code: def make_gather_nd_tests(options):
      """Make a set of tests to do gather_nd."""
  
      test_parameters = [
          {
              "params_dtype": [
                  tf.float32,
                  tf.int16,
                  tf.int32,
                  tf.int64,
                  tf.string,
                  tf.bool,
              ],
              "params_shape": [[5, 1]],
              "indices_dtype": [tf.int16, tf.int32, tf.int64],
              "indices_shape": [[1, 1]],
          },
          {
              "params_dtype": [
                  tf.float32,
                  tf.int16,
                  tf.int32,
                  tf.int64,
                  tf.string,
                  tf.bool,
              ],
              "params_shape": [[5, 5]],
              "indices_dtype": [tf.int16, tf.int32, tf.int64],
              "indices_shape": [[2, 1], [2, 2]],
          },
          {
              "params_dtype": [
                  tf.float32,
                  tf.int16,
                  tf.int32,
                  tf.int64,
                  tf.string,
                  tf.bool,
              ],
              "params_shape": [[5, 5, 10]],
              "indices_dtype": [tf.int16, tf.int32, tf.int64],
              "indices_shape": [[3, 1], [2, 2], [2, 3], [2, 1, 3]],
          },
          {
              "params_dtype": [tf.float32, tf.string],
              "params_shape": [[1, 0]],
              "indices_dtype": [tf.int64],
              "indices_shape": [[0, 2]],
          },
      ]
  
      def build_graph(parameters):
          """Build the gather_nd op testing graph."""
          params = tf.compat.v1.placeholder(
              dtype=parameters["params_dtype"],
              name="params",
              shape=parameters["params_shape"],
          )
          indices = tf.compat.v1.placeholder(
              dtype=parameters["indices_dtype"],
              name="indices",
              shape=parameters["indices_shape"],
          )
          out = tf.gather_nd(params, indices)
          return [params, indices], [out]
  
      def build_inputs(parameters, sess, inputs, outputs):
          params = create_tensor_data(
              parameters["params_dtype"], parameters["params_shape"]
          )
          indices = create_tensor_data(
              parameters["indices_dtype"],
              parameters["indices_shape"],
              0,
              parameters["params_shape"][0] - 1,
          )
          return [params, indices], sess.run(
              outputs, feed_dict=dict(zip(inputs, [params, indices]))
          )
  
      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_gather_nd_tests(options) and returns: list,  list, list,  sess