/* Copyright (c) 2016 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. */ #pragma once #ifdef __xpu__ #include #include #include "paddle/fluid/operators/elementwise/elementwise_op.h" #include "paddle/fluid/operators/elementwise/elementwise_op_broadcast.cu.h" #include "paddle/fluid/operators/elementwise/elementwise_xpu.h" #include "paddle/fluid/platform/device/device_wrapper.h" #else #include #include #include "paddle/fluid/operators/elementwise/elementwise_op.h" // only can include the headers in paddle/phi/include dirs #include "paddle/phi/kernels/elementwise_grad_kernel.h" #include "paddle/phi/kernels/math_kernel.h" #endif namespace paddle { namespace operators { template class ElementwiseAddKernel : public framework::OpKernel { public: void Compute(const framework::ExecutionContext& ctx) const override { #ifdef __xpu__ std::vector ins; std::vector outs; int axis = PackTensorsIntoVector(ctx, &ins, &outs); const auto& xpu_ctx = ctx.template device_context(); paddle::operators::LaunchElementwiseCudaKernel, 1>( xpu_ctx, ins, &outs, axis, kps::AddFunctor()); #else auto *x = ctx.Input("X"); auto *y = ctx.Input("Y"); auto *z = ctx.Output("Out"); z->mutable_data(ctx.GetPlace()); auto &dev_ctx = ctx.device_context(); int axis = ctx.Attr("axis"); phi::AddRawKernel( static_cast::TYPE &>(dev_ctx), *x, *y, axis, z); #endif } }; } // namespace operators } // namespace paddle