| #include "caffe2/core/context_gpu.h" | 
 | #include "caffe2/operators/clip_op.h" | 
 |  | 
 | namespace caffe2 { | 
 | namespace { | 
 |  | 
 | template <typename T> | 
 | __device__ T cuda_min(T x, T y); | 
 | template <typename T> | 
 | __device__ T cuda_max(T x, T y); | 
 | template <> | 
 | __device__ float cuda_min(float x, float y) { return fminf(x, y); } | 
 | template <> | 
 | __device__ float cuda_max(float x, float y) { return fmaxf(x, y); } | 
 |  | 
 | // Disabled since we don't use it right now. | 
 | /* | 
 | template <> | 
 | __device__ double cuda_min(double x, double y) { return fmin(x, y); } | 
 | template <> | 
 | __device__ double cuda_max(double x, double y) { return fmax(x, y); } | 
 | */ | 
 |  | 
 |  | 
 | template <typename T> | 
 | __global__ void ClipKernel(const int N, const T minval, const T maxval, | 
 |                            const T* X, T* Y) { | 
 |   CUDA_1D_KERNEL_LOOP(i, N) { | 
 |     Y[i] = cuda_min<T>(cuda_max<T>(X[i], minval), maxval); | 
 |   } | 
 | } | 
 |  | 
 | template <typename T> | 
 | __global__ void ClipGradientKernel(const int N,  const T minval, | 
 |                                    const T maxval, const T* Y, | 
 |                                    const T* dY, T* dX) { | 
 |   CUDA_1D_KERNEL_LOOP(i, N) { | 
 |     dX[i] = dY[i] * (Y[i] > minval && Y[i] < maxval); | 
 |   } | 
 | } | 
 | }  // namespace | 
 |  | 
 | template <> | 
 | bool ClipOp<float, CUDAContext>::RunOnDevice() { | 
 |   auto& X = Input(0); | 
 |   auto* Y = Output(0); | 
 |   CAFFE_ENFORCE_GT(X.size(), 0); | 
 |   Y->ResizeLike(X); | 
 |   ClipKernel<<<CAFFE_GET_BLOCKS(X.size()), CAFFE_CUDA_NUM_THREADS, | 
 |                0, context_.cuda_stream()>>>( | 
 |       X.size(), min_, max_, X.data<float>(), Y->mutable_data<float>()); | 
 |   return true; | 
 | } | 
 |  | 
 | template <> | 
 | bool ClipGradientOp<float, CUDAContext>::RunOnDevice() { | 
 |   auto& Y = Input(0); | 
 |   auto& dY = Input(1); | 
 |   auto* dX = Output(0); | 
 |   CAFFE_ENFORCE_GT(Y.size(), 0); | 
 |   CAFFE_ENFORCE_EQ(dY.size(), Y.size()); | 
 |   dX->ResizeLike(Y); | 
 |   ClipGradientKernel<<<CAFFE_GET_BLOCKS(Y.size()), CAFFE_CUDA_NUM_THREADS, | 
 |                        0, context_.cuda_stream()>>>( | 
 |       Y.size(), min_, max_, Y.data<float>(), dY.data<float>(), | 
 |       dX->mutable_data<float>()); | 
 |   return true; | 
 | } | 
 |  | 
 | REGISTER_CUDA_OPERATOR(Clip, ClipOp<float, CUDAContext>); | 
 | REGISTER_CUDA_OPERATOR(ClipGradient, ClipGradientOp<float, CUDAContext>); | 
 | }  // namespace caffe2 |