code: def make_l2norm_tests(options):
      """Make a set of tests to do l2norm."""
  
      # Chose a set of parameters
      test_parameters = [
          {
              "input_shape": [
                  [5, 7],
                  [1, 1, 1, 1],
                  [1, 3, 4, 3],
                  [3, 15, 14, 3],
              ],
              "dim": [0, 1, 2, 3, [2, 3], -2],
              "epsilon": [None, 1e-12, 1e-3],
              "fully_quantize": [False],
          },
          {
              "input_shape": [
                  [1, 1, 1, 1],
                  [1, 3, 4, 3],
                  [3, 15, 14, 3],
              ],
              "dim": [3],
              "epsilon": [None, 1e-12],
              "fully_quantize": [True],
          },
          {  # use another group of test so the dim is set to fuse to tfl.l2norm
              "input_shape": [[5, 7]],
              "dim": [1],
              "epsilon": [None, 1e-12],
              "fully_quantize": [True],
          },
      ]
  
      def build_graph(parameters):
          input_tensor = tf.compat.v1.placeholder(
              dtype=tf.float32,
              name="input",
              shape=parameters["input_shape"],
          )
          if parameters["epsilon"]:
              out = tf.nn.l2_normalize(
                  input_tensor,
                  parameters["dim"],
                  epsilon=parameters["epsilon"],
              )
          else:
              out = tf.nn.l2_normalize(input_tensor, parameters["dim"])
          return [input_tensor], [out]
  
      def build_inputs(parameters, sess, inputs, outputs):
          input_values = create_tensor_data(
              np.float32,
              parameters["input_shape"],
              min_value=-1,
              max_value=1,
          )
          return [input_values], sess.run(
              outputs, feed_dict=dict(zip(inputs, [input_values]))
          )
  
      make_zip_of_tests(
          options,
          test_parameters,
          build_graph,
          build_inputs,
          expected_tf_failures=9,
      )
  
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_l2norm_tests(options) and returns: list,  list, list,  sess