parameters: (self, decay, num_updates=None, name="ExponentialMovingAverage")
docstring: Creates a new ExponentialMovingAverage object.
  
      The `apply()` method has to be called to create shadow variables and add
      ops to maintain moving averages.
  
      The optional `num_updates` parameter allows one to tweak the decay rate
      dynamically. .  It is typical to pass the count of training steps, usually
      kept in a variable that is incremented at each step, in which case the
      decay rate is lower at the start of training.  This makes moving averages
      move faster.  If passed, the actual decay rate used is:
  
        `min(decay, (1 + num_updates) / (10 + num_updates))`
  
      Args:
        decay: Float.  The decay to use.
        num_updates: Optional count of number of updates applied to variables.
        name: String. Optional prefix name to use for the name of ops added in
          `apply()`.
docstring_summary: Creates a new ExponentialMovingAverage object.
docstring_tokens: Creates a new ExponentialMovingAverage object .
function: def __init__(self, decay, num_updates=None, name="ExponentialMovingAverage"):
      """Creates a new ExponentialMovingAverage object.
  
      The `apply()` method has to be called to create shadow variables and add
      ops to maintain moving averages.
  
      The optional `num_updates` parameter allows one to tweak the decay rate
      dynamically. .  It is typical to pass the count of training steps, usually
      kept in a variable that is incremented at each step, in which case the
      decay rate is lower at the start of training.  This makes moving averages
      move faster.  If passed, the actual decay rate used is:
  
        `min(decay, (1 + num_updates) / (10 + num_updates))`
  
      Args:
        decay: Float.  The decay to use.
        num_updates: Optional count of number of updates applied to variables.
        name: String. Optional prefix name to use for the name of ops added in
          `apply()`.
      """
      self._decay = decay
      self._num_updates = num_updates
      self._name = name
      self._averages = {}
function_tokens: def __init__ ( self , decay , num_updates = None , name = "ExponentialMovingAverage" ) : self . _decay = decay self . _num_updates = num_updates self . _name = name self . _averages = { }