Pin memory in dataloaders by default
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@ -19,11 +19,11 @@ def create_dataloader(dataset, dataset_opt, opt=None, sampler=None):
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shuffle = True
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shuffle = True
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return torch.utils.data.DataLoader(dataset, batch_size=batch_size, shuffle=shuffle,
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return torch.utils.data.DataLoader(dataset, batch_size=batch_size, shuffle=shuffle,
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num_workers=num_workers, sampler=sampler, drop_last=True,
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num_workers=num_workers, sampler=sampler, drop_last=True,
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pin_memory=False)
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pin_memory=True)
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else:
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else:
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batch_size = dataset_opt['batch_size'] or 1
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batch_size = dataset_opt['batch_size'] or 1
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return torch.utils.data.DataLoader(dataset, batch_size=batch_size, shuffle=False, num_workers=max(int(batch_size/2), 1),
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return torch.utils.data.DataLoader(dataset, batch_size=batch_size, shuffle=False, num_workers=max(int(batch_size/2), 1),
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pin_memory=False)
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pin_memory=True)
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def create_dataset(dataset_opt):
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def create_dataset(dataset_opt):
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