This (adding .item() to each tensor) worked for me:
    if batch_idx % args.log_interval == 0:
        print('Train Epoch: {} [{}/{}]\t'
              'Loss: {:.4f} ({:.4f}) \t'
              'Acc: {:.2f}% ({:.2f}%) \t'
              'Emb_Norm: {:.2f} ({:.2f})'.format(
            epoch, batch_idx * num_items, len(train_loader.dataset),
            losses.val.item(), losses.avg.item(), 
            100. * accs.val.item(), 100. * accs.avg.item(), emb_norms.val.item(), emb_norms.avg.item()))