code: def gelu(x, approximate=False):
      """Gaussian error linear unit (GELU) activation function.
  
      The Gaussian error linear unit (GELU) is defined as:
  
      `gelu(x) = x * P(X <= x)` where `P(X) ~ N(0, 1)`,
      i.e. `gelu(x) = 0.5 * x * (1 + erf(x / sqrt(2)))`.
  
      GELU weights inputs by their value, rather than gating
      inputs by their sign as in ReLU.
  
      Args:
          x: Input tensor.
          approximate: A `bool`, whether to enable approximation.
  
      Reference:
  
      - [Hendrycks et al., 2016](https://arxiv.org/abs/1606.08415)
      """
      return ops.gelu(x, approximate=approximate)
  
imports: from keras import backend
  from keras import ops
  from keras.api_export import keras_export
label_desc: Use image node_id 10 for calling a global function with example usage: gelu(x, approximate) and returns: ops