo(annotation=NoneType, required=True, discriminator='type')]]
 
 **BatchAxis:**
-#### `inputs.axes.id` _internal.validated_string.Valid ≝ `batch`
+#### `inputs.axes.id` AxisId ≝ `batch`
 
 
-
    _internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]
 
-
-
-_internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]
-
-
    
 
 #### `inputs.axes.description` str ≝ ``
 
@@ -172,16 +166,10 @@ _internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator
 
 
 **ChannelAxis:**
-#### `inputs.axes.id` _internal.validated_string.Valid ≝ `channel`
+#### `inputs.axes.id` AxisId ≝ `channel`
 
 
-
    _internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]
 
-
-
-_internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]
-
-
    
 
 #### `inputs.axes.description` str ≝ ``
 
@@ -200,16 +188,10 @@ _internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator
 Sequence[_internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator]]]
 
 **IndexAxis:**
-#### `inputs.axes.id` _internal.validated_string.Valid ≝ `index`
-
+#### `inputs.axes.id` AxisId ≝ `index`
 
-
    _internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]
 
-
 
-_internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]
-
-
    
 
 #### `inputs.axes.description` str ≝ ``
 
@@ -248,16 +230,10 @@ _internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator
 
 
 
-##### `inputs.axes.size.axis_id` _internal.validated_string.Valid
-
-
-
    _internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]
+##### `inputs.axes.size.axis_id` AxisId
 
-
 
-_internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]
 
-
    
 
 ##### `inputs.axes.size.offset` int ≝ `0`
 
@@ -272,16 +248,10 @@ _internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator
 
 
 **TimeInputAxis:**
-#### `inputs.axes.id` _internal.validated_string.Valid ≝ `time`
-
+#### `inputs.axes.id` AxisId ≝ `time`
 
-
    _internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]
-
-
 
-_internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]
 
-
    
 
 #### `inputs.axes.description` str ≝ ``
 
@@ -320,16 +290,10 @@ _internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator
 
 
 
-##### `inputs.axes.size.axis_id` _internal.validated_string.Valid
-
-
-
    _internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]
+##### `inputs.axes.size.axis_id` AxisId
 
-
 
-_internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]
 
-
    
 
 ##### `inputs.axes.size.offset` int ≝ `0`
 
@@ -384,17 +348,11 @@ Optional[Literal of
 
 
 **SpaceInputAxis:**
-#### `inputs.axes.id` _internal.validated_string.Valid ≝ `x`
+#### `inputs.axes.id` AxisId ≝ `x`
 
 [*Examples:*](#inputsaxesid) ['x', 'y', 'z']
 
-
    _internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]
 
-
-
-_internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]
-
-
    
 
 #### `inputs.axes.description` str ≝ ``
 
@@ -433,16 +391,10 @@ _internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator
 
 
 
-##### `inputs.axes.size.axis_id` _internal.validated_string.Valid
+##### `inputs.axes.size.axis_id` AxisId
 
 
-
    _internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]
-
-
-
-_internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]
 
-
    
 
 ##### `inputs.axes.size.offset` int ≝ `0`
 
@@ -844,14 +796,8 @@ Sequence of Union of
 
 [*Example:*](#inputspreprocessingikwargsaxis) 'channel'
 
-
    Optional[_internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]*]
-
-
 
-Optional[_internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]
-(Predicate(func= at 0x7f3030c36160>))]
-
-
    
+Optional[AxisId (Predicate(func= at 0x7bb25d470ea0>))]
 
 ##### `inputs.preprocessing.i.kwargs.gain` Union ≝ `1.0`
 
@@ -907,14 +853,8 @@ Union[float (Ge(ge=1e-06)), Sequence[float (Ge(ge=1e-06))] (MinLen(min_length=1)
 
 [*Examples:*](#inputspreprocessingikwargsaxis) ['channel', 'index']
 
-
    Optional[_internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]*]
-
-
-
-Optional[_internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]
-(Predicate(func= at 0x7f3030c36160>))]
 
-
    
+Optional[AxisId (Predicate(func= at 0x7bb25d470ea0>))]
 
 
 
@@ -937,13 +877,8 @@ Optional[_internal.validated_string.ValidatedString[Annotated[str, MinLen, After
 
 [*Example:*](#inputspreprocessingikwargsaxes) ('batch', 'x', 'y')
 
