add decode part to the nerv-kaldi tutorial

4 files changed, 27 insertions, 8 deletions

diff --git a/kaldi_io/tools/convert_from_kaldi_pretrain.sh b/kaldi_io/tools/convert_from_kaldi_pretrain.sh
index dc8ec8e..78f532f 100755
--- a/kaldi_io/tools/convert_from_kaldi_pretrain.sh
+++ b/kaldi_io/tools/convert_from_kaldi_pretrain.sh
@@ -23,7 +23,6 @@ dir=$6
 kaldi_to_nerv=$nerv_kaldi/tools/kaldi_to_nerv
 mkdir $dir -p
 mkdir $dir/log -p
-false && {
 ###### PREPARE DATASETS ######
 cp $data/feats.scp $dir/train_sorted.scp
 cp $data_cv/feats.scp $dir/cv.scp
@@ -42,10 +41,9 @@ nnet_init=$dir/nnet_output.init
 nnet-initialize --binary=false $nnet_proto $nnet_init
 
 ###### MODEL PARAMETER CONVERSION ######
-$kaldi_to_nerv $nnet_init $dir/nnet_output.nerv
+$kaldi_to_nerv $nnet_init $dir/nnet_output.nerv $hid_num
 $kaldi_to_nerv <(nnet-copy --binary=false $pretrain_dir/${hid_num}.dbn -) $dir/nnet_init.nerv
 $kaldi_to_nerv <(nnet-copy --binary=false $pretrain_dir/final.feature_transform -) $dir/nnet_trans.nerv
-}
 ###### PREPARE FOR DECODING #####
 echo "Using PDF targets from dirs '$alidir' '$alidir_cv'"
 # training targets in posterior format,
diff --git a/kaldi_io/tools/kaldi_to_nerv b/kaldi_io/tools/kaldi_to_nerv
index d08894d..78469f8 100755
--- a/kaldi_io/tools/kaldi_to_nerv
+++ b/kaldi_io/tools/kaldi_to_nerv
diff --git a/kaldi_io/tools/kaldi_to_nerv.cpp b/kaldi_io/tools/kaldi_to_nerv.cpp
index 0282b7c..f16de44 100644
--- a/kaldi_io/tools/kaldi_to_nerv.cpp
+++ b/kaldi_io/tools/kaldi_to_nerv.cpp
@@ -3,23 +3,40 @@
 #include <string>
 #include <cstring>
 #include <cassert>
+#include <cstdlib>
 
 char token[1024];
 char output[1024];
-double mat[4096][4096];
+
+double **new_matrix(int nrow, int ncol) {
+    double **mat = new double *[nrow];
+    int i;
+    for (i = 0; i < nrow; i++)
+        mat[i] = new double[ncol];
+    return mat;
+}
+
+void free_matrix(double **mat, int nrow, int ncol) {
+    int i;
+    for (i = 0; i < nrow; i++)
+        delete [] mat[i];
+    delete [] mat;
+}
+
 int main(int argc, char **argv) {
     FILE *fin;
     std::ofstream fout;
-    assert(argc == 3);
+    assert(argc >= 3);
     fin = fopen(argv[1], "r");
     fout.open(argv[2]);
     assert(fin != NULL);
-    int cnt = 0;
+    int cnt = argc > 3 ? atoi(argv[3]) : 0;
     bool shift;
     while (fscanf(fin, "%s", token) != EOF)
     {
         int nrow, ncol;
         int i, j;
+        double **mat;
         if (strcmp(token, "<AffineTransform>") == 0)
         {
             double lrate, blrate, mnorm;
@@ -29,6 +46,7 @@ int main(int argc, char **argv) {
             fscanf(fin, "%s", token);
             assert(*token == '[');
             printf("%d %d\n", nrow, ncol);
+            mat = new_matrix(nrow, ncol);
             for (j = 0; j < ncol; j++)
                 for (i = 0; i < nrow; i++)
                     fscanf(fin, "%lf", mat[i] + j);
@@ -75,12 +93,14 @@ int main(int argc, char **argv) {
                 fout.seekp(0, std::ios_base::end);
                 cnt++;
             }
+            free_matrix(mat, nrow, ncol);
         }
         else if ((shift = (strcmp(token, "<AddShift>") == 0)) ||
                 strcmp(token, "<Rescale>") == 0)
         {
             double lrate, blrate, mnorm;
             fscanf(fin, "%d %d", &ncol, &ncol);
+            mat = new_matrix(1, ncol);
             fscanf(fin, "%s %lf",
                     token, &lrate);
             fscanf(fin, "%s", token);
@@ -107,6 +127,7 @@ int main(int argc, char **argv) {
             fout.seekp(0, std::ios_base::end);
             fscanf(fin, "%s", token);
             assert(*token == ']');
+            free_matrix(mat, 1, ncol);
         }
     }
     return 0;
diff --git a/kaldi_io/tools/nerv_to_kaldi.lua b/kaldi_io/tools/nerv_to_kaldi.lua
index 804f09b..fba6a6c 100644
--- a/kaldi_io/tools/nerv_to_kaldi.lua
+++ b/kaldi_io/tools/nerv_to_kaldi.lua
@@ -1,8 +1,8 @@
--- usage: nerv config_file nerv_param_input tnet_output
+-- usage: nerv nerv_to_kaldi.lua config_file nerv_param_input kaldi_param_output
 
 dofile(arg[1])
 param_repo = nerv.ParamRepo()
-param_repo:import({arg[2], gconf.initialized_param[2]}, nil, gconf)
+param_repo:import({arg[2]}, nil, gconf)
 layer_repo = make_layer_repo(param_repo)
 f = assert(io.open(arg[3], "w"))