code: def test_rrelu_old(dtype, training):
      x = tf.constant([-2.0, -1.0, 0.0, 1.0, 2.0], dtype=dtype)
      lower = 0.1
      upper = 0.2
  
      tf.random.set_seed(SEED)
      training_results = {
          np.float16: [-0.288330078, -0.124206543, 0, 1, 2],
          np.float32: [-0.26851666, -0.116421416, 0, 1, 2],
          np.float64: [
              -0.3481333923206531,
              -0.17150176242558851,
              0,
              1,
              2,
          ],
      }
      result = rrelu(x, lower, upper, training=training, seed=SEED)
      if training:
          expect_result = training_results.get(dtype)
      else:
          expect_result = [
              -0.30000001192092896,
              -0.15000000596046448,
              0,
              1,
              2,
          ]
      test_utils.assert_allclose_according_to_type(
          result, expect_result
      )
  
imports: import pytest
  import numpy
  import tensorflow
  from tensorflow_addons.activations import rrelu
  from tensorflow_addons.utils import test_utils
label_desc: Use image node_id 1 for calling a global function with example usage: test_rrelu_old(dtype, training) without return types