code: def elu(x, out=None):
      """
      Exponential linear (unit) transfer function.
  
      Parameters
      ----------
      x : numpy array
          Input data.
      out : numpy array, optional
          Array to hold the output data.
  
      Returns
      -------
      numpy array
          Exponential linear of input data
  
      References
      ----------
      .. [1] Djork-Arné Clevert, Thomas Unterthiner, Sepp Hochreiter (2015):
         Fast and Accurate Deep Network Learning by Exponential Linear Units
         (ELUs), http://arxiv.org/abs/1511.07289
      """
      if out is None:
          out = x.copy()
      elif out is not x:
          out[:] = x[:]
      m = x < 0
      out[m] = np.exp(x[m]) - 1
      return out
  
file_path: madmom/madmom/ml/nn/activations.py
imports: from __future__ import absolute_import, division, print_function
  import numpy
label_desc: Use image node_id 5 for calling a global function with example usage: elu(x, out) and returns: out