local RNNLayer = nerv.class('nerv.RNNLayer', 'nerv.GraphLayer')
function RNNLayer:__init(id, global_conf, layer_conf)
self.id = id
self.dim_in = layer_conf.dim_in
self.dim_out = layer_conf.dim_out
self.gconf = layer_conf.gconf
self:check_dim_len(1, 1)
local din = layer_conf.dim_in[1]
local dout = layer_conf.dim_out[1]
local pr = layer_conf.pr
if pr == nil then
pr = nerv.ParamRepo()
end
local layers = {
['nerv.AffineLayer'] = {
main = {dim_in = {din, dout}, dim_out = {dout}, pr = pr},
},
['nerv.SigmoidLayer'] = {
sigmoid = {dim_in = {dout}, dim_out = {dout}},
},
['nerv.DuplicateLayer'] = {
dup = {dim_in = {dout}, dim_out = {dout, dout}},
}
}
local connections = {
{'[1]', 'main[1]', 0},
{'main[1]', 'sigmoid[1]', 0},
{'sigmoid[1]', 'dup[1]', 0},
{'dup[1]', 'main[2]', 1},
{'dup[2]', '