修改test_mixdataloader中的工具函数名，防止被pytest执行

tests/core/dataloaders/torch_dataloader/test_mixdataloader.py

@@ -17,7 +17,7 @@ d2 = DataSet({'x': [[101, 201], [201, 301, 401], [100]] * 10, 'y': [20, 10, 10]
 d3 = DataSet({'x': [[1000, 2000], [0], [2000, 3000, 4000, 5000]] * 100, 'y': [100, 100, 200] * 100})
 
 
-def test_pad_val(tensor, val=0):
+def _test_pad_val(tensor, val=0):
     if isinstance(tensor, torch.Tensor):
         tensor = tensor.tolist()
     for item in tensor:
@@ -45,7 +45,7 @@ class TestMixDataLoader:
             if idx > 1:
                 # d3
                 assert batch['x'].shape == torch.Size([16, 4])
-            assert test_pad_val(batch['x'], val=0)
+            assert _test_pad_val(batch['x'], val=0)
 
         # collate_fn = Callable
         def collate_batch(batch):
@@ -74,13 +74,13 @@ class TestMixDataLoader:
         dl2 = MixDataLoader(datasets=datasets, mode='sequential', collate_fn=collate_fns, drop_last=True)
         for idx, batch in enumerate(dl2):
             if idx == 0:
-                assert test_pad_val(batch['x'], val=-1)
+                assert _test_pad_val(batch['x'], val=-1)
                 assert batch['x'].shape == torch.Size([16, 4])
             if idx == 1:
-                assert test_pad_val(batch['x'], val=-2)
+                assert _test_pad_val(batch['x'], val=-2)
                 assert batch['x'].shape == torch.Size([16, 3])
             if idx > 1:
-                assert test_pad_val(batch['x'], val=-3)
+                assert _test_pad_val(batch['x'], val=-3)
                 assert batch['x'].shape == torch.Size([16, 4])
 
         # sampler 为 str
@@ -101,7 +101,7 @@ class TestMixDataLoader:
             if idx > 1:
                 # d3
                 assert batch['x'].shape == torch.Size([16, 4])
-            assert test_pad_val(batch['x'], val=0)
+            assert _test_pad_val(batch['x'], val=0)
 
         for idx, batch in enumerate(dl4):
             if idx == 0:
@@ -118,7 +118,7 @@ class TestMixDataLoader:
             if idx > 1:
                 # d3
                 assert batch['x'].shape == torch.Size([16, 4])
-            assert test_pad_val(batch['x'], val=0)
+            assert _test_pad_val(batch['x'], val=0)
 
         # sampler 为 Dict
         samplers = {'d1': SequentialSampler(d1),
@@ -137,7 +137,7 @@ class TestMixDataLoader:
             if idx > 1:
                 # d3
                 assert batch['x'].shape == torch.Size([16, 4])
-            assert test_pad_val(batch['x'], val=0)
+            assert _test_pad_val(batch['x'], val=0)
 
         # ds_ratio 为 'truncate_to_least'
         dl6 = MixDataLoader(datasets=datasets, mode='sequential', ds_ratio='truncate_to_least', drop_last=True)
@@ -154,7 +154,7 @@ class TestMixDataLoader:
                 # d3
                 assert batch['x'][:3].tolist() == [[1000, 2000, 0, 0], [0, 0, 0, 0], [2000, 3000, 4000, 5000]]
                 assert batch['x'].shape == torch.Size([16, 4])
-            assert test_pad_val(batch['x'], val=0)
+            assert _test_pad_val(batch['x'], val=0)
             if idx > 2:
                 raise ValueError(f"ds_ratio: 'truncate_to_least' error")
 
@@ -170,7 +170,7 @@ class TestMixDataLoader:
             if 36 <= idx < 54:
                 # d3
                 assert batch['x'].shape == torch.Size([16, 4])
-            assert test_pad_val(batch['x'], val=0)
+            assert _test_pad_val(batch['x'], val=0)
             if idx >= 54:
                 raise ValueError(f"ds_ratio: 'pad_to_most' error")
 
