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/* 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 "paddle/memory/memcpy.h"
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#include "paddle/platform/enforce.h"
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namespace paddle {
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namespace framework {
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template <typename... T>
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struct SizeOfTypeFunctor;
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template <typename T>
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struct SizeOfTypeFunctor<T> {
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size_t operator()(std::type_index type) const {
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if (typeid(T).hash_code() == type.hash_code()) {
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return sizeof(T);
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} else {
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return 0UL;
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}
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}
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};
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template <>
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struct SizeOfTypeFunctor<> {
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size_t operator()(std::type_index type) const { return 0UL; }
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};
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template <typename HEAD, typename... TAIL>
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struct SizeOfTypeFunctor<HEAD, TAIL...> {
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size_t operator()(std::type_index type) const {
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SizeOfTypeFunctor<HEAD> head;
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size_t head_size = head(type);
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if (head_size != 0) {
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return head_size;
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}
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SizeOfTypeFunctor<TAIL...> tail;
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return tail(type);
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}
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};
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static inline size_t SizeOfType(std::type_index type) {
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SizeOfTypeFunctor<int, float, double, int16_t, int64_t> functor;
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size_t size = functor(type);
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PADDLE_ENFORCE(size != 0UL, "Cannot get size of type %s", type.name());
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return size;
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}
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inline void Tensor::check_memory_size() const {
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PADDLE_ENFORCE_NOT_NULL(
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holder_, "Tensor holds no memory. Call Tensor::mutable_data first.");
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PADDLE_ENFORCE_GE(
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holder_->size(), memory_size() + 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.\n"
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"or maybe the required data-type mismatches the data already stored.");
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}
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inline size_t Tensor::memory_size() const {
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return holder_ == nullptr ? 0UL : numel() * SizeOfType(type());
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}
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template <typename T>
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inline const T* Tensor::data() const {
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check_memory_size();
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PADDLE_ENFORCE(std::is_same<T, void>::value ||
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holder_->type().hash_code() == typeid(T).hash_code(),
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"Tensor holds the wrong type, it holds %s",
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this->holder_->type().name());
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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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inline T* Tensor::data() {
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check_memory_size();
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PADDLE_ENFORCE(std::is_same<T, void>::value ||
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holder_->type().hash_code() == typeid(T).hash_code(),
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"Tensor holds the wrong type, it holds %s",
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this->holder_->type().name());
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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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inline T* Tensor::mutable_data(DDim dims, platform::Place place) {
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static_assert(std::is_pod<T>::value, "T must be POD");
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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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inline T* Tensor::mutable_data(platform::Place place) {
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static_assert(std::is_pod<T>::value, "T must be POD");
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return reinterpret_cast<T*>(mutable_data(place, typeid(T)));
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}
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inline void* Tensor::mutable_data(platform::Place place, std::type_index type) {
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if (holder_ != nullptr) {
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holder_->set_type(type);
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}
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PADDLE_ENFORCE_GT(
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numel(), 0,
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"When calling this method, the Tensor's numel must be larger than zero. "
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"Please check Tensor::Resize has been called first.");
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int64_t size = numel() * SizeOfType(type);
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/* some versions of boost::variant don't have operator!= */
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if (holder_ == nullptr || !(holder_->place() == place) ||
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holder_->size() < size + offset_) {
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if (platform::is_cpu_place(place)) {
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holder_.reset(new PlaceholderImpl<platform::CPUPlace>(
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boost::get<platform::CPUPlace>(place), size, type));
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} else if (platform::is_gpu_place(place)) {
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#ifndef PADDLE_WITH_CUDA
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PADDLE_THROW("'GPUPlace' is not supported in CPU only device.");
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}
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#else
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holder_.reset(new PlaceholderImpl<platform::GPUPlace>(
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boost::get<platform::GPUPlace>(place), size, type));
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}
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#endif
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offset_ = 0;
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}
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return reinterpret_cast<void*>(reinterpret_cast<uintptr_t>(holder_->ptr()) +
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offset_);
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}
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inline void* Tensor::mutable_data(platform::Place place) {
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PADDLE_ENFORCE(this->holder_ != nullptr,
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"Cannot invoke mutable data if current hold nothing");
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return mutable_data(place, holder_->type());
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}
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inline Tensor& Tensor::ShareDataWith(const Tensor& src) {
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src.check_memory_size();
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*this = src;
