code: def elu(x, alpha=1.0):
      """Exponential Linear Unit.
  
      The exponential linear unit (ELU) with `alpha > 0` is define as:
  
      - `x` if `x > 0`
      - alpha * `exp(x) - 1` if `x < 0`
  
      ELUs have negative values which pushes the mean of the activations
      closer to zero.
  
      Mean activations that are closer to zero enable faster learning as they
      bring the gradient closer to the natural gradient.
      ELUs saturate to a negative value when the argument gets smaller.
      Saturation means a small derivative which decreases the variation
      and the information that is propagated to the next layer.
  
      Args:
          x: Input tensor.
  
      Reference:
  
      - [Clevert et al., 2016](https://arxiv.org/abs/1511.07289)
      """
      return ops.elu(x, alpha=alpha)
  
imports: from keras import backend
  from keras import ops
  from keras.api_export import keras_export
label_desc: Use image node_id 5 for calling a global function with example usage: elu(x, alpha) and returns: ops