| #include "caffe2/operators/acos_op.h" |
| |
| #include <algorithm> |
| #include <functional> |
| |
| #include "caffe2/core/context_gpu.h" |
| |
| namespace caffe2 { |
| |
| namespace { |
| |
| __global__ void AcosGradientCUDAKernel( |
| const int N, |
| const float* dY, |
| const float* X, |
| float* dX) { |
| CUDA_1D_KERNEL_LOOP(i, N) { |
| #if __CUDA_ARCH__ >= 350 |
| dX[i] = -__ldg(dY + i) * rsqrtf(1.0f - __ldg(X + i) * __ldg(X + i)); |
| #else |
| dX[i] = -dY[i] * rsqrtf(1.0f - X[i] * X[i]); |
| #endif |
| } |
| } |
| |
| } // namespace |
| |
| template <> |
| template <typename T> |
| bool AcosGradientFunctor<CUDAContext>::Forward( |
| const std::vector<int>& X_dims, |
| const std::vector<int>& /* dY_dims */, |
| const T* X, |
| const T* dY, |
| T* dX, |
| CUDAContext* context) const { |
| const int size = std::accumulate( |
| X_dims.cbegin(), X_dims.cend(), 1, std::multiplies<int>()); |
| AcosGradientCUDAKernel<<< |
| CAFFE_GET_BLOCKS(size), |
| CAFFE_CUDA_NUM_THREADS, |
| 0, |
| context->cuda_stream()>>>(size, dY, X, dX); |
| C10_CUDA_KERNEL_LAUNCH_CHECK(); |
| |
| return true; |
| } |
| |
| REGISTER_CUDA_OPERATOR( |
| Acos, |
| UnaryElementwiseOp< |
| TensorTypes<float>, |
| CUDAContext, |
| AcosFunctor<CUDAContext>>); |
| REGISTER_CUDA_OPERATOR( |
| AcosGradient, |
| BinaryElementwiseOp< |
| TensorTypes<float>, |
| CUDAContext, |
| AcosGradientFunctor<CUDAContext>>); |
| |
| } // namespace caffe2 |