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#include "caffe2/operators/cube_op.h"
#include <algorithm>
#include <functional>
#include "caffe2/core/context_gpu.h"
namespace caffe2 {
namespace {
template <typename T>
__global__ void
CubeGradientCUDAKernel(const int N, const T* dY, const T* X, T* dX) {
CUDA_1D_KERNEL_LOOP(i, N) {
#if __CUDA_ARCH__ >= 350
dX[i] = __ldg(dY + i) * __ldg(X + i) * __ldg(X + i) * T(3);
#else
dX[i] = dY[i] * X[i] * X[i] * T(3);
#endif
}
}
} // namespace
template <>
template <typename T>
bool CubeGradientFunctor<CUDAContext>::Forward(
const std::vector<int>& dY_dims,
const std::vector<int>& /* X_dims */,
const T* dY,
const T* X,
T* dX,
CUDAContext* context) const {
const int size = std::accumulate(
dY_dims.cbegin(), dY_dims.cend(), 1, std::multiplies<int>());
CubeGradientCUDAKernel<T>
<<<CAFFE_GET_BLOCKS(size),
CAFFE_CUDA_NUM_THREADS,
0,
context->cuda_stream()>>>(size, dY, X, dX);
return true;
}
REGISTER_CUDA_OPERATOR(
Cube,
UnaryElementwiseOp<NumericTypes, CUDAContext, CubeFunctor<CUDAContext>>);
REGISTER_CUDA_OPERATOR(
CubeGradient,
BinaryElementwiseOp<
NumericTypes,
CUDAContext,
CubeGradientFunctor<CUDAContext>>);
} // namespace caffe2
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