code: def test_extract_sub_model(self):
      x_shape = (3, 4, 5)
      y_shape = (3, 4, 5)
  
      @make_tf_graph([x_shape, y_shape])
      def build_model(x, y):
          return tf.nn.relu(x), tf.math.add(x, y)
  
      model, inputs, outputs = build_model
      if isinstance(outputs[0], six.string_types):
          first_output_name = outputs[0]
      else:
          first_output_name = outputs[0].name.split(":")[0]
      mlmodel = converter.convert(model, outputs=[first_output_name])
      assert mlmodel is not None
  
imports: import numpy
  import os
  import six
  import pytest
  import shutil
  import tempfile
  import coremltools
  import coremltools.converters
  from coremltools._deps import _IS_MACOS
  import coremltools.proto.FeatureTypes_pb2
  from coremltools import TensorType, ImageType, RangeDim, EnumeratedShapes
  from coremltools.converters.mil.testing_utils import random_gen
  from coremltools.converters.mil.frontend.tensorflow.converter import TFConverter
  from coremltools.converters.mil.frontend.tensorflow.test.testing_utils import frontend, make_tf_graph, run_compare_tf, get_tf_keras_io_names
label_desc: Use image node_id 6 for calling the TestTf1ModelInputsOutputs obj's underlying member method code with example usage: obj.test_extract_sub_model() and returns: tf,  tf