code: def test_selu(self):
      alpha = 1.6732632423543772848170429916717
      scale = 1.0507009873554804934193349852946
  
      positive_values = np.array([[1, 2]], dtype=backend.floatx())
      result = activations.selu(positive_values[np.newaxis, :])[0]
      self.assertAllClose(result, positive_values * scale, rtol=1e-05)
  
      negative_values = np.array([[-1, -2]], dtype=backend.floatx())
      result = activations.selu(negative_values[np.newaxis, :])[0]
      true_result = (np.exp(negative_values) - 1) * scale * alpha
      self.assertAllClose(result, true_result)
  
imports: import numpy
  from keras import activations
  from keras import backend
  from keras import testing
label_desc: Use image node_id 16 for calling the ActivationsTest obj's underlying member method code with example usage: obj.test_selu() without return types