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#data loader
batch_size = 32 # The batch size
num_workers = 0 # Subprocess for loading the data

train_loader = torch.utils.data.DataLoader(dataset=train_dataset, batch_size=batch_size, 
                                           num_workers=num_workers, shuffle=True) # shuffle every epoch in training set to avoid training biases

print(train_loader)
print(train_loader.__dict__) # Information held by the dataloader
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