Thanks Thomas.  I tried the following and got an error.

for b, (image, label, policy) in enumerate(train_loader):
policy_list.append(policy.split.data.cpu().numpy())
image = Variable(image).cuda()
    with torch.no_grad():
        output = model(image)
        train_output.append(output.split.data.cpu().numpy())


The policy (ID) and image are tensors so should I split them, save those to a variable then append them to my list?