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authortxh18 <[email protected]>2015-12-04 14:58:17 +0800
committertxh18 <[email protected]>2015-12-04 14:58:17 +0800
commit618450eb71817ded45c422f35d8fede2d52a66b2 (patch)
treefaab52eb3f6507331703b656c62a9e2ebf3b3f92
parent39815c1faccbc64221579a4e13d193d64e68897b (diff)
added log_redirect to SUtil
-rw-r--r--nerv/examples/lmptb/lm_trainer.lua14
-rw-r--r--nerv/examples/lmptb/lstmlm_ptb_main.lua89
-rw-r--r--nerv/examples/lmptb/m-tests/sutil_test.lua3
-rw-r--r--nerv/tnn/sutil.lua15
4 files changed, 73 insertions, 48 deletions
diff --git a/nerv/examples/lmptb/lm_trainer.lua b/nerv/examples/lmptb/lm_trainer.lua
index e5384b1..9ef4794 100644
--- a/nerv/examples/lmptb/lm_trainer.lua
+++ b/nerv/examples/lmptb/lm_trainer.lua
@@ -7,7 +7,7 @@ require 'lmptb.lmseqreader'
local LMTrainer = nerv.class('nerv.LMTrainer')
-local printf = nerv.printf
+--local printf = nerv.printf
--The bias param update in nerv don't have wcost added
function nerv.BiasParam:update_by_gradient(gradient)
@@ -87,10 +87,10 @@ function LMTrainer.lm_process_file_rnn(global_conf, fn, tnn, do_train)
--print log
if result["rnn"].cn_w > next_log_wcn then
next_log_wcn = next_log_wcn + global_conf.log_w_num
- 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"))
+ nerv.printf("%s %d words processed %s.\n", global_conf.sche_log_pre, result["rnn"].cn_w, os.date())
+ nerv.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:%.5f clock time\n", key, value)
+ nerv.printf("\t [global_conf.timer]: time spent on %s:%.5f clock time\n", key, value)
end
global_conf.timer:flush()
nerv.LMUtil.wait(0.1)
@@ -108,9 +108,9 @@ function LMTrainer.lm_process_file_rnn(global_conf, fn, tnn, do_train)
--break --debug
end
- printf("%s Displaying result:\n", global_conf.sche_log_pre)
- printf("%s %s\n", global_conf.sche_log_pre, result:status("rnn"))
- printf("%s Doing on %s end.\n", global_conf.sche_log_pre, fn)
+ nerv.printf("%s Displaying result:\n", global_conf.sche_log_pre)
+ nerv.printf("%s %s\n", global_conf.sche_log_pre, result:status("rnn"))
+ nerv.printf("%s Doing on %s end.\n", global_conf.sche_log_pre, fn)
return result
end
diff --git a/nerv/examples/lmptb/lstmlm_ptb_main.lua b/nerv/examples/lmptb/lstmlm_ptb_main.lua
index a49e5c2..681c308 100644
--- a/nerv/examples/lmptb/lstmlm_ptb_main.lua
+++ b/nerv/examples/lmptb/lstmlm_ptb_main.lua
@@ -7,7 +7,7 @@ require 'lmptb.lmseqreader'
require 'lm_trainer'
--[[global function rename]]--
-local printf = nerv.printf
+--local printf = nerv.printf
local LMTrainer = nerv.LMTrainer
--[[global function rename ends]]--
@@ -15,13 +15,13 @@ local LMTrainer = nerv.LMTrainer
--first_time: bool
--Returns: a ParamRepo
function prepare_parameters(global_conf, iter)
- printf("%s preparing parameters...\n", global_conf.sche_log_pre)
+ nerv.printf("%s preparing parameters...\n", global_conf.sche_log_pre)
global_conf.paramRepo = nerv.ParamRepo()
local paramRepo = global_conf.paramRepo
if iter == -1 then --first time
- printf("%s first time, prepare some pre-set parameters, and leaving other parameters to auto-generation...\n", global_conf.sche_log_pre)
+ nerv.printf("%s first time, prepare some pre-set parameters, and leaving other parameters to auto-generation...\n", global_conf.sche_log_pre)
local f = nerv.ChunkFile(global_conf.param_fn .. '.0', 'w')
f:close()
--[[
@@ -56,10 +56,10 @@ function prepare_parameters(global_conf, iter)
return nil
end
- printf("%s loading parameter from file %s...\n", global_conf.sche_log_pre, global_conf.param_fn .. '.' .. tostring(iter))
