dlpy.blocks.Bidirectional¶
-
class
dlpy.blocks.
Bidirectional
(n, n_blocks=1, rnn_type='gru', output_type='samelength', dropout=0.2, max_output_length=None, src_layers=None, name=None)¶ Bidirectional RNN layers
- Parameters
- nint or list of int
Specifies the number of neurons in the recurrent layer. If n_blocks=1, then n should be an int. If n_blocks > 1, then n can be an int or a list of ints to indicate the number of neurons in each block.
- n_blocksint, optional
Specifies the number of bidirectional recurrent layer blocks. Default: 1
- rnn_typestring, optional
Specifies the type of the rnn layer. Default: GRU Valid Values: RNN, LSTM, GRU
- output_typestring, optional
Specifies the output type of the recurrent layer. Default: SAMELENGTH Valid Values: ENCODING, SAMELENGTH, ARBITRARYLENGTH
- max_output_lengthint, mostly optional
Specifies the maximum number of tokens to generate when the outputType parameter is set to ARBITRARYLENGTH.
- dropoutfloat, optional
Specifies the dropout rate. Default: 0.2
- src_layerslist, optional
Specifies the list of source layers for the layer.
- namestring, optional
Specifies layer names. If not specified, ‘RNN’ is used
- Returns
- :class:`Bidirectional’
-
__init__
(n, n_blocks=1, rnn_type='gru', output_type='samelength', dropout=0.2, max_output_length=None, src_layers=None, name=None)¶ Initialize self. See help(type(self)) for accurate signature.
Methods
__init__
(n[, n_blocks, rnn_type, …])Initialize self.
add_layers
()Add layers for the block
compile
([block_num])Convert the options into DLPy layer definition.
get_last_layers
()Return last two layers, if they exist
get_layers
()Return list of layers
Attributes
type