Merge a9ec30e into a7f8e96

mmcls/apis/train.py

@@ -6,30 +6,14 @@
 import torch
 import torch.distributed as dist
 from mmcv.parallel import MMDataParallel, MMDistributedDataParallel
-from mmcv.runner import (DistSamplerSeedHook, build_optimizer, build_runner,
-                         get_dist_info)
+from mmcv.runner import (DistSamplerSeedHook, Fp16OptimizerHook,
+                         build_optimizer, build_runner, get_dist_info)
+from mmcv.runner.hooks import DistEvalHook, EvalHook
 
 from mmcls.core import DistOptimizerHook
 from mmcls.datasets import build_dataloader, build_dataset
 from mmcls.utils import get_root_logger
 
-# TODO import eval hooks from mmcv and delete them from mmcls
-try:
-    from mmcv.runner.hooks import EvalHook, DistEvalHook
-except ImportError:
-    warnings.warn('DeprecationWarning: EvalHook and DistEvalHook from mmcls '
-                  'will be deprecated.'
-                  'Please install mmcv through master branch.')
-    from mmcls.core import EvalHook, DistEvalHook
-
-# TODO import optimizer hook from mmcv and delete them from mmcls
-try:
-    from mmcv.runner import Fp16OptimizerHook
-except ImportError:
-    warnings.warn('DeprecationWarning: FP16OptimizerHook from mmcls will be '
-                  'deprecated. Please install mmcv>=1.1.4.')
-    from mmcls.core import Fp16OptimizerHook
-
 
 def init_random_seed(seed=None, device='cuda'):
     """Initialize random seed.

mmcls/core/__init__.py

@@ -1,6 +1,5 @@
 # Copyright (c) OpenMMLab. All rights reserved.
 from .evaluation import *  # noqa: F401, F403
-from .fp16 import *  # noqa: F401, F403
 from .hook import *  # noqa: F401, F403
 from .optimizers import *  # noqa: F401, F403
 from .utils import *  # noqa: F401, F403

mmcls/core/evaluation/__init__.py

@@ -1,12 +1,10 @@
 # Copyright (c) OpenMMLab. All rights reserved.
-from .eval_hooks import DistEvalHook, EvalHook
 from .eval_metrics import (calculate_confusion_matrix, f1_score, precision,
                            precision_recall_f1, recall, support)
 from .mean_ap import average_precision, mAP
 from .multilabel_eval_metrics import average_performance
 
 __all__ = [
-    'DistEvalHook', 'EvalHook', 'precision', 'recall', 'f1_score', 'support',
-    'average_precision', 'mAP', 'average_performance',
-    'calculate_confusion_matrix', 'precision_recall_f1'
+    'precision', 'recall', 'f1_score', 'support', 'average_precision', 'mAP',
+    'average_performance', 'calculate_confusion_matrix', 'precision_recall_f1'
 ]