/* 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 #include "paddle/framework/ddim.h" #include "paddle/memory/memory.h" #include "paddle/platform/enforce.h" #include "paddle/platform/place.h" #include "unsupported/Eigen/CXX11/Tensor" namespace paddle { namespace pybind { namespace details { // forward declare template struct CastToPyBufferImpl; } // namespace details } // namespace pybind namespace framework { class Tensor { template friend struct paddle::pybind::details::CastToPyBufferImpl; template friend struct EigenTensor; template friend struct EigenVector; public: Tensor() : offset_(0) {} template const T* data() const { EnforceSufficientMemory(); return reinterpret_cast( reinterpret_cast(holder_->ptr()) + offset_); } template T* data() { EnforceSufficientMemory(); return reinterpret_cast(reinterpret_cast(holder_->ptr()) + offset_); } template ::value>::type* = nullptr> T* mutable_data(DDim dims, platform::Place place) { Resize(dims); return mutable_data(place); } template ::value>::type* = nullptr> T* mutable_data(platform::Place place) { PADDLE_ENFORCE(product(dims_) > 0, "Tensor's 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() < product(dims_) * sizeof(T) + offset_) { if (platform::is_cpu_place(place)) { holder_.reset(new PlaceholderImpl( boost::get(place), product(dims_) * sizeof(T))); } else if (platform::is_gpu_place(place)) { #ifdef PADDLE_ONLY_CPU PADDLE_THROW("'GPUPlace' is not supported in CPU only device."); #else holder_.reset(new PlaceholderImpl( boost::get(place), product(dims_) * sizeof(T))); #endif } else { PADDLE_THROW("Unknown 'place'."); } offset_ = 0; } return reinterpret_cast(reinterpret_cast(holder_->ptr()) + offset_); } template void ShareDataWith(const Tensor& src) { src.EnforceSufficientMemory(); *this = src; } template void CopyFrom(const Tensor& src, 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.EnforceSufficientMemory(); size_t size = product(src.dims_) * sizeof(T); Resize(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 { EnforceSufficientMemory(); PADDLE_ENFORCE(begin_idx >= 0, "Slice begin index is less than zero."); PADDLE_ENFORCE(end_idx <= dims_[0], "Slice end index is 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."); int base = product(dims_) / dims_[0]; Tensor dst; dst.holder_ = holder_; DDim dst_dims = dims_; dst_dims[0] = end_idx - begin_idx; dst.Resize(dst_dims); dst.offset_ = offset_ + begin_idx * base * sizeof(T); return dst; } void Resize(const DDim& dims) { dims_ = dims; } const DDim& dims() const { return dims_; } paddle::platform::Place place() const { return holder_->place(); } 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 platform::Place place() const = 0; virtual size_t size() const = 0; virtual std::type_index type() const = 0; }; template struct PlaceholderImpl : public Placeholder { PlaceholderImpl(PlaceType place, size_t size) : ptr_(static_cast(memory::Alloc(place, size)), memory::PODDeleter(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_; } virtual std::type_index type() const { return std::type_index(typeid(T)); } std::unique_ptr> ptr_; platform::Place place_; // record the place of ptr_. size_t size_; // size of the memory block. }; template inline void EnforceSufficientMemory() const { PADDLE_ENFORCE(holder_ != nullptr, "Tenosr holds no memory. Call Tensor::mutable_data first."); PADDLE_ENFORCE(holder_->size() >= product(dims_) * 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_; // A PlaceHolder may be shared by more than one tensor. Some of them may be // slices of the others. So the offset_ is introduced here to indicate the // byte offset between PlaceHolder::ptr_ and where tensor's data really // begins. size_t offset_; }; } // namespace framework } // namespace paddle