fix-lints

turbo-llm · Nov 18, 2024 · 6222186 · 6222186
1 parent 5720536
commit 6222186
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Showing 8 changed files with 31 additions and 35 deletions.
diff --git a/turbo_alignment/cherry_picks/multimodal.py b/turbo_alignment/cherry_picks/multimodal.py
@@ -1,10 +1,10 @@
 from typing import Iterable
 
 import torch
+import wandb
 from PIL import Image
 from transformers import PreTrainedTokenizerBase
 
-import wandb
 from turbo_alignment.cherry_picks.base import CherryPickCallbackBase
 from turbo_alignment.dataset.multimodal import InferenceMultimodalDataset
 from turbo_alignment.generators.multimodal import MultimodalGenerator

diff --git a/turbo_alignment/common/logging/weights_and_biases.py b/turbo_alignment/common/logging/weights_and_biases.py
@@ -1,9 +1,9 @@
 from typing import Any
 
+import wandb
 from wandb.sdk.lib.disabled import RunDisabled
 from wandb.sdk.wandb_run import Run
 
-import wandb
 from turbo_alignment.settings.logging.weights_and_biases import WandbSettings
 
 

diff --git a/turbo_alignment/common/tf/callbacks/logging.py b/turbo_alignment/common/tf/callbacks/logging.py
@@ -3,6 +3,7 @@
 
 import numpy as np
 import pandas as pd
+import wandb
 from clearml import Task
 from transformers import (
     TrainerCallback,
@@ -13,7 +14,6 @@
 from wandb.sdk.lib.disabled import RunDisabled
 from wandb.sdk.wandb_run import Run
 
-import wandb
 from turbo_alignment.common.logging import get_project_logger
 
 logger = get_project_logger()

diff --git a/turbo_alignment/metrics/__init__.py b/turbo_alignment/metrics/__init__.py
@@ -1,5 +1,6 @@
 from turbo_alignment.metrics.distinctness import DistinctnessMetric
 from turbo_alignment.metrics.diversity import DiversityMetric
+from turbo_alignment.metrics.exact_match import ExactMatchMetric
 from turbo_alignment.metrics.kl import KLMetric
 from turbo_alignment.metrics.length import LengthMetric
 from turbo_alignment.metrics.meteor import MeteorMetric
@@ -10,4 +11,3 @@
 from turbo_alignment.metrics.reward import RewardMetric
 from turbo_alignment.metrics.rouge import RougeMetric
 from turbo_alignment.metrics.self_bleu import SelfBleuMetric
-from turbo_alignment.metrics.exact_match import ExactMatchMetric
diff --git a/turbo_alignment/metrics/distinctness.py b/turbo_alignment/metrics/distinctness.py
@@ -1,4 +1,5 @@
 from collections import defaultdict
+
 from transformers.tokenization_utils_base import PreTrainedTokenizerBase
 
 from turbo_alignment.metrics.metric import Metric

diff --git a/turbo_alignment/metrics/exact_match.py b/turbo_alignment/metrics/exact_match.py
@@ -1,5 +1,6 @@
 import json
-from datetime import datetime, timedelta
+from datetime import datetime
+
 from turbo_alignment.dataset.chat import InferenceChatDataset
 from turbo_alignment.metrics.metric import Metric
 from turbo_alignment.metrics.registry import ExactMatchMetricSettings
@@ -23,11 +24,11 @@ def compute(self, **kwargs) -> list[MetricResults]:
             raise ValueError('predictions should not be None')
 
         (
-            ref_functions,
+            _,
             ref_arguments,
         ) = self._parse_function_with_arguments(references)
         (
-            pred_functions,
+            _,
             pred_arguments,
         ) = self._parse_function_with_arguments(predictions)
 
@@ -36,80 +37,73 @@ def compute(self, **kwargs) -> list[MetricResults]:
             if 'date' in selected_key:
                 for day_lift in self._settings.possible_day_lifts:
                     temp_hits = []
-                    for pred_argument, ref_argument in zip(
-                            pred_arguments, ref_arguments):
+                    for pred_argument, ref_argument in zip(pred_arguments, ref_arguments):
                         temp_hits.append(
                             self._full_match_argument(
                                 parsed_predicted_arguments=pred_argument,
                                 parsed_reference_arguments=ref_argument,
                                 selected_key=selected_key,
-                                day_lift=day_lift
+                                day_lift=day_lift,
                             )
                         )
-                    label = selected_key +'_'+str(day_lift)
+                    label = selected_key + '_' + str(day_lift)
                     element_wise_scores.append(ElementWiseScores(label=label, values=temp_hits))
             else:
                 temp_hits = []
-                for pred_argument, ref_argument in zip(
-                        pred_arguments, ref_arguments):
+                for pred_argument, ref_argument in zip(pred_arguments, ref_arguments):
                     temp_hits.append(
                         self._full_match_argument(
                             parsed_predicted_arguments=pred_argument,
                             parsed_reference_arguments=ref_argument,
-                            selected_key=selected_key
+                            selected_key=selected_key,
                         )
                     )
                 label = selected_key
                 element_wise_scores.append(ElementWiseScores(label=label, values=temp_hits))
         return [MetricResults(element_wise_scores=element_wise_scores, need_average=True)]
 
