fix the bug in Merge

source/network/XBackwardShape.cpp

@@ -246,13 +246,16 @@ void XShapeGrad::GradMerge(XTensor * node, bool isEfficient)
                 dims[j++] = input->dimSize[i];
             }
         }
-        dims[0] = -dims[0];
+
+        dims[0] = -abs(dims[0]);
         XTensor gradInputSmall(input->order - leadDim, dims,
                                input->dataType, input->denseRatio,
                                input->devID, input->mem);
 
-        dims[whereToMerge - leadDim] *= dims[0];
-        XTensor gradNodeSmall(node->order - leadDim, dims + leadDim + 1,
+        dims[whereToMerge - leadDim] *= abs(dims[0]);
+        int * dimsNode = dims + 1;
+        dimsNode[0] = -abs(dimsNode[0]);
+        XTensor gradNodeSmall(node->order - leadDim, dimsNode,
                               node->dataType, node->denseRatio,
                               node->devID, node->mem);
 

source/tensor/core/shape/Merge.cpp

@@ -32,14 +32,14 @@ namespace nts { // namespace nts(NiuTrans.Tensor)
 /*
 transform a tensor by merging it along with a dimension.
 
-e.g., (N/3, M, 3) -> (N, M)
+e.g., (3, M, N/3) -> (M, N)
 
 >> s - the source tensor
 >> t - the target tensor (for return)
 >> whereToMerge - the merging operation is along with which dimension
->> leadingDim - the leading dimension of merging, take (N/3, M, 3) -> (N, M) 
-   for example, whereToMerge = 0 (i.e., the dimension for "N/3")
-   leadingDim = 2 (i.e., the dimension for "3")
+>> leadingDim - the leading dimension of merging, take (3, M, N/3) -> (M, N)
+                for example, whereToMerge = 2 (i.e., the dimension for "N/3")
+                leadingDim = 0 (i.e., the dimension for "3")
 */
 void _Merge(const XTensor * s, XTensor * t, int whereToMerge, int leadingDim)
 {