don't register the DummyDataset

open-mmlab · Oct 20, 2022 · 290fec3 · 290fec3
1 parent 12f346d
commit 290fec3
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Showing 2 changed files with 4 additions and 8 deletions.
diff --git a/tests/test_core/test_delivers/test_function_outputs_deliver.py b/tests/test_core/test_delivers/test_function_outputs_deliver.py
@@ -12,7 +12,6 @@
 from mmengine.logging import MMLogger
 from mmengine.model import BaseModel, ExponentialMovingAverage
 from mmengine.optim import OptimWrapper
-from mmengine.registry import DATASETS
 from mmengine.runner import Runner
 from torch.utils.data import Dataset
 
@@ -43,7 +42,6 @@ def forward(self, inputs, data_sample, mode='tensor'):
             return outputs
 
 
-@DATASETS.register_module()
 class DummyDataset(Dataset):
     METAINFO = dict()  # type: ignore
     data = torch.randn(12, 2)
@@ -133,12 +131,12 @@ def test_ema_hook(self):
         runner = Runner(
             model=model,
             train_dataloader=dict(
-                dataset=dict(type='DummyDataset'),
+                dataset=DummyDataset(),
                 sampler=dict(type='DefaultSampler', shuffle=True),
                 batch_size=3,
                 num_workers=0),
             val_dataloader=dict(
-                dataset=dict(type='DummyDataset'),
+                dataset=DummyDataset(),
                 sampler=dict(type='DefaultSampler', shuffle=False),
                 batch_size=3,
                 num_workers=0),

diff --git a/tests/test_core/test_recorders/test_func_inputs_recorder.py b/tests/test_core/test_recorders/test_func_inputs_recorder.py
@@ -12,7 +12,6 @@
 from mmengine.logging import MMLogger
 from mmengine.model import BaseModel, ExponentialMovingAverage
 from mmengine.optim import OptimWrapper
-from mmengine.registry import DATASETS
 from mmengine.runner import Runner
 from torch.utils.data import Dataset
 
@@ -45,7 +44,6 @@ def forward(self, inputs, data_sample, mode='tensor'):
             return outputs
 
 
-@DATASETS.register_module()
 class DummyDataset(Dataset):
     METAINFO = dict()  # type: ignore
     data = torch.randn(12, 2)
@@ -108,12 +106,12 @@ def test_ema_hook(self):
         runner = Runner(
             model=model,
             train_dataloader=dict(
-                dataset=dict(type='DummyDataset'),
+                dataset=DummyDataset(),
                 sampler=dict(type='DefaultSampler', shuffle=True),
                 batch_size=3,
                 num_workers=0),
             val_dataloader=dict(
-                dataset=dict(type='DummyDataset'),
+                dataset=DummyDataset(),
                 sampler=dict(type='DefaultSampler', shuffle=False),
                 batch_size=3,
                 num_workers=0),