added update_select_rows to doc

3 files changed, 6 insertions, 6 deletions

diff --git a/nerv/doc/nerv_matrix.md b/nerv/doc/nerv_matrix.md
index 54bf440..b915dee 100644
--- a/nerv/doc/nerv_matrix.md
+++ b/nerv/doc/nerv_matrix.md
@@ -67,6 +67,8 @@ Copy the content of the __Matrix__ `self` to a __CuMatrix__ `a`.
 `idx` should be a row vector. This function copy the rows of `ma` to `self` according to `idx`, in other words, it assigns `ma[idx[i]]` to `self[i]`.
 * __void Matrix.copy_rows_fromd_by_idx(Matrix self, CuMatrix b, CuMatrix idx)__  
 `idx` needs to a row vector matrix, it stacks the rows of index `idx` of the __CuMatrix__ `b` and copies to `self`.
+* __void Matrix.update_select_rows(Matrix self, Matrix err, Matrix idx, double alpha, double beta)__  
+Update selected rows of `self`, i.e. `self[idx[i]] = self[idx[i]] * (1 - beta * alpha) + alpha * err[i]`.
 * __void Matrix.add(Matrix self, Matrix ma, Matrix mb, Element_type alpha, Element_type beta)__  
 It sets the content of __Matrix__ `self` to be `alpha * ma + beta * mb`.__Matrix__ `ma,mb,self` should be of the same size.
 * __void Matrix.mul(Matrix self, Matrix ma, Matrix mb, Element_type alpha, Element_type beta, [string ta, string tb])__  
diff --git a/nerv/examples/lmptb/main.lua b/nerv/examples/lmptb/main.lua
index d505456..1939eda 100644
--- a/nerv/examples/lmptb/main.lua
+++ b/nerv/examples/lmptb/main.lua
@@ -224,9 +224,11 @@ function propagateFile(global_conf, dagL, fn, config)
             if (result["rnn"].cn_w % global_conf.log_w_num == 0) then
                 printf("%s %d words processed %s.\n", global_conf.sche_log_pre, result["rnn"].cn_w, os.date()) 
                 printf("\t%s log prob per sample :%f.\n", global_conf.sche_log_pre, result:logp_sample("rnn"));
+                --[[
                 for key, value in pairs(global_conf.timer.rec) do
                     printf("\t [global_conf.timer]: time spent on %s:%.5fs\n", key, value)
                 end
+                ]]--
                 --comment this for debughtx
                 global_conf.timer:flush()
                 --nerv.CuMatrix.print_profile()
@@ -272,7 +274,7 @@ if (set == "ptb") then
 
         hidden_size = 200,
         batch_size = 10,
-        bptt = 3, --train bptt_block's words. could be set to zero
+        bptt = 6, --train bptt_block's words. could be set to zero
         max_iter = 18,
         param_random = function() return (math.random() / 5 - 0.1) end,
         independent = true,
@@ -281,7 +283,7 @@ if (set == "ptb") then
         valid_fn = valid_fn,
         test_fn = test_fn,
         sche_log_pre = "[SCHEDULER]:",
-        log_w_num = 500000, --give a message when log_w_num words have been processed
+        log_w_num = 100000, --give a message when log_w_num words have been processed
         timer = nerv.Timer()
     }
     global_conf.work_dir = work_dir_base.."/h"..global_conf.hidden_size.."bp"..global_conf.bptt.."slr"..global_conf.lrate --..os.date("_%bD%dH%H") --comment this for testing
diff --git a/nerv/nn/layer_dag.lua b/nerv/nn/layer_dag.lua
index 4904f4f..73bb77d 100644
--- a/nerv/nn/layer_dag.lua
+++ b/nerv/nn/layer_dag.lua
@@ -251,9 +251,7 @@ function DAGLayer:update(bp_err, input, output)
     -- print("update")
     for id, ref in pairs(self.queue) do
         -- print(ref.layer.id)
-        self.gconf.timer:tic("(update)"..ref.layer.id);
         ref.layer:update(ref.err_inputs, ref.inputs, ref.outputs)
-        self.gconf.timer:toc("(update)"..ref.layer.id);
     end
 end
 
@@ -264,9 +262,7 @@ function DAGLayer:propagate(input, output)
     for i = 1, #self.queue do
         local ref = self.queue[i]
         -- print(ref.layer.id)
-        self.gconf.timer:tic("(propagate)"..ref.layer.id);
         ret = ref.layer:propagate(ref.inputs, ref.outputs)
-        self.gconf.timer:toc("(propagate)"..ref.layer.id); 
     end
     return ret
 end