revise logging/logger.py for ci

Author: hanhaowen-mt

mmengine/hooks/empty_cache_hook.py

@@ -4,7 +4,7 @@
 import torch
 
 from mmengine.registry import HOOKS
-from ..device import is_cuda_available, is_musa_available
+from ..device import is_musa_available
 from .hook import Hook
 
 DATA_BATCH = Optional[Union[dict, tuple, list]]
@@ -50,9 +50,8 @@ def _after_iter(self,
             mode (str): Current mode of runner. Defaults to 'train'.
         """
         if self._do_after_iter:
-            if is_cuda_available():
-                torch.cuda.empty_cache()
-            elif is_musa_available():
+            torch.cuda.empty_cache()
+            if is_musa_available():
                 torch.musa.empty_cache()
 
     def _before_epoch(self, runner, mode: str = 'train') -> None:
@@ -63,9 +62,8 @@ def _before_epoch(self, runner, mode: str = 'train') -> None:
             mode (str): Current mode of runner. Defaults to 'train'.
         """
         if self._do_before_epoch:
-            if is_cuda_available():
-                torch.cuda.empty_cache()
-            elif is_musa_available():
+            torch.cuda.empty_cache()
+            if is_musa_available():
                 torch.musa.empty_cache()
 
     def _after_epoch(self, runner, mode: str = 'train') -> None:
@@ -76,7 +74,6 @@ def _after_epoch(self, runner, mode: str = 'train') -> None:
             mode (str): Current mode of runner. Defaults to 'train'.
         """
         if self._do_after_epoch:
-            if is_cuda_available():
-                torch.cuda.empty_cache()
-            elif is_musa_available():
+            torch.cuda.empty_cache()
+            if is_musa_available():
                 torch.musa.empty_cache()

mmengine/logging/logger.py

@@ -14,7 +14,6 @@
 
 from mmengine.utils import ManagerMixin
 from mmengine.utils.manager import _accquire_lock, _release_lock
-from ..device import is_cuda_available, is_musa_available
 
 
 class FilterDuplicateWarning(logging.Filter):
@@ -399,24 +398,17 @@ def _get_device_id():
     except ImportError:
         return 0
     else:
-        local_rank = int(os.getenv('LOCAL_RANK', '0'))
-        if is_cuda_available():
-            cuda_visible_devices = os.getenv('CUDA_VISIBLE_DEVICES', None)
-            if cuda_visible_devices is None:
-                num_device = torch.cuda.device_count()
-                cuda_visible_devices = list(range(num_device))
-            else:
-                cuda_visible_devices = cuda_visible_devices.split(',')
-            try:
-                return int(cuda_visible_devices[local_rank])
-            except ValueError:
-                # handle case for Multi-Instance GPUs
-                # see #1148 for details
-                return cuda_visible_devices[local_rank]
-        elif is_musa_available():
+        MUSA_AVAILABLE = False
+        try:
+            import torch_musa
+            MUSA_AVAILABLE = True
+        except ImportError:
+            pass
+        if MUSA_AVAILABLE:
+            local_rank = int(os.getenv('LOCAL_RANK', '0'))
             musa_visible_devices = os.getenv('MUSA_VISIBLE_DEVICES', None)
             if musa_visible_devices is None:
-                num_device = torch.musa.device_count()
+                num_device = torch_musa.device_count()
                 musa_visible_devices = list(range(num_device))
             else:
                 musa_visible_devices = musa_visible_devices.split(',')
@@ -427,8 +419,22 @@ def _get_device_id():
                 # see #1148 for details
                 return musa_visible_devices[local_rank]
         else:
+            local_rank = int(os.getenv('LOCAL_RANK', '0'))
             # TODO: return device id of npu and mlu.
-            return local_rank
+            if not torch.cuda.is_available():
+                return local_rank
+            cuda_visible_devices = os.getenv('CUDA_VISIBLE_DEVICES', None)
+            if cuda_visible_devices is None:
+                num_device = torch.cuda.device_count()
+                cuda_visible_devices = list(range(num_device))
+            else:
+                cuda_visible_devices = cuda_visible_devices.split(',')
+            try:
+                return int(cuda_visible_devices[local_rank])
+            except ValueError:
+                # handle case for Multi-Instance GPUs
+                # see #1148 for details
+                return cuda_visible_devices[local_rank]
 
 
 def _get_host_info() -> str:

tests/test_hooks/test_empty_cache_hook.py

@@ -1,15 +1,9 @@
 # Copyright (c) OpenMMLab. All rights reserved.
-import unittest
 from unittest.mock import patch
 
-from mmengine.device import is_musa_available
 from mmengine.testing import RunnerTestCase
 
 
-# TODO:[email protected]
-@unittest.skipIf(
-    is_musa_available(),
-    'torch_musa do not support torch.musa.reset_peak_memory_stats() yet')
 class TestEmptyCacheHook(RunnerTestCase):
 
     def test_with_runner(self):

tests/test_runner/test_log_processor.py

@@ -1,6 +1,5 @@
 # Copyright (c) OpenMMLab. All rights reserved.
 import copy
-import unittest
 from unittest.mock import MagicMock, patch
 
 import numpy as np
@@ -251,10 +250,7 @@ def test_collect_non_scalars(self):
         assert tag['metric1'] is metric1
         assert tag['metric2'] is metric2
 
-    # TODO:[email protected]
-    @unittest.skipIf(
-         is_musa_available(),
-         'musa backend do not support torch.cuda.reset_peak_memory_stats')
+    # TODO:[email protected] MUSA does not support it yet!
     @patch('torch.cuda.max_memory_allocated', MagicMock())
     @patch('torch.cuda.reset_peak_memory_stats', MagicMock())
     def test_get_max_memory(self):