code: def make_broadcast_args_tests(options):
      """Make a set of tests to do broadcast_args."""
  
      # Chose a set of parameters
      test_parameters = [
          {
              "dtype": [tf.int64, tf.int32],
              "input1_shape": [[1], [4], [3, 4], [1, 3, 4]],
              "input2_shape": [[6, 4, 3, 4]],
          },
          {
              "dtype": [tf.int64, tf.int32],
              "input1_shape": [[1, 4, 0]],
              "input2_shape": [[3, 1, 0], [3, 4, 1]],
          },
      ]
  
      def build_graph(parameters):
          """Build the graph for broadcast_args tests."""
          shape1_tensor = tf.compat.v1.placeholder(
              dtype=parameters["dtype"],
              name="input1",
              shape=[len(parameters["input1_shape"])],
          )
          shape2_tensor = tf.compat.v1.placeholder(
              dtype=parameters["dtype"],
              name="input2",
              shape=[len(parameters["input2_shape"])],
          )
  
          out = tf.raw_ops.BroadcastArgs(
              s0=shape1_tensor, s1=shape2_tensor
          )
          return [shape1_tensor, shape2_tensor], [out]
  
      def build_inputs(parameters, sess, inputs, outputs):
          input_values = [
              np.array(parameters["input1_shape"]).astype(
                  parameters["dtype"].as_numpy_dtype
              ),
              np.array(parameters["input2_shape"]).astype(
                  parameters["dtype"].as_numpy_dtype
              ),
          ]
          return input_values, sess.run(
              outputs, feed_dict=dict(zip(inputs, input_values))
          )
  
      make_zip_of_tests(
          options, test_parameters, build_graph, build_inputs
      )
  
imports: import numpy
  import tensorflow
  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_args_tests(options) and returns: list,  list, input_values,  sess