refactor evaluation

mmcls/evaluation/__init__.py

@@ -0,0 +1,2 @@
+# Copyright (c) OpenMMLab. All rights reserved.
+from .metrics import *  # noqa: F401,F403

mmcls/evaluation/metrics/multi_label.py

@@ -56,7 +56,7 @@ class MultiLabelMetric(BaseMetric):
 
     Examples:
         >>> import torch
-        >>> from mmcls.metrics import MultiLabelMetric
+        >>> from mmcls.evaluation import MultiLabelMetric
         >>> # ------ The Basic Usage for category indices labels -------
         >>> y_pred = [[0], [1], [0, 1], [3]]
         >>> y_true = [[0, 3], [0, 2], [1], [3]]
@@ -444,7 +444,7 @@ class AveragePrecision(BaseMetric):
 
     Examples:
         >>> import torch
-        >>> from mmcls.metrics import AveragePrecision
+        >>> from mmcls.evaluation import AveragePrecision
         >>> # --------- The Basic Usage for one-hot pred scores ---------
         >>> y_pred = torch.Tensor([[0.9, 0.8, 0.3, 0.2],
         ...                        [0.1, 0.2, 0.2, 0.1],

mmcls/evaluation/metrics/single_label.py

@@ -73,7 +73,7 @@ class Accuracy(BaseMetric):
 
     Examples:
         >>> import torch
-        >>> from mmcls.metrics import Accuracy
+        >>> from mmcls.evaluation import Accuracy
         >>> # -------------------- The Basic Usage --------------------
         >>> y_pred = [0, 2, 1, 3]
         >>> y_true = [0, 1, 2, 3]
@@ -311,7 +311,7 @@ class SingleLabelMetric(BaseMetric):
 
     Examples:
         >>> import torch
-        >>> from mmcls.metrics import SingleLabelMetric
+        >>> from mmcls.evaluation import SingleLabelMetric
         >>> # -------------------- The Basic Usage --------------------
         >>> y_pred = [0, 1, 1, 3]
         >>> y_true = [0, 2, 1, 3]

mmcls/models/heads/cls_head.py

@@ -5,7 +5,7 @@ import torch
 import torch.nn.functional as F
 
 from mmcls.data import ClsDataSample
-from mmcls.metrics import Accuracy
+from mmcls.evaluation.metrics import Accuracy
 from mmcls.registry import MODELS
 from .base_head import BaseHead
 

mmcls/models/heads/conformer_head.py

@@ -5,7 +5,7 @@ import torch
 import torch.nn as nn
 
 from mmcls.data import ClsDataSample
-from mmcls.metrics import Accuracy
+from mmcls.evaluation.metrics import Accuracy
 from mmcls.registry import MODELS
 from .cls_head import ClsHead
 

mmcls/utils/setup_env.py

@@ -76,7 +76,7 @@ def register_all_modules(init_default_scope: bool = True) -> None:
     import mmcls.data  # noqa: F401,F403
     import mmcls.datasets  # noqa: F401,F403
     import mmcls.engine  # noqa: F401,F403
-    import mmcls.metrics  # noqa: F401,F403
+    import mmcls.evaluation  # noqa: F401,F403
     import mmcls.models  # noqa: F401,F403
     import mmcls.visualization  # noqa: F401,F403
 

tests/test_evaluation/test_metrics/test_multi_label.py

@@ -7,7 +7,7 @@ import torch
 from mmengine.evaluator import Evaluator
 
 from mmcls.data import ClsDataSample
-from mmcls.metrics import AveragePrecision, MultiLabelMetric
+from mmcls.evaluation.metrics import AveragePrecision, MultiLabelMetric
 from mmcls.utils import register_all_modules
 
 register_all_modules()

tests/test_evaluation/test_metrics/test_single_label.py

@@ -6,7 +6,7 @@ import numpy as np
 import torch
 
 from mmcls.data import ClsDataSample
-from mmcls.metrics import Accuracy, SingleLabelMetric
+from mmcls.evaluation.metrics import Accuracy, SingleLabelMetric
 from mmcls.registry import METRICS