IndexError: theta transpose

[gauravkuppa]

I am working off of the PyTorch branch, and I am trying to use different data with DTAN. For some data, the PyTorch branch works perfectly well.

For other data, I get this following error: IndexError: Dimension out of range (expected to be in range of [-1, 0], but got 1)

Here is the traceback:

Traceback (most recent call last):
  File "/home/dtan/examples/UCR_alignment.py", line 115, in <module>
    run_UCR_alignment(args, dataset_name='pcgg_first_fourth')#, dataset_name="pfi_transfer_ECG")
  File "/home/dtan/examples/UCR_alignment.py", line 102, in run_UCR_alignment
    model = train(args, train_loader, validation_loader, DTANargs, Experiment, print_model=True)
  File "/home/dtan/models/train_model.py", line 40, in train
    train_loss = train_epoch(train_loader, device, optimizer, model, channels, DTANargs)
  File "/home/dtan/models/train_model.py", line 72, in train_epoch
    loss = alignment_loss(output, target, thetas, channels, DTANargs)
  File "/home/dtan/DTAN/alignment_loss.py", line 40, in alignment_loss
    prior_loss += 0.1*smoothness_norm(DTANargs.T, theta, DTANargs.lambda_smooth, DTANargs.lambda_var, print_info=False)
  File "/home/dtan/DTAN/smoothness_prior.py", line 103, in smoothness_norm
    theta_T = torch.transpose(theta, 0, 1)
IndexError: Dimension out of range (expected to be in range of [-1, 0], but got 1)

Any idea what might be causing this? Is there anything I have to do to the data to allow it to the data to make it work?

Thank you!

[Ron Shapira Weber]

Completely missed this issue, terribly sorry!

The issue was fixed.
It happens when the per-class batchsize=1, which might happen for the validation set.
There was a redundant torch.squeeze at the prior computation which removed the batch dim. I have removed it and it seems to fix this issue.

Ron