+ nerv.printf("%s loading parameter from file %s...\n", global_conf.sche_log_pre, global_conf.param_fn .. '.' .. tostring(iter))
paramRepo:import({global_conf.param_fn .. '.' .. tostring(iter)}, nil, global_conf)
- printf("%s preparing parameters end.\n", global_conf.sche_log_pre)
+ nerv.printf("%s preparing parameters end.\n", global_conf.sche_log_pre)
return nil
end
@@ -67,7 +67,7 @@ end
--global_conf: table
--Returns: nerv.LayerRepo
function prepare_layers(global_conf)
- printf("%s preparing layers...\n", global_conf.sche_log_pre)
+ nerv.printf("%s preparing layers...\n", global_conf.sche_log_pre)
local pr = global_conf.paramRepo
@@ -125,7 +125,7 @@ function prepare_layers(global_conf)
--]]
local layerRepo = nerv.LayerRepo(layers, pr, global_conf)
- printf("%s preparing layers end.\n", global_conf.sche_log_pre)
+ nerv.printf("%s preparing layers end.\n", global_conf.sche_log_pre)
return layerRepo
end
@@ -133,7 +133,7 @@ end
--layerRepo: nerv.LayerRepo
--Returns: a nerv.TNN
function prepare_tnn(global_conf, layerRepo)
- printf("%s Generate and initing TNN ...\n", global_conf.sche_log_pre)
+ nerv.printf("%s Generate and initing TNN ...\n", global_conf.sche_log_pre)
--input: input_w, input_w, ... input_w_now, last_activation
local connections_t = {
@@ -178,7 +178,7 @@ function prepare_tnn(global_conf, layerRepo)
tnn:init(global_conf.batch_size, global_conf.chunk_size)
- printf("%s Initing TNN end.\n", global_conf.sche_log_pre)
+ nerv.printf("%s Initing TNN end.\n", global_conf.sche_log_pre)
return tnn
end
@@ -202,7 +202,7 @@ test_fn = data_dir .. '/ptb.test.txt.adds'
vocab_fn = data_dir .. '/vocab'
global_conf = {
- lrate = 0.15, wcost = 1e-5, momentum = 0, clip_t = 10,
+ lrate = 0.15, wcost = 1e-5, momentum = 0, clip_t = 2,
cumat_type = nerv.CuMatrixFloat,
mmat_type = nerv.MMatrixFloat,
nn_act_default = 0,
@@ -214,7 +214,7 @@ global_conf = {
max_iter = 45,
lr_decay = 1.003,
decay_iter = 10,
- param_random = function() return (math.random() / 50 - 0.01) end,
+ param_random = function() return (math.random() / 5 - 0.1) end,
dropout_str = "0.5",
train_fn = train_fn,
@@ -303,12 +303,12 @@ local commands_str = "train:test"
local commands = {}
local test_iter = -1
-if (arg[2] ~= nil) then
- printf("%s applying arg[2](%s)...\n", global_conf.sche_log_pre, arg[2])
+if arg[2] ~= nil then
+ nerv.printf("%s applying arg[2](%s)...\n", global_conf.sche_log_pre, arg[2])
loadstring(arg[2])()
nerv.LMUtil.wait(0.5)
else
- printf("%s no user setting, all default...\n", global_conf.sche_log_pre)
+ nerv.printf("%s no user setting, all default...\n", global_conf.sche_log_pre)
end
global_conf.work_dir = global_conf.work_dir_base .. 'h' .. global_conf.hidden_size .. 'l' .. global_conf.layer_num --.. 'ch' .. global_conf.chunk_size .. 'ba' .. global_conf.batch_size .. 'slr' .. global_conf.lrate .. 'wc' .. global_conf.wcost
@@ -316,32 +316,39 @@ global_conf.train_fn_shuf = global_conf.work_dir .. '/train_fn_shuf'
global_conf.train_fn_shuf_bak = global_conf.train_fn_shuf .. '_bak'
global_conf.param_fn = global_conf.work_dir .. "/params"
global_conf.dropout_list = nerv.SUtil.parse_schedule(global_conf.dropout_str)
+global_conf.log_fn = global_conf.work_dir .. '/lstm_tnn_' .. commands_str .. '_log'
commands = nerv.SUtil.parse_commands_set(commands_str)
+
+nerv.printf("%s creating work_dir...\n", global_conf.sche_log_pre)
+nerv.LMUtil.wait(1)
+os.execute("mkdir -p "..global_conf.work_dir)
+os.execute("cp " .. global_conf.train_fn .. " " .. global_conf.train_fn_shuf)
+
+--redirecting log outputs!
