code: def test_tf_image_resize(self, compute_unit, backend, size, method):
      if backend[0] == "mlprogram" and size == (1, 1):
          pytest.xfail(
              "rdar://79699954 (Nearest neighbor resize numerical mismatch when output size is (1,1))"
          )
  
      if backend[0] == "neuralnetwork":
          pytest.skip("nn backend not supported")
  
      x_shape = tuple(np.random.randint(low=1, high=3, size=4))
  
      @make_tf_graph([x_shape])
      def build_model(x):
          return tf.image.resize(x, size=size, method=method)
  
      model, inputs, outputs = build_model
      input_values = [
          random_gen(x_shape, -100, 100),
      ]
      input_dict = dict(zip(inputs, input_values))
      TensorFlowBaseTest.run_compare_tf(
          model,
          input_dict,
          outputs,
          compute_unit=compute_unit,
          backend=backend,
      )
  
imports: import itertools
  import numpy
  import pytest
  import coremltools
  from coremltools.converters.mil import testing_reqs
  from coremltools.converters.mil.frontend.tensorflow.test.testing_utils import TensorFlowBaseTest
  from coremltools.converters.mil.frontend.tensorflow2.test.testing_utils import TensorFlow2BaseTest
  from coremltools.converters.mil.frontend.tensorflow2.test.testing_utils import make_tf2_graph
  from coremltools.converters.mil.testing_utils import random_gen
label_desc: Use image node_id 3 for calling the TestResizeNearestNeighbor obj's underlying member method code with example usage: obj.test_tf_image_resize(compute_unit, backend, size, method) and returns: tf