code: def test_default_data_types(self, backend):
      @make_tf_graph([(2, 2)])
      def build_model(x):
          return tf.nn.relu(x)
  
      model, inputs, outputs = build_model
      mlmodel = converter.convert(model, convert_to=backend[0])
      assert mlmodel is not None
      spec = mlmodel.get_spec()
  
      # Defaults should be FLOAT32 instead of DOUBLE
      it = spec.description.input[0].type.multiArrayType.dataType
      assert it == ft.ArrayFeatureType.ArrayDataType.Value("FLOAT32")
      ot = spec.description.output[0].type.multiArrayType.dataType
      assert ot == ft.ArrayFeatureType.ArrayDataType.Value("FLOAT32")
  
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 15 for calling the TestTfModelInputsOutputs obj's underlying member method code with example usage: obj.test_default_data_types(backend) and returns: tf