dlpy.layers.Recurrent

class dlpy.layers.Recurrent(n, name=None, act='AUTO', fcmp_act=None, init=None, std=None, mean=None, truncation_factor=None, rnn_type='LSTM', output_type='ENCODING', max_output_length=None, reversed_=None, dropout=None, init_bias=None, src_layers=None)

RNN layer

Parameters

nint

Specifies the number of neurons.

namestring, optional

Specifies the name of the layer.

actstring, optional

Specifies the activation function. Valid Values: AUTO, IDENTITY, LOGISTIC, SIGMOID, TANH, RECTIFIER, RELU, SOFPLUS, ELU, LEAKY, FCMP Default: AUTO

fcmp_actstring, optional

Specifies the FCMP activation function for the layer.

initstring, optional

Specifies the initialization scheme for the layer. Valid Values: XAVIER, UNIFORM, NORMAL, CAUCHY, XAVIER1, XAVIER2, MSRA, MSRA1, MSRA2 Default: XAVIER

stdfloat, optional

Specifies the standard deviation value when the init parameter is set to NORMAL.

meanfloat, optional

Specifies the mean value when the init parameter is set to NORMAL.

truncation_factorfloat, optional

Specifies the truncation threshold (truncationFactor x std), when the init parameter is set to NORMAL

rnn_typestring, optional

Specifies the type of the rnn layer. Possible Values: RNN, LSTM, GRU Default: RNN

output_typestring, optional

Specifies the output type of the recurrent layer. Valid Values: ENCODING, SAMELENGTH, ARBITRARYLENGTH Default: ENCODING

max_output_lengthint, optional

Specifies the maximum number of tokens to generate when the outputType parameter is set to ARBITRARYLENGTH.

reversedbool, optional

Specifies the direction of the rnn layer. Default: False

dropoutfloat, optional

Specifies the dropout rate. Default: 0

init_biasfloat, optional

Specifies the initial bias for the layer. Default: None

src_layersiter-of-Layers, optional

Specifies the layers directed to this layer.

Returns

Recurrent

__init__(n, name=None, act='AUTO', fcmp_act=None, init=None, std=None, mean=None, truncation_factor=None, rnn_type='LSTM', output_type='ENCODING', max_output_length=None, reversed_=None, dropout=None, init_bias=None, src_layers=None)

Initialize self. See help(type(self)) for accurate signature.

Methods

__init__(n[, name, act, fcmp_act, init, …])	Initialize self.
count_instances()
format_name([block_num, local_count])	Format the name of the layer
get_number_of_instances()
to_model_params()	Convert the model configuration to CAS action parameters

Attributes

can_be_last_layer
kernel_size
layer_id
num_bias
num_features
num_weights
number_of_instances
output_size
rnn_summary	Return a DataFrame containing the layer information for rnn models
summary	Return a DataFrame containing the layer information
type
type_desc
type_label