import tensorflow as tf

    self._initializers = util.check_initializers(
        initializers, self.POSSIBLE_INITIALIZER_KEYS)

  def _set_default_initializer(self, var_name):
    """Sets up a default initializer for a variable if one doesn't exist.

    For the offset (beta), a zeros initializer is used by default.
    For the scale (gamma), a ones initializer is used by default.

    Args:
      var_name: name of variable as a string.
    """
    if var_name not in self._initializers:
      if var_name == self.GAMMA:
        self._initializers[self.GAMMA] = tf.ones_initializer()
      elif var_name == self.BETA:
        self._initializers[self.BETA] = tf.zeros_initializer

  def _build_statistics_variance(self, input_batch,
                                 reduction_indices, use_batch_stats):
    """Builds the statistics part of the graph when using moving variance.

    Args:
      input_batch: Input batch Tensor.
      reduction_indices: Indices of `input_batch` to reduce over.
      use_batch_stats: Boolean to indicate if batch statistics should be
        calculated, otherwise moving averages are returned.

