Comments (1)
I don't know why this happened but I found out that if you use windows this will be solved by setting num_workers to zero
train_loader = torch.utils.data.DataLoader(train_dataset, batch_size=batch_size, shuffle=True,collate_fn=train_dataset.collate_fn, num_workers=workers,pin_memory=True)
from a-pytorch-tutorial-to-object-detection.
Related Issues (20)
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from a-pytorch-tutorial-to-object-detection.