@@ -187,7 +187,7 @@ class TestMixDataLoader:
             if 4 <= idx < 41:
                 # d3
                 assert batch['x'].shape == torch.Size([16, 4])
-            assert test_pad_val(batch['x'], val=0)
+            assert _test_pad_val(batch['x'], val=0)
             if idx >= 41:
                 raise ValueError(f"ds_ratio: 'pad_to_most' error")
 
@@ -201,7 +201,7 @@ class TestMixDataLoader:
                 # d3
                 assert batch['x'].shape == torch.Size([16, 4])
 
-            assert test_pad_val(batch['x'], val=0)
+            assert _test_pad_val(batch['x'], val=0)
             if idx >= 19:
                 raise ValueError(f"ds_ratio: 'pad_to_most' error")
 
@@ -209,7 +209,7 @@ class TestMixDataLoader:
         datasets = {'d1': d1, 'd2': d2, 'd3': d3}
         dl = MixDataLoader(datasets=datasets, mode='mix', collate_fn='auto', drop_last=True)
         for idx, batch in enumerate(dl):
-            assert test_pad_val(batch['x'], val=0)
+            assert _test_pad_val(batch['x'], val=0)
             if idx >= 22:
                 raise ValueError(f"out of range")
 
@@ -224,7 +224,7 @@ class TestMixDataLoader:
         dl1 = MixDataLoader(datasets=datasets, mode='mix', collate_fn=collate_batch, drop_last=True)
         for idx, batch in enumerate(dl1):
             assert isinstance(batch['x'], list)
-            assert test_pad_val(batch['x'], val=0)
+            assert _test_pad_val(batch['x'], val=0)
             if idx >= 22:
                 raise ValueError(f"out of range")
 
@@ -237,12 +237,12 @@ class TestMixDataLoader:
         # sampler 为 str
         dl3 = MixDataLoader(datasets=datasets, mode='mix', sampler='seq', drop_last=True)
         for idx, batch in enumerate(dl3):
-            assert test_pad_val(batch['x'], val=0)
+            assert _test_pad_val(batch['x'], val=0)
             if idx >= 22:
                 raise ValueError(f"out of range")
         dl4 = MixDataLoader(datasets=datasets, mode='mix', sampler='rand', drop_last=True)
         for idx, batch in enumerate(dl4):
-            assert test_pad_val(batch['x'], val=0)
+            assert _test_pad_val(batch['x'], val=0)
             if idx >= 22:
                 raise ValueError(f"out of range")
         # sampler 为 Dict
@@ -251,7 +251,7 @@ class TestMixDataLoader:
                     'd3': RandomSampler(d3)}
         dl5 = MixDataLoader(datasets=datasets, mode='mix', sampler=samplers, drop_last=True)
         for idx, batch in enumerate(dl5):
-            assert test_pad_val(batch['x'], val=0)
+            assert _test_pad_val(batch['x'], val=0)
             if idx >= 22:
                 raise ValueError(f"out of range")
         # ds_ratio 为 'truncate_to_least'
@@ -333,7 +333,7 @@ class TestMixDataLoader:
                 assert batch['x'].shape[1] == 4
             if idx > 20:
                 raise ValueError(f"out of range")
-            test_pad_val(batch['x'], val=0)
+            _test_pad_val(batch['x'], val=0)
 
