// Copyright (c) 2020 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 #include "paddle/fluid/framework/op_registry.h" #include "paddle/fluid/framework/operator.h" // only can include the headers in paddle/pten/api dirs #include "paddle/pten/api/lib/utils/tensor_utils.h" #include "paddle/pten/include/core.h" #include "paddle/pten/kernels/complex_kernel.h" namespace paddle { namespace operators { using Tensor = framework::Tensor; template <typename DeviceContext, typename T> class ConjKernel : public framework::OpKernel<T> { public: void Compute(const framework::ExecutionContext& context) const override { const Tensor* x = context.Input<Tensor>("X"); Tensor* out = context.Output<Tensor>("Out"); out->mutable_data<T>(context.GetPlace(), size_t(x->numel() * sizeof(T))); auto& dev_ctx = context.device_context<DeviceContext>(); auto pt_x = paddle::experimental::MakePtenDenseTensor(*x); auto pt_out = paddle::experimental::MakePtenDenseTensor(*out); // call new kernel pten::ConjKernel<T, DeviceContext>(dev_ctx, *pt_x.get(), pt_out.get()); } }; DECLARE_INPLACE_OP_INFERER(ConjOpInplaceInferer, {"X", "Out"}); } // namespace operators } // namespace paddle