layers.py 文件源码

def __init__(self, num_units, forget_bias=1.0, input_size=None,
               state_is_tuple=False, activation=tanh, hyper_num_units=128, hyper_embedding_size=32, is_layer_norm = True):
    """Initialize the basic LSTM cell.
    Args:
      num_units: int, The number of units in the LSTM cell.
      hyper_num_units: int, The number of units in the HyperLSTM cell.
      forget_bias: float, The bias added to forget gates (see above).
      input_size: Deprecated and unused.
      state_is_tuple: If True, accepted and returned states are 2-tuples of
        the `c_state` and `m_state`.  By default (False), they are concatenated
        along the column axis.  This default behavior will soon be deprecated.
      activation: Activation function of the inner states.
    """
    if not state_is_tuple:
      print("%s: Using a concatenated state is slower and will soon be "
                   "deprecated.  Use state_is_tuple=True.", self)
    if input_size is not None:
        print("%s: The input_size parameter is deprecated.", self)
    self._num_units = num_units
    self._forget_bias = forget_bias
    self._state_is_tuple = state_is_tuple
    self._activation = activation
    self.hyper_num_units = hyper_num_units
    self.total_num_units = self._num_units + self.hyper_num_units
    self.hyper_cell = rnn_cell.BasicLSTMCell(hyper_num_units)
    self.hyper_embedding_size= hyper_embedding_size
    self.is_layer_norm = is_layer_norm