code: def make_broadcast_gradient_args_tests(options):
      """Make a set of tests to do broadcast_gradient_args."""
  
      test_parameters = [
          {
              "input_case": [
                  "ALL_EQUAL",
                  "ONE_DIM",
                  "NON_BROADCASTABLE",
              ],
              "dtype": [tf.dtypes.int32, tf.dtypes.int64],
          }
      ]
  
      def build_graph(parameters):
          """Build the op testing graph."""
          input1 = tf.compat.v1.placeholder(
              dtype=parameters["dtype"], name="input1"
          )
          input2 = tf.compat.v1.placeholder(
              dtype=parameters["dtype"], name="input2"
          )
          output1, output2 = tf.raw_ops.BroadcastGradientArgs(
              s0=input1, s1=input2
          )
          return [input1, input2], [output1, output2]
  
      def build_inputs(parameters, sess, inputs, outputs):
          dtype = parameters["dtype"].as_numpy_dtype()
  
          if parameters["input_case"] == "ALL_EQUAL":
              values = [
                  np.array([2, 4, 1, 3], dtype=dtype),
                  np.array([2, 4, 1, 3], dtype=dtype),
              ]
          elif parameters["input_case"] == "ONE_DIM":
              values = [
                  np.array([2, 4, 1, 3], dtype=dtype),
                  np.array([2, 1, 1, 3], dtype=dtype),
              ]
          elif parameters["input_case"] == "NON_BROADCASTABLE":
              values = [
                  np.array([2, 4, 1, 3], dtype=dtype),
                  np.array([2, 5, 1, 3], dtype=dtype),
              ]
          return values, sess.run(
              outputs, feed_dict=dict(zip(inputs, values))
          )
  
      extra_convert_options = ExtraConvertOptions()
      extra_convert_options.allow_custom_ops = True
      make_zip_of_tests(
          options,
          test_parameters,
          build_graph,
          build_inputs,
          extra_convert_options,
          expected_tf_failures=2,
      )
  
imports: import numpy
  import tensorflow
  from tensorflow.lite.testing.zip_test_utils import ExtraConvertOptions
  from tensorflow.lite.testing.zip_test_utils import make_zip_of_tests
  from tensorflow.lite.testing.zip_test_utils import register_make_test_function
label_desc: Use image node_id 1 for calling a global function with example usage: make_broadcast_gradient_args_tests(options) and returns: list,  list, values,  sess