[OTE Enhancements] - Add pydocstyle to pre-commit configurations.

.pre-commit-config.yaml

@@ -85,3 +85,15 @@ repos:
         types: [python]
         args: ["--score=no"]
         exclude: "tests"
+
+  - repo: https://github.com/PyCQA/pydocstyle
+    rev: 6.1.1
+    hooks:
+      - id: pydocstyle
+        additional_dependencies: [toml]
+        name: pydocstyle
+        entry: pydocstyle
+        language: python
+        types: [python]
+        files: '^external/anomaly/.*\.py'
+        exclude: "external/anomaly/tests"

external/anomaly/adapters/anomalib/callbacks/__init__.py

@@ -1,6 +1,4 @@
-"""
-Callbacks for OTE inference
-"""
+"""Callbacks for OTE inference."""
 
 # Copyright (C) 2021 Intel Corporation
 #

external/anomaly/adapters/anomalib/callbacks/inference.py

@@ -1,6 +1,4 @@
-"""
-Inference Callbacks for OTE inference
-"""
+"""Inference Callbacks for OTE inference."""
 
 # Copyright (C) 2021 Intel Corporation
 #

external/anomaly/adapters/anomalib/callbacks/progress.py

@@ -1,6 +1,4 @@
-"""
-Progressbar Callback for OTE task
-"""
+"""Progressbar Callback for OTE task."""
 
 # Copyright (C) 2021 Intel Corporation
 #
@@ -24,8 +22,9 @@
 
 
 class ProgressCallback(TQDMProgressBar):
-    """
-    Modifies progress callback to show completion of the entire training step
+    """Progress Callback.
+
+    Modify progress callback to show completion of the entire training step.
     """
 
     def __init__(self, parameters: Optional[Union[TrainParameters, InferenceParameters]] = None) -> None:
@@ -40,61 +39,47 @@ def __init__(self, parameters: Optional[Union[TrainParameters, InferenceParamete
             self.update_progress_callback = default_progress_callback
 
     def on_train_start(self, trainer, pl_module):
-        """
-        Store max epochs and current epoch from trainer
-        """
+        """Store max epochs and current epoch from trainer."""
         super().on_train_start(trainer, pl_module)
         self.current_epoch = trainer.current_epoch
         self.max_epochs = trainer.max_epochs
         self._reset_progress()
 
     def on_predict_start(self, trainer, pl_module):
-        """
-        Reset progress bar when prediction starts.
-        """
+        """Reset progress bar when prediction starts."""
         super().on_predict_start(trainer, pl_module)
         self._reset_progress()
 
     def on_test_start(self, trainer, pl_module):
-        """
-        Reset progress bar when testing starts.
-        """
+        """Reset progress bar when testing starts."""
         super().on_test_start(trainer, pl_module)
         self._reset_progress()
 
     def on_train_batch_end(self, trainer, pl_module, outputs, batch, batch_idx):
-        """
-        Adds training completion percentage to the progress bar
-        """
+        """Adds training completion percentage to the progress bar."""
         super().on_train_batch_end(trainer, pl_module, outputs, batch, batch_idx)
         self.current_epoch = trainer.current_epoch
         self._update_progress(stage="train")
 
     def on_predict_batch_end(self, trainer, pl_module, outputs, batch, batch_idx, dataloader_idx):
-        """
-        Adds prediction completion percentage to the progress bar
-        """
+        """Adds prediction completion percentage to the progress bar."""
         super().on_predict_batch_end(trainer, pl_module, outputs, batch, batch_idx, dataloader_idx)
         self._update_progress(stage="predict")
 
     def on_test_batch_end(self, trainer, pl_module, outputs, batch, batch_idx, dataloader_idx):
-        """
-        Adds testing completion percentage to the progress bar
-        """
+        """Adds testing completion percentage to the progress bar."""
         super().on_test_batch_end(trainer, pl_module, outputs, batch, batch_idx, dataloader_idx)
         self._update_progress(stage="test")
 
     def _reset_progress(self):
         self._progress = 0.0
 
     def _get_progress(self, stage: str = "train") -> float:
-        """
-        Get progress for train and test stages.
+        """Get progress for train and test stages.
 
         Args:
             stage (str, optional): Train or Test stages. Defaults to "train".
         """
-
         if stage == "train":
             # Progress is calculated on the upper bound (max epoch).
             # Early stopping might stop the training before the progress reaches 100%

external/anomaly/adapters/anomalib/callbacks/score_report.py

@@ -1,4 +1,4 @@
-"""Score reporting callback"""
+"""Score reporting callback."""
 
