I have 4D data (N, 3, 64, 64) – basically N 64x64 RGB images where N is the set of rotations of the images – and I would like to use DataLoader.  So, the tensor shape I desire is (batch_size, N, 3, 64, 64).  However, it appears I can only feed DataLoader a tensor shape (batch_size, A, B, C).  So I could only get DataLoader to work by setting batch_size = 1, and let N be viewed as the size of the batch.  This approach does work, but it takes a very long time to train.  It would be nice to run multiple batches of (Nx3x64x64) simultaneously using DataLoader.  Is there a way to do this?  If so, could you please provide an example of how to implement it?