So awkward, I try to print those (see below) but the program  completely skips the prints, I use size because this is a line from the official document here (Fivecrop part: https://pytorch.org/docs/stable/torchvision/transforms.html 9
         label = label.cuda(async=True)
            input_var = Variable(data).cuda()
            
            #print len(input_var)
            target_var = Variable(label).cuda()
 
            bs, ncrops, c, h, w = input_var.size()
            print input_var.size
            result = self.model(input_var.view(-1, c, h, w)) # fuse batch size and ncrops
            print result.size

            # compute output
            output = self.model(result)
            print output.size
            loss = self.criterion(output, target_var)

Though this is the shape I get from the dataloader (no batch) = five crops, channels, dim, dim
==> Training data : 437  videos (5, 20, 224, 224)
==> Validation data : 2964  frames (5, 20, 224, 224)