(self,
               num_units,
               forget_bias=1.0,
               use_recurrent_dropout=False,
               dropout_keep_prob=0.90,
               use_layer_norm=True,
               hyper_num_units=256,
               hyper_embedding_size=32,
               hyper_use_recurrent_dropout=False)
Initialize the Layer Norm HyperLSTM cell.

    Args:
      num_units: int, The number of units in the LSTM cell.
      forget_bias: float, The bias added to forget gates (default 1.0).
      use_recurrent_dropout: Whether to use Recurrent Dropout (default False)
      dropout_keep_prob: float, dropout keep probability (default 0.90)
      use_layer_norm: boolean. (default True)
        Controls whether we use LayerNorm layers in main LSTM & HyperLSTM cell.
      hyper_num_units: int, number of units in HyperLSTM cell.
        (default is 128, recommend experimenting with 256 for larger tasks)
      hyper_embedding_size: int, size of signals emitted from HyperLSTM cell.
        (default is 16, recommend trying larger values for large datasets)
      hyper_use_recurrent_dropout: boolean. (default False)
        Controls whether HyperLSTM cell also uses recurrent dropout.
        Recommend turning this on only if hyper_num_units becomes large (>= 512)
Initialize the Layer Norm HyperLSTM cell.
Initialize the Layer Norm HyperLSTM cell .
def __init__(self,
               num_units,
               forget_bias=1.0,
               use_recurrent_dropout=False,
               dropout_keep_prob=0.90,
               use_layer_norm=True,
               hyper_num_units=256,
               hyper_embedding_size=32,
               hyper_use_recurrent_dropout=False):
    """Initialize the Layer Norm HyperLSTM cell.

    Args:
      num_units: int, The number of units in the LSTM cell.
      forget_bias: float, The bias added to forget gates (default 1.0).
      use_recurrent_dropout: Whether to use Recurrent Dropout (default False)
      dropout_keep_prob: float, dropout keep probability (default 0.90)
      use_layer_norm: boolean. (default True)
        Controls whether we use LayerNorm layers in main LSTM & HyperLSTM cell.
      hyper_num_units: int, number of units in HyperLSTM cell.
        (default is 128, recommend experimenting with 256 for larger tasks)
      hyper_embedding_size: int, size of signals emitted from HyperLSTM cell.
        (default is 16, recommend trying larger values for large datasets)
      hyper_use_recurrent_dropout: boolean. (default False)
        Controls whether HyperLSTM cell also uses recurrent dropout.
        Recommend turning this on only if hyper_num_units becomes large (>= 512)
    """
    self.num_units = num_units
    self.forget_bias = forget_bias
    self.use_recurrent_dropout = use_recurrent_dropout
    self.dropout_keep_prob = dropout_keep_prob
    self.use_layer_norm = use_layer_norm
    self.hyper_num_units = hyper_num_units
    self.hyper_embedding_size = hyper_embedding_size
    self.hyper_use_recurrent_dropout = hyper_use_recurrent_dropout

    self.total_num_units = self.num_units + self.hyper_num_units

    if self.use_layer_norm:
      cell_fn = LayerNormLSTMCell
    else:
      cell_fn = LSTMCell
    self.hyper_cell = cell_fn(
        hyper_num_units,
        use_recurrent_dropout=hyper_use_recurrent_dropout,
        dropout_keep_prob=dropout_keep_prob)
def __init__ ( self , num_units , forget_bias = 1.0 , use_recurrent_dropout = False , dropout_keep_prob = 0.90 , use_layer_norm = True , hyper_num_units = 256 , hyper_embedding_size = 32 , hyper_use_recurrent_dropout = False ) : self . num_units = num_units self . forget_bias = forget_bias self . use_recurrent_dropout = use_recurrent_dropout self . dropout_keep_prob = dropout_keep_prob self . use_layer_norm = use_layer_norm self . hyper_num_units = hyper_num_units self . hyper_embedding_size = hyper_embedding_size self . hyper_use_recurrent_dropout = hyper_use_recurrent_dropout self . total_num_units = self . num_units + self . hyper_num_units if self . use_layer_norm : cell_fn = LayerNormLSTMCell else : cell_fn = LSTMCell self . hyper_cell = cell_fn ( hyper_num_units , use_recurrent_dropout = hyper_use_recurrent_dropout , dropout_keep_prob = dropout_keep_prob )