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paddlepaddle--paddle/paddle/phi/backends/onednn/axpy_handler.h
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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.
#pragma once
#include <memory>
#include "dnnl.hpp" // NOLINT
namespace phi {
namespace funcs {
///
/// @brief Helper class for AXPY execution using oneDNN library.
///
/// @tparam T Data type.
///
template <typename T>
class OneDNNAXPYHandler {
public:
OneDNNAXPYHandler(OneDNNAXPYHandler&) = delete;
OneDNNAXPYHandler(OneDNNAXPYHandler&&) = delete;
OneDNNAXPYHandler& operator=(OneDNNAXPYHandler&) = delete;
OneDNNAXPYHandler& operator=(OneDNNAXPYHandler&&) = delete;
///
/// @brief Constructor.
///
/// @param[in] n The number of elements in tensor (assumed 1D
/// tensor)
/// @param[in] alpha The alpha coefficient.
/// @param[in] onednn_engine The oneDNN engine.
///
OneDNNAXPYHandler(int64_t n, T alpha, dnnl::engine onednn_engine);
///
/// @brief Executes AXPY.
///
/// @param[in] x The pointer to input X tensor data.
/// @param[out] y The pointer to output Y tensor data.
///
void operator()(const T* x, T* y);
private:
OneDNNAXPYHandler() = delete;
// Private implementation idiom to hide dependency on oneDNN headers.
class Impl;
// We need custom deleter, since the compiler is unable to parameterize
// an allocator's default deleter due to incomplete type.
std::unique_ptr<Impl, void (*)(Impl*)> pimpl_;
};
} // namespace funcs
} // namespace phi