code: def test_gpu_trainable(module, num_encs):
      m = importlib.import_module(module)
      args = make_arg(num_encs=num_encs)
      model = m.E2E([2 for _ in range(num_encs)], 2, args)
      if "pytorch" in module:
          batch = prepare_inputs("pytorch", num_encs, is_cuda=True)
          model.cuda()
      loss = model(*batch)
      loss.backward()
  
imports: from __future__ import division
  import argparse
  import importlib
  import os
  import tempfile
  from test.utils_test import make_dummy_json
  import numpy
  import pytest
  import torch
  from espnet.nets.pytorch_backend.nets_utils import pad_list
  from espnet.utils.training.batchfy import make_batchset
label_desc: Use image node_id 12 for calling a global function with example usage: test_gpu_trainable(module, num_encs) without return types