changed auto-generating params, won not save in global_conf.param

1 files changed, 7 insertions, 6 deletions

diff --git a/nerv/examples/lmptb/tnn_ptb_main.lua b/nerv/examples/lmptb/tnn_ptb_main.lua
index 9156b61..16024a8 100644
--- a/nerv/examples/lmptb/tnn_ptb_main.lua
+++ b/nerv/examples/lmptb/tnn_ptb_main.lua
@@ -69,12 +69,12 @@ end
 function prepare_layers(global_conf)
     printf("%s preparing layers...\n", global_conf.sche_log_pre)
     
-    local paramRepo = global_conf.paramRepo
+    local pr = global_conf.paramRepo
 
     local du = false
 
     --local recurrentLconfig = {{["bp"] = "bp_h", ["ltp_hh"] = "ltp_hh"}, {["dim_in"] = {global_conf.hidden_size, global_conf.hidden_size}, ["dim_out"] = {global_conf.hidden_size}, ["break_id"] = global_conf.vocab:get_sen_entry().id, ["independent"] = global_conf.independent, ["clip"] = 10}}
-    local recurrentLconfig = {{}, {["dim_in"] = {global_conf.hidden_size, global_conf.hidden_size}, ["dim_out"] = {global_conf.hidden_size}, ["clip"] = 10, ["direct_update"] = du}}
+    local recurrentLconfig = {{}, {["dim_in"] = {global_conf.hidden_size, global_conf.hidden_size}, ["dim_out"] = {global_conf.hidden_size}, ["clip"] = 10, ["direct_update"] = du, ["pr"] = pr}}
 
     local layers = {
         ["nerv.AffineRecurrentLayer"] = {
@@ -82,7 +82,7 @@ function prepare_layers(global_conf)
         },
 
         ["nerv.SelectLinearLayer"] = {
-            ["selectL1"] = {{}, {["dim_in"] = {1}, ["dim_out"] = {global_conf.hidden_size}, ["vocab"] = global_conf.vocab}},
+            ["selectL1"] = {{}, {["dim_in"] = {1}, ["dim_out"] = {global_conf.hidden_size}, ["vocab"] = global_conf.vocab, ["pr"] = pr}},
         },
         
         ["nerv.SigmoidLayer"] = {
@@ -94,7 +94,7 @@ function prepare_layers(global_conf)
         },
 
         ["nerv.AffineLayer"] = {
-            ["outputL"] = {{}, {["dim_in"] = {global_conf.hidden_size}, ["dim_out"] = {global_conf.vocab:size()}, ["direct_update"] = du}},
+            ["outputL"] = {{}, {["dim_in"] = {global_conf.hidden_size}, ["dim_out"] = {global_conf.vocab:size()}, ["direct_update"] = du, ["pr"] = pr}},
         },
 
         ["nerv.SoftmaxCELayerT"] = {
@@ -111,7 +111,7 @@ function prepare_layers(global_conf)
     end
     --]]
 
-    local layerRepo = nerv.LayerRepo(layers, paramRepo, global_conf)
+    local layerRepo = nerv.LayerRepo(layers, pr, global_conf)
     printf("%s preparing layers end.\n", global_conf.sche_log_pre)
     return layerRepo
 end
@@ -220,7 +220,7 @@ global_conf = {
     test_fn = test_fn,
     vocab_fn = vocab_fn,
     sche_log_pre = "[SCHEDULER]:",
-    log_w_num = 40000, --give a message when log_w_num words have been processed
+    log_w_num = 400000, --give a message when log_w_num words have been processed
     timer = nerv.Timer(),
     work_dir_base = '/home/slhome/txh18/workspace/sentenceCompletion/EXP-Nerv/rnnlm_test'
 }
@@ -305,6 +305,7 @@ end
 if start_iter == -1 or start_iter == 0 then
     print("===INITIAL VALIDATION===") 
     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
     local result = LMTrainer.lm_process_file(global_conf, global_conf.valid_fn, tnn, false) --false update!
     nerv.LMUtil.wait(1)