code: def model():
      return chainer.Sequential(
          L.Convolution2D(None, 16, 5, 1, 2),
          F.relu,
          L.Convolution2D(16, 8, 5, 1, 2),
          F.relu,
          L.Convolution2D(8, 5, 5, 1, 2),
          F.relu,
          L.Linear(None, 100),
          L.BatchNormalization(100),
          F.relu,
          L.Linear(100, 10),
      )
  
file_path: chainer/tests/onnx_chainer_tests/test_export_testcase.py
imports: import os
  import chainer
  import chainer.functions
  import chainer.links
  import numpy
  import onnx
  import pytest
  from onnx_chainer import export_testcase
  from onnx_chainer import export
label_desc: Use image node_id 1 for calling a global function with example usage: model() and returns: chainer