code: def check_model_expect(
      test_path, input_names=None, rtol=1e-5, atol=1e-5
  ):
      if not MXNET_AVAILABLE:
          raise ImportError("MXNet is not found on checking module.")
  
      model_path = os.path.join(test_path, "model.onnx")
      sym, arg, aux = mxnet.contrib.onnx.import_model(model_path)
  
      mx_input_names = [
          graph_input
          for graph_input in sym.list_inputs()
          if graph_input not in arg and graph_input not in aux
      ]
      if input_names is not None:
          assert list(sorted(input_names)) == list(
              sorted(mx_input_names)
          )
  
      test_data_sets = sorted(
          [
              p
              for p in os.listdir(test_path)
              if p.startswith("test_data_set_")
          ]
      )
      for test_data in test_data_sets:
          test_data_path = os.path.join(test_path, test_data)
          assert os.path.isdir(test_data_path)
          inputs, outputs = load_test_data(
              test_data_path, mx_input_names, sym.list_outputs()
          )
  
          data_shapes = [
              (name, array.shape) for name, array in inputs.items()
          ]
          mod = mxnet.mod.Module(
              symbol=sym,
              data_names=mx_input_names,
              context=mxnet.cpu(),
              label_names=None,
          )
          mod.bind(
              for_training=chainer.config.train,
              data_shapes=data_shapes,
              label_shapes=None,
          )
          mod.set_params(
              arg_params=arg,
              aux_params=aux,
              allow_missing=True,
              allow_extra=True,
          )
          Batch = collections.namedtuple("Batch", ["data"])
          mx_input = [
              mxnet.nd.array(array) for array in inputs.values()
          ]
          mod.forward(Batch(mx_input))
          mx_outputs = [y.asnumpy() for y in mod.get_outputs()]
          for cy, my in zip(outputs.values(), mx_outputs):
              np.testing.assert_allclose(cy, my, rtol=rtol, atol=atol)
  
imports: import collections
  import os
  import warnings
  import chainer
  import numpy
  from onnx_chainer.testing.test_onnxruntime import load_test_data
label_desc: Use image node_id 1 for calling a global function with example usage: check_model_expect(test_path, input_names, rtol, atol) without return types