code: def simple_cnn():
      model = ModelHelper(
          name="r", arg_scope={"order": "NCHW", "is_test": True}
      )
      brew.conv(model, "data", "conv1", 3, 16, kernel=3, stride=1)
      brew.spatial_bn(model, "conv1", "conv1_spatbn", 16, epsilon=1e-3)
      brew.relu(model, "conv1_spatbn", "relu1")
      return model, [(1, 3, 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 6 for calling a global function with example usage: simple_cnn() and returns: model,  list