Merge branch 'master' into gnn-llm-model-integration

.github/labeler.yml

@@ -54,5 +54,5 @@ benchmark:
   - changed-files:
       - any-glob-to-any-file: ["benchmark/**/*", "torch_geometric/profile/**/*"]
 
-skip-changelog:
+auto-skip-changelog:
   - head-branch: ['^skip', '^pre-commit-ci']

.github/workflows/changelog.yml

@@ -13,4 +13,4 @@ jobs:
       - name: Enforce changelog entry
         uses: dangoslen/changelog-enforcer@v3
         with:
-          skipLabels: 'skip-changelog'
+          skipLabels: skip-changelog, auto-skip-changelog

CHANGELOG.md

@@ -33,6 +33,7 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 
 ### Changed
 
+- Added the `fmt` arg to `Dataset.get_summary` ([#9408](https://github.com/pyg-team/pytorch_geometric/pull/9408))
 - Skipped zero atom molecules in `MoleculeNet` ([#9318](https://github.com/pyg-team/pytorch_geometric/pull/9318))
 - Ensure proper parallelism in `OnDiskDataset` for multi-threaded `get` calls ([#9140](https://github.com/pyg-team/pytorch_geometric/pull/9140))
 - Allow `None` outputs in `FeatureStore.get_tensor()` - `KeyError` should now be raised based on the implementation in `FeatureStore._get_tensor()` ([#9102](https://github.com/pyg-team/pytorch_geometric/pull/9102))

torch_geometric/data/dataset.py

@@ -367,9 +367,15 @@ def get_summary(self) -> Any:
         from torch_geometric.data.summary import Summary
         return Summary.from_dataset(self)
 
-    def print_summary(self) -> None:
-        r"""Prints summary statistics of the dataset to the console."""
-        print(str(self.get_summary()))
+    def print_summary(self, fmt: str = "psql") -> None:
+        r"""Prints summary statistics of the dataset to the console.
+
+        Args:
+            fmt (str, optional): Summary tables format. Available table formats
+                can be found `here <https://github.com/astanin/python-tabulate?
+                tab=readme-ov-file#table-format>`__. (default: :obj:`"psql"`)
+        """
+        print(self.get_summary().format(fmt=fmt))
 
     def to_datapipe(self) -> Any:
         r"""Converts the dataset into a :class:`torch.utils.data.DataPipe`.

torch_geometric/data/summary.py

@@ -117,7 +117,14 @@ def from_dataset(
             num_edges_per_type=num_edges_per_type,
         )
 
-    def __repr__(self) -> str:
+    def format(self, fmt: str = "psql") -> str:
+        r"""Formats summary statistics of the dataset.
+
+        Args:
+            fmt (str, optional): Summary tables format. Available table formats
+                can be found `here <https://github.com/astanin/python-tabulate?
+                tab=readme-ov-file#table-format>`__. (default: :obj:`"psql"`)
+        """
         from tabulate import tabulate
 
         body = f'{self.name} (#graphs={self.num_graphs}):\n'
@@ -127,7 +134,7 @@ def __repr__(self) -> str:
         for field in Stats.__dataclass_fields__:
             row = [field] + [f'{getattr(s, field):.1f}' for s in stats]
             content.append(row)
-        body += tabulate(content, headers='firstrow', tablefmt='psql')
+        body += tabulate(content, headers='firstrow', tablefmt=fmt)
 
         if self.num_nodes_per_type is not None:
             content = [['']]
@@ -140,7 +147,7 @@ def __repr__(self) -> str:
                 ]
                 content.append(row)
             body += "\nNumber of nodes per node type:\n"
-            body += tabulate(content, headers='firstrow', tablefmt='psql')
+            body += tabulate(content, headers='firstrow', tablefmt=fmt)
 
         if self.num_edges_per_type is not None:
             content = [['']]
@@ -156,6 +163,9 @@ def __repr__(self) -> str:
                 ]
                 content.append(row)
             body += "\nNumber of edges per edge type:\n"
-            body += tabulate(content, headers='firstrow', tablefmt='psql')
+            body += tabulate(content, headers='firstrow', tablefmt=fmt)
 
         return body
+
+    def __repr__(self) -> str:
+        return self.format()

torch_geometric/nn/module_dict.py

@@ -1,4 +1,4 @@
-from typing import Final, Iterable, Mapping, Optional, Set, Tuple, Union
+from typing import Final, Iterable, Mapping, Optional, Tuple, Union
 
 import torch
 from torch.nn import Module
@@ -11,7 +11,7 @@
 # internal representation and converts it back to `.` in the external
 # representation. It also allows passing tuples as keys.
 class ModuleDict(torch.nn.ModuleDict):
-    CLASS_ATTRS: Final[Set[str]] = set(dir(torch.nn.ModuleDict))
+    CLASS_ATTRS: Final[Tuple[str, ...]] = tuple(dir(torch.nn.ModuleDict))
 
     def __init__(
         self,

torch_geometric/nn/parameter_dict.py

@@ -1,4 +1,4 @@
-from typing import Final, Iterable, Mapping, Optional, Set, Tuple, Union
+from typing import Final, Iterable, Mapping, Optional, Tuple, Union
 
 import torch
 from torch.nn import Parameter
@@ -11,7 +11,7 @@
 # internal representation and converts it back to `.` in the external
 # representation. It also allows passing tuples as keys.
 class ParameterDict(torch.nn.ParameterDict):
-    CLASS_ATTRS: Final[Set[str]] = set(dir(torch.nn.ParameterDict))
+    CLASS_ATTRS: Final[Tuple[str, ...]] = set(dir(torch.nn.ParameterDict))
 
     def __init__(
         self,

torch_geometric/testing/decorators.py

@@ -7,6 +7,7 @@
 
 import torch
 from packaging.requirements import Requirement
+from packaging.version import Version
 
 from torch_geometric.typing import WITH_METIS, WITH_PYG_LIB, WITH_TORCH_SPARSE
 from torch_geometric.visualization.graph import has_graphviz
@@ -180,12 +181,7 @@ def has_package(package: str) -> bool:
     if not hasattr(module, '__version__'):
         return True
 
-    version = module.__version__
-    # `req.specifier` does not support `.dev` suffixes, e.g., for
-    # `pyg_lib==0.1.0.dev*`, so we manually drop them:
-    if '.dev' in version:
-        version = '.'.join(version.split('.dev')[:-1])
-
+    version = Version(module.__version__).base_version
     return version in req.specifier