 # Copyright (C) 2020 Intel Corporation
 #
@@ -21,9 +21,7 @@
 
 
 class ScoreReportingCallback(Callback):
-    """
-    Callback for reporting score.
-    """
+    """Callback for reporting score."""
 
     def __init__(self, parameters: Optional[TrainParameters] = None) -> None:
         if parameters is not None:
@@ -32,9 +30,7 @@ def __init__(self, parameters: Optional[TrainParameters] = None) -> None:
             self.score_reporting_callback = None
 
     def on_validation_epoch_end(self, trainer, pl_module):  # pylint: disable=unused-argument
-        """
-        If score exists in trainer.logged_metrics, report the score.
-        """
+        """If score exists in trainer.logged_metrics, report the score."""
         if self.score_reporting_callback is not None:
             score = None
             metric = getattr(self.score_reporting_callback, "metric", None)

external/anomaly/adapters/anomalib/config/__init__.py

@@ -1,6 +1,4 @@
-"""
-Initialization of Configurable parameter conversion between OTE and Anomalib.
-"""
+"""Initialization of Configurable parameter conversion between OTE and Anomalib."""
 
 # Copyright (C) 2021 Intel Corporation
 #

external/anomaly/adapters/anomalib/config/anomalib_config.py

@@ -1,6 +1,4 @@
-"""
-Configurable parameter conversion between OTE and Anomalib.
-"""
+"""Configurable parameter conversion between OTE and Anomalib."""
 
 # Copyright (C) 2021 Intel Corporation
 #
@@ -26,13 +24,18 @@
 
 
 def get_anomalib_config(task_name: str, ote_config: ConfigurableParameters) -> Union[DictConfig, ListConfig]:
-    """
-    Create an anomalib config object that matches the values specified in the OTE config.
+    """Get anomalib configuration.
+
+    Create an anomalib config object that matches the values specified in the
+    OTE config.
 
     Args:
-        ote_config: ConfigurableParameters: OTE config object parsed from configuration.yaml file
+        ote_config: ConfigurableParameters: OTE config object parsed from
+            configuration.yaml file
+
     Returns:
-        Anomalib config object for the specified model type with overwritten default values.
+        Anomalib config object for the specified model type with overwritten
+        default values.
     """
     config_path = Path(anomalib.__file__).parent / "models" / task_name.lower() / "config.yaml"
     anomalib_config = get_configurable_parameters(model_name=task_name.lower(), config_path=config_path)
@@ -41,7 +44,7 @@ def get_anomalib_config(task_name: str, ote_config: ConfigurableParameters) -> U
 
 
 def _anomalib_config_mapper(anomalib_config: Union[DictConfig, ListConfig], ote_config: ConfigurableParameters):
-    """Returns mapping from learning parameters to anomalib parameters
+    """Return mapping from learning parameters to anomalib parameters.
 
     Args:
         anomalib_config: DictConfig: Anomalib config object
@@ -64,13 +67,16 @@ def _anomalib_config_mapper(anomalib_config: Union[DictConfig, ListConfig], ote_
 
 
 def update_anomalib_config(anomalib_config: Union[DictConfig, ListConfig], ote_config: ConfigurableParameters):
-    """
-    Overwrite the default parameter values in the anomalib config with the values specified in the OTE config. The
-    function is recursively called for each parameter group present in the OTE config.
+    """Update anomalib configuration.
+
+    Overwrite the default parameter values in the anomalib config with the
+    values specified in the OTE config. The function is recursively called for
+    each parameter group present in the OTE config.
 
     Args:
         anomalib_config: DictConfig: Anomalib config object
-        ote_config: ConfigurableParameters: OTE config object parsed from configuration.yaml file
+        ote_config: ConfigurableParameters: OTE config object parsed from
+            configuration.yaml file
     """
     for param in ote_config.parameters:
         assert param in anomalib_config.keys(), f"Parameter {param} not present in anomalib config."

external/anomaly/adapters/anomalib/data/__init__.py

@@ -1,6 +1,4 @@
-"""
-Initialization of Anomaly Dataset Utils
-"""
+"""Initialization of Anomaly Dataset Utils."""
 
 # Copyright (C) 2021 Intel Corporation
 #

external/anomaly/adapters/anomalib/data/data.py

@@ -1,6 +1,4 @@
-"""
-Anomaly Dataset Utils
-"""
+"""Anomaly Dataset Utils."""
 
 # Copyright (C) 2021 Intel Corporation
 #
@@ -39,8 +37,8 @@
 
 
 class OTEAnomalyDataset(Dataset):
-    """
-    Anomaly Dataset Adaptor
+    """Anomaly Dataset Adaptor.
+
     This class converts OTE Dataset into Anomalib dataset that
     is a sub-class of Vision Dataset.
 
@@ -71,9 +69,25 @@ def __init__(self, config: Union[DictConfig, ListConfig], dataset: DatasetEntity
         )
 
     def __len__(self) -> int:
+        """Get size of the dataset.
+
+        Returns:
+            int: Size of the dataset.
+        """
         return len(self.dataset)
 
     def __getitem__(self, index: int) -> Dict[str, Union[int, Tensor]]:
+        """Get dataset item.
+
+        Args:
+            index (int): Index of the dataset sample.
+
+        Raises:
+            ValueError: When the task type is not supported.
+
+        Returns:
+            Dict[str, Union[int, Tensor]]: Dataset item.
+        """
         dataset_item = self.dataset[index]
         item: Dict[str, Union[int, Tensor]] = {}
         item = {"index": index}
@@ -98,8 +112,8 @@ def __getitem__(self, index: int) -> Dict[str, Union[int, Tensor]]:
 
 
 class OTEAnomalyDataModule(LightningDataModule):
-    """
-    Anomaly DataModule
+    """Anomaly DataModule.
+
     This class converts OTE Dataset into Anomalib dataset and stores
     train/val/test dataloaders.
 
