class_docstr: Rectified Linear Unit (ReLu) activation function, :math:`f(x) = \max(x, 0)`.
  Can optionally set a slope which will make this a Leaky ReLu.
docstr: Returns the Exponential Linear activation
  
  Arguments:
      x (Tensor or optree): Input value
  
  Returns:
      Tensor or optree: output activation
docstr_tok: ["Returns","the","Exponential","Linear","activation","Arguments",":","x","(","Tensor","or","optree",")",":","Input","value","Returns",":","Tensor","or","optree",":","output","activation"]
code: def __call__(self, x, nglayer=None):
      """
      Returns the Exponential Linear activation
  
      Arguments:
          x (Tensor or optree): Input value
  
      Returns:
          Tensor or optree: output activation
      """
      return self.be.fprop_relu(nglayer, x, self.slope)
  
imports: from __future__ import division
  from neon.transforms.transform import Transform
label_desc: Use image node_id 2 for calling the Rectlin obj's underlying member method code with example usage: obj.__call__(x, nglayer) and returns: self