misuse of dimSize and dimSizeRDI

source/tensor/core/arithmetic/MatrixMul.cpp

@@ -50,8 +50,8 @@ Obviously C = A * B performs normal matrix multiplication if A = y * z and B = x
 >> parallelRunner - parallel processing module
 */
 void _MatrixMul(const XTensor * a, MATRIX_TRANS_TYPE transposedA,
-               const XTensor * b, MATRIX_TRANS_TYPE transposedB,
-               XTensor * c, DTYPE alpha, DTYPE beta, XPRunner * parallelRunner)
+                const XTensor * b, MATRIX_TRANS_TYPE transposedB,
+                XTensor * c, DTYPE alpha, DTYPE beta, XPRunner * parallelRunner)
 {
     CheckNTErrors((a && b && c), "Empty input tensors!");
     CheckNTErrors((a->dataType == b->dataType && a->dataType == c->dataType),
@@ -210,9 +210,9 @@ Obviously C = A * B performs normal matrix multiplication if A = y * z and B = x
 XTensor MatrixMul(const XTensor &a, MATRIX_TRANS_TYPE transposedA, const XTensor &b, MATRIX_TRANS_TYPE transposedB, 
                  DTYPE alpha, DTYPE beta, XPRunner * parallelRunner)
 {
-    CheckNTErrors((&a != &NULLTensor && &b != &NULLTensor), "Empty input tensors!");
-    CheckNTErrors((a.dataType == b.dataType), "Input tensors should have the same data type!");
-    CheckNTErrors((a.order >= 2 && b.order >= 2), "Input tensors must have a order >= 2!");
+    CheckNTErrors(&a != &NULLTensor && &b != &NULLTensor, "Empty input tensors!");
+    CheckNTErrors(a.dataType == b.dataType, "Input tensors should have the same data type!");
+    CheckNTErrors(a.order >= 2 && b.order >= 2, "Input tensors must have a order >= 2!");
 
     int an = transposedA == X_TRANS ? a.dimSizeRDI[0] : a.dimSizeRDI[1];
     int am = transposedA == X_TRANS ? a.dimSizeRDI[1] : a.dimSizeRDI[0];
@@ -224,15 +224,15 @@ XTensor MatrixMul(const XTensor &a, MATRIX_TRANS_TYPE transposedA, const XTensor
     int order = a.order + b.order - 2;
     int sub = 0;
     int * dimSize = new int[order];
-    for (int i = 2; i < a.order; i++)
-        dimSize[sub++] = a.dimSizeRDI[i];
     for (int i = 2; i < b.order; i++)
-        dimSize[sub++] = b.dimSizeRDI[i];
+        dimSize[sub++] = b.dimSizeRDI[b.order + 1 - i];
+    for (int i = 2; i < a.order; i++)
+        dimSize[sub++] = a.dimSizeRDI[a.order + 1 - i];
     dimSize[sub++] = an;
     dimSize[sub++] = bm;
 
-    XTensor c = NewTensor(order, dimSize, a.dataType, a.denseRatio, a.devID, a.mem);
-    c.SetZeroAll();
+    float dr = (!a.isSparse || !b.isSparse) ? 1.0F : MAX(a.denseRatio, b.denseRatio);
+    XTensor c(order, dimSize, a.dataType, dr, a.devID, a.mem);
     c.SetTMP();
 
     /* call _MatrixMul function */