code: def test_keras_saved_model_file(self):
      keras_model = tf.keras.Sequential(
          [
              tf.keras.layers.Flatten(
                  input_shape=(28, 28), batch_size=1
              ),
              tf.keras.layers.Dense(10, activation=tf.nn.relu),
          ]
      )
      keras_model.save(self.saved_model_dir, save_format="tf")
      mlmodel = converter.convert(
          self.saved_model_dir, 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 4 for calling the TestTf2ModelFormats obj's underlying member method code with example usage: obj.test_keras_saved_model_file() without return types