Merge pull request #4 from uphantom/master

support fastnn multi-thread TNetReader

2 files changed, 159 insertions, 8 deletions

diff --git a/htk_io/tools/nerv_to_tnet.cpp b/htk_io/tools/nerv_to_tnet.cpp
new file mode 100644
index 0000000..91be7db
--- /dev/null
+++ b/htk_io/tools/nerv_to_tnet.cpp
@@ -0,0 +1,89 @@
+#include <stdio.h>
+#include <stdlib.h>
+#include <string>
+#include <cstring>
+#include <iostream>
+#include <fstream>
+
+char token[1024];
+typedef struct node
+{
+	double **mat;
+	int nrow;
+	int ncol;
+	int index;
+}node;
+
+int main(int argc, char **argv)
+{
+	if (argc != 3)
+    	{   
+        	printf("%s nerv.model.in tnet.model.out\n", argv[0]);
+    	}   
+
+    	freopen(argv[1], "r", stdin);
+    	freopen(argv[2], "w", stdout);
+	node* trans[100], *bp[100];
+	int layers = 0;
+	int i, j, k;
+	char type[128];
+	int idx = 0;
+	char *flag = "affine";
+	while (NULL != gets(token))
+    	{   
+        	int nrow, ncol;
+		if (token[0] == '{')
+		{
+			char *ss = strstr(token, flag);	
+    			if (sscanf(ss, "affine%d_%[a-z]", &idx, type) == 2)
+			{
+				node *no = new node;
+				scanf("%d %d", &nrow, &ncol);	
+				no->nrow = nrow;
+				no->ncol = ncol;
+				no->index = idx;
+				no->mat = (double **)malloc(nrow * sizeof(double *));
+				for (i = 0; i < nrow; i++)
+                		no->mat[i] = (double *)malloc(ncol * sizeof(double));
+                		for (i = 0; i < nrow; i++)
+            				for (j = 0; j < ncol; j++)
+                    			scanf("%lf", no->mat[i] + j);
+				
+				if (nrow == 1)
+					bp[idx] = no;
+				else
+					trans[idx] = no;		
+				layers++;
+			}
+		}
+	}
+	if (layers%2)
+	{
+		perror("number layers of LinearTrans and Bias is not the same.\n");
+		return -1;
+	}
+
+	layers /= 2;
+	for (i = 0; i < layers; i++)
+	{
+		printf("<biasedlinearity> %d %d\n", trans[i]->ncol, trans[i]->nrow);
+		printf("m %d %d\n", trans[i]->ncol, trans[i]->nrow);
+		for (j = 0; j < trans[i]->ncol; j++)
+		{
+			for (k = 0; k < trans[i]->nrow; k++)
+				printf("%.10lf ", trans[i]->mat[k][j]);		
+			printf("\n");
+		}
+		printf("v %d", bp[i]->ncol);	
+		for (j = 0; j < bp[i]->ncol; j++)
+			printf(" %.10lf", bp[i]->mat[0][j]);
+		printf("\n");	
+		if (i != layers - 1 && trans[i+1]->ncol < trans[i+1]->nrow)
+		printf("<sigmoid> %d %d\n", bp[i]->ncol, bp[i]->ncol);
+	}
+	printf("<softmax> %d %d\n", bp[layers - 1]->ncol, bp[layers - 1]->ncol);
+	perror("done!\n");
+
+	return 0;
+}
+
diff --git a/htk_io/tools/tnet_to_nerv.cpp b/htk_io/tools/tnet_to_nerv.cpp
index a779a25..f96781a 100644
--- a/htk_io/tools/tnet_to_nerv.cpp
+++ b/htk_io/tools/tnet_to_nerv.cpp
@@ -2,14 +2,22 @@
 #include <fstream>
 #include <string>
 #include <cstring>
-#include <cstdlib>
+#include <stdlib.h>
 char token[1024];
 char output[1024];
 double **mat;
 int main(int argc, char **argv) {
+
+    if (argc != 3)
+    {
+	printf("%s tnet.model.in nerv.model.out\n", argv[0]);
+    }
+
     std::ofstream fout;
-    fout.open(argv[1]);
-    int cnt = 0;
+    freopen(argv[1], "r", stdin);
+    fout.open(argv[2]);
+    int cnt = 0, bias = 1, win = 1;
+    long length = 0, base = 0;
     while (scanf("%s", token) != EOF)
     {
         int nrow, ncol;
@@ -19,13 +27,13 @@ int main(int argc, char **argv) {
             scanf("%d %d", &ncol, &nrow);
             scanf("%s %d %d", token, &ncol, &nrow);
             printf("%d %d\n", nrow, ncol);
-            mat = (double **)malloc(nrow * sizeof(double *));
+	    mat = (double **)malloc(nrow * sizeof(double *));
             for (i = 0; i < nrow; i++)
                 mat[i] = (double *)malloc(ncol * sizeof(double));
             for (j = 0; j < ncol; j++)
                 for (i = 0; i < nrow; i++)
                     scanf("%lf", mat[i] + j);
-            long base = fout.tellp();
+            base = fout.tellp();
             sprintf(output, "%16d", 0);
             fout << output;
             sprintf(output, "{type=\"nerv.LinearTransParam\",id=\"affine%d_ltp\"}\n",
@@ -38,10 +46,8 @@ int main(int argc, char **argv) {
                 for (j = 0; j < ncol; j++)
                     fout << mat[i][j] << " ";
                 fout << std::endl;
-                free(mat[i]);
             }
-            free(mat);
-            long length = fout.tellp() - base;
+            length = fout.tellp() - base;
             fout.seekp(base);
             sprintf(output, "[%13lu]\n", length);
             fout << output;
@@ -69,6 +75,62 @@ int main(int argc, char **argv) {
                 cnt++;
             }
         }
+	else if (strcmp(token, "<bias>") == 0)
+	{
+		scanf("%d %d", &ncol, &nrow);
+		scanf("%s %d", token, &ncol);	
+		base = fout.tellp();
+		nrow = 1;	
+		mat = (double **)malloc(nrow * sizeof(double *));
+            	for (i = 0; i < nrow; i++)
+                	mat[i] = (double *)malloc(ncol * sizeof(double));
+            	for (j = 0; j < ncol; j++)
+                	for (i = 0; i < nrow; i++)
+                    		scanf("%lf", mat[i] + j);
+                sprintf(output, "%16d", 0);
+                fout << output;
+                sprintf(output, "{type=\"nerv.MatrixParam\",id=\"bias%d\"}\n",bias);
+                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);
+                bias++;
+	}
+	else if (strcmp(token, "<window>") == 0)
+        {
+                scanf("%d %d", &ncol, &nrow);
+                scanf("%s %d", token, &ncol);
+                base = fout.tellp();
+		nrow = 1;
+                mat = (double **)malloc(nrow * sizeof(double *));
+                for (i = 0; i < nrow; i++)
+                        mat[i] = (double *)malloc(ncol * sizeof(double));
+                for (j = 0; j < ncol; j++)
+                        for (i = 0; i < nrow; i++)
+                                scanf("%lf", mat[i] + j);
+                sprintf(output, "%16d", 0);
+                fout << output;
+                sprintf(output, "{type=\"nerv.MatrixParam\",id=\"window%d\"}\n",win);
+                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);
+                win++;
+        }
     }
     return 0;
 }