code: def make_relu1_tests(options):
      """Make a set of tests to do relu1."""
  
      # Chose a set of parameters
      test_parameters = [
          {
              "input_shape": [
                  [],
                  [1, 1, 1, 1],
                  [1, 3, 4, 3],
                  [3, 15, 14, 3],
              ],
              "fully_quantize": [True, False],
              "input_range": [(-2, 8)],
          }
      ]
  
      def build_graph(parameters):
          input_tensor = tf.compat.v1.placeholder(
              dtype=tf.float32,
              name="input",
              shape=parameters["input_shape"],
          )
          # Note that the following is not supported:
          #   out = tf.maximum(-1.0, tf.minimum(input_tensor, 1.0))
          out = tf.minimum(1.0, tf.maximum(input_tensor, -1.0))
          return [input_tensor], [out]
  
      def build_inputs(parameters, sess, inputs, outputs):
          min_value, max_value = parameters["input_range"]
          input_values = create_tensor_data(
              np.float32,
              parameters["input_shape"],
              min_value,
              max_value,
          )
          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_relu1_tests(options) and returns: list,  list, list,  sess