class_docstr: The layer that calculates the GELU activation function
  for each element of the single input:
  :math:`f(x) = x * 0.5 * ( 1 + erf( x / sqrt(2) ) )` or approx.: `f(x) = x * sigmoid( 1.702 * x )`
  
  :param input_layer: The input layer and the number of its output. If no number
      is specified, the first output will be connected.
  :type input_layer: object, tuple(object, int)
  :param name: The layer name.
  :type name: str, default=None
  
  .. rubric:: Layer inputs:
  
  (1) a data blob of any size
  
  .. rubric:: Layer outputs:
  
  (1) a data blob of the same size as the input,
      with activation function values on each of the input elements
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docstr: 'precise' (calculate GELU using the error function) or 'sigmoid_approximate' (using an approximation x * sigmoid(1.702x))
          
docstr_tok: ["'precise","'","(","calculate","GELU","using","the","error","function",")","or","'sigmoid_approximate","'","(","using","an","approximation","x","*","sigmoid","(","1.702x",")",")"]
code: def calculation_mode(
      self,
  ) -> Literal["precise", "sigmoid_approximate"]:
      """'precise' (calculate GELU using the error function) or 'sigmoid_approximate' (using an approximation x * sigmoid(1.702x))"""
      return self._internal.get_calculation_mode()
  
imports: import neoml.PythonWrapper
  from .Dnn import Layer
  from neoml.Utils import check_input_layers
  import typing
label_desc: Use image node_id 2 for calling the GELU obj's underlying member method code with example usage: obj.calculation_mode() and returns: self