From 93eb84aca23526959b76401fd6509f151a589e9a Mon Sep 17 00:00:00 2001
From: Determinant <ted.sybil@gmail.com>
Date: Sun, 13 Mar 2016 16:18:36 +0800
Subject: add TNet tutorial; support converting global transf from TNet format

---
 htk_io/tools/tnet_to_nerv.c   | 57 -------------------------------------------
 htk_io/tools/tnet_to_nerv.cpp | 47 +++++++++++++++++++++++++++++++++--
 2 files changed, 45 insertions(+), 59 deletions(-)
 delete mode 100644 htk_io/tools/tnet_to_nerv.c

(limited to 'htk_io/tools')

diff --git a/htk_io/tools/tnet_to_nerv.c b/htk_io/tools/tnet_to_nerv.c
deleted file mode 100644
index 5774819..0000000
--- a/htk_io/tools/tnet_to_nerv.c
+++ /dev/null
@@ -1,57 +0,0 @@
-#include <stdio.h>
-#include <string.h>
-#include <stdlib.h>
-char token[1024];
-double mat[4096][4096];
-int main() {
-    FILE *fout = fopen("converted.nerv", "w");
-    int cnt = 0;
-    while (scanf("%s", token) != EOF)
-    {
-        int nrow, ncol;
-        int i, j;
-        if (strcmp(token, "<biasedlinearity>") == 0)
-        {
-            scanf("%d %d", &ncol, &nrow);
-            scanf("%s %d %d", token, &ncol, &nrow);
-            printf("%d %d\n", nrow, ncol);
-            for (j = 0; j < ncol; j++)
-                for (i = 0; i < nrow; i++)
-                    scanf("%lf", mat[i] + j);
-            off_t base = ftello(fout);
-            fprintf(fout, "%16d", 0);
-            fprintf(fout, "{type=\"nerv.LinearTransParam\",id=\"affine%d_ltp\"}\n",
-                            cnt);
-            fprintf(fout, "%d %d\n", nrow, ncol);
-            for (i = 0; i < nrow; i++)
-            {
-                for (j = 0; j < ncol; j++)
-                    fprintf(fout, "%.8f ", mat[i][j]);
-                fprintf(fout, "\n");
-            }
-            size_t length = ftello(fout) - base;
-            fseeko(fout, base, SEEK_SET);
-            fprintf(fout, "[%13lu]\n", length);
-            fseeko(fout, 0, SEEK_END);
-            if (scanf("%s %d", token, &ncol) == 2 && *token == 'v')
-            {
-                base = ftello(fout);
-                for (j = 0; j < ncol; j++)
-                    scanf("%lf", mat[0] + j);
-                fprintf(fout, "%16d", 0);
-                fprintf(fout, "{type=\"nerv.BiasParam\",id=\"affine%d_bp\"}\n",
-                        cnt);
-                fprintf(fout, "1 %d\n", ncol);
-                for (j = 0; j < ncol; j++)
-                    fprintf(fout, "%.8f ", mat[0][j]);
-                fprintf(fout, "\n");
-                length = ftello(fout) - base;
-                fseeko(fout, base, SEEK_SET);
-                fprintf(fout, "[%13lu]\n", length);
-                cnt++;
-                fseeko(fout, 0, SEEK_END);
-            }
-        }
-    }
-    return 0;
-}
diff --git a/htk_io/tools/tnet_to_nerv.cpp b/htk_io/tools/tnet_to_nerv.cpp
index 63a104d..067097e 100644
--- a/htk_io/tools/tnet_to_nerv.cpp
+++ b/htk_io/tools/tnet_to_nerv.cpp
@@ -4,6 +4,7 @@
 #include <cstring>
 #include <cassert>
 #include <cstdlib>
+#include <map>
 
 char token[1024];
 char output[1024];
@@ -23,6 +24,18 @@ void free_matrix(double **mat, int nrow, int ncol) {
     delete [] mat;
 }
 
+int cnt0;
+std::map<std::string, int> param_cnt;
+int get_param_cnt(const std::string &key) {
+    std::map<std::string, int>::iterator it = param_cnt.find(key);
+    if (it == param_cnt.end())
+    {
+        param_cnt[key] = cnt0 + 1;
+        return cnt0;
+    }
+    return it->second++;
+}
+
 int main(int argc, char **argv) {
     FILE *fin;
     std::ofstream fout;
@@ -30,12 +43,14 @@ int main(int argc, char **argv) {
     fin = fopen(argv[1], "r");
     fout.open(argv[2]);
     assert(fin != NULL);
-    int cnt = argc > 3 ? atoi(argv[3]) : 0;
+    cnt0 = argc > 3 ? atoi(argv[3]) : 0;
+    bool shift;
     while (fscanf(fin, "%s", token) != EOF)
     {
         int nrow, ncol;
         int i, j;
         double **mat;
+        int cnt = get_param_cnt(token);
         if (strcmp(token, "<biasedlinearity>") == 0)
         {
             fscanf(fin, "%d %d", &ncol, &nrow);
@@ -84,10 +99,38 @@ int main(int argc, char **argv) {
                 sprintf(output, "[%13lu]\n", length);
                 fout << output;
                 fout.seekp(0, std::ios_base::end);
-                cnt++;
             }
             free_matrix(mat, nrow, ncol);
         }
+        else if ((shift = (strcmp(token, "<bias>") == 0)) ||
+                strcmp(token, "<window>") == 0)
+        {
+            fscanf(fin, "%d %d", &ncol, &nrow);
+            printf("%d %d\n", nrow, ncol);
+            assert(nrow == ncol);
+            mat = new_matrix(1, ncol);
+            assert(fscanf(fin, "%s %d", token, &ncol) == 2 && *token == 'v');
+            for (j = 0; j < ncol; j++)
+                    fscanf(fin, "%lf", mat[0] + j);
+            long base = fout.tellp();
+            sprintf(output, "%16d", 0);
+            fout << output;
+            sprintf(output, "{type=\"nerv.BiasParam\",id=\"%s%d\"}\n",
+                    shift ? "bias" : "window",
+                    cnt);
+            fout << output;
+            sprintf(output, "%d %d\n", 1, ncol);
+            fout << output;
+            for (j = 0; j < ncol; j++)
+                fout << mat[0][j] << " ";
+            fout << std::endl;
+            long length = fout.tellp() - base;
+            fout.seekp(base);
+            sprintf(output, "[%13lu]\n", length);
+            fout << output;
+            fout.seekp(0, std::ios_base::end);
+            free_matrix(mat, 1, ncol);
+        }
     }
     return 0;
 }
-- 
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