-
    Optional[Sequence[bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]]]
-
-
-
-Optional[Sequence[bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]]]
 
-
    
+Optional[Sequence[bioimageio.spec.model.v0_5.AxisId]]
 
 ##### `inputs.preprocessing.i.kwargs.eps` float ≝ `1e-06`
 
@@ -971,13 +906,8 @@ Optional[Sequence[bioimageio.spec._internal.validated_string.ValidatedString[Ann
 
 [*Example:*](#inputspreprocessingikwargsaxes) ('batch', 'x', 'y')
 
-
    Optional[Sequence[bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]]]
-
-
-
-Optional[Sequence[bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]]]
 
-
    
+Optional[Sequence[bioimageio.spec.model.v0_5.AxisId]]
 
 ##### `inputs.preprocessing.i.kwargs.min_percentile` float ≝ `0.0`
 
@@ -1058,16 +988,10 @@ _internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator
 Sequence[typing.Annotated[typing.Union[bioimageio.spec.model.v0_5.BatchAxis, bioimageio.spec.model.v0_5.ChannelAxis, bioimageio.spec.model.v0_5.IndexAxis, bioimageio.spec.model.v0_5.TimeOutputAxis, bioimageio.spec.model.v0_5.SpaceOutputAxis], FieldInfo(annotation=NoneType, required=True, discriminator='type')]]
 
 **BatchAxis:**
-#### `outputs.axes.id` _internal.validated_string.Valid ≝ `batch`
-
-
-
    _internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]
+#### `outputs.axes.id` AxisId ≝ `batch`
 
-
 
-_internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]
 
-
    
 
 #### `outputs.axes.description` str ≝ ``
 
@@ -1085,16 +1009,10 @@ _internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator
 
 
 **ChannelAxis:**
-#### `outputs.axes.id` _internal.validated_string.Valid ≝ `channel`
+#### `outputs.axes.id` AxisId ≝ `channel`
 
 
-
    _internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]
 
-
-
-_internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]
-
-
    
 
 #### `outputs.axes.description` str ≝ ``
 
@@ -1113,16 +1031,10 @@ _internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator
 Sequence[_internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator]]]
 
 **IndexAxis:**
-#### `outputs.axes.id` _internal.validated_string.Valid ≝ `index`
-
-
-
    _internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]
+#### `outputs.axes.id` AxisId ≝ `index`
 
-
 
-_internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]
 
-
    
 
 #### `outputs.axes.description` str ≝ ``
 
@@ -1161,16 +1073,10 @@ _internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator
 
 
 
-##### `outputs.axes.size.axis_id` _internal.validated_string.Valid
+##### `outputs.axes.size.axis_id` AxisId
 
 
-
    _internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]
 
-
-
-_internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]
-
-
    
 
 ##### `outputs.axes.size.offset` int ≝ `0`
 
@@ -1190,16 +1096,10 @@ _internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator
 
 
 
-#### `outputs.axes.id` _internal.validated_string.Valid ≝ `time`
-
-
-
    _internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]
+#### `outputs.axes.id` AxisId ≝ `time`
 
-
 
-_internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]
 
-
    
 
 #### `outputs.axes.description` str ≝ ``
 
@@ -1238,16 +1138,10 @@ _internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator
 
 
 
-##### `outputs.axes.size.axis_id` _internal.validated_string.Valid
-
+##### `outputs.axes.size.axis_id` AxisId
 
-
    _internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]
-
-
 
-_internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]
 
-
    
 
 ##### `outputs.axes.size.offset` int ≝ `0`
 
@@ -1307,17 +1201,11 @@ Optional[Literal of
 
 
 
-#### `outputs.axes.id` _internal.validated_string.Valid ≝ `x`
+#### `outputs.axes.id` AxisId ≝ `x`
 
 [*Examples:*](#outputsaxesid) ['x', 'y', 'z']
 
-
    _internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]
 
-
-
-_internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]
-
-
    
 
 #### `outputs.axes.description` str ≝ ``
 
@@ -1356,16 +1244,10 @@ _internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator
 
 
 
-##### `outputs.axes.size.axis_id` _internal.validated_string.Valid
+##### `outputs.axes.size.axis_id` AxisId
 
 
-
    _internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]
 
