def test_replace_sampler_with_multiprocessing_context(tmpdir):
"""
This test verifies that replace_sampler conserves multiprocessing context
"""
train = RandomDataset(32, 64)
context = 'spawn'
train = DataLoader(train,
batch_size=32,
num_workers=2,
multiprocessing_context=context,
shuffle=True)
class ExtendedBoringModel(BoringModel):
def train_dataloader(self):
return train
trainer = Trainer(
max_epochs=1,
progress_bar_refresh_rate=20,
overfit_batches=5,
)
new_data_loader = trainer.replace_sampler(train,
SequentialSampler(train.dataset))
assert (new_data_loader.multiprocessing_context ==
train.multiprocessing_context)
def test_dataloader(self):
return torch.utils.data.DataLoader(RandomDataset(32, 64))
def val_dataloader(self):
dl1 = torch.utils.data.DataLoader(RandomDataset(32, 64))
dl2 = torch.utils.data.DataLoader(RandomDataset(32, 64))
return [dl1, dl2]
def train_dataloader(self):
seed_everything(42)
return torch.utils.data.DataLoader(RandomDataset(32, 64))
def test_dataloader(self):
return [torch.utils.data.DataLoader(RandomDataset(32, 64)) for _ in range(num_dataloaders)]
def val_dataloader(self):
return [
torch.utils.data.DataLoader(RandomDataset(32, 64)),
torch.utils.data.DataLoader(RandomDataset(32, 64))
]
def test_dataloader(self):
return DataLoader(RandomDataset(32, 64), batch_size=4)