Move all hooks in MPA into OTX common mmcv adapter (#1922)

Author: Soobee Lee

docs/source/guide/reference/mpa/modules/hooks.rst

@@ -6,6 +6,5 @@ Modules
 
    models/index
    datasets
-   hooks
    ov/index
    utils

docs/source/guide/reference/mpa/modules/index.rst

@@ -275,7 +275,7 @@ def extract_feat(self, img):
 if is_mmdeploy_enabled():
     from mmdeploy.core import FUNCTION_REWRITER
 
-    from otx.mpa.modules.hooks.recording_forward_hooks import (  # pylint: disable=ungrouped-imports
+    from otx.algorithms.common.adapters.mmcv.hooks.recording_forward_hook import (  # pylint: disable=ungrouped-imports
         FeatureVectorHook,
         ReciproCAMHook,
     )

otx/algorithms/classification/adapters/mmcls/models/classifiers/sam_classifier.py

@@ -1,6 +1,6 @@
 """Adapters for mmcv support."""
 
-# Copyright (C) 2021-2023 Intel Corporation
+# Copyright (C) 2022-2023 Intel Corporation
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
@@ -14,40 +14,76 @@
 # See the License for the specific language governing permissions
 # and limitations under the License.
 
-from .base_hook import (
-    CancelTrainingHook,
-    EarlyStoppingHook,
-    EMAMomentumUpdateHook,
+from .adaptive_training_hook import AdaptiveTrainSchedulingHook
+from .cancel_hook import CancelInterfaceHook, CancelTrainingHook
+from .checkpoint_hook import (
+    CheckpointHookWithValResults,
     EnsureCorrectBestCheckpointHook,
-    OTXLoggerHook,
-    OTXProgressHook,
+    SaveInitialWeightHook,
+)
+from .composed_dataloaders_hook import ComposedDataLoadersHook
+from .custom_model_ema_hook import CustomModelEMAHook, EMAMomentumUpdateHook
+from .dual_model_ema_hook import DualModelEMAHook
+from .early_stopping_hook import (
+    EarlyStoppingHook,
+    LazyEarlyStoppingHook,
     ReduceLROnPlateauLrUpdaterHook,
     StopLossNanTrainingHook,
-    TwoCropTransformHook,
 )
-from .checkpoint_hook import CheckpointHookWithValResults
-from .eval_hook import CustomEvalHook
+from .eval_hook import CustomEvalHook, DistCustomEvalHook
+from .force_train_hook import ForceTrainModeHook
 from .fp16_sam_optimizer_hook import Fp16SAMOptimizerHook
 from .ib_loss_hook import IBLossHook
+from .logger_hook import LoggerReplaceHook, OTXLoggerHook
+from .model_ema_v2_hook import ModelEmaV2Hook
 from .no_bias_decay_hook import NoBiasDecayHook
+from .progress_hook import OTXProgressHook
+from .recording_forward_hook import (
+    ActivationMapHook,
+    BaseRecordingForwardHook,
+    EigenCamHook,
+    FeatureVectorHook,
+)
 from .sam_optimizer_hook import SAMOptimizerHook
 from .semisl_cls_hook import SemiSLClsHook
+from .task_adapt_hook import TaskAdaptHook
+from .two_crop_transform_hook import TwoCropTransformHook
+from .unbiased_teacher_hook import UnbiasedTeacherHook
+from .workflow_hook import WorkflowHook
 
 __all__ = [
+    "AdaptiveTrainSchedulingHook",
+    "CancelInterfaceHook",
+    "CancelTrainingHook",
     "CheckpointHookWithValResults",
+    "EnsureCorrectBestCheckpointHook",
+    "ComposedDataLoadersHook",
     "CustomEvalHook",
+    "DistCustomEvalHook",
+    "EarlyStoppingHook",
+    "LazyEarlyStoppingHook",
+    "ReduceLROnPlateauLrUpdaterHook",
+    "EMAMomentumUpdateHook",
+    "ForceTrainModeHook",
+    "Fp16SAMOptimizerHook",
+    "StopLossNanTrainingHook",
     "IBLossHook",
+    "OTXLoggerHook",
+    "LoggerReplaceHook",
+    "CustomModelEMAHook",
+    "DualModelEMAHook",
+    "ModelEmaV2Hook",
     "NoBiasDecayHook",
+    "OTXProgressHook",
+    "BaseRecordingForwardHook",
+    "EigenCamHook",
+    "ActivationMapHook",
+    "FeatureVectorHook",
     "SAMOptimizerHook",
-    "Fp16SAMOptimizerHook",
+    "SaveInitialWeightHook",
     "SemiSLClsHook",
-    "CancelTrainingHook",
-    "OTXLoggerHook",
-    "OTXProgressHook",
-    "EarlyStoppingHook",
-    "ReduceLROnPlateauLrUpdaterHook",
-    "EnsureCorrectBestCheckpointHook",
-    "StopLossNanTrainingHook",
-    "EMAMomentumUpdateHook",
+    "TaskAdaptHook",
     "TwoCropTransformHook",
+    "UnbiasedTeacherHook",
+    "WorkflowHook",
 ]

otx/algorithms/common/adapters/mmcv/hooks/__init__.py

@@ -1,4 +1,5 @@
-# Copyright (C) 2022 Intel Corporation
+"""Adaptive training schedule hook."""
+# Copyright (C) 2023 Intel Corporation
 # SPDX-License-Identifier: Apache-2.0
 #
 
@@ -8,15 +9,19 @@
 from mmcv.runner.hooks.checkpoint import CheckpointHook
 from mmcv.runner.hooks.evaluation import EvalHook
 
-from otx.mpa.modules.hooks.early_stopping_hook import EarlyStoppingHook
+from otx.algorithms.common.adapters.mmcv.hooks.early_stopping_hook import (
+    EarlyStoppingHook,
+)
 from otx.mpa.utils.logger import get_logger
 
 logger = get_logger()
 
+# pylint: disable=too-many-arguments, too-many-instance-attributes
+
 
 @HOOKS.register_module()
 class AdaptiveTrainSchedulingHook(Hook):
-    """Adaptive Training Scheduling Hook
+    """Adaptive Training Scheduling Hook.
 
     Depending on the size of iteration per epoch, adaptively update the validation interval and related values.
 
@@ -58,6 +63,7 @@ def __init__(
         self._original_interval = None
 
     def before_run(self, runner):
+        """Before run."""
         if self.enable_eval_before_run:
             hook = self.get_evalhook(runner)
             if hook is None:
@@ -68,6 +74,7 @@ def before_run(self, runner):
             hook.start = 0
 
     def before_train_iter(self, runner):
+        """Before train iter."""
         if self.enable_eval_before_run and self._original_interval is not None:
             hook = self.get_evalhook(runner)
             hook.interval = self._original_interval
@@ -110,10 +117,12 @@ def before_train_iter(self, runner):
             self._initialized = True
 
     def get_adaptive_interval(self, iter_per_epoch):
+        """Get adaptive interval."""
         adaptive_interval = max(round(math.exp(self.decay * iter_per_epoch) * self.max_interval), 1)
         return adaptive_interval
 
     def get_evalhook(self, runner):
+        """Get evaluation hook."""
         target_hook = None
         for hook in runner.hooks:
             if isinstance(hook, EvalHook):