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return *this;
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}
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inline void Tensor::CopyFrom(const Tensor& src,
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const platform::Place& dst_place,
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const platform::DeviceContext& ctx) {
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src.check_memory_size();
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Resize(src.dims());
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auto src_place = src.holder_->place();
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auto src_ptr = src.data<void>();
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auto dst_ptr = mutable_data(dst_place, src.type());
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auto size = src.numel() * SizeOfType(src.type());
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if (platform::is_cpu_place(src_place) && platform::is_cpu_place(dst_place)) {
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memory::Copy(boost::get<platform::CPUPlace>(dst_place), dst_ptr,
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boost::get<platform::CPUPlace>(src_place), src_ptr, size);
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}
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#ifdef PADDLE_WITH_CUDA
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else if (platform::is_gpu_place(src_place) &&
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platform::is_cpu_place(dst_place)) {
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auto src_gpu_place = boost::get<platform::GPUPlace>(src_place);
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auto dst_cpu_place = boost::get<platform::CPUPlace>(dst_place);
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auto ctx_place = ctx.GetPlace();
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PADDLE_ENFORCE(platform::is_gpu_place(ctx_place));
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auto ctx_gpu_place = boost::get<platform::GPUPlace>(ctx_place);
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PADDLE_ENFORCE_EQ(src_gpu_place, ctx_gpu_place);
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memory::Copy(
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dst_cpu_place, dst_ptr, src_gpu_place, src_ptr, size,
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reinterpret_cast<const platform::CUDADeviceContext&>(ctx).stream());
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} else if (platform::is_cpu_place(src_place) &&
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platform::is_gpu_place(dst_place)) {
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auto src_cpu_place = boost::get<platform::CPUPlace>(src_place);
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auto dst_gpu_place = boost::get<platform::GPUPlace>(dst_place);
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auto ctx_place = ctx.GetPlace();
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PADDLE_ENFORCE(platform::is_gpu_place(ctx_place));
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auto ctx_gpu_place = boost::get<platform::GPUPlace>(ctx_place);
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PADDLE_ENFORCE_EQ(dst_gpu_place, ctx_gpu_place);
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memory::Copy(
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dst_gpu_place, dst_ptr, src_cpu_place, src_ptr, size,
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reinterpret_cast<const platform::CUDADeviceContext&>(ctx).stream());
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} else if (platform::is_gpu_place(src_place) &&
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platform::is_gpu_place(dst_place)) {
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auto src_gpu_place = boost::get<platform::GPUPlace>(src_place);
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auto dst_gpu_place = boost::get<platform::GPUPlace>(dst_place);
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auto ctx_place = ctx.GetPlace();
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PADDLE_ENFORCE(platform::is_gpu_place(ctx_place));
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auto ctx_gpu_place = boost::get<platform::GPUPlace>(ctx_place);
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PADDLE_ENFORCE_EQ(src_gpu_place, ctx_gpu_place);
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memory::Copy(
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dst_gpu_place, dst_ptr, src_gpu_place, src_ptr, size,
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reinterpret_cast<const platform::CUDADeviceContext&>(ctx).stream());
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}
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#endif
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}
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template <typename T>
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inline void Tensor::CopyFromVector(const std::vector<T>& src,
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const platform::DeviceContext& ctx) {
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auto dst_place = ctx.GetPlace();
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auto src_ptr = static_cast<const void*>(src.data());
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platform::CPUPlace src_place;
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auto dst_ptr = static_cast<void*>(mutable_data<T>(dst_place));
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auto size = src.size() * sizeof(T);
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if (platform::is_cpu_place(dst_place)) {
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memory::Copy(boost::get<platform::CPUPlace>(dst_place), dst_ptr, src_place,
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src_ptr, size);
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}
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#ifdef PADDLE_WITH_CUDA
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else if (platform::is_gpu_place(dst_place)) {
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memory::Copy(
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boost::get<platform::GPUPlace>(dst_place), dst_ptr, src_place, src_ptr,
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size,
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reinterpret_cast<const platform::CUDADeviceContext&>(ctx).stream());
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}
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#endif
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}
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inline Tensor Tensor::Slice(int begin_idx, int end_idx) const {
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check_memory_size();
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PADDLE_ENFORCE_GE(begin_idx, 0,
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"The start row index must be greater than 0.");
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PADDLE_ENFORCE_LE(end_idx, dims_[0], "The end row index is out of bound.");
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PADDLE_ENFORCE_LT(
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begin_idx, end_idx,
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"The start row index must be lesser than the end row index.");
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if (dims_[0] == 1) {
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return *this;
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} else {
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size_t base = numel() / 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 * SizeOfType(type());
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return dst;
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}
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}
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inline Tensor& Tensor::Resize(const DDim& dims) {
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dims_ = dims;
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return *this;
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}
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inline const DDim& Tensor::dims() const { return dims_; }
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inline int64_t Tensor::numel() const { return product(dims_); }
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inline Tensor ReshapeToMatrix(const Tensor& src, int num_col_dims) {
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Tensor res;
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res.ShareDataWith(src);
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res.Resize(flatten_to_2d(src.dims(), num_col_dims));
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return res;
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}
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} // namespace framework
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} // namespace paddle
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