class_docstr: The layer that divides its inputs element by element.
  
  :param input_layers: The input layers to be connected. 
      The integer in each tuple specifies the number of the output.
      If not set, the first output will be used.
  :type input_layers: list of object, tuple(object, int)
  :param name: The layer name.
  :type name: str, default=None
  
  .. rubric:: Layer inputs:
  
  The layer should have two inputs of the same size.
  
  .. rubric:: Layer outputs:
  
  The layer has one output of the same size as the inputs.
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code: def __init__(self, input_layers, name=None):
      if type(input_layers) is PythonWrapper.EltwiseDiv:
          super().__init__(input_layers)
          return
  
      layers, outputs = check_input_layers(input_layers, 0)
  
      internal = PythonWrapper.EltwiseDiv(str(name), layers, outputs)
      super().__init__(internal)
  
imports: import neoml.PythonWrapper
  from .Dnn import Layer
  from neoml.Utils import check_input_layers
label_desc: Use image node_id 1 to create a new EltwiseDiv object from inherited base classes: Layer with example: obj = EltwiseDiv(input_layers, name)