To use PyTorch's DataLoader with multiple workers for generative model training, you can set the num_workers parameter to parallelize data loading.
Here is the code reference you can refer to:
In the above code, we are using the following:
Key insight: num_workers=4 enables parallel data loading, improving training efficiency for large datasets. Adjust the value based on your system's CPU capabilities.
Hence, by referring to the above you can use PyTorch s DataLoader with multiple workers for generative model training.