code: def make_tile_tests(options):
      """Make a set of tests to do tile."""
      test_parameters = [
          {
              "input_dtype": [tf.float32, tf.int32, tf.bool, tf.string],
              "input_shape": [[3, 2, 1], [2, 2, 2]],
              "multiplier_dtype": [tf.int32, tf.int64],
              "multiplier_shape": [[3]],
          },
          {
              "input_dtype": [tf.float32, tf.int32],
              "input_shape": [[]],
              "multiplier_dtype": [tf.int32, tf.int64],
              "multiplier_shape": [[0]],
          },
          {
              "input_dtype": [tf.float32],
              "input_shape": [[3, 2, 1]],
              "multiplier_dtype": [tf.int32, tf.int64],
              "multiplier_shape": [[3]],
              "fully_quantize": [True],
              # The input range is used to create representative dataset for both
              # input and multiplier so it needs to be positive.
              "input_range": [(1, 10)],
          },
      ]
  
      def build_graph(parameters):
          """Build the tile op testing graph."""
          input_value = tf.compat.v1.placeholder(
              dtype=parameters["input_dtype"],
              shape=parameters["input_shape"],
              name="input",
          )
          multiplier_value = tf.compat.v1.placeholder(
              dtype=parameters["multiplier_dtype"],
              shape=parameters["multiplier_shape"],
              name="multiplier",
          )
          out = tf.tile(input_value, multiplier_value)
          return [input_value, multiplier_value], [out]
  
      def build_inputs(parameters, sess, inputs, outputs):
          min_value, max_value = parameters.get(
              "input_range", (-10, 10)
          )
          input_value = create_tensor_data(
              parameters["input_dtype"],
              parameters["input_shape"],
              min_value=min_value,
              max_value=max_value,
          )
          multipliers_value = create_tensor_data(
              parameters["multiplier_dtype"],
              parameters["multiplier_shape"],
              min_value=0,
          )
          return [input_value, multipliers_value], sess.run(
              outputs,
              feed_dict={
                  inputs[0]: input_value,
                  inputs[1]: multipliers_value,
              },
          )
  
      make_zip_of_tests(
          options, test_parameters, build_graph, build_inputs
      )
  
imports: import tensorflow
  from tensorflow.lite.testing.zip_test_utils import create_tensor_data
  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_tile_tests(options) and returns: list,  list, list,  sess