1 files changed, 109 insertions, 0 deletions
diff --git a/kaldi_io/tools/kaldi_to_nerv.cpp b/kaldi_io/tools/kaldi_to_nerv.cpp
new file mode 100644
index 0000000..1edb0f2
--- /dev/null
+++ b/kaldi_io/tools/kaldi_to_nerv.cpp
@@ -0,0 +1,109 @@
+#include <cstdio>
+#include <fstream>
+#include <string>
+#include <cstring>
+#include <cassert>
+
+char token[1024];
+char output[1024];
+double mat[4096][4096];
+int main(int argc, char **argv) {
+    std::ofstream fout;
+    fout.open(argv[1]);
+    int cnt = 0;
+    bool shift;
+    while (scanf("%s", token) != EOF)
+    {
+        int nrow, ncol;
+        int i, j;
+        if (strcmp(token, "<AffineTransform>") == 0)
+        {
+            double lrate, blrate, mnorm;
+            scanf("%d %d", &ncol, &nrow);
+            scanf("%s %lf %s %lf %s %lf",
+                    token, &lrate, token, &blrate, token, &mnorm);
+            scanf("%s", token);
+            assert(*token == '[');
+            printf("%d %d\n", nrow, ncol);
+            for (j = 0; j < ncol; j++)
+                for (i = 0; i < nrow; i++)
+                    scanf("%lf", mat[i] + j);
+            long base = fout.tellp();
+            sprintf(output, "%16d", 0);
+            fout << output;
+            sprintf(output, "{type=\"nerv.LinearTransParam\",id=\"affine%d_ltp\"}\n",
+                    cnt);
+            fout << output;
+            sprintf(output, "%d %d\n", nrow, ncol);
+            fout << output;
+            for (i = 0; i < nrow; i++)
+            {
+                for (j = 0; j < ncol; j++)
+                    fout << mat[i][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);
+            scanf("%s", token);
+            assert(*token == ']');
+            if (scanf("%s", token) == 1 && *token == '[')
+            {
+                base = fout.tellp();
+                for (j = 0; j < ncol; j++)
+                    scanf("%lf", mat[0] + j);
+                sprintf(output, "%16d", 0);
+                fout << output;
+                sprintf(output, "{type=\"nerv.BiasParam\",id=\"affine%d_bp\"}\n",
+                        cnt);
+                fout << output;
+                sprintf(output, "1 %d\n", ncol);
+                fout << output;
+                for (j = 0; j < ncol; j++)
+                    fout << mat[0][j] << " ";
+                fout << std::endl;
+                length = fout.tellp() - base;
+                fout.seekp(base);
+                sprintf(output, "[%13lu]\n", length);
+                fout << output;
+                fout.seekp(0, std::ios_base::end);
+                cnt++;
+            }
+        }
+        else if ((shift = (strcmp(token, "<AddShift>") == 0)) ||
+                strcmp(token, "<Rescale>") == 0)
+        {
+            double lrate, blrate, mnorm;
+            scanf("%d %d", &ncol, &ncol);
+            scanf("%s %lf",
+                    token, &lrate);
+            scanf("%s", token);
+            assert(*token == '[');
+            printf("%d\n", ncol);
+            for (j = 0; j < ncol; j++)
+                    scanf("%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);
+            scanf("%s", token);
+            assert(*token == ']');
+        }
+    }
+    return 0;
+}