add MODX to make the functions accept dimension index with a minus value

source/tensor/XGlobal.h

@@ -157,7 +157,9 @@ extern bool useCUDA;
 #define XPRINT7(VERBOSE,FILEH,STR,ARG,ARG2,ARG3,ARG4,ARG5,ARG6,ARG7) {if(VERBOSE<=verboseLevel) {fprintf(FILEH,STR,ARG,ARG2,ARG3,ARG4,ARG5,ARG6,ARG7);FFLUSH(FILEH);}}
 #define XPRINT8(VERBOSE,FILEH,STR,ARG,ARG2,ARG3,ARG4,ARG5,ARG6,ARG7,ARG8) {if(VERBOSE<=verboseLevel) {fprintf(FILEH,STR,ARG,ARG2,ARG3,ARG4,ARG5,ARG6,ARG7,ARG8);FFLUSH(FILEH);}}
 
-#define B2I(V) V==0?false:true
+#define B2I(V) V == 0 ? false : true
+
+#define MODX(a, b) int(b == 0 ? a : a - floor(double(a)/b) * b)
 
 /* BLAS interfaces */
 #ifdef DOUBELPRICSION

source/tensor/core/arithmetic/DivDim.cpp

@@ -42,6 +42,8 @@ i.e., a is divided with b by broadcasting
 */
 void _DivDim(const XTensor * a, const XTensor * b, XTensor * c, int n, DTYPE alpha)
 {
+    n = MODX(n, a->order);
+
     CheckNTErrors(a && b && c, "Empty tensor input!");
     CheckNTErrors(a->unitNum == c->unitNum, "Unmatched tensors in division!");
     CheckNTErrors(a->dataType == b->dataType && a->dataType == c->dataType,
@@ -151,6 +153,8 @@ XTensor DivDim(const XTensor &a, const XTensor &b, int n, DTYPE alpha)
 {
     XTensor c(&a);
     c.SetTMPFlag();
+
+    n = MODX(n, a.order);
     
     /* call _Div function */
     _DivDim(&a, &b, &c, n, alpha);

source/tensor/core/arithmetic/MultiplyDim.cpp

@@ -42,8 +42,10 @@ i.e., a is multiplied with b by broadcasting
 >> n - the dimension index
 >> alpha - the scaling factor
 */
-void _MultiplyDim(const XTensor * a, const XTensor * b, XTensor * c, int n, DTYPE alpha) {
-    
+void _MultiplyDim(const XTensor * a, const XTensor * b, XTensor * c, int n, DTYPE alpha) 
+{
+    n = MODX(n, a->order);
+
     CheckNTErrors(a && b && c, "Empty tensor input!");
     CheckNTErrors(a->unitNum == c->unitNum, "Unmatched tensors in multiplication!");
     CheckNTErrors(a->dataType == b->dataType && a->dataType == c->dataType,
@@ -151,6 +153,8 @@ XTensor MultiplyDim(const XTensor &a, const XTensor &b, int n)
     XTensor c(&a);
     c.SetTMPFlag();
 
+    n = MODX(n, a.order);
+
     /* call _Multiply function */
     _MultiplyDim(&a, &b, &c, n, 0);
 

source/tensor/core/arithmetic/SubDim.cpp

@@ -42,6 +42,8 @@ i.e., a is subtracted with b by broadcasting
 */
 void _SubDim(const XTensor * a, const XTensor * b, XTensor * c, int n, DTYPE beta)
 {
+    n = MODX(n, a->order);
+
 	CheckNTErrors(a && b && c, "Empty tensor input!");
 	CheckNTErrors(a->unitNum == c->unitNum, "Unmatched tensors in subtraction!");
 	CheckNTErrors(a->dataType == b->dataType && a->dataType == c->dataType,
@@ -152,6 +154,8 @@ XTensor SubDim(const XTensor &a, const XTensor &b, int n, DTYPE beta)
 	XTensor c(&a);
 	c.SetTMPFlag();
 
+    n = MODX(n, a.order);
+
 	/* call _Sub function */
 	_SubDim(&a, &b, &c, n, beta);
 

source/tensor/core/arithmetic/SumDim.cpp

@@ -46,6 +46,8 @@ i.e., a is summed with b by broadcasting
 */
 void _SumDim(const XTensor * a, const XTensor * b, XTensor * c, int n, DTYPE beta)
 {
+    n = MODX(n, a->order);
+
     CheckNTErrors(a && b && c, "Empty tensor input!");
     CheckNTErrors(a->unitNum == c->unitNum, "Unmatched tensors in addition!");
     CheckNTErrors(a->dataType == b->dataType && a->dataType == c->dataType,
@@ -169,6 +171,8 @@ XTensor SumDim(const XTensor &a, const XTensor &b, int n, DTYPE beta)
 {
     XTensor c(&a);
     c.SetTMPFlag();
+
+    n = MODX(n, a.order);
     
     /* call _SumDim function */
     _SumDim(&a, &b, &c, n, beta);