(self, flat_x_target, flat_rnn_output)
Core loss calculation method for flattened outputs.

    Args:
      flat_x_target: The flattened ground truth vectors, sized
        `[sum(x_length), self._output_depth]`.
      flat_rnn_output: The flattened output from all timeputs of the RNN,
        sized `[sum(x_length), rnn_output_size]`.
    Returns:
      r_loss: The unreduced reconstruction losses, sized `[sum(x_length)]`.
      metric_map: A map of metric names to tuples, each of which contain the
        pair of (value_tensor, update_op) from a tf.metrics streaming metric.
Core loss calculation method for flattened outputs.
Core loss calculation method for flattened outputs .
def _flat_reconstruction_loss(self, flat_x_target, flat_rnn_output):
    """Core loss calculation method for flattened outputs.

    Args:
      flat_x_target: The flattened ground truth vectors, sized
        `[sum(x_length), self._output_depth]`.
      flat_rnn_output: The flattened output from all timeputs of the RNN,
        sized `[sum(x_length), rnn_output_size]`.
    Returns:
      r_loss: The unreduced reconstruction losses, sized `[sum(x_length)]`.
      metric_map: A map of metric names to tuples, each of which contain the
        pair of (value_tensor, update_op) from a tf.metrics streaming metric.
    """
    pass
def _flat_reconstruction_loss ( self , flat_x_target , flat_rnn_output ) : pass