code: def test_keras_h5_file(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)
      keras_model.save(self.model_path_h5, save_format="h5")
      mlmodel = converter.convert(
          self.model_path_h5,
          inputs=[TensorType(input_names[0], (3, 4, 5))],
          outputs=["Identity"],
          source=frontend,
      )
      assert mlmodel is not None
  
imports: import os
  import shutil
  import tempfile
  import pytest
  import coremltools.converters
  from coremltools.converters.mil.input_types import TensorType
  from coremltools.converters.mil.frontend.tensorflow.test.testing_utils import get_tf_keras_io_names
  from coremltools.converters.mil.frontend.tensorflow.test import testing_utils
  from coremltools.converters.mil.frontend.tensorflow2.test.testing_utils import make_tf2_graph, run_compare_tf2
  from coremltools.converters.mil.frontend.tensorflow.test.test_load import frontend, TestTf1ModelInputsOutputs
label_desc: Use image node_id 5 for calling the TestTf2ModelFormats obj's underlying member method code with example usage: obj.test_keras_h5_file() without return types