-
-    def _full_match_argument(self, parsed_predicted_arguments, parsed_reference_arguments,
-                             selected_key,day_lift=None) -> bool:
+    def _full_match_argument(
+        self, parsed_predicted_arguments, parsed_reference_arguments, selected_key, day_lift=None
+    ) -> bool:
         key = selected_key
         possible_day_lift = day_lift
         if 'date' in key:
             try:
                 predicted_date_obj = datetime.strptime(parsed_reference_arguments[key], '%Y-%m-%d')
                 reference_date_obj = datetime.strptime(parsed_predicted_arguments[key], '%Y-%m-%d')
-                if abs((predicted_date_obj - reference_date_obj).days) <= possible_day_lift:
-                    return True
-                else:
-                    return False
+                return abs((predicted_date_obj - reference_date_obj).days) <= possible_day_lift
             except (ValueError, TypeError):
                 return False
         else:
             try:
-                return parsed_reference_arguments[self._settings.selected_argument_key] \
-                       == parsed_predicted_arguments[self._settings.selected_argument_key]
-            except:
+                return parsed_reference_arguments[key] == parsed_predicted_arguments[key]
+            except Exception as e:
+                print(f'error in match-argument{e}')
                 return False
 
-
-    def _parse_function_with_arguments(self, inputs: InferenceChatDataset | list[list[str]])\
-            -> tuple[list, list]:
+    def _parse_function_with_arguments(self, inputs: InferenceChatDataset | list[list[str]]) -> tuple[list, list]:
         functions = []
         arguments = []
         for input_batch in inputs:
             for input in input_batch:
                 input_splitted = self._load_json(input)
                 if len(input_splitted) == 2:
-                    functions.append(input_splitted.get('name',''))
-                    arguments.append(input_splitted.get('parameters',''))
+                    functions.append(input_splitted.get('name', ''))
+                    arguments.append(input_splitted.get('parameters', ''))
                 else:
                     functions.append('')
                     arguments.append('')
         return functions, arguments
 
-
     @staticmethod
     def _load_json(data):
         try:
-            return  json.loads(data)
+            return json.loads(data)
         except json.JSONDecodeError as e:
             error_position = e.pos
-            fixed_json = data[:error_position] + "null," + data[error_position + 1:]
+            fixed_json = data[:error_position] + 'null,' + data[error_position + 1 :]
             try:
-                return  json.loads(fixed_json)
+                return json.loads(fixed_json)
             except json.JSONDecodeError as e2:
+                print(f'error in load-json in match-argument{e2}')
                 return {}
diff --git a/turbo_alignment/metrics/registry.py b/turbo_alignment/metrics/registry.py
@@ -1,4 +1,5 @@
 from enum import Enum
+
 from pydantic import field_validator
 
 from turbo_alignment.common.registry import Registrable
@@ -103,7 +104,7 @@ class RetrievalUtilitySettings(MetricSettings):
 @MetricSettingsRegistry.register(MetricType.EXACT_MATCH)
 class ExactMatchMetricSettings(MetricSettings):
     selected_argument_keys: list[str]
-    possible_day_lifts: list[int] = [0,1,3]
+    possible_day_lifts: list[int] = [0, 1, 3]
 
     class Config:
         env_prefix: str = 'EXACT_MATCH_METRIC_'
diff --git a/turbo_alignment/trainers/dpo.py b/turbo_alignment/trainers/dpo.py
@@ -26,9 +26,9 @@
 from turbo_alignment.settings.pipelines.train.dpo import (
     APODownLossSettings,
     APOZeroLossSettings,
+    ASFTLossSettings,
     CPOLossSettings,
     DPOLossesType,
-    ASFTLossSettings,
     HingeLossSettings,
     IPOLossSettings,
     KTOLossSettings,