code: def test_unsupported_input_dtype_in_tf_graph_fp64(
      self, float64_input_model
  ):
      # test that no error is raised when no dtype is provided by the user,
      # and the TF graph's input dtype is not supported.
      # In this case, it will be mapped to the closest supported dtype
      mlmodel = ct.convert(
          float64_input_model,
          minimum_deployment_target=ct.target.macOS12,
      )
      assert_input_dtype(mlmodel, expected_type_str="fp32")
      verify_prediction(mlmodel)
  
imports: import itertools
  import os
  import tempfile
  import numpy
  import pytest
  import coremltools
  from coremltools._deps import _HAS_TF_1, _HAS_TF_2, MSG_TF1_NOT_FOUND
  from coremltools.converters.mil.testing_reqs import backends, compute_units
  from coremltools.converters.mil.testing_utils import assert_cast_ops_count, assert_input_dtype, assert_ops_in_mil_program, assert_output_dtype, assert_prog_input_type, assert_prog_output_type, assert_spec_input_image_type, assert_spec_output_image_type, get_op_types_in_program, verify_prediction
  from coremltools.proto import FeatureTypes_pb2
  from coremltools.test.api.test_api_examples import TestInputs
label_desc: Use image node_id 5 for calling the TestInputOutputConversionAPI obj's underlying member method code with example usage: obj.test_unsupported_input_dtype_in_tf_graph_fp64(float64_input_model) without return types