diff options
Diffstat (limited to 'lua/select_linear.lua')
-rw-r--r-- | lua/select_linear.lua | 62 |
1 files changed, 0 insertions, 62 deletions
diff --git a/lua/select_linear.lua b/lua/select_linear.lua deleted file mode 100644 index a7e20cc..0000000 --- a/lua/select_linear.lua +++ /dev/null @@ -1,62 +0,0 @@ -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.vocab = layer_conf.vocab - self.ltp = self:find_param("ltp", layer_conf, global_conf, nerv.LinearTransParam, {self.vocab, self.dim_out[1]}) --layer_conf.ltp - - 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) - --use this to produce reproducable result, don't forget to set the dropout to zero! - --for i = 1, input[1]:nrow(), 1 do - -- local word_vec = self.ltp.trans[input[1][i - 1][0]] - -- word_vec:add(word_vec, bp_err[1][i - 1], 1, - self.gconf.lrate / self.gconf.batch_size) - --end - - --I tried the update_select_rows kernel which uses atomicAdd, but it generates unreproducable result - self.ltp.trans:update_select_rows_by_colidx(bp_err[1], input[1], - self.gconf.lrate / self.gconf.batch_size, 0) - self.ltp.trans:add(self.ltp.trans, self.ltp.trans, 1.0, - self.gconf.lrate * self.gconf.wcost) -end - -function SL:propagate(input, output) - --for i = 0, input[1]:ncol() - 1, 1 do - -- if (input[1][0][i] > 0) then - -- output[1][i]:copy_fromd(self.ltp.trans[input[1][0][i]]) - -- else - -- output[1][i]:fill(0) - -- end - --end - output[1]:copy_rows_fromd_by_colidx(self.ltp.trans, input[1]) -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 |