提交 19e669a9 编写于 作者: Y Yu Yang

Add legacy_allocator

test=develop
上级 1cb7e7dd
add_subdirectory(detail)
add_subdirectory(allocation)
cc_library(malloc SRCS malloc.cc DEPS buddy_allocator place enforce allocator_facade)
cc_library(malloc SRCS malloc.cc DEPS place enforce allocator_facade)
cc_library(memcpy SRCS memcpy.cc DEPS place)
cc_library(memory
......
......@@ -3,6 +3,7 @@ cc_library(cpu_allocator SRCS cpu_allocator.cc DEPS allocator)
cc_library(best_fit_allocator SRCS best_fit_allocator.cc DEPS allocator)
cc_library(locked_allocator SRCS locked_allocator.cc DEPS allocator)
cc_library(buffered_allocator SRCS buffered_allocator.cc DEPS allocator)
cc_library(legacy_allocator SRCS legacy_allocator.cc DEPS allocator buddy_allocator)
cc_test(buffered_allocator_test SRCS buffered_allocator_test.cc DEPS best_fit_allocator locked_allocator buffered_allocator cpu_allocator)
if (WITH_GPU)
......@@ -53,6 +54,7 @@ cc_library(allocator_facade SRCS allocator_facade.cc DEPS
retry_allocator
buffered_allocator
allocator_strategy
legacy_allocator
)
nv_test(allocation_and_eigen_test SRCS allocation_and_eigen_test.cu DEPS allocator_facade)
......
......@@ -37,11 +37,7 @@ const char* BadAlloc::what() const noexcept { return msg_.c_str(); }
void AllocationDeleter::operator()(Allocation* allocation) const {
auto* allocator = allocation->allocator();
if (allocator) {
allocator->Free(allocation);
} else {
delete allocation; // Compatible for legacy allocation.
}
}
} // namespace allocation
......
......@@ -19,10 +19,12 @@
#include <vector>
#include "paddle/fluid/memory/allocation/aligned_allocator.h"
#include "paddle/fluid/memory/allocation/allocator_facade.h"
#include "paddle/fluid/memory/allocation/allocator_strategy.h"
#include "paddle/fluid/memory/allocation/auto_increment_allocator.h"
#include "paddle/fluid/memory/allocation/best_fit_allocator.h"
#include "paddle/fluid/memory/allocation/conditional_allocator.h"
#include "paddle/fluid/memory/allocation/cpu_allocator.h"
#include "paddle/fluid/memory/allocation/legacy_allocator.h"
#include "paddle/fluid/memory/allocation/locked_allocator.h"
#include "paddle/fluid/memory/allocation/retry_allocator.h"
#include "paddle/fluid/memory/allocation/zero_size_allocator.h"
......@@ -190,13 +192,29 @@ class AllocatorFacadePrivate {
~AllocatorFacadePrivate() = default;
AllocatorFacadePrivate() {
if (GetAllocatorStrategy() == AllocatorStrategy::kLegacy) {
InitLegacyAllocator();
} else {
InitCPUAllocator();
InitCUDAAllocator();
InitCUDAPinnedAllocator();
WrapZeroSizeAllocator();
}
}
private:
void InitLegacyAllocator() {
std::vector<platform::Place> places{platform::CPUPlace()};
#ifdef PADDLE_WITH_CUDA
for (int dev_id = 0; dev_id < platform::GetCUDADeviceCount(); ++dev_id) {
places.emplace_back(platform::CUDAPlace(dev_id));
}
#endif
for (auto& p : places) {
allocators_[p] = std::make_shared<LegacyAllocator>(p);
}
}
void InitCPUAllocator() {
allocators_[platform::CPUPlace()] = std::make_shared<CPUManagedAllocator>();
}
......