-
-
-_internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]
-
-
    
 
 ##### `outputs.axes.size.offset` int ≝ `0`
 
@@ -1768,14 +1650,8 @@ Sequence of Union of
 
 [*Example:*](#outputspostprocessingikwargsaxis) 'channel'
 
-
    Optional[_internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]*]
 
-
-
-Optional[_internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]
-(Predicate(func= at 0x7f3030c36160>))]
-
-
    
+Optional[AxisId (Predicate(func= at 0x7bb25d470ea0>))]
 
 ##### `outputs.postprocessing.i.kwargs.gain` Union ≝ `1.0`
 
@@ -1831,14 +1707,8 @@ Union[float (Ge(ge=1e-06)), Sequence[float (Ge(ge=1e-06))] (MinLen(min_length=1)
 
 [*Examples:*](#outputspostprocessingikwargsaxis) ['channel', 'index']
 
-
    Optional[_internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]*]
 
-
-
-Optional[_internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]
-(Predicate(func= at 0x7f3030c36160>))]
-
-
    
+Optional[AxisId (Predicate(func= at 0x7bb25d470ea0>))]
 
 
 
@@ -1861,13 +1731,8 @@ Optional[_internal.validated_string.ValidatedString[Annotated[str, MinLen, After
 
 [*Example:*](#outputspostprocessingikwargsaxes) ('batch', 'x', 'y')
 
-
    Optional[Sequence[bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]]]
 
-
-
-Optional[Sequence[bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]]]
-
-
    
+Optional[Sequence[bioimageio.spec.model.v0_5.AxisId]]
 
 ##### `outputs.postprocessing.i.kwargs.eps` float ≝ `1e-06`
 
@@ -1895,13 +1760,8 @@ Optional[Sequence[bioimageio.spec._internal.validated_string.ValidatedString[Ann
 
 [*Example:*](#outputspostprocessingikwargsaxes) ('batch', 'x', 'y')
 
-
    Optional[Sequence[bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]]]
 
-
-
-Optional[Sequence[bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]]]
-
-
    
+Optional[Sequence[bioimageio.spec.model.v0_5.AxisId]]
 
 ##### `outputs.postprocessing.i.kwargs.min_percentile` float ≝ `0.0`
 
@@ -1961,13 +1821,8 @@ _internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator
 
 [*Example:*](#outputspostprocessingikwargsaxes) ('batch', 'x', 'y')
 
-
    Optional[Sequence[bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]]]
 
-
-
-Optional[Sequence[bioimageio.spec._internal.validated_string.ValidatedString[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]]]
-
-
    
+Optional[Sequence[bioimageio.spec.model.v0_5.AxisId]]
 
 ##### `outputs.postprocessing.i.kwargs.eps` float ≝ `1e-06`
 
@@ -2659,10 +2514,10 @@ The supported image formats are: ('.gif', '.jpeg', '.jpg', '.png', '.svg')
 
 Sequence of Union of
 - _internal.url.HttpUrl
-- Path (PathType(path_type='file'); Predicate(func=))
+- Path (PathType(path_type='file'); Predicate(func=))
 - _internal.io.RelativeFilePath
 
-(WithSuffix(suffix=('.gif', '.jpeg', '.jpg', '.png', '.svg'), case_sensitive=False); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
+(WithSuffix(suffix=('.gif', '.jpeg', '.jpg', '.png', '.svg'), case_sensitive=False); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
 
 
 
@@ -2686,7 +2541,7 @@ Union of
   - _internal.url.HttpUrl
   - Url (max_length=2083 allowed_schemes=['http', 'https'])
 
-  (AfterValidator(func=); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
+  (AfterValidator(wo_special_file_name); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
 - str (Len(min_length=1, max_length=2))
 - None
 
@@ -2837,7 +2692,7 @@ _internal.validated_string.ValidatedString[Annotated[str, MinLen, Annotated[Type
 
 
 
-## `timestamp` _internal.types.Datetime ≝ `root=datetime.datetime(2024, 3, 13, 14, 32, 39, 909186)`
+## `timestamp` _internal.types.Datetime ≝ `root=datetime.datetime(2024, 3, 14, 14, 46, 38, 123308)`
 
 
 
@@ -2883,10 +2738,10 @@ The supported image formats are: ('.gif', '.jpeg', '.jpg', '.png', '.svg')
 
