parameters: (data: NodeInput, alpha: NumericType, name: Optional[str] = None)
return_statement: return _get_node_factory().create("Elu", [as_node(data)], {"alpha": alpha})
docstring: Perform Exponential Linear Unit operation element-wise on data from input node.
  
      Computes exponential linear: alpha * (exp(data) - 1) if < 0, data otherwise.
  
      For more information refer to:
      `Fast and Accurate Deep Network Learning by Exponential Linear Units (ELUs)
      <http://arxiv.org/abs/1511.07289>`_
  
      :param data: Input tensor. One of: input node, array or scalar.
      :param alpha: Scalar multiplier for negative values.
      :param name: Optional output node name.
      :return: The new node performing an ELU operation on its input data element-wise.
docstring_summary: Perform Exponential Linear Unit operation element-wise on data from input node.
docstring_tokens: Perform Exponential Linear Unit operation element - wise on data from input node .
function: def elu(data: NodeInput, alpha: NumericType, name: Optional[str] = None) -> Node:
      """Perform Exponential Linear Unit operation element-wise on data from input node.
  
      Computes exponential linear: alpha * (exp(data) - 1) if < 0, data otherwise.
  
      For more information refer to:
      `Fast and Accurate Deep Network Learning by Exponential Linear Units (ELUs)
      <http://arxiv.org/abs/1511.07289>`_
  
      :param data: Input tensor. One of: input node, array or scalar.
      :param alpha: Scalar multiplier for negative values.
      :param name: Optional output node name.
      :return: The new node performing an ELU operation on its input data element-wise.
      """
      return _get_node_factory().create("Elu", [as_node(data)], {"alpha": alpha})
function_tokens: def elu ( data : NodeInput , alpha : NumericType , name : Optional [ str ] = None ) -> Node : return _get_node_factory ( ) . create ( "Elu" , [ as_node ( data ) ] , { "alpha" : alpha } )