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)