/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve. 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 #include #include #include "paddle/framework/ddim.h" #include "paddle/framework/enforce.h" #include "paddle/framework/tensor_types.h" #include "paddle/memory/memory.h" #include "paddle/platform/place.h" #include "unsupported/Eigen/CXX11/Tensor" namespace paddle { namespace framework { class Tensor { public: Tensor() : numel_(0), offset_(0) {} Tensor& operator=(const Tensor& src) = delete; template const T* data() const { CheckDims(); return reinterpret_cast( reinterpret_cast(holder_->ptr()) + offset_); } template T* raw_data() const { CheckDims(); return reinterpret_cast(reinterpret_cast(holder_->ptr()) + offset_); } template T* mutable_data(DDim dims, paddle::platform::Place place) { set_dims(dims); return mutable_data(place); } template T* mutable_data(paddle::platform::Place place) { PADDLE_ENFORCE(numel_ > 0, "Tensor::numel_ must be larger than zero to call " "Tensor::mutable_data. Call Tensor::set_dim first."); if (holder_ == nullptr || !(holder_->place() == place) /* some versions of boost::variant don't have operator!= */ || holder_->size() < numel_ * sizeof(T) + offset_) { if (platform::is_cpu_place(place)) { holder_.reset(new PlaceholderImpl( boost::get(place), numel_ * sizeof(T))); } #ifdef __CUDACC__ else if (platform::is_gpu_place(place)) { holder_.reset(new PlaceholderImpl( boost::get(place), numel_ * sizeof(T))); } #else else if (platform::is_gpu_place(place)) { PADDLE_ENFORCE(true, "GPU not support!"); } #endif offset_ = 0; } return reinterpret_cast(reinterpret_cast(holder_->ptr()) + offset_); } template typename TTypes::Tensor shaped(DDim new_dims) { Eigen::array dims = paddle::framework::ToEigenDSizes(new_dims); return typename TTypes::Tensor(raw_data(), dims); } template typename TTypes::Tensor tensor() { return typename TTypes::Tensor( raw_data(), paddle::framework::ToEigenDSizes(dims_)); } // flat to rank = 1 template typename TTypes::Flat flat() { return shaped(make_ddim({static_cast(numel_)})); } // to TensorType Vec template typename TTypes::Vec vec() { return tensor(); } // to TensorType Matrix template typename TTypes::Matrix matrix() { return tensor(); } // const versions of all the methods above. template typename TTypes::Tensor shaped(DDim new_dims) const { Eigen::array dims = paddle::framework::ToEigenDSizes(new_dims); return typename TTypes::Tensor(data(), dims); } template typename TTypes::ConstantTensor tensor() const { return typename TTypes::Tensor( data(), paddle::framework::ToEigenDSizes(dims_)); } template typename TTypes::ConstFlat flat() const { return shaped(make_ddim({static_cast(numel_)})); } template typename TTypes::ConstVec vec() const { return tensor(); } template typename TTypes::ConstMatrix matrix() const { return tensor(); } template void ShareDataFrom(const Tensor& src) { src.CheckDims(); holder_ = src.holder_; set_dims(src.dims()); offset_ = src.offset_; } template void CopyFrom(const Tensor& src, paddle::platform::Place dst_place) { PADDLE_ENFORCE(platform::is_cpu_place(src.holder_->place()) && platform::is_cpu_place(dst_place), "Tensor::CopyFrom only support CPU now."); src.CheckDims(); size_t size = src.numel_ * sizeof(T); set_dims(src.dims()); const void* src_ptr = static_cast(src.data()); void* dst_ptr = static_cast(mutable_data(dst_place)); memcpy(dst_ptr, src_ptr, size); } template Tensor Slice(const int& begin_idx, const int& end_idx) const { CheckDims(); PADDLE_ENFORCE(begin_idx >= 0 && end_idx <= dims_[0], "Slice index is less than zero or out of bound."); PADDLE_ENFORCE(begin_idx < end_idx, "Begin index must be less than end index."); PADDLE_ENFORCE(dims_[0] != 1, "Can not slice a tensor with dims_[0] = 1."); std::vector d = vectorize(dims_); int base = 1; for (size_t i = 1; i < d.size(); ++i) { base *= d[i]; } Tensor dst; dst.holder_ = holder_; DDim dst_dims = dims_; dst_dims[0] = end_idx - begin_idx; dst.set_dims(dst_dims); dst.offset_ = offset_ + begin_idx * base * sizeof(T); return dst; } void set_dims(const DDim& dims) { if (dims == dims_) { return; } dims_ = dims; numel_ = product(dims_); } DDim dims() const { return dims_; } private: // Placeholder hides type T, so it doesn't appear as a template // parameter of Variable. struct Placeholder { virtual ~Placeholder() {} virtual void* ptr() const = 0; virtual paddle::platform::Place place() const = 0; virtual size_t size() const = 0; }; template struct PlaceholderImpl : public Placeholder { private: template class Deleter { public: Deleter(PType place) : place_(place) {} void operator()(T* ptr) { paddle::memory::Free(place_, static_cast(ptr)); } private: PType place_; }; public: PlaceholderImpl(PlaceType place, size_t size) : ptr_(static_cast(paddle::memory::Alloc(place, size)), Deleter(place)), place_(place), size_(size) {} virtual void* ptr() const { return static_cast(ptr_.get()); } virtual size_t size() const { return size_; } virtual paddle::platform::Place place() const { return place_; } std::unique_ptr> ptr_; paddle::platform::Place place_; // record the place of ptr_. size_t size_; // size of the memory block. }; template inline void CheckDims() const { PADDLE_ENFORCE(holder_ != nullptr, "Tenosr holds no memory. Call Tensor::mutable_data first."); PADDLE_ENFORCE(holder_->size() >= numel_ * sizeof(T) + offset_, "Tensor's dims_ is out of bound. Call Tensor::mutable_data " "first to re-allocate memory."); } std::shared_ptr holder_; // holds the memory block if allocated. DDim dims_; size_t numel_; // cache of `product(dims_)` size_t offset_; // marks the begin of tensor data area. }; } // namespace framework } // namespace paddle