dlpy.layers.Dense

class dlpy.layers.Dense(n, name=None, act='relu', fcmp_act=None, init=None, std=None, mean=None, truncation_factor=None, init_bias=None, dropout=None, include_bias=None, src_layers=None, **kwargs)

Bases: dlpy.layers.Layer

Fully connected layer

Parameters:

n : int

Specifies the number of neurons.

name : string, optional

Specifies the name of the layer.

act : string, optional

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

fcmp_act : string, optional

Specifies the FCMP activation function for the layer.

init : string, optional

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

std : float, optional

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

mean : float, optional

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

truncation_factor : float, optional

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

init_bias : float, optional

Specifies the initial bias for the layer.

dropout : float, optional

Specifies the dropout rate.
Default: 0

include_bias : bool, optional

Includes bias neurons (default).

src_layers : iter-of-Layers, optional

Specifies the layers directed to this layer.

Returns:

Dense

__init__(n, name=None, act='relu', fcmp_act=None, init=None, std=None, mean=None, truncation_factor=None, init_bias=None, dropout=None, include_bias=None, src_layers=None, **kwargs)

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