+nerv.SUtil.log_redirect(global_conf.log_fn)
+
----------------printing options---------------------------------
-printf("%s printing global_conf...\n", global_conf.sche_log_pre)
+nerv.printf("%s printing global_conf...\n", global_conf.sche_log_pre)
for id, value in pairs(global_conf) do
- print(id, value)
+ nerv.printf("%s:\t%s\n", id, tostring(value))
end
nerv.LMUtil.wait(2)
-printf("%s printing training scheduling options...\n", global_conf.sche_log_pre)
-print("lr_half", lr_half)
-print("start_iter", start_iter)
-print("ppl_last", ppl_last)
-print("commds_str", commands_str)
-print("test_iter", test_iter)
-printf("%s printing training scheduling end.\n", global_conf.sche_log_pre)
+
+nerv.printf("%s printing training scheduling options...\n", global_conf.sche_log_pre)
+nerv.printf("lr_half:%s\n", tostring(lr_half))
+nerv.printf("start_iter:%s\n", tostring(start_iter))
+nerv.printf("ppl_last:%s\n", tostring(ppl_last))
+nerv.printf("commds_str:%s\n", commands_str)
+nerv.printf("test_iter:%s\n", tostring(test_iter))
+nerv.printf("%s printing training scheduling end.\n", global_conf.sche_log_pre)
nerv.LMUtil.wait(2)
------------------printing options end------------------------------
math.randomseed(1)
-printf("%s creating work_dir...\n", global_conf.sche_log_pre)
-os.execute("mkdir -p "..global_conf.work_dir)
-os.execute("cp " .. global_conf.train_fn .. " " .. global_conf.train_fn_shuf)
-
local vocab = nerv.LMVocab()
global_conf["vocab"] = vocab
-printf("%s building vocab...\n", global_conf.sche_log_pre)
+nerv.printf("%s building vocab...\n", global_conf.sche_log_pre)
global_conf.vocab:build_file(global_conf.vocab_fn, false)
ppl_rec = {}
@@ -352,7 +359,7 @@ if commands["train"] == 1 then
end
if start_iter == -1 or start_iter == 0 then
- print("===INITIAL VALIDATION===")
+ nerv.printf("===INITIAL VALIDATION===\n")
local tnn = load_net(global_conf, 0)
global_conf.paramRepo = tnn:get_params() --get auto-generted params
global_conf.paramRepo:export(global_conf.param_fn .. '.0', nil) --some parameters are auto-generated, saved again to param.0 file
@@ -368,27 +375,27 @@ if commands["train"] == 1 then
start_iter = 1
- print()
+ nerv.printf("\n")
end
for iter = start_iter, global_conf.max_iter, 1 do
final_iter = iter --for final testing
global_conf.sche_log_pre = "[SCHEDULER ITER"..iter.." LR"..global_conf.lrate.."]:"
tnn = load_net(global_conf, iter - 1)
- printf("===ITERATION %d LR %f===\n", iter, global_conf.lrate)
+ nerv.printf("===ITERATION %d LR %f===\n", iter, global_conf.lrate)
global_conf.dropout_rate = nerv.SUtil.sche_get(global_conf.dropout_list, iter)
result = LMTrainer.lm_process_file_rnn(global_conf, global_conf.train_fn_shuf, tnn, true) --true update!
global_conf.dropout_rate = 0
ppl_rec[iter] = {}
ppl_rec[iter].train = result:ppl_all("rnn")
--shuffling training file
- printf("%s shuffling training file\n", global_conf.sche_log_pre)
+ nerv.printf("%s shuffling training file\n", global_conf.sche_log_pre)
os.execute('cp ' .. global_conf.train_fn_shuf .. ' ' .. global_conf.train_fn_shuf_bak)
os.execute('cat ' .. global_conf.train_fn_shuf_bak .. ' | sort -R --random-source=/dev/zero > ' .. global_conf.train_fn_shuf)
- printf("===PEEK ON TEST %d===\n", iter)
+ nerv.printf("===PEEK ON TEST %d===\n", iter)
result = LMTrainer.lm_process_file_rnn(global_conf, global_conf.test_fn, tnn, false) --false update!
ppl_rec[iter].test = result:ppl_all("rnn")
- printf("===VALIDATION %d===\n", iter)
+ nerv.printf("===VALIDATION %d===\n", iter)
result = LMTrainer.lm_process_file_rnn(global_conf, global_conf.valid_fn, tnn, false) --false update!
