code: def test_add_v2(self, compute_unit, backend, rank):
      x_shape = list(np.random.randint(low=2, high=5, size=rank))
      y_shape = x_shape[:]
      for i in range(rank):
          if np.random.randint(4) == 0:
              y_shape[i] = 1
      if np.random.randint(2) == 0:
          y_shape = [1] + y_shape
  
      @make_tf_graph([x_shape, y_shape])
      def build_model(x, y):
          return tf.raw_ops.AddV2(x=x, y=y)
  
      model, inputs, outputs = build_model
  
      input_values = [
          np.random.randint(low=-1, high=1, size=x_shape).astype(
              np.float32
          ),
          np.random.randint(low=-1, high=1, size=y_shape).astype(
              np.float32
          ),
      ]
  
      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 TestElementWiseBinaryTF2 obj's underlying member method code with example usage: obj.test_add_v2(compute_unit, backend, rank) and returns: tf