code: def make_one_hot_tests(options):
      """Make a set of tests to do one_hot."""
  
      test_parameters = [
          {
              "indices_type": [tf.int32, tf.int64],
              "indices_shape": [[3], [4, 4], [1, 5], [5, 1]],
              "axis": [0, 1],
              "dtype": [tf.int32, tf.int64, tf.float32],
              "provide_optional_inputs": [True, False],
          }
      ]
  
      def build_graph(parameters):
          """Build the one_hot op testing graph."""
          indices = tf.compat.v1.placeholder(
              dtype=parameters["indices_type"],
              name="indices",
              shape=parameters["indices_shape"],
          )
          depth = tf.compat.v1.placeholder(
              dtype=tf.int32, name="depth", shape=()
          )
  
          if not parameters["provide_optional_inputs"]:
              out = tf.one_hot(indices=indices, depth=depth)
              return [indices, depth], [out]
  
          on_value = tf.compat.v1.placeholder(
              dtype=parameters["dtype"], name="on_value", shape=()
          )
          off_value = tf.compat.v1.placeholder(
              dtype=parameters["dtype"], name="off_value", shape=()
          )
          out = tf.one_hot(
              indices=indices,
              depth=depth,
              on_value=on_value,
              off_value=off_value,
              axis=parameters["axis"],
              dtype=parameters["dtype"],
          )
          return [indices, depth, on_value, off_value], [out]
  
      def build_inputs(parameters, sess, inputs, outputs):
          """Build the input for one_hot op."""
          input_values = [
              create_tensor_data(
                  parameters["indices_type"],
                  shape=parameters["indices_shape"],
                  min_value=-1,
                  max_value=10,
              ),
              create_tensor_data(
                  tf.int32, shape=None, min_value=1, max_value=10
              ),
          ]
  
          if parameters["provide_optional_inputs"]:
              input_values.append(
                  create_tensor_data(
                      parameters["dtype"],
                      shape=None,
                      min_value=1,
                      max_value=10,
                  )
              )
              input_values.append(
                  create_tensor_data(
                      parameters["dtype"],
                      shape=None,
                      min_value=-1,
                      max_value=0,
                  )
              )
  
          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_one_hot_tests(options) and returns: list,  list, input_values,  sess, list,  list