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Add reduce functions for FDTensor (PaddlePaddle#81)
* Add eigen tensor structure * Add Reduce function * Add cpp unittest framework * Add reduce function unittest * Add pr template * Add comments and docs for reduce function * Fix typo * Add ENABLE_FDTENSOR_FUNC macro * Add Todo comment * Add CheckData overload * Fix CheckData overload operator() Co-authored-by: Jason <[email protected]>
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| <!-- Demo: https://github.com/PaddlePaddle/Paddle/pull/24810 --> | ||
| ### PR types | ||
| <!-- One of [ New features | Bug fixes | Function optimization | Performance optimization | Breaking changes | Others ] --> | ||
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| ### PR changes | ||
| <!-- One of [ OPs | APIs | Docs | Others ] --> | ||
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| ### Describe | ||
| <!-- Describe what this PR does --> |
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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. | ||
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| #include "fastdeploy/function/eigen.h" | ||
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| namespace fastdeploy { | ||
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| std::shared_ptr<EigenDeviceWrapper> EigenDeviceWrapper::instance_ = nullptr; | ||
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| std::shared_ptr<EigenDeviceWrapper> EigenDeviceWrapper::GetInstance() { | ||
| if (instance_ == nullptr) { | ||
| instance_ = std::make_shared<EigenDeviceWrapper>(); | ||
| } | ||
| return instance_; | ||
| } | ||
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| const Eigen::DefaultDevice* EigenDeviceWrapper::GetDevice() const { | ||
| return &device_; | ||
| } | ||
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| } // namespace fastdeploy |
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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. | ||
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| #pragma once | ||
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| #include <algorithm> | ||
| #include <memory> | ||
| #include <vector> | ||
| #include "fastdeploy/core/fd_tensor.h" | ||
| #include "unsupported/Eigen/CXX11/Tensor" | ||
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| namespace fastdeploy { | ||
| // EigenDim converts shape into Eigen::DSizes. | ||
| template <int D> | ||
| struct EigenDim { | ||
| using Type = Eigen::DSizes<Eigen::DenseIndex, D>; | ||
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| static Type From(const std::vector<int64_t>& dims) { | ||
| Type ret; | ||
| for (int64_t d = 0; d < dims.size(); d++) { | ||
| ret[d] = dims[d]; | ||
| } | ||
| return ret; | ||
| } | ||
| }; | ||
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| // Interpret FDTensor as EigenTensor and EigenConstTensor. | ||
| template <typename T, size_t D, int MajorType = Eigen::RowMajor, | ||
| typename IndexType = Eigen::DenseIndex> | ||
| struct EigenTensor { | ||
| using Type = Eigen::TensorMap<Eigen::Tensor<T, D, MajorType, IndexType>>; | ||
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| using ConstType = | ||
| Eigen::TensorMap<Eigen::Tensor<const T, D, MajorType, IndexType>>; | ||
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| static Type From(FDTensor& tensor, | ||
| const std::vector<int64_t>& dims) { // NOLINT | ||
| return Type(reinterpret_cast<T*>(tensor.Data()), EigenDim<D>::From(dims)); | ||
| } | ||
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| static Type From(FDTensor& tensor) { // NOLINT | ||
| return From(tensor, tensor.shape); | ||
| } // NOLINT | ||
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| static ConstType From(const FDTensor& tensor, | ||
| const std::vector<int64_t>& dims) { | ||
| return ConstType(reinterpret_cast<const T*>(tensor.Data()), | ||
| EigenDim<D>::From(dims)); | ||
| } | ||
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| static ConstType From(const FDTensor& tensor) { | ||
| return From(tensor, tensor.shape); | ||
| } | ||
| }; | ||
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| template <typename T, int MajorType = Eigen::RowMajor, | ||
| typename IndexType = Eigen::DenseIndex> | ||
| struct EigenScalar { | ||
| // Scalar tensor (implemented as a rank-0 tensor) of scalar type T. | ||
| using Type = Eigen::TensorMap< | ||
| Eigen::TensorFixedSize<T, Eigen::Sizes<>, MajorType, IndexType>>; | ||
| using ConstType = Eigen::TensorMap< | ||
| Eigen::TensorFixedSize<const T, Eigen::Sizes<>, MajorType, IndexType>>; | ||
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| static Type From(FDTensor& tensor) { | ||
| return Type(reinterpret_cast<T*>(tensor.Data())); | ||
| } // NOLINT | ||
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| static ConstType From(const FDTensor& tensor) { | ||
| return ConstType(reinterpret_cast<const T*>(tensor.Data())); | ||
| } | ||
| }; | ||
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| template <typename T, int MajorType = Eigen::RowMajor, | ||
| typename IndexType = Eigen::DenseIndex> | ||
| struct EigenVector : public EigenTensor<T, 1, MajorType, IndexType> { | ||
| // Flatten reshapes a Tensor into an EigenVector. | ||
| static typename EigenVector::Type Flatten(FDTensor& tensor) { // NOLINT | ||
| return EigenVector::From(tensor, {tensor.Numel()}); | ||
| } | ||
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| static typename EigenVector::ConstType Flatten( | ||
| const FDTensor& tensor) { // NOLINT | ||
| return EigenVector::From(tensor, {tensor.Numel()}); | ||
| } | ||
| }; | ||
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| class EigenDeviceWrapper { | ||
| public: | ||
| static std::shared_ptr<EigenDeviceWrapper> GetInstance(); | ||
| const Eigen::DefaultDevice* GetDevice() const; | ||
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| private: | ||
| Eigen::DefaultDevice device_; | ||
| static std::shared_ptr<EigenDeviceWrapper> instance_; | ||
| }; | ||
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| } // namespace fastdeploy |
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