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authortxh18 <[email protected]>2015-10-28 15:06:27 +0800
committertxh18 <[email protected]>2015-10-28 15:06:27 +0800
commitaf99db1c6bc4823cc6ff094f24e963acd4788ef1 (patch)
tree6b33abba8eb72475b0cdddb55435efa9e23ceb03
parent7c95640c95f1cc1d84b4d49fa97fd922748b88a7 (diff)
added update_select_rows to doc
-rw-r--r--nerv/doc/nerv_matrix.md2
-rw-r--r--nerv/examples/lmptb/main.lua6
-rw-r--r--nerv/nn/layer_dag.lua4
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