code: def test_relu6(self):
      relu6_vectorized = np.vectorize(_ref_relu6)
  
      # Test positive values less than 6
      positive_values = np.random.uniform(0, 5.9, (2, 5))
      result = activations.relu6(positive_values[np.newaxis, :])[0]
      expected = relu6_vectorized(positive_values)
      self.assertAllClose(result, expected, rtol=1e-05)
  
      # Test positive values greater than 6
      positive_values_above_6 = np.random.uniform(6.1, 10, (2, 5))
      result = activations.relu6(
          positive_values_above_6[np.newaxis, :]
      )[0]
      expected = relu6_vectorized(positive_values_above_6)
      self.assertAllClose(result, expected, rtol=1e-05)
  
      # Test negative values
      negative_values = np.random.uniform(-1, 0, (2, 5))
      result = activations.relu6(negative_values[np.newaxis, :])[0]
      expected = relu6_vectorized(negative_values)
      self.assertAllClose(result, expected, rtol=1e-05)
  
imports: import numpy
  from keras import activations
  from keras import backend
  from keras import testing
label_desc: Use image node_id 31 for calling the ActivationsTest obj's underlying member method code with example usage: obj.test_relu6() without return types