class_docstr: Creates a module that uses the moving average weights of another module.
class_docstr_tok: ["Creates","a","module","that","uses","the","moving","average","weights","of","another","module","."]
docstr: Calls the original module with moving average weights.
docstr_tok: ["Calls","the","original","module","with","moving","average","weights","."]
code: def __call__(self, *args, **kwargs):
      """Calls the original module with moving average weights."""
      return self.ema.replace_vars(self.__wrapped__)(*args, **kwargs)
  
file_path: objax/objax/optimizer/ema.py
imports: from typing import Callable, Tuple, List
  import jax.numpy
  from objax.module import Module, ModuleList
  from objax.typing import JaxArray
  from objax.util import class_name
  from objax.variable import RandomState, TrainRef, StateVar, TrainVar, VarCollection
label_desc: Use image node_id 2 for calling the ExponentialMovingAverageModule obj's underlying member method code with example usage: obj.__call__() and returns: self