code: def test_tf_keras(self, backend):
      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,
          convert_to=backend[0],
      )
      assert mlmodel is not None
  
imports: import os
  import shutil
  import tempfile
  import numpy
  import pytest
  import coremltools
  import coremltools.converters
  import coremltools.proto.FeatureTypes_pb2
  from coremltools import EnumeratedShapes, ImageType, RangeDim, TensorType
  from coremltools._deps import _HAS_TF_1, _IS_MACOS, MSG_TF1_NOT_FOUND
  from coremltools.converters.mil.frontend.tensorflow.converter import TFConverter
  from coremltools.converters.mil.frontend.tensorflow.test.testing_utils import TensorFlowBaseTest, get_tf_keras_io_names, make_tf_graph
  from coremltools.converters.mil.testing_reqs import backends
  from coremltools.converters.mil.testing_utils import random_gen
label_desc: Use image node_id 6 for calling the TestTf1ModelFormats obj's underlying member method code with example usage: obj.test_tf_keras(backend) without return types