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Clean elementwise_op_function (#15502)

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test=develop
inference-pre-release-gpu
chengduo 6 years ago committed by GitHub
parent 5cfc40dea8
commit bf91d11ed5
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1 changed files with 0 additions and 62 deletions
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paddle/fluid/operators/elementwise/elementwise_op_function.h
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@ -277,68 +277,6 @@ class TransformFunctor {
Functor func_;
};
#define EIGEN_FUNCTOR(name, eigen_op) \
struct Eigen##name##Functor { \
template <typename DeviceContext, typename T> \
inline void Run(const framework::Tensor *x, const framework::Tensor *y, \
framework::Tensor *z, \
const framework::ExecutionContext &ctx) { \
auto x_e = framework::EigenVector<T>::Flatten(*x); \
auto y_e = framework::EigenVector<T>::Flatten(*y); \
auto z_e = framework::EigenVector<T>::Flatten(*z); \
z_e.device( \
*ctx.template device_context<DeviceContext>().eigen_device()) = \
eigen_op(x_e, y_e); \
} \
template <typename DeviceContext, typename T> \
inline void RunBroadCast(const framework::Tensor *x, \
const framework::Tensor *y, framework::Tensor *z, \
const framework::ExecutionContext &ctx, int pre, \
int n) { \
auto x_e = framework::EigenVector<T>::Flatten(*x); \
auto y_e = framework::EigenVector<T>::Flatten(*y); \
auto z_e = framework::EigenVector<T>::Flatten(*z); \
auto y_bcast = y_e.reshape(Eigen::DSizes<int, 2>(1, n)) \
.broadcast(Eigen::DSizes<int, 2>(pre, 1)) \
.reshape(Eigen::DSizes<int, 1>(x_e.size())); \
z_e.device( \
*ctx.template device_context<DeviceContext>().eigen_device()) = \
eigen_op(x_e, y_bcast); \
} \
template <typename DeviceContext, typename T> \
inline void RunBroadCast2(const framework::Tensor *x, \
const framework::Tensor *y, \
framework::Tensor *z, \
const framework::ExecutionContext &ctx, int pre, \
int n, int post) { \
auto x_e = framework::EigenVector<T>::Flatten(*x); \
auto y_e = framework::EigenVector<T>::Flatten(*y); \
auto z_e = framework::EigenVector<T>::Flatten(*z); \
auto y_bcast = y_e.reshape(Eigen::DSizes<int, 3>(1, n, 1)) \
.broadcast(Eigen::DSizes<int, 3>(pre, 1, post)) \
.reshape(Eigen::DSizes<int, 1>(x_e.size())); \
z_e.device( \
*ctx.template device_context<DeviceContext>().eigen_device()) = \
eigen_op(x_e, y_bcast); \
} \
}
#define EIGEN_ADD(x, y) ((x) + (y))
EIGEN_FUNCTOR(Add, EIGEN_ADD);
#define EIGEN_SUB(x, y) ((x) - (y))
EIGEN_FUNCTOR(Sub, EIGEN_SUB);
#define EIGEN_MUL(x, y) ((x) * (y))
EIGEN_FUNCTOR(Mul, EIGEN_MUL);
#define EIGEN_DIV(x, y) ((x) / (y))
EIGEN_FUNCTOR(Div, EIGEN_DIV);
template <typename T, typename DX_OP, typename DY_OP>
struct ElemwiseGradNoBroadcast {
const T *x_;

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