code: def make_topk_tests(options):
      """Make a set of tests to do topk."""
  
      test_parameters = [
          {
              "input_dtype": [tf.float32, tf.int32, tf.int16],
              "input_k_dtype": [tf.int32, tf.int16],
              "input_shape": [[10], [5, 20]],
              "input_k": [None, 1, 3],
              "output_index_dtype": [tf.int32, tf.int16],
          }
      ]
  
      def build_graph(parameters):
          """Build the topk op testing graph."""
          input_value = tf.compat.v1.placeholder(
              dtype=parameters["input_dtype"],
              name="input",
              shape=parameters["input_shape"],
          )
          if parameters["input_k"] is not None:
              k = tf.compat.v1.placeholder(
                  dtype=parameters["input_k_dtype"],
                  name="input_k",
                  shape=[],
              )
              inputs = [input_value, k]
          else:
              k = tf.constant(
                  3, name="k", dtype=parameters["input_k_dtype"]
              )
              inputs = [input_value]
          out = tf.nn.top_k(
              input_value,
              k,
              index_type=parameters["output_index_dtype"],
          )
          return inputs, [out[1]]
  
      def build_inputs(parameters, sess, inputs, outputs):
          input_value = create_tensor_data(
              parameters["input_dtype"], parameters["input_shape"]
          )
          if parameters["input_k"] is not None:
              k = np.array(
                  parameters["input_k"],
                  dtype=parameters["input_k_dtype"].as_numpy_dtype,
              )
              return [input_value, k], sess.run(
                  outputs, feed_dict=dict(zip(inputs, [input_value, k]))
              )
          else:
              return [input_value], sess.run(
                  outputs, feed_dict=dict(zip(inputs, [input_value]))
              )
  
      # TF currently does not support infering int16 scalar from tensor,
      # i.e. input_k = None x input_k_dtype = int16 cases.
      make_zip_of_tests(
          options,
          test_parameters,
          build_graph,
          build_inputs,
      )
  
imports: import numpy
  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_topk_tests(options) and returns: inputs,  list, list,  sess, list,  sess