// 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 void AddKernel(const Context& dev_ctx, const DenseTensor& x, const DenseTensor& y, DenseTensor* out) { int axis = -1; AddRawKernel(dev_ctx, x, y, axis, out); } template void SubtractKernel(const Context& dev_ctx, const DenseTensor& x, const DenseTensor& y, DenseTensor* out) { int axis = -1; SubtractRawKernel(dev_ctx, x, y, axis, out); } template void DivideKernel(const Context& dev_ctx, const DenseTensor& x, const DenseTensor& y, DenseTensor* out) { int axis = -1; DivideRawKernel(dev_ctx, x, y, axis, out); } template void MultiplyKernel(const Context& dev_ctx, const DenseTensor& x, const DenseTensor& y, DenseTensor* out) { int axis = -1; MultiplyRawKernel(dev_ctx, x, y, axis, out); } template void MaximumKernel(const Context& dev_ctx, const DenseTensor& x, const DenseTensor& y, DenseTensor* out) { int axis = -1; MaximumRawKernel(dev_ctx, x, y, axis, out); } template void MinimumKernel(const Context& dev_ctx, const DenseTensor& x, const DenseTensor& y, DenseTensor* out) { int axis = -1; MinimumRawKernel(dev_ctx, x, y, axis, out); } template void ModuloKernel(const Context& dev_ctx, const DenseTensor& x, const DenseTensor& y, DenseTensor* out) { int axis = -1; ModuloRawKernel(dev_ctx, x, y, axis, out); } } // namespace phi using complex64 = ::phi::dtype::complex; using complex128 = ::phi::dtype::complex; 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) {} #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) {} #endif