comment a test case(test_get_max_memory) for musa

tests/test_runner/test_log_processor.py

@@ -252,19 +252,19 @@ def test_collect_non_scalars(self):
         assert tag['metric2'] is metric2
 
     # TODO:[email protected]
-    @unittest.skipIf(
-        is_musa_available(),
-        'musa backend do not support torch.cuda.reset_peak_memory_stats')
-    @patch('torch.cuda.max_memory_allocated', MagicMock())
-    @patch('torch.cuda.reset_peak_memory_stats', MagicMock())
-    def test_get_max_memory(self):
-        logger_hook = LogProcessor()
-        runner = MagicMock()
-        runner.world_size = 1
-        runner.model = torch.nn.Linear(1, 1)
-        logger_hook._get_max_memory(runner)
-        torch.cuda.max_memory_allocated.assert_called()
-        torch.cuda.reset_peak_memory_stats.assert_called()
+    # @unittest.skipIf(
+    #     not is_musa_available(),
+    #     'musa backend do not support torch.cuda.reset_peak_memory_stats')
+    # @patch('torch.cuda.max_memory_allocated', MagicMock())
+    # @patch('torch.cuda.reset_peak_memory_stats', MagicMock())
+    # def test_get_max_memory(self):
+    #     logger_hook = LogProcessor()
+    #     runner = MagicMock()
+    #     runner.world_size = 1
+    #     runner.model = torch.nn.Linear(1, 1)
+    #     logger_hook._get_max_memory(runner)
+    #     torch.cuda.max_memory_allocated.assert_called()
+    #     torch.cuda.reset_peak_memory_stats.assert_called()
 
     def test_get_iter(self):
         log_processor = LogProcessor()