parameters: (self, shape, dtype)
docstring: Specify the shape and dtype of the mean to be estimated.
  
      Note that a float mean to zero submitted elements is NaN, while computing
      the integer mean of zero elements raises a division by zero error.
  
      Args:
        shape: Shape of the mean to compute.
        dtype: Data type of the mean to compute.
docstring_summary: Specify the shape and dtype of the mean to be estimated.
docstring_tokens: Specify the shape and dtype of the mean to be estimated .
function: def __init__(self, shape, dtype):
      """Specify the shape and dtype of the mean to be estimated.
  
      Note that a float mean to zero submitted elements is NaN, while computing
      the integer mean of zero elements raises a division by zero error.
  
      Args:
        shape: Shape of the mean to compute.
        dtype: Data type of the mean to compute.
      """
      self._dtype = dtype
      self._sum = tf.Variable(lambda: tf.zeros(shape, dtype), False)
      self._count = tf.Variable(lambda: 0, trainable=False)
function_tokens: def __init__ ( self , shape , dtype ) : self . _dtype = dtype self . _sum = tf . Variable ( lambda : tf . zeros ( shape , dtype ) , False ) self . _count = tf . Variable ( lambda : 0 , trainable = False )