[Refactor] Use `MMLogger` from MMEngine in `get_logger` and `print_log`.

mmcls/core/hook/precise_bn_hook.py

@@ -4,13 +4,13 @@
 
 import itertools
 import logging
-from typing import List, Optional
+from typing import List, Optional, Union
 
 import mmcv
 import torch
 import torch.nn as nn
 from mmcv.runner import EpochBasedRunner, get_dist_info
-from mmcv.utils import print_log
+from mmengine.logging import print_log
 from mmengine.hooks import Hook
 from torch.functional import Tensor
 from torch.nn import GroupNorm
@@ -52,10 +52,11 @@ def scaled_all_reduce(tensors: List[Tensor], num_gpus: int) -> List[Tensor]:
 
 
 @torch.no_grad()
-def update_bn_stats(model: nn.Module,
-                    loader: DataLoader,
-                    num_samples: int = 8192,
-                    logger: Optional[logging.Logger] = None) -> None:
+def update_bn_stats(
+        model: nn.Module,
+        loader: DataLoader,
+        num_samples: int = 8192,
+        logger: Optional[Union[logging.Logger, str]] = None) -> None:
     """Computes precise BN stats on training data.
 
     Args:
@@ -63,8 +64,15 @@ def update_bn_stats(model: nn.Module,
         loader (DataLoader): PyTorch dataloader._dataloader
         num_samples (int): The number of samples to update the bn stats.
             Defaults to 8192.
-        logger (:obj:`logging.Logger` | None): Logger for logging.
-            Default: None.
+        logger (logging.Logger or str, optional): If the type of logger is
+        ``logging.Logger``, we directly use logger to log messages.
+            Some special loggers are:
+            - "silent": No message will be printed.
+            - "current": Use latest created logger to log message.
+            - other str: Instance name of logger. The corresponding logger
+            will log message if it has been created, otherwise will raise a
+            `ValueError`.
+            - None: The `print()` method will be used to print log messages.
     """
     # get dist info
     rank, world_size = get_dist_info()

mmcls/datasets/dataset_wrappers.py

@@ -4,7 +4,7 @@ import math
 from collections import defaultdict
 
 import numpy as np
-from mmcv.utils import print_log
+from mmengine.logging import print_log
 from torch.utils.data.dataset import ConcatDataset as _ConcatDataset
 
 from mmcls.registry import DATASETS
@@ -57,8 +57,16 @@ class ConcatDataset(_ConcatDataset):
             indices (list, optional): The indices of samples corresponding to
                 the results. It's unavailable on ConcatDataset.
                 Defaults to None.
-            logger (logging.Logger | str, optional): Logger used for printing
-                related information during evaluation. Defaults to None.
+            logger (logging.Logger or str, optional): If the type of logger is
+            ``logging.Logger``, we directly use logger to log messages.
+                Some special loggers are:
+                - "silent": No message will be printed.
+                - "current": Use latest created logger to log message.
+                - other str: Instance name of logger. The corresponding logger
+                will log message if it has been created, otherwise will raise a
+                `ValueError`.
+                - None: The `print()` method will be used to print log
+                messages.
 
         Returns:
             dict[str: float]: AP results of the total dataset or each separate

mmcls/models/backbones/vision_transformer.py

@@ -316,7 +316,7 @@ class VisionTransformer(BaseBackbone):
 
         ckpt_pos_embed_shape = state_dict[name].shape
         if self.pos_embed.shape != ckpt_pos_embed_shape:
-            from mmcv.utils import print_log
+            from mmengine.logging import print_log
             logger = get_root_logger()
             print_log(
                 f'Resize the pos_embed shape from {ckpt_pos_embed_shape} '

mmcls/utils/logger.py

@@ -3,7 +3,7 @@ import json
 import logging
 from collections import defaultdict
 
-from mmcv.utils import get_logger
+from mmengine.logging import MMLogger
 
 
 def get_root_logger(log_file=None, log_level=logging.INFO):
@@ -17,7 +17,15 @@ def get_root_logger(log_file=None, log_level=logging.INFO):
     Returns:
         :obj:`logging.Logger`: The obtained logger
     """
-    return get_logger('mmcls', log_file, log_level)
+    try:
+        return MMLogger.get_instance(
+            'mmcls',
+            logger_name='mmcls',
+            log_file=log_file,
+            log_level=log_level)
+    except AssertionError:
+        # if root logger already existed, no extra kwargs needed.
+        return MMLogger.get_instance('mmcls')
 
 
 def load_json_log(json_log):

tests/test_runtime/test_preciseBN_hook.py

@@ -5,8 +5,7 @@ import torch
 import torch.nn as nn
 from mmcv.parallel import MMDataParallel, MMDistributedDataParallel
 from mmcv.runner import EpochBasedRunner, IterBasedRunner, build_optimizer
-from mmcv.utils import get_logger
-from mmcv.utils.logging import print_log
+from mmengine.logging import MMLogger, print_log
 from torch.utils.data import DataLoader, Dataset
 
 from mmcls.core.hook import PreciseBNHook
@@ -102,7 +101,7 @@ def test_precise_bn():
     loader = DataLoader(test_dataset, batch_size=2)
     model = ExampleModel()
     optimizer = build_optimizer(model, optimizer_cfg)
-    logger = get_logger('precise_bn')
+    logger = MMLogger.get_instance('precise_bn')
     runner = EpochBasedRunner(
         model=model,
         batch_processor=None,

tests/test_utils/test_logger.py

@@ -3,14 +3,13 @@ import os
 import os.path as osp
 import tempfile
 
-import mmcv.utils.logging
-
+from mmengine.logging import MMLogger
 from mmcls.utils import get_root_logger, load_json_log
 
 
 def test_get_root_logger():
-    # Reset the initialized log
-    mmcv.utils.logging.logger_initialized = {}
+    # set all logger instance
+    MMLogger._instance_dict = {}
     with tempfile.TemporaryDirectory() as tmpdirname:
         log_path = osp.join(tmpdirname, 'test.log')
 
@@ -33,7 +32,6 @@ def test_get_root_logger():
         for handler in handlers:
             handler.close()
             logger.removeHandler(handler)
-        os.remove(log_path)
 
 
 def test_load_json_log():

tools/visualizations/vis_cam.py

@@ -2,12 +2,12 @@
 import argparse
 import copy
 import math
-import pkg_resources
 import re
 from pathlib import Path
 
 import mmcv
 import numpy as np
+import pkg_resources
 from mmcv import Config, DictAction
 from mmcv.utils import to_2tuple
 from torch.nn import BatchNorm1d, BatchNorm2d, GroupNorm, LayerNorm