 Sequence of Union of
 - _internal.url.HttpUrl
-- Path (PathType(path_type='file'); Predicate(func=))
+- Path (PathType(path_type='file'); Predicate(func=))
 - _internal.io.RelativeFilePath
 
-(WithSuffix(suffix=('.gif', '.jpeg', '.jpg', '.png', '.svg'), case_sensitive=False); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
+(WithSuffix(suffix=('.gif', '.jpeg', '.jpg', '.png', '.svg'), case_sensitive=False); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
 
 
 
@@ -3026,7 +2881,7 @@ Union of
   - _internal.url.HttpUrl
   - Url (max_length=2083 allowed_schemes=['http', 'https'])
 
-  (AfterValidator(func=); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
+  (AfterValidator(wo_special_file_name); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
 - str (Len(min_length=1, max_length=2))
 - None
 
@@ -3131,11 +2986,11 @@ Optional[_internal.version_type.Version]
 
 
 Optional[Union of
-- Path (PathType(path_type='file'); Predicate(func=))
+- Path (PathType(path_type='file'); Predicate(func=))
 - _internal.io.RelativeFilePath
 - _internal.url.HttpUrl
 
-(AfterValidator(_validate_md_suffix); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))]
+(AfterValidator(_validate_md_suffix); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))]
 
 
 
diff --git a/user_docs/notebook_descr_latest.md b/user_docs/notebook_descr_latest.md
index b0683ce89..dd3832adc 100644
--- a/user_docs/notebook_descr_latest.md
+++ b/user_docs/notebook_descr_latest.md
@@ -114,7 +114,7 @@ Union[_internal.license_id.LicenseId, _internal.license_id.DeprecatedLicenseId]
 Union of
 - _internal.url.HttpUrl (WithSuffix(suffix='.ipynb', case_sensitive=True))
 - Path
-  (PathType(path_type='file'); Predicate(func=); WithSuffix(suffix='.ipynb', case_sensitive=True))
+  (PathType(path_type='file'); Predicate(func=); WithSuffix(suffix='.ipynb', case_sensitive=True))
 - _internal.io.RelativeFilePath (WithSuffix(suffix='.ipynb', case_sensitive=True))
 
 
@@ -197,10 +197,10 @@ The supported image formats are: ('.gif', '.jpeg', '.jpg', '.png', '.svg')
 
 Sequence of Union of
 - _internal.url.HttpUrl
-- Path (PathType(path_type='file'); Predicate(func=))
+- Path (PathType(path_type='file'); Predicate(func=))
 - _internal.io.RelativeFilePath
 
-(WithSuffix(suffix=('.gif', '.jpeg', '.jpg', '.png', '.svg'), case_sensitive=False); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
+(WithSuffix(suffix=('.gif', '.jpeg', '.jpg', '.png', '.svg'), case_sensitive=False); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
 
 
 
@@ -213,11 +213,11 @@ Sequence of Union of
 
 
 Optional[Union of
-- Path (PathType(path_type='file'); Predicate(func=))
+- Path (PathType(path_type='file'); Predicate(func=))
 - _internal.io.RelativeFilePath
 - _internal.url.HttpUrl
 
-(AfterValidator(_validate_md_suffix); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))]
+(AfterValidator(_validate_md_suffix); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))]
 
 
 
@@ -241,7 +241,7 @@ Union of
   - _internal.url.HttpUrl
   - Url (max_length=2083 allowed_schemes=['http', 'https'])
 
-  (AfterValidator(func=); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
+  (AfterValidator(wo_special_file_name); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
 - str (Len(min_length=1, max_length=2))
 - None
 
diff --git a/user_docs/notebook_descr_v0-2-4.md b/user_docs/notebook_descr_v0-2-4.md
index 97625f75c..d806b02d8 100644
--- a/user_docs/notebook_descr_v0-2-4.md
+++ b/user_docs/notebook_descr_v0-2-4.md
@@ -42,7 +42,7 @@ Bioimage.io description of a Jupyter Notebook.
 Union of
 - _internal.url.HttpUrl (WithSuffix(suffix='.ipynb', case_sensitive=True))
 - Path
-  (PathType(path_type='file'); Predicate(func=); WithSuffix(suffix='.ipynb', case_sensitive=True))
+  (PathType(path_type='file'); Predicate(func=); WithSuffix(suffix='.ipynb', case_sensitive=True))
 - _internal.io.RelativeFilePath (WithSuffix(suffix='.ipynb', case_sensitive=True))
 