ppl_rec[iter].valid = result:ppl_all("rnn")
ppl_rec[iter].lr = global_conf.lrate
@@ -396,10 +403,10 @@ if commands["train"] == 1 then
global_conf.lrate = (global_conf.lrate * 0.6)
end
if ppl_rec[iter].valid < ppl_last then
- printf("%s PPL improves, saving net to file %s.%d...\n", global_conf.sche_log_pre, global_conf.param_fn, iter)
+ nerv.printf("%s PPL improves, saving net to file %s.%d...\n", global_conf.sche_log_pre, global_conf.param_fn, iter)
global_conf.paramRepo:export(global_conf.param_fn .. '.' .. tostring(iter), nil)
else
- printf("%s PPL did not improve, rejected, copying param file of last iter...\n", global_conf.sche_log_pre)
+ nerv.printf("%s PPL did not improve, rejected, copying param file of last iter...\n", global_conf.sche_log_pre)
os.execute('cp ' .. global_conf.param_fn..'.'..tostring(iter - 1) .. ' ' .. global_conf.param_fn..'.'..tostring(iter))
end
if ppl_last / ppl_rec[iter].valid < global_conf.lr_decay or lr_half == true then
@@ -408,21 +415,21 @@ if commands["train"] == 1 then
if ppl_rec[iter].valid < ppl_last then
ppl_last = ppl_rec[iter].valid
end
- printf("\n")
+ nerv.printf("\n")
nerv.LMUtil.wait(2)
end
nerv.info("saving final nn to param.final")
os.execute('cp ' .. global_conf.param_fn .. '.' .. tostring(final_iter) .. ' ' .. global_conf.param_fn .. '.final')
- printf("===VALIDATION PPL record===\n")
+ nerv.printf("===VALIDATION PPL record===\n")
for i, _ in pairs(ppl_rec) do
- printf("<ITER%d LR%.5f train:%.3f valid:%.3f test:%.3f> \n", i, ppl_rec[i].lr, ppl_rec[i].train, ppl_rec[i].valid, ppl_rec[i].test)
+ nerv.printf("<ITER%d LR%.5f train:%.3f valid:%.3f test:%.3f> \n", i, ppl_rec[i].lr, ppl_rec[i].train, ppl_rec[i].valid, ppl_rec[i].test)
end
- printf("\n")
+ nerv.printf("\n")
end --if commands["train"]
if commands["test"] == 1 then
- printf("===FINAL TEST===\n")
+ nerv.printf("===FINAL TEST===\n")
global_conf.sche_log_pre = "[SCHEDULER FINAL_TEST]:"
if final_iter ~= -1 and test_iter == -1 then
test_iter = final_iter
diff --git a/nerv/examples/lmptb/m-tests/sutil_test.lua b/nerv/examples/lmptb/m-tests/sutil_test.lua
index 95660d9..08a812c 100644
--- a/nerv/examples/lmptb/m-tests/sutil_test.lua
+++ b/nerv/examples/lmptb/m-tests/sutil_test.lua
@@ -10,3 +10,6 @@ for p, v in pairs(coms) do
end
nerv.sss = "sss"
print(nerv.sss)
+
+fh = assert(io.open("/home/slhome/txh18/workspace/nerv/play/try", "w"))
+fh:write("!!!2")
diff --git a/nerv/tnn/sutil.lua b/nerv/tnn/sutil.lua
index d88bd8e..78f88c0 100644
--- a/nerv/tnn/sutil.lua
+++ b/nerv/tnn/sutil.lua
@@ -62,3 +62,18 @@ function Util.parse_commands_set(str)
end
return coms
end
+
+function Util.log_redirect(fn)
+ nerv.log_fh = assert(io.open(fn, "w"))
+ nerv.info("CAUTION[LOG_REDIRECT], all nerv.printf/info/warning/error calls will be double-written to %s", fn)
+ nerv.printf =
+ function (fmt, ...)
+ io.write(nerv.sprintf(fmt, ...))
+ nerv.log_fh:write(nerv.sprintf(fmt, ...))
+ end
+ nerv.error =
+ function (fmt, ...)
+ nerv.log_fh:write(nerv.sprintf("[nerv] internal error:" .. fmt .. "\n", ...))
+ error(nerv.sprintf("[nerv] internal error: " .. fmt .. "\n", ...))
+ end
+end