/* 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 "paddle/memory/memcpy.h" namespace paddle { namespace framework { template inline void Tensor::check_memory_size() 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."); } template inline const T* Tensor::data() const { check_memory_size(); return reinterpret_cast( reinterpret_cast(holder_->ptr()) + offset_); } template inline T* Tensor::data() { check_memory_size(); return reinterpret_cast(reinterpret_cast(holder_->ptr()) + offset_); } template inline T* Tensor::mutable_data(DDim dims, platform::Place place) { static_assert(std::is_pod::value, "T must be POD"); Resize(dims); return mutable_data(place); } template inline T* Tensor::mutable_data(platform::Place place) { static_assert(std::is_pod::value, "T must be POD"); PADDLE_ENFORCE(product(dims_) > 0, "Tensor's numel must be larger than zero to call " "Tensor::mutable_data. Call Tensor::set_dim first."); /* some versions of boost::variant don't have operator!= */ size_t size = product(dims_) * sizeof(T); if (holder_ == nullptr || !(holder_->place() == place) || holder_->size() < size + offset_) { if (platform::is_cpu_place(place)) { holder_.reset(new PlaceholderImpl( boost::get(place), size)); } 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), size)); } #endif offset_ = 0; } return reinterpret_cast(reinterpret_cast(holder_->ptr()) + offset_); } template inline void Tensor::ShareDataWith(const Tensor& src) { src.check_memory_size(); *this = src; } template inline void Tensor::CopyFrom(const Tensor& src, const platform::Place& dst_place) { src.check_memory_size(); Resize(src.dims()); auto src_place = src.holder_->place(); auto src_ptr = static_cast(src.data()); auto dst_ptr = static_cast(mutable_data(dst_place)); auto size = product(src.dims_) * sizeof(T); if (platform::is_cpu_place(src_place) && platform::is_cpu_place(dst_place)) { memory::Copy(boost::get(dst_place), dst_ptr, boost::get(src_place), src_ptr, size); } #ifndef PADDLE_ONLY_CPU else if (platform::is_gpu_place(src_place) && platform::is_cpu_place(dst_place)) { memory::Copy(boost::get(dst_place), dst_ptr, boost::get(src_place), src_ptr, size, 0); } else if (platform::is_cpu_place(src_place) && platform::is_gpu_place(dst_place)) { memory::Copy(boost::get(dst_place), dst_ptr, boost::get(src_place), src_ptr, size, 0); } else if (platform::is_gpu_place(src_place) && platform::is_gpu_place(dst_place)) { memory::Copy(boost::get(dst_place), dst_ptr, boost::get(src_place), src_ptr, size, 0); } #endif } template inline Tensor Tensor::Slice(const int& begin_idx, const int& end_idx) const { check_memory_size(); 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; } inline void Tensor::Resize(const DDim& dims) { dims_ = dims; } inline const DDim& Tensor::dims() const { return dims_; } } // namespace framework } // namespace paddle