         # collate_fn = Callable
         def collate_batch(batch):
@@ -361,16 +361,16 @@ class TestMixDataLoader:
         dl1 = MixDataLoader(datasets=datasets, mode='polling', collate_fn=collate_fns, batch_size=18)
         for idx, batch in enumerate(dl1):
             if idx == 0 or idx == 3:
-                assert test_pad_val(batch['x'], val=-1)
+                assert _test_pad_val(batch['x'], val=-1)
                 assert batch['x'][:3].tolist() == [[1, 2, -1, -1], [2, 3, 4, -1], [4, 5, 6, 7]]
                 assert batch['x'].shape[1] == 4
             elif idx == 1 or idx == 4:
                 # d2
-                assert test_pad_val(batch['x'], val=-2)
+                assert _test_pad_val(batch['x'], val=-2)
                 assert batch['x'][:3].tolist() == [[101, 201, -2], [201, 301, 401], [100, -2, -2]]
                 assert batch['x'].shape[1] == 3
             elif idx == 2 or 4 < idx <= 20:
-                assert test_pad_val(batch['x'], val=-3)
+                assert _test_pad_val(batch['x'], val=-3)
                 assert batch['x'][:3].tolist() == [[1000, 2000, -3, -3], [0, -3, -3, -3], [2000, 3000, 4000, 5000]]
                 assert batch['x'].shape[1] == 4
             if idx > 20:
@@ -392,7 +392,7 @@ class TestMixDataLoader:
                 assert batch['x'].shape[1] == 4
             if idx > 20:
                 raise ValueError(f"out of range")
-            test_pad_val(batch['x'], val=0)
+            _test_pad_val(batch['x'], val=0)
         for idx, batch in enumerate(dl3):
             if idx == 0 or idx == 3:
                 assert batch['x'].shape[1] == 4
@@ -403,7 +403,7 @@ class TestMixDataLoader:
                 assert batch['x'].shape[1] == 4
             if idx > 20:
                 raise ValueError(f"out of range")
-            test_pad_val(batch['x'], val=0)
+            _test_pad_val(batch['x'], val=0)
         # sampler 为 Dict
         samplers = {'d1': SequentialSampler(d1),
                     'd2': SequentialSampler(d2),
@@ -421,7 +421,7 @@ class TestMixDataLoader:
                 assert batch['x'].shape[1] == 4
             if idx > 20:
                 raise ValueError(f"out of range")
-            test_pad_val(batch['x'], val=0)
+            _test_pad_val(batch['x'], val=0)
 
         # ds_ratio 为 'truncate_to_least'
         dl5 = MixDataLoader(datasets=datasets, mode='polling', ds_ratio='truncate_to_least', batch_size=18)
@@ -438,7 +438,7 @@ class TestMixDataLoader:
                 assert batch['x'].shape[1] == 4
             if idx > 5:
                 raise ValueError(f"out of range")
-            test_pad_val(batch['x'], val=0)
+            _test_pad_val(batch['x'], val=0)
 
         # ds_ratio 为 'pad_to_most'
         dl6 = MixDataLoader(datasets=datasets, mode='polling', ds_ratio='pad_to_most', batch_size=18)
@@ -457,7 +457,7 @@ class TestMixDataLoader:
                 assert batch['x'].shape[1] == 4
             if idx >= 51:
                 raise ValueError(f"out of range")
-            test_pad_val(batch['x'], val=0)
+            _test_pad_val(batch['x'], val=0)
 
         # ds_ratio 为 Dict[str, float]
         ds_ratio = {'d1': 1.0, 'd2': 2.0, 'd3': 2.0}
@@ -475,7 +475,7 @@ class TestMixDataLoader:
                 assert batch['x'].shape[1] == 4
             if idx > 39:
                 raise ValueError(f"out of range")
-            test_pad_val(batch['x'], val=0)
+            _test_pad_val(batch['x'], val=0)
 
         ds_ratio = {'d1': 0.1, 'd2': 0.6, 'd3': 1.0}
         dl8 = MixDataLoader(datasets=datasets, mode='polling', ds_ratio=ds_ratio, batch_size=18)
@@ -493,4 +493,4 @@ class TestMixDataLoader:
 
             if idx > 18:
                 raise ValueError(f"out of range")
-            test_pad_val(batch['x'], val=0)
+            _test_pad_val(batch['x'], val=0)