Convolutional GRU

CGRU

These are optional parameters for the CGRUnits inside a MDGRU block.

periodic convolution on input x (dtype=bool)

--periodic_convolution_x False

periodic convolution on input h (dtype=bool)

--periodic_convolution_h False

use Bernoulli distribution (insted of Gaussian) for dropconnect (dtype=bool)

--use_bernoulli False

use dropconnect on input x (dtype=bool)

--dropconnectx False

use dropconnect on input h (dtype=bool)

--dropconnecth False

add batch normalization at the input x in gate (dtype=bool)

--add_x_bn

add batch normalization at the input h in candidate (dtype=bool)

--add_h_bn False

add batch normalization at the candidates input and state (dtype=bool)

--add_a_bn False

add residual learning to the input x of each cgru (dtype=bool)

--resgrux False

add residual learning to the input h of each cgru (dtype=bool)

--resgruh False

move the reset gate to the location the original GRU applies it at (dtype=bool)

--put_r_back False

apply dropconnect on the candidate weights as well (dtype=bool)

--use_dropconnect_on_state False

Module contents