code: def test_infer_inputs_and_outputs(self):
      x_shape = (3, 4, 5)
  
      @make_tf_graph([x_shape])
      def build_model(x):
          return tf.nn.relu(x)
  
      model, inputs, outputs = build_model
      mlmodel = converter.convert(model)
      assert mlmodel is not None
  
      input_values = [random_gen(x_shape, -10.0, 10.0)]
      input_dict = dict(zip(inputs, input_values))
      run_compare_tf(model, input_dict, outputs)
  
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 5 for calling the TestTf1ModelInputsOutputs obj's underlying member method code with example usage: obj.test_infer_inputs_and_outputs() and returns: tf