code: def test_graphdef_from_tf_function(self, backend):
      class build_model(tf.Module):
          def __init__(self):
              self.dense = tf.keras.layers.Dense(256, activation="relu")
  
          input_signature = [
              tf.TensorSpec(
                  name="input", shape=(128, 128), dtype=tf.float32
              ),
          ]
  
          @tf.function(input_signature=input_signature)
          def call(self, x):
              x = self.dense(x)
              return x
  
      model = build_model()
  
      from tensorflow.python.framework.convert_to_constants import (
          convert_variables_to_constants_v2,
      )
  
      frozen_graph_func = convert_variables_to_constants_v2(
          model.call.get_concrete_function()
      )
      frozen_graph_def = frozen_graph_func.graph.as_graph_def()
  
      mlmodel = converter.convert(
          frozen_graph_def, convert_to=backend[0]
      )
      assert mlmodel is not None
  
imports: import os
  import shutil
  import tempfile
  import pytest
  import coremltools.converters
  from coremltools.converters.mil.frontend.tensorflow.test.test_load import frontend
  from coremltools.converters.mil.frontend.tensorflow.test.testing_utils import get_tf_keras_io_names
  from coremltools.converters.mil.input_types import TensorType
  from coremltools.converters.mil.testing_reqs import backends
label_desc: Use image node_id 10 for calling the TestTf2ModelFormats obj's underlying member method code with example usage: obj.test_graphdef_from_tf_function(backend) and returns: x