code: def _check_output_and_gradient(self, model_path, import_prefix=False):
      model = ModelTest_model(
          model_path=model_path, node_dict={"v1": "var1"}
      )
      input_name = "input:0"
      output_name = "output:0"
      if import_prefix:
          input_name = "import/" + input_name
          output_name = "import/" + output_name
      out = model.sess.run(output_name, feed_dict={input_name: 3})
      self.assertEqual(out, 333.0)
  
      model.loss = model.sess.graph.get_tensor_by_name(output_name)
  
      # Make sure that loaded graph can be modified
      model._make_gradient_tensors()
      grad = model.sess.run(
          model.bottlenecks_gradients["v1"], feed_dict={input_name: 555}
      )
      self.assertEqual(grad, 555.0)
  
file_path: tcav/tcav/model_test.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import tensorflow
  from tensorflow.python.framework import graph_util
  from tensorflow.python.platform import googletest
  from tcav.model import ModelWrapper
label_desc: Use image node_id 3 for calling the ModelTest obj's underlying member method code with example usage: obj._check_output_and_gradient(model_path, import_prefix) without return types