 
@@ -70,7 +70,7 @@ Sequence of Union of
 - _internal.url.HttpUrl
 - Url (max_length=2083 allowed_schemes=['http', 'https'])
 
-(AfterValidator(func=); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
+(AfterValidator(wo_special_file_name); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
 
 
 
@@ -187,10 +187,10 @@ The supported image formats are: ('.gif', '.jpeg', '.jpg', '.png', '.svg')
 
 Sequence of Union of
 - _internal.url.HttpUrl
-- Path (PathType(path_type='file'); Predicate(func=))
+- Path (PathType(path_type='file'); Predicate(func=))
 - _internal.io.RelativeFilePath
 
-(WithSuffix(suffix=('.gif', '.jpeg', '.jpg', '.png', '.svg'), case_sensitive=False); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
+(WithSuffix(suffix=('.gif', '.jpeg', '.jpg', '.png', '.svg'), case_sensitive=False); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
 
 
 
@@ -208,7 +208,7 @@ Optional[Union of
 - _internal.url.HttpUrl
 - Url (max_length=2083 allowed_schemes=['http', 'https'])
 
-(AfterValidator(func=); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))]
+(AfterValidator(wo_special_file_name); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))]
 
 
 
@@ -237,7 +237,7 @@ Union of
   - _internal.url.HttpUrl
   - Url (max_length=2083 allowed_schemes=['http', 'https'])
 
-  (AfterValidator(func=); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
+  (AfterValidator(wo_special_file_name); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
 - str (Len(min_length=1, max_length=2))
 - None
 
diff --git a/user_docs/notebook_descr_v0-2.md b/user_docs/notebook_descr_v0-2.md
index 97625f75c..d806b02d8 100644
--- a/user_docs/notebook_descr_v0-2.md
+++ b/user_docs/notebook_descr_v0-2.md
@@ -42,7 +42,7 @@ Bioimage.io description of a Jupyter Notebook.
 Union of
 - _internal.url.HttpUrl (WithSuffix(suffix='.ipynb', case_sensitive=True))
 - Path
-  (PathType(path_type='file'); Predicate(func=); WithSuffix(suffix='.ipynb', case_sensitive=True))
+  (PathType(path_type='file'); Predicate(func=); WithSuffix(suffix='.ipynb', case_sensitive=True))
 - _internal.io.RelativeFilePath (WithSuffix(suffix='.ipynb', case_sensitive=True))
 
 
@@ -70,7 +70,7 @@ Sequence of Union of
 - _internal.url.HttpUrl
 - Url (max_length=2083 allowed_schemes=['http', 'https'])
 
-(AfterValidator(func=); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
+(AfterValidator(wo_special_file_name); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
 
 
 
@@ -187,10 +187,10 @@ The supported image formats are: ('.gif', '.jpeg', '.jpg', '.png', '.svg')
 
 Sequence of Union of
 - _internal.url.HttpUrl
-- Path (PathType(path_type='file'); Predicate(func=))
+- Path (PathType(path_type='file'); Predicate(func=))
 - _internal.io.RelativeFilePath
 
-(WithSuffix(suffix=('.gif', '.jpeg', '.jpg', '.png', '.svg'), case_sensitive=False); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
+(WithSuffix(suffix=('.gif', '.jpeg', '.jpg', '.png', '.svg'), case_sensitive=False); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
 
 
 
@@ -208,7 +208,7 @@ Optional[Union of
 - _internal.url.HttpUrl
 - Url (max_length=2083 allowed_schemes=['http', 'https'])
 
-(AfterValidator(func=); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))]
+(AfterValidator(wo_special_file_name); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))]
 
 
 
@@ -237,7 +237,7 @@ Union of
   - _internal.url.HttpUrl
   - Url (max_length=2083 allowed_schemes=['http', 'https'])
 
