code: def simple_resnet():
      model = ModelHelper(
          name="r", arg_scope={"order": "NCHW", "is_test": True}
      )
      resnet.create_resnet_32x32(
          model,
          "data",
          num_input_channels=1,
          num_groups=1,
          num_labels=5,
          is_test=True,
      )
      return model, [(1, 1, 32, 32)]
  
imports: import unittest
  import numpy
  import copy
  from hypothesis import given
  import hypothesis.strategies
  from caffe2.python.model_helper import ModelHelper
  from caffe2.python.models import resnet
  from caffe2.python import workspace, brew
  import caffe2.python.hypothesis_test_util
  import caffe2.python.mkl.rewrite_graph
label_desc: Use image node_id 8 for calling a global function with example usage: simple_resnet() and returns: model,  list