[Enhancement] Unify the use of print_log and logger

mmengine/model/base_module.py

@@ -95,15 +95,12 @@ def init_weights(self):
             for sub_module in self.modules():
                 sub_module._params_init_info = self._params_init_info
 
-        logger = MMLogger.get_current_instance()
-        logger_name = logger.instance_name
-
         module_name = self.__class__.__name__
         if not self._is_init:
             if self.init_cfg:
                 print_log(
                     f'initialize {module_name} with init_cfg {self.init_cfg}',
-                    logger=logger_name,
+                    logger='current',
                     level=logging.DEBUG)
 
                 init_cfgs = self.init_cfg
@@ -145,7 +142,6 @@ def init_weights(self):
                 level=logging.WARNING)
 
         if is_top_level_module:
-            # self._dump_init_info(logger_name)
             self._dump_init_info()
 
             for sub_module in self.modules():
@@ -154,14 +150,9 @@ def init_weights(self):
     @master_only
     def _dump_init_info(self):
         """Dump the initialization information to a file named
-        `initialization.log.json` in workdir.
-
-        Args:
-            logger_name (str): The name of logger.
-        """
+        `initialization.log.json` in workdir."""
 
         logger = MMLogger.get_current_instance()
-        logger_name = logger.instance_name
         with_file_handler = False
         # dump the information to the logger file if there is a `FileHandler`
         for handler in logger.handlers:
@@ -176,10 +167,9 @@ def _dump_init_info(self):
                 with_file_handler = True
         if not with_file_handler:
             for name, param in self.named_parameters():
-                print_log(
+                logger.info(
                     f'\n{name} - {param.shape}: '
-                    f"\n{self._params_init_info[param]['init_info']} \n ",
-                    logger=logger_name)
+                    f"\n{self._params_init_info[param]['init_info']} \n ")
 
     def __repr__(self):
         s = super().__repr__()

mmengine/model/utils.py

@@ -84,14 +84,13 @@ def traverse(grad_fn):
                     traverse(grad_fn)
 
     traverse(loss.grad_fn)
-    from mmengine.logging import MMLogger
-    logger = MMLogger.get_current_instance()
     for n, p in model.named_parameters():
         if p not in parameters_in_graph and p.requires_grad:
-            logger.log(
-                level=logging.ERROR,
-                msg=f'{n} with shape {p.size()} is not '
-                f'in the computational graph \n')
+            print_log(
+                f'{n} with shape {p.size()} is not '
+                f'in the computational graph \n',
+                logger='current',
+                level=logging.ERROR)
 
 
 def merge_dict(*args):

mmengine/runner/runner.py

@@ -1971,13 +1971,10 @@ def resume(self,
         current_seed = self._randomness_cfg.get('seed')
         if resumed_seed is not None and resumed_seed != current_seed:
             if current_seed is not None:
-                print_log(
-                    f'The value of random seed in the '
-                    f'checkpoint "{resumed_seed}" is '
-                    f'different from the value in '
-                    f'`randomness` config "{current_seed}"',
-                    logger='current',
-                    level=logging.WARNING)
+                self.logger.warning(f'The value of random seed in the '
+                                    f'checkpoint "{resumed_seed}" is '
+                                    f'different from the value in '
+                                    f'`randomness` config "{current_seed}"')
             self._randomness_cfg.update(seed=resumed_seed)
             self.set_randomness(**self._randomness_cfg)
 
@@ -1988,13 +1985,11 @@ def resume(self,
         # np.ndarray, which cannot be directly judged as equal or not,
         # therefore we just compared their dumped results.
         if pickle.dumps(resumed_dataset_meta) != pickle.dumps(dataset_meta):
-            print_log(
+            self.logger.warning(
                 'The dataset metainfo from the resumed checkpoint is '
                 'different from the current training dataset, please '
                 'check the correctness of the checkpoint or the training '
-                'dataset.',
-                logger='current',
-                level=logging.WARNING)
+                'dataset.')
 
         self.message_hub.load_state_dict(checkpoint['message_hub'])
 
@@ -2006,11 +2001,9 @@ def resume(self,
 
         # resume param scheduler
         if resume_param_scheduler and self.param_schedulers is None:
-            print_log(
+            self.logger.warning(
                 '`resume_param_scheduler` is True but `self.param_schedulers` '
-                'is None, so skip resuming parameter schedulers',
-                logger='current',
-                level=logging.WARNING)
+                'is None, so skip resuming parameter schedulers')
             resume_param_scheduler = False
         if 'param_schedulers' in checkpoint and resume_param_scheduler:
             self.param_schedulers = self.build_param_scheduler(  # type: ignore
@@ -2167,11 +2160,9 @@ def save_checkpoint(
 
         # save param scheduler state dict
         if save_param_scheduler and self.param_schedulers is None:
-            print_log(
+            self.logger.warning(
                 '`save_param_scheduler` is True but `self.param_schedulers` '
-                'is None, so skip saving parameter schedulers',
-                logger='current',
-                level=logging.WARNING)
+                'is None, so skip saving parameter schedulers')
             save_param_scheduler = False
         if save_param_scheduler:
             if isinstance(self.param_schedulers, dict):

mmengine/visualization/vis_backend.py

@@ -1,6 +1,7 @@
 # Copyright (c) OpenMMLab. All rights reserved.
 import copy
 import functools
+import logging
 import os
 import os.path as osp
 import warnings
@@ -13,7 +14,7 @@
 
 from mmengine.config import Config
 from mmengine.fileio import dump
-from mmengine.logging import MMLogger
+from mmengine.logging import print_log
 from mmengine.registry import VISBACKENDS
 from mmengine.utils.dl_utils import TORCH_VERSION
 
@@ -42,12 +43,13 @@ def wrapper(obj: object, *args, **kwargs):
         # `_env_initialized` is False, call `_init_env` and set
         # `_env_initialized` to True
         if not getattr(obj, '_env_initialized', False):
-            logger = MMLogger.get_current_instance()
-            logger.debug('Attribute `_env_initialized` is not defined in '
-                         f'{type(obj)} or `{type(obj)}._env_initialized is '
-                         'False, `_init_env` will be called and '
-                         f'{type(obj)}._env_initialized will be set to '
-                         'True')
+            print_log(
+                'Attribute `_env_initialized` is not defined in '
+                f'{type(obj)} or `{type(obj)}._env_initialized is '
+                'False, `_init_env` will be called and '
+                f'{type(obj)}._env_initialized will be set to True',
+                logger='current',
+                level=logging.DEBUG)
             obj._init_env()  # type: ignore
             obj._env_initialized = True  # type: ignore