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187 lines
6.4 KiB
187 lines
6.4 KiB
/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License. */
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#pragma once
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#include <cstdint>
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#include <cstring>
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#include <memory>
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#include <typeindex>
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#include "paddle/framework/ddim.h"
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#include "paddle/memory/memory.h"
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#include "paddle/platform/enforce.h"
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#include "paddle/platform/place.h"
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#include "unsupported/Eigen/CXX11/Tensor"
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namespace paddle {
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namespace pybind {
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namespace details { // forward declare
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template <bool less, size_t i, typename... args>
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struct CastToPyBufferImpl;
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} // namespace details
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} // namespace pybind
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namespace framework {
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class Tensor {
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template <bool less, size_t i, typename... args>
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friend struct paddle::pybind::details::CastToPyBufferImpl;
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template <typename T, size_t D, int MajorType, typename IndexType>
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friend struct EigenTensor;
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template <typename T, int MajorType, typename IndexType>
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friend struct EigenVector;
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public:
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Tensor() : offset_(0) {}
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template <typename T>
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const T* data() const {
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EnforceSufficientMemory<T>();
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return reinterpret_cast<const T*>(
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reinterpret_cast<uintptr_t>(holder_->ptr()) + offset_);
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}
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template <typename T>
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T* data() {
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EnforceSufficientMemory<T>();
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return reinterpret_cast<T*>(reinterpret_cast<uintptr_t>(holder_->ptr()) +
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offset_);
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}
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template <typename T>
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T* mutable_data(DDim dims, platform::Place place) {
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Resize(dims);
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return mutable_data<T>(place);
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}
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template <typename T>
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T* mutable_data(platform::Place place) {
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PADDLE_ENFORCE(product(dims_) > 0,
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"Tensor's numel must be larger than zero to call "
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"Tensor::mutable_data. Call Tensor::set_dim first.");
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if (holder_ == nullptr ||
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!(holder_->place() ==
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place) /* some versions of boost::variant don't have operator!= */
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|| holder_->size() < product(dims_) * sizeof(T) + offset_) {
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if (platform::is_cpu_place(place)) {
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holder_.reset(new PlaceholderImpl<T, platform::CPUPlace>(
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boost::get<platform::CPUPlace>(place), product(dims_) * sizeof(T)));
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} else if (platform::is_gpu_place(place)) {
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#ifdef PADDLE_ONLY_CPU
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PADDLE_THROW("'GPUPlace' is not supported in CPU only device.");
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#else
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holder_.reset(new PlaceholderImpl<T, platform::GPUPlace>(
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boost::get<platform::GPUPlace>(place), product(dims_) * sizeof(T)));
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#endif
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} else {
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PADDLE_THROW("Unknown 'place'.");
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}
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offset_ = 0;
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}
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return reinterpret_cast<T*>(reinterpret_cast<uintptr_t>(holder_->ptr()) +
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offset_);
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}
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template <typename T>
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void ShareDataWith(const Tensor& src) {
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src.EnforceSufficientMemory<T>();
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*this = src;
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}
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template <typename T>
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void CopyFrom(const Tensor& src, platform::Place dst_place) {
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PADDLE_ENFORCE(platform::is_cpu_place(src.holder_->place()) &&
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platform::is_cpu_place(dst_place),
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"Tensor::CopyFrom only support CPU now.");
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src.EnforceSufficientMemory<T>();
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size_t size = product(src.dims_) * sizeof(T);
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Resize(src.dims());
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const void* src_ptr = static_cast<const void*>(src.data<T>());
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void* dst_ptr = static_cast<void*>(mutable_data<T>(dst_place));
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memcpy(dst_ptr, src_ptr, size);
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}
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template <typename T>
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Tensor Slice(const int& begin_idx, const int& end_idx) const {
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EnforceSufficientMemory<T>();
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PADDLE_ENFORCE(begin_idx >= 0, "Slice begin index is less than zero.");
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PADDLE_ENFORCE(end_idx <= dims_[0], "Slice end index is out of bound.");
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PADDLE_ENFORCE(begin_idx < end_idx,
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"Begin index must be less than end index.");
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PADDLE_ENFORCE(dims_[0] != 1, "Can not slice a tensor with dims_[0] = 1.");
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int base = product(dims_) / dims_[0];
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Tensor dst;
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dst.holder_ = holder_;
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DDim dst_dims = dims_;
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dst_dims[0] = end_idx - begin_idx;
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dst.Resize(dst_dims);
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dst.offset_ = offset_ + begin_idx * base * sizeof(T);
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return dst;
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}
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void Resize(const DDim& dims) { dims_ = dims; }
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const DDim& dims() const { return dims_; }
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private:
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// Placeholder hides type T, so it doesn't appear as a template
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// parameter of Variable.
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struct Placeholder {
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virtual ~Placeholder() {}
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virtual void* ptr() const = 0;
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virtual platform::Place place() const = 0;
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virtual size_t size() const = 0;
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virtual std::type_index type() const = 0;
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};
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template <typename T, typename PlaceType>
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struct PlaceholderImpl : public Placeholder {
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PlaceholderImpl(PlaceType place, size_t size)
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: ptr_(static_cast<T*>(memory::Alloc(place, size)),
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memory::PodDeleter<T, PlaceType>(place)),
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place_(place),
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size_(size) {}
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virtual void* ptr() const { return static_cast<void*>(ptr_.get()); }
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virtual size_t size() const { return size_; }
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virtual paddle::platform::Place place() const { return place_; }
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virtual std::type_index type() const { return std::type_index(typeid(T)); }
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std::unique_ptr<T, memory::PodDeleter<T, PlaceType>> ptr_;
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platform::Place place_; // record the place of ptr_.
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size_t size_; // size of the memory block.
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};
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template <typename T>
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inline void EnforceSufficientMemory() const {
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PADDLE_ENFORCE(holder_ != nullptr,
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"Tenosr holds no memory. Call Tensor::mutable_data first.");
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PADDLE_ENFORCE(holder_->size() >= product(dims_) * sizeof(T) + offset_,
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"Tensor's dims_ is out of bound. Call Tensor::mutable_data "
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"first to re-allocate memory.");
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}
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std::shared_ptr<Placeholder> holder_; // holds the memory block if allocated.
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DDim dims_;
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// A PlaceHolder may be shared by more than one tensor. Some of them may be
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// slices of the others. So the offset_ is introduced here to indicate the
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// byte offset between PlaceHolder::ptr_ and where tensor's data really
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// begins.
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size_t offset_;
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};
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} // namespace framework
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} // namespace paddle
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