code: def make_mirror_pad_tests(options):
      """Make a set of tests to do mirror_pad."""
  
      test_parameters = [
          {
              "input_shape": [[2, 3]],
              "padding_matrix": [[[1, 1], [2, 1]]],
              "mode": ["REFLECT"],
              "type": ["const"],
              "fully_quantize": [True, False],
          },
          {
              "input_shape": [[2, 3]],
              "padding_matrix": [[[1, 1], [1, 1]]],
              "mode": ["REFLECT"],
              "type": ["const"],
              "fully_quantize": [False],
          },
          {
              "input_shape": [[2, 3]],
              "padding_matrix": [[[1, 1], [2, 1]]],
              "mode": ["SYMMETRIC"],
              "type": ["placeholder"],
              "fully_quantize": [False],
          },
          {
              "input_shape": [[2, 3]],
              "padding_matrix": [[[1, 1], [2, 1]]],
              "mode": ["REFLECT"],
              "type": ["placeholder"],
              "fully_quantize": [False],
          },
          {
              "input_shape": [[3]],
              "padding_matrix": [[[0, 2]]],
              "mode": ["SYMMETRIC"],
              "type": ["placeholder"],
              "fully_quantize": [False],
          },
          {
              "input_shape": [[3]],
              "padding_matrix": [[[0, 2]]],
              "mode": ["SYMMETRIC"],
              "type": ["const"],
              "fully_quantize": [False],
          },
          {
              "input_shape": [[3]],
              "padding_matrix": [[[0, 2]]],
              "mode": ["REFLECT"],
              "type": ["const"],
              "fully_quantize": [False, True],
              "quant_16x8": [False, True],
          },
          {
              "input_shape": [[3, 2, 4, 5]],
              "padding_matrix": [[[1, 1], [2, 2], [1, 1], [1, 1]]],
              "mode": ["SYMMETRIC"],
              "type": ["placeholder"],
              "fully_quantize": [False],
          },
      ]
  
      def build_graph(parameters):
          """Build the graph for the test case."""
  
          input_tensor = tf.compat.v1.placeholder(
              dtype=tf.float32,
              name="input",
              shape=parameters["input_shape"],
          )
          if (
              parameters["type"] != "const"
              and not parameters["fully_quantize"]
          ):
              padding_matrix = tf.compat.v1.placeholder(
                  dtype=tf.int32,
                  name="padding",
                  shape=[len(parameters["input_shape"]), 2],
              )
              input_tensors = [input_tensor, padding_matrix]
          else:
              padding_matrix = tf.constant(
                  np.array(parameters["padding_matrix"])
              )
              input_tensors = [input_tensor]
          output = tf.pad(
              tensor=input_tensor,
              paddings=padding_matrix,
              mode=parameters["mode"],
          )
  
          return input_tensors, [output]
  
      def build_inputs(parameters, sess, inputs, outputs):
          if not parameters["fully_quantize"]:
              input_values = [
                  create_tensor_data(
                      tf.float32, parameters["input_shape"]
                  )
              ]
          else:
              input_values = [
                  create_tensor_data(
                      tf.float32,
                      parameters["input_shape"],
                      min_value=-1,
                      max_value=1,
                  )
              ]
          if parameters["type"] != "const":
              input_values.append(
                  np.array(parameters["padding_matrix"])
              )
          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 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_mirror_pad_tests(options) and returns: input_tensors,  list, input_values,  sess