class_docstr: The Average module outputs the element-wise average of the outputs from multiple modules.
  
  Parameters
  ----------
  module_list: list
      The list of modules.
  weight: float 
      A value elementwise multiplied to module outputs.
  scope: str, optional
      Scope for module variables.
  reuse: bool, optional
      Whether or not to reuse module variables.
class_docstr_tok: ["The","Average","module","outputs","the","element-wise","average","of","the","outputs","from","multiple","modules",".","Parameters","--","--","--","--","--","module_list",":","list","The","list","of","modules",".","weight",":","float","A","value","elementwise","multiplied","to","module","outputs",".","scope",":","str",",","optional","Scope","for","module","variables",".","reuse",":","bool",",","optional","Whether","or","not","to","reuse","module","variables","."]
code: def __init__(self, module_list, weight=1.0, scope=None, reuse=False):
      self._module_list = module_list
      self._weight = weight
  
      super(Average, self).__init__(scope=scope, reuse=reuse)
  
imports: import tensorflow
  from openrec.tf1.legacy.modules.fusions import Fusion
label_desc: Use image node_id 1 to create a new Average object from inherited base classes: Fusion with example: obj = Average(module_list, weight, scope, reuse)