diff options
Diffstat (limited to 'nerv/examples/lmptb/lmptb/layer/select_linear.lua')
-rw-r--r-- | nerv/examples/lmptb/lmptb/layer/select_linear.lua | 58 |
1 files changed, 58 insertions, 0 deletions
diff --git a/nerv/examples/lmptb/lmptb/layer/select_linear.lua b/nerv/examples/lmptb/lmptb/layer/select_linear.lua new file mode 100644 index 0000000..4798536 --- /dev/null +++ b/nerv/examples/lmptb/lmptb/layer/select_linear.lua @@ -0,0 +1,58 @@ +local SL = nerv.class('nerv.SelectLinearLayer', 'nerv.Layer') + +--id: string +--global_conf: table +--layer_conf: table +--Get Parameters +function SL:__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 = global_conf + + self.ltp = layer_conf.ltp + self.vocab = layer_conf.vocab + + self:check_dim_len(1, 1) +end + +--Check parameter +function SL:init(batch_size) + if (self.dim_in[1] ~= 1) then --one word id + nerv.error("mismatching dimensions of ltp and input") + end + if (self.dim_out[1] ~= self.ltp.trans:ncol()) then + nerv.error("mismatching dimensions of bp and output") + end + + self.batch_size = bath_size + self.ltp:train_init() +end + +function SL:update(bp_err, input, output) + for i = 1, input[1]:nrow(), 1 do + if (input[1][i - 1][0] ~= 0) then + local word_vec = self.ltp.trans[input[1][i - 1][0] - 1] + word_vec:add(word_vec, bp_err[1][i - 1], 1, - self.gconf.lrate / self.gconf.batch_size) + end + end +end + +function SL:propagate(input, output) + for i = 0, input[1]:nrow() - 1, 1 do + if (input[1][i][0] > 0) then + output[1][i]:copy_fromd(self.ltp.trans[input[1][i][0] - 1]) + else + output[1][i]:fill(0) + end + end +end + +function SL:back_propagate(bp_err, next_bp_err, input, output) + --input is compressed, do nothing +end + +function SL:get_params() + local paramRepo = nerv.ParamRepo({self.ltp}) + return paramRepo +end |