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elementwise_kernel.cc
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elementwise_kernel.cc
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// Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
#include "paddle/phi/kernels/elementwise_kernel.h"
#include "paddle/phi/backends/all_context.h"
#include "paddle/phi/core/kernel_registry.h"
namespace phi {
template <typename T, typename Context>
void AddKernel(const Context& dev_ctx,
const DenseTensor& x,
const DenseTensor& y,
DenseTensor* out) {
int axis = -1;
AddRawKernel<T>(dev_ctx, x, y, axis, out);
}
template <typename T, typename Context>
void SubtractKernel(const Context& dev_ctx,
const DenseTensor& x,
const DenseTensor& y,
DenseTensor* out) {
int axis = -1;
SubtractRawKernel<T>(dev_ctx, x, y, axis, out);
}
template <typename T, typename Context>
void DivideKernel(const Context& dev_ctx,
const DenseTensor& x,
const DenseTensor& y,
DenseTensor* out) {
int axis = -1;
DivideRawKernel<T>(dev_ctx, x, y, axis, out);
}
template <typename T, typename Context>
void MultiplyKernel(const Context& dev_ctx,
const DenseTensor& x,
const DenseTensor& y,
DenseTensor* out) {
int axis = -1;
MultiplyRawKernel<T>(dev_ctx, x, y, axis, out);
}
template <typename T, typename Context>
void MaximumKernel(const Context& dev_ctx,
const DenseTensor& x,
const DenseTensor& y,
DenseTensor* out) {
int axis = -1;
MaximumRawKernel<T>(dev_ctx, x, y, axis, out);
}
template <typename T, typename Context>
void MinimumKernel(const Context& dev_ctx,
const DenseTensor& x,
const DenseTensor& y,
DenseTensor* out) {
int axis = -1;
MinimumRawKernel<T>(dev_ctx, x, y, axis, out);
}
template <typename T, typename Context>
void ModuloKernel(const Context& dev_ctx,
const DenseTensor& x,
const DenseTensor& y,
DenseTensor* out) {
int axis = -1;
ModuloRawKernel<T>(dev_ctx, x, y, axis, out);
}
template <typename T, typename Context>
void FloorDivideKernel(const Context& dev_ctx,
const DenseTensor& x,
const DenseTensor& y,
DenseTensor* out) {
int axis = -1;
FloorDivideRawKernel<T>(dev_ctx, x, y, axis, out);
}
template <typename T, typename Context>
void ElementwisePowKernel(const Context& dev_ctx,
const DenseTensor& x,
const DenseTensor& y,
DenseTensor* out) {
int axis = -1;
ElementwisePowRawKernel<T>(dev_ctx, x, y, axis, out);
}
template <typename T, typename Context>
void ElementwiseHeavisideKernel(const Context& dev_ctx,
const DenseTensor& x,
const DenseTensor& y,
DenseTensor* out) {
int axis = -1;
ElementwiseHeavisideRawKernel<T>(dev_ctx, x, y, axis, out);
}
} // namespace phi
using complex64 = ::phi::dtype::complex<float>;
using complex128 = ::phi::dtype::complex<double>;
PD_REGISTER_KERNEL(add,
CPU,
ALL_LAYOUT,
phi::AddKernel,
float,
double,
int16_t,
int,
int64_t,
complex64,
complex128) {}
PD_REGISTER_KERNEL(subtract,
CPU,
ALL_LAYOUT,
phi::SubtractKernel,
float,
double,
int16_t,
int,
int64_t,
complex64,
complex128,
phi::dtype::bfloat16) {}
PD_REGISTER_KERNEL(divide,
CPU,
ALL_LAYOUT,
phi::DivideKernel,
float,
double,
int,
int64_t,
complex64,
complex128) {}
PD_REGISTER_KERNEL(multiply,
CPU,
ALL_LAYOUT,
phi::MultiplyKernel,
float,
double,
int,
int64_t,
bool,
complex64,
complex128,
phi::dtype::bfloat16) {}
PD_REGISTER_KERNEL(maximum,
CPU,
ALL_LAYOUT,
phi::MaximumKernel,
float,
double,
int,
int64_t,
phi::dtype::bfloat16) {}
PD_REGISTER_KERNEL(minimum,
CPU,
ALL_LAYOUT,
phi::MinimumKernel,
float,
double,
int,
int64_t,
phi::dtype::bfloat16) {}
PD_REGISTER_KERNEL(
modulo, CPU, ALL_LAYOUT, phi::ModuloKernel, float, double, int, int64_t) {}
PD_REGISTER_KERNEL(
floor_divide, CPU, ALL_LAYOUT, phi::FloorDivideKernel, int, int64_t) {}
PD_REGISTER_KERNEL(elementwise_heaviside,
CPU,
ALL_LAYOUT,
phi::ElementwiseHeavisideKernel,
float,
double,
int,
int64_t) {}
PD_REGISTER_KERNEL(elementwise_pow,
CPU,
ALL_LAYOUT,
phi::ElementwisePowKernel,
float,
double,
int,
int64_t) {}
#if defined(PADDLE_WITH_CUDA) || defined(PADDLE_WITH_HIP)
PD_REGISTER_KERNEL(add,
GPU,
ALL_LAYOUT,
phi::AddKernel,
float,
double,
int16_t,
int,
int64_t,
phi::dtype::float16,
phi::dtype::bfloat16,
complex64,
complex128) {}
PD_REGISTER_KERNEL(subtract,
GPU,
ALL_LAYOUT,
phi::SubtractKernel,
float,
double,
int16_t,
int,
int64_t,
phi::dtype::float16,
complex64,
complex128,
phi::dtype::bfloat16) {}
PD_REGISTER_KERNEL(divide,
GPU,
ALL_LAYOUT,
phi::DivideKernel,
float,
double,
int,
int64_t,
phi::dtype::float16,
phi::dtype::bfloat16,
complex64,
complex128) {}
PD_REGISTER_KERNEL(multiply,
GPU,
ALL_LAYOUT,
phi::MultiplyKernel,
float,
double,
int,
int64_t,
bool,
phi::dtype::float16,
phi::dtype::bfloat16,
complex64,
complex128) {}
PD_REGISTER_KERNEL(maximum,
GPU,
ALL_LAYOUT,
phi::MaximumKernel,
float,
double,
int,
int64_t,
phi::dtype::float16,
phi::dtype::bfloat16) {}
PD_REGISTER_KERNEL(minimum,
GPU,
ALL_LAYOUT,
phi::MinimumKernel,
float,
double,
int,
int64_t,
phi::dtype::float16,
phi::dtype::bfloat16) {}
PD_REGISTER_KERNEL(
modulo, GPU, ALL_LAYOUT, phi::ModuloKernel, float, double, int, int64_t) {}
PD_REGISTER_KERNEL(
floor_divide, GPU, ALL_LAYOUT, phi::FloorDivideKernel, int, int64_t) {}
PD_REGISTER_KERNEL(elementwise_heaviside,
GPU,
ALL_LAYOUT,
phi::ElementwiseHeavisideKernel,
float,
double,
int,
int64_t) {}
PD_REGISTER_KERNEL(elementwise_pow,
GPU,
ALL_LAYOUT,
phi::ElementwisePowKernel,
float,
double,
int,
int64_t) {}
#endif