code: def test_tf_keras(self):
      keras_model = tf.keras.Sequential(
          [tf.keras.layers.ReLU(input_shape=(4, 5), batch_size=3)]
      )
      input_names, output_names = get_tf_keras_io_names(keras_model)
      mlmodel = converter.convert(
          keras_model,
          inputs=[TensorType(input_names[0], (3, 4, 5))],
          outputs=["Identity"],
          source=frontend,
      )
      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 TestTf1ModelFormats obj's underlying member method code with example usage: obj.test_tf_keras() without return types