@@ -131,8 +145,7 @@ def __init__(self, config: Union[DictConfig, ListConfig], dataset: DatasetEntity
         self.predict_ote_dataset: DatasetEntity
 
     def setup(self, stage: Optional[str] = None) -> None:
-        """
-        Setup Anomaly Data Module
+        """Setup Anomaly Data Module.
 
         Args:
             stage (Optional[str], optional): train/val/test stages.
@@ -172,8 +185,10 @@ def summary(self):
     def train_dataloader(
         self,
     ) -> Union[DataLoader, List[DataLoader], Dict[str, DataLoader]]:
-        """
-        Train Dataloader
+        """Train Dataloader.
+
+        Returns:
+            Union[DataLoader, List[DataLoader], Dict[str, DataLoader]]: Train dataloader.
         """
         dataset = OTEAnomalyDataset(self.config, self.train_ote_dataset, self.task_type)
         return DataLoader(
@@ -184,8 +199,10 @@ def train_dataloader(
         )
 
     def val_dataloader(self) -> Union[DataLoader, List[DataLoader]]:
-        """
-        Validation Dataloader
+        """Validation Dataloader.
+
+        Returns:
+            Union[DataLoader, List[DataLoader]]: Validation Dataloader.
         """
         global_dataset, local_dataset = split_local_global_dataset(self.val_ote_dataset)
         logger.info(f"Global annotations: {len(global_dataset)}")
@@ -204,8 +221,10 @@ def val_dataloader(self) -> Union[DataLoader, List[DataLoader]]:
         )
 
     def test_dataloader(self) -> Union[DataLoader, List[DataLoader]]:
-        """
-        Test Dataloader
+        """Test Dataloader.
+
+        Returns:
+            Union[DataLoader, List[DataLoader]]: Test Dataloader.
         """
         dataset = OTEAnomalyDataset(self.config, self.test_ote_dataset, self.task_type)
         return DataLoader(
@@ -216,8 +235,10 @@ def test_dataloader(self) -> Union[DataLoader, List[DataLoader]]:
         )
 
     def predict_dataloader(self) -> Union[DataLoader, List[DataLoader]]:
-        """
-        Predict Dataloader
+        """Predict Dataloader.
+
+        Returns:
+            Union[DataLoader, List[DataLoader]]: Predict Dataloader.
         """
         dataset = OTEAnomalyDataset(self.config, self.predict_ote_dataset, self.task_type)
         return DataLoader(

external/anomaly/adapters/anomalib/data/dataset.py

@@ -45,7 +45,8 @@ def __init__(
         val_subset: Optional[Dict[str, str]] = None,
         test_subset: Optional[Dict[str, str]] = None,
     ):
-        """
+        """Base Anomaly Dataset.
+
         Args:
             train_subset (Optional[Dict[str, str]], optional): Path to annotation
                 and dataset used for training. Defaults to None.

external/anomaly/adapters/anomalib/data/mvtec.py

@@ -108,10 +108,12 @@ def __init__(
 
     def get_samples(self) -> DataFrame:
         """Get MVTec samples.
+
         Get MVTec samples in a pandas DataFrame. Update the certain columns
         to match the OTE naming terminology. For example, column `split` is
         renamed to `subset`. Labels are also renamed by creating their
         corresponding OTE LabelEntities
+
         Returns:
             DataFrame: Final list of samples comprising all the required
                 information to create the OTE Dataset.
@@ -139,6 +141,7 @@ def get_samples(self) -> DataFrame:
 
     def generate(self) -> DatasetEntity:
         """Generate OTE Anomaly Dataset.
+
         Returns:
             DatasetEntity: Output OTE Anomaly Dataset from an MVTec
         """

external/anomaly/adapters/anomalib/logger/logger.py

@@ -20,6 +20,7 @@ def get_logger(
     be directly returned. During initialization, a StreamHandler will always be
     added. If `log_file` is specified and the process rank is 0, a FileHandler
     will also be added.
+
     Args:
         name (str): Logger name.
         log_file (str | None): The log filename. If specified, a FileHandler
@@ -29,6 +30,7 @@ def get_logger(
             "Error" thus be silent most of the time.
         file_mode (str): The file mode used in opening log file.
             Defaults to 'w'.
+
     Returns:
         logging.Logger: The expected logger.
     """

external/anomaly/configs/base/__init__.py

@@ -1,6 +1,4 @@
-"""
-Base configurable parameter for anomaly tasks
-"""
+"""Base configurable parameter for anomaly tasks."""
 
 # Copyright (C) 2022 Intel Corporation
 #