code: def make_splitv_tests(options):
      """Make a set of tests to do tf.split_v."""
  
      test_parameters = [
          {
              "input_shape": [[1, 3, 4, 6], [2, 4, 1], [6, 4], [8]],
              "size_splits": [
                  [2, 2],
                  [1, 3],
                  [4, 2],
                  [5, 3],
                  [-1, 1],
                  [-1, 2],
                  [-1, 4],
              ],
              "axis": [0, 1, 2, 3, -4, -3, -2, -1],
          }
      ]
  
      def build_graph(parameters):
          input_tensor = tf.compat.v1.placeholder(
              dtype=tf.float32,
              name="input",
              shape=parameters["input_shape"],
          )
          out = tf.split(
              input_tensor,
              parameters["size_splits"],
              parameters["axis"],
          )
          return [input_tensor], [out[0]]
  
      def build_inputs(parameters, sess, inputs, outputs):
          values = [
              create_tensor_data(np.float32, parameters["input_shape"])
          ]
          return values, sess.run(
              outputs, feed_dict=dict(zip(inputs, values))
          )
  
      make_zip_of_tests(
          options,
          test_parameters,
          build_graph,
          build_inputs,
          expected_tf_failures=158,
      )
  
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_splitv_tests(options) and returns: list,  list, values,  sess