Haochenye/fix logging (#167)

* remove LoggerHook master_only

* remogve \t in log string

* fix lint

* Fix lint

mmengine/hooks/logger_hook.py

@@ -9,7 +9,6 @@ from typing import Optional, Sequence, Union
 
 import torch
 
-from mmengine.dist import master_only
 from mmengine.fileio import FileClient
 from mmengine.hooks import Hook
 from mmengine.registry import HOOKS
@@ -239,7 +238,6 @@ class LoggerHook(Hook):
                 runner.logger.info((f'{local_filepath} was removed due to the '
                                     '`self.keep_local=False`'))
 
-    @master_only
     def _log_train(self, runner) -> None:
         """Collect and record training logs which start named with "train/*".
 
@@ -272,9 +270,9 @@ class LoggerHook(Hook):
         # by iter:  Iter [100/100000]
         if self.by_epoch:
             log_str = f'Epoch [{cur_epoch}]' \
-                      f'[{cur_iter}/{len(runner.train_loop.dataloader)}]\t'
+                      f'[{cur_iter}/{len(runner.train_loop.dataloader)}] '
         else:
-            log_str = f'Iter [{cur_iter}/{runner.train_loop.max_iters}]\t'
+            log_str = f'Iter [{cur_iter}/{runner.train_loop.max_iters}] '
         log_str += f'{lr_momentum_str}, '
         # Calculate eta time.
         self.time_sec_tot += (tag['time'] * self.interval)
@@ -303,7 +301,6 @@ class LoggerHook(Hook):
         runner.writer.add_scalars(
             tag, step=runner.iter + 1, file_path=self.json_log_path)
 
-    @master_only
     def _log_val(self, runner) -> None:
         """Collect and record training logs which start named with "val/*".
 
@@ -321,9 +318,9 @@ class LoggerHook(Hook):
         # by iter: Iter[val] [1000]
         if self.by_epoch:
             # runner.epoch += 1 has been done before val workflow
-            log_str = f'Epoch(val) [{cur_epoch}][{eval_iter}]\t'
+            log_str = f'Epoch(val) [{cur_epoch}][{eval_iter}] '
         else:
-            log_str = f'Iter(val) [{eval_iter}]\t'
+            log_str = f'Iter(val) [{eval_iter}] '
 
         log_items = []
         for name, val in tag.items():

mmengine/visualization/writer.py

@@ -10,6 +10,7 @@ import numpy as np
 import torch
 
 from mmengine.data import BaseDataElement
+from mmengine.dist import master_only
 from mmengine.fileio import dump
 from mmengine.registry import VISUALIZERS, WRITERS
 from mmengine.utils import TORCH_VERSION, ManagerMixin
@@ -796,6 +797,7 @@ class ComposedWriter(ManagerMixin):
         for writer in self._writers:
             writer.add_scalar(name, value, step, **kwargs)
 
+    @master_only
     def add_scalars(self,
                     scalar_dict: dict,
                     step: int = 0,

tests/test_hook/test_logger_hook.py

@@ -161,7 +161,7 @@ class TestLoggerHook:
         eta_str = str(datetime.timedelta(seconds=int(eta_second)))
         if by_epoch:
             if torch.cuda.is_available():
-                log_str = 'Epoch [2][2/5]\t' \
+                log_str = 'Epoch [2][2/5] ' \
                           f"lr: {train_infos['lr']:.3e} " \
                           f"momentum: {train_infos['momentum']:.3e}, " \
                           f'eta: {eta_str}, ' \
@@ -170,7 +170,7 @@ class TestLoggerHook:
                           f'memory: 100, ' \
                           f"loss_cls: {train_infos['loss_cls']:.4f}\n"
             else:
-                log_str = 'Epoch [2][2/5]\t' \
+                log_str = 'Epoch [2][2/5] ' \
                           f"lr: {train_infos['lr']:.3e} " \
                           f"momentum: {train_infos['momentum']:.3e}, " \
                           f'eta: {eta_str}, ' \
@@ -180,7 +180,7 @@ class TestLoggerHook:
             assert out == log_str
         else:
             if torch.cuda.is_available():
-                log_str = 'Iter [11/50]\t' \
+                log_str = 'Iter [11/50] ' \
                           f"lr: {train_infos['lr']:.3e} " \
                           f"momentum: {train_infos['momentum']:.3e}, " \
                           f'eta: {eta_str}, ' \
@@ -189,7 +189,7 @@ class TestLoggerHook:
                           f'memory: 100, ' \
                           f"loss_cls: {train_infos['loss_cls']:.4f}\n"
             else:
-                log_str = 'Iter [11/50]\t' \
+                log_str = 'Iter [11/50] ' \
                           f"lr: {train_infos['lr']:.3e} " \
                           f"momentum: {train_infos['momentum']:.3e}, " \
                           f'eta: {eta_str}, ' \
@@ -212,11 +212,11 @@ class TestLoggerHook:
         runner.writer.add_scalars.assert_called_with(
             metric, step=11, file_path='tmp.json')
         if by_epoch:
-            assert out == 'Epoch(val) [1][5]\taccuracy: 0.9000, ' \
+            assert out == 'Epoch(val) [1][5] accuracy: 0.9000, ' \
                           'data_time: 1.0000\n'
 
         else:
-            assert out == 'Iter(val) [5]\taccuracy: 0.9000, ' \
+            assert out == 'Iter(val) [5] accuracy: 0.9000, ' \
                           'data_time: 1.0000\n'
 
     def test_get_window_size(self):