added small opt: use mmatrix in lm_trainer and reader

1 files changed, 12 insertions, 5 deletions

diff --git a/nerv/examples/lmptb/lm_trainer.lua b/nerv/examples/lmptb/lm_trainer.lua
index 7dd70e2..62d8b50 100644
--- a/nerv/examples/lmptb/lm_trainer.lua
+++ b/nerv/examples/lmptb/lm_trainer.lua
@@ -15,17 +15,18 @@ function LMTrainer.lm_process_file(global_conf, fn, tnn, do_train)
     reader:open_file(fn)
     local result = nerv.LMResult(global_conf, global_conf.vocab)
     result:init("rnn")
-    
+        
     global_conf.timer:flush()
     tnn:flush_all() --caution: will also flush the inputs from the reader!
 
     local next_log_wcn = global_conf.log_w_num
+    local neto_bakm = global_conf.mmat_type(global_conf.batch_size, 1) --space backup matrix for network output
 
     while (1) do
         global_conf.timer:tic('most_out_loop_lmprocessfile')
 
         local r, feeds
-
+        global_conf.timer:tic('tnn_beforeprocess')
         r, feeds = tnn:getfeed_from_reader(reader)
         if r == false then 
             break 
@@ -39,6 +40,7 @@ function LMTrainer.lm_process_file(global_conf, fn, tnn, do_train)
                 end
             end
         end
+        global_conf.timer:toc('tnn_beforeprocess')
 
         --[[
         for j = 1, global_conf.chunk_size, 1 do
@@ -56,15 +58,20 @@ function LMTrainer.lm_process_file(global_conf, fn, tnn, do_train)
             tnn:net_backpropagate(false) 
             tnn:net_backpropagate(true)
         end
- 
+
+        global_conf.timer:tic('tnn_afterprocess')
         for t = 1, global_conf.chunk_size, 1 do
+            tnn.outputs_m[t][1]:copy_toh(neto_bakm)
             for i = 1, global_conf.batch_size, 1 do
                 if (feeds.labels_s[t][i] ~= global_conf.vocab.null_token) then
-                    result:add("rnn", feeds.labels_s[t][i], math.exp(tnn.outputs_m[t][1][i - 1][0]))
+                    --result:add("rnn", feeds.labels_s[t][i], math.exp(tnn.outputs_m[t][1][i - 1][0]))
+                    result:add("rnn", feeds.labels_s[t][i], math.exp(neto_bakm[i - 1][0]))
                 end
             end            
         end
-        tnn:move_right_to_nextmb()
+        tnn:move_right_to_nextmb({0}) --only copy for time 0
+        global_conf.timer:toc('tnn_afterprocess')
+
         global_conf.timer:toc('most_out_loop_lmprocessfile')
 
         --print log