code: def make_unique_tests(options):
      """Make a set of tests for Unique op."""
  
      test_parameters = [
          {
              "input_shape": [[1]],
              "index_type": [tf.int32, tf.int64, None],
              "input_values": [3],
          },
          {
              "input_shape": [[5]],
              "index_type": [tf.int32, tf.int64],
              "input_values": [[3, 2, 1, 2, 3]],
          },
          {
              "input_shape": [[7]],
              "index_type": [tf.int32, tf.int64],
              "input_values": [[1, 1, 1, 1, 1, 1, 1]],
          },
          {
              "input_shape": [[5]],
              "index_type": [tf.int32, tf.int64],
              "input_values": [[3, 2, 1, 0, -1]],
          },
      ]
  
      def build_graph(parameters):
          """Build the graph for the test case."""
  
          input_tensor = tf.compat.v1.placeholder(
              dtype=tf.int32,
              name="input",
              shape=parameters["input_shape"],
          )
          if parameters["index_type"] is None:
              output = tf.unique(input_tensor)
          else:
              output = tf.unique(input_tensor, parameters["index_type"])
  
          return [input_tensor], output
  
      def build_inputs(parameters, sess, inputs, outputs):
          input_values = [
              create_tensor_data(tf.int32, parameters["input_shape"])
          ]
          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 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_unique_tests(options) and returns: list,  output, input_values,  sess