-  (AfterValidator(func=); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
+  (AfterValidator(wo_special_file_name); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
 - str (Len(min_length=1, max_length=2))
 - None
 
diff --git a/user_docs/notebook_descr_v0-3-0.md b/user_docs/notebook_descr_v0-3-0.md
index b0683ce89..dd3832adc 100644
--- a/user_docs/notebook_descr_v0-3-0.md
+++ b/user_docs/notebook_descr_v0-3-0.md
@@ -114,7 +114,7 @@ Union[_internal.license_id.LicenseId, _internal.license_id.DeprecatedLicenseId]
 Union of
 - _internal.url.HttpUrl (WithSuffix(suffix='.ipynb', case_sensitive=True))
 - Path
-  (PathType(path_type='file'); Predicate(func=); WithSuffix(suffix='.ipynb', case_sensitive=True))
+  (PathType(path_type='file'); Predicate(func=); WithSuffix(suffix='.ipynb', case_sensitive=True))
 - _internal.io.RelativeFilePath (WithSuffix(suffix='.ipynb', case_sensitive=True))
 
 
@@ -197,10 +197,10 @@ The supported image formats are: ('.gif', '.jpeg', '.jpg', '.png', '.svg')
 
 Sequence of Union of
 - _internal.url.HttpUrl
-- Path (PathType(path_type='file'); Predicate(func=))
+- Path (PathType(path_type='file'); Predicate(func=))
 - _internal.io.RelativeFilePath
 
-(WithSuffix(suffix=('.gif', '.jpeg', '.jpg', '.png', '.svg'), case_sensitive=False); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
+(WithSuffix(suffix=('.gif', '.jpeg', '.jpg', '.png', '.svg'), case_sensitive=False); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
 
 
 
@@ -213,11 +213,11 @@ Sequence of Union of
 
 
 Optional[Union of
-- Path (PathType(path_type='file'); Predicate(func=))
+- Path (PathType(path_type='file'); Predicate(func=))
 - _internal.io.RelativeFilePath
 - _internal.url.HttpUrl
 
-(AfterValidator(_validate_md_suffix); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))]
+(AfterValidator(_validate_md_suffix); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))]
 
 
 
@@ -241,7 +241,7 @@ Union of
   - _internal.url.HttpUrl
   - Url (max_length=2083 allowed_schemes=['http', 'https'])
 
-  (AfterValidator(func=); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
+  (AfterValidator(wo_special_file_name); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
 - str (Len(min_length=1, max_length=2))
 - None
 
diff --git a/user_docs/notebook_descr_v0-3.md b/user_docs/notebook_descr_v0-3.md
index b0683ce89..dd3832adc 100644
--- a/user_docs/notebook_descr_v0-3.md
+++ b/user_docs/notebook_descr_v0-3.md
@@ -114,7 +114,7 @@ Union[_internal.license_id.LicenseId, _internal.license_id.DeprecatedLicenseId]
 Union of
 - _internal.url.HttpUrl (WithSuffix(suffix='.ipynb', case_sensitive=True))
 - Path
-  (PathType(path_type='file'); Predicate(func=); WithSuffix(suffix='.ipynb', case_sensitive=True))
+  (PathType(path_type='file'); Predicate(func=); WithSuffix(suffix='.ipynb', case_sensitive=True))
 - _internal.io.RelativeFilePath (WithSuffix(suffix='.ipynb', case_sensitive=True))
 
 
@@ -197,10 +197,10 @@ The supported image formats are: ('.gif', '.jpeg', '.jpg', '.png', '.svg')
 
 Sequence of Union of
 - _internal.url.HttpUrl
-- Path (PathType(path_type='file'); Predicate(func=))
+- Path (PathType(path_type='file'); Predicate(func=))
 - _internal.io.RelativeFilePath
 
-(WithSuffix(suffix=('.gif', '.jpeg', '.jpg', '.png', '.svg'), case_sensitive=False); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
+(WithSuffix(suffix=('.gif', '.jpeg', '.jpg', '.png', '.svg'), case_sensitive=False); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
 
 
 
@@ -213,11 +213,11 @@ Sequence of Union of
 
 
 Optional[Union of
-- Path (PathType(path_type='file'); Predicate(func=))
+- Path (PathType(path_type='file'); Predicate(func=))
 - _internal.io.RelativeFilePath
 - _internal.url.HttpUrl
 
-(AfterValidator(_validate_md_suffix); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))]
+(AfterValidator(_validate_md_suffix); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))]
 
 
 
@@ -241,7 +241,7 @@ Union of
   - _internal.url.HttpUrl
   - Url (max_length=2083 allowed_schemes=['http', 'https'])
 
-  (AfterValidator(func=); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
+  (AfterValidator(wo_special_file_name); PlainSerializer(func=, return_type=PydanticUndefined, when_used='unless-none'))
 - str (Len(min_length=1, max_length=2))
 - None