Update the CUDA kernel.

paddle/operators/math/math_function.cu

@@ -274,15 +274,14 @@ void set_constant_with_place<platform::CUDAPlace>(
 }
 
 template <typename T>
-__global__ void RowwiseAddKernel(const T* a, const T* b, T* c, int64_t height,
-                                 int64_t width) {
-  int64_t num = height * width;
+__global__ void RowwiseAddKernel(const T* a, const T* b, T* c, int width,
+                                 int num) {
+  T tmp = 1.0 / width;
   for (int i = blockIdx.x * blockDim.x + threadIdx.x; i < num;
        i += blockDim.x * gridDim.x) {
-    int h = i / width;
-    int w = i % width;
-    int idx = h * width + w;
-    c[idx] = a[idx] + b[w];
+    int h = i * tmp;
+    int w = i - h * width;
+    c[i] = a[i] + b[w];
   }
 }
 
@@ -292,11 +291,14 @@ struct RowwiseAdd<platform::CUDADeviceContext, T> {
                   const framework::Tensor& input,
                   const framework::Tensor& vector, framework::Tensor* output) {
     auto in_dims = input.dims();
+    auto size = input.numel() / in_dims[0];
+    PADDLE_ENFORCE_EQ(vector.numel(), size);
+    PADDLE_ENFORCE_EQ(output->dims(), in_dims);
     int blocks = 512;
     int grids = (input.numel() + blocks - 1) / blocks;
     RowwiseAddKernel<T><<<grids, blocks, 0, context.stream()>>>(
-        input.data<T>(), vector.data<T>(), output->data<T>(), in_dims[0],
-        in_dims[1]);
+        input.data<T>(), vector.data<T>(), output->data<T>(),
+        static_cast<int>(in_dims[1]), static_cast<int>(input.numel()));
   }
 };