code: def test(self, compute_unit, backend, rank, tf_op):
      if backend[0] == "neuralnetwork":
          pytest.skip("nn backend not supported")
  
      x_shape = tuple(np.random.randint(low=1, high=4, size=rank))
  
      @make_tf_graph([x_shape])
      def build_model(x):
          return tf_op(x)
  
      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 1 for calling the TestActivationSiLU obj's underlying member method code with example usage: obj.test(compute_unit, backend, rank, tf_op) and returns: tf_op