......@@ -35,12 +35,6 @@ class BufferedAllocator : public Allocator {
~BufferedAllocator();
// std::unique_ptr<Allocation> Allocate(
// size_t size, Allocator::Attr attr = Allocator::Attr::kDefault)
// override;
//
// void FreeUniquePtr(std::unique_ptr<Allocation> allocation) override;
bool IsAllocThreadSafe() const override;
// only used in unittest
......
// Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
//
// 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.
#include "paddle/fluid/memory/allocation/legacy_allocator.h"
#include <string>
#include "glog/logging.h"
#include "paddle/fluid/memory/detail/buddy_allocator.h"
#include "paddle/fluid/memory/detail/system_allocator.h"
#include "paddle/fluid/platform/gpu_info.h"
#include "paddle/fluid/string/printf.h"
DEFINE_bool(init_allocated_mem, false,
"It is a mistake that the values of the memory allocated by "
"BuddyAllocator are always zeroed in some op's implementation. "
"To find this error in time, we use init_allocated_mem to indicate "
"that initializing the allocated memory with a small value "
"during unit testing.");
DECLARE_double(fraction_of_gpu_memory_to_use);
namespace paddle {
namespace memory {
namespace legacy {
template <typename Place>
void *Alloc(const Place &place, size_t size);
template <typename Place>
void Free(const Place &place, void *p);
template <typename Place>
size_t Used(const Place &place);
struct Usage : public boost::static_visitor<size_t> {
size_t operator()(const platform::CPUPlace &cpu) const;
size_t operator()(const platform::CUDAPlace &gpu) const;
size_t operator()(const platform::CUDAPinnedPlace &cuda_pinned) const;
};
size_t memory_usage(const platform::Place &p);
using BuddyAllocator = detail::BuddyAllocator;
BuddyAllocator *GetCPUBuddyAllocator() {
// We tried thread_local for inference::RNN1 model, but that not works much
// for multi-thread test.
static std::once_flag init_flag;
static detail::BuddyAllocator *a = nullptr;
std::call_once(init_flag, []() {
a = new detail::BuddyAllocator(
std::unique_ptr<detail::SystemAllocator>(new detail::CPUAllocator),
platform::CpuMinChunkSize(), platform::CpuMaxChunkSize());
});
return a;
}
// We compared the NaiveAllocator with BuddyAllocator in CPU memory allocation,
// seems they are almost the same overhead.
struct NaiveAllocator {
void *Alloc(size_t size) { return malloc(size); }
void Free(void *p) {
PADDLE_ENFORCE(p);
free(p);
}
static NaiveAllocator *Instance() {
static NaiveAllocator x;
return &x;
}
private:
std::mutex lock_;
};
template <>
void *Alloc<platform::CPUPlace>(const platform::CPUPlace &place, size_t size) {
VLOG(10) << "Allocate " << size << " bytes on " << platform::Place(place);
void *p = GetCPUBuddyAllocator()->Alloc(size);
if (FLAGS_init_allocated_mem) {
memset(p, 0xEF, size);
}
VLOG(100) << " pointer=" << p;
return p;
}
template <>
void Free<platform::CPUPlace>(const platform::CPUPlace &place, void *p) {
VLOG(10) << "Free pointer=" << p << " on " << platform::Place(place);
GetCPUBuddyAllocator()->Free(p);
}
template <>
size_t Used<platform::CPUPlace>(const platform::CPUPlace &place) {
return GetCPUBuddyAllocator()->Used();
}
#ifdef PADDLE_WITH_CUDA
BuddyAllocator *GetGPUBuddyAllocator(int gpu_id) {
static std::once_flag init_flag;
static detail::BuddyAllocator **a_arr = nullptr;
std::call_once(init_flag, [gpu_id]() {
int gpu_num = platform::GetCUDADeviceCount();
PADDLE_ENFORCE(gpu_id < gpu_num, "gpu_id:%d should < gpu_num:%d", gpu_id,
gpu_num);
a_arr = new BuddyAllocator *[gpu_num];
for (int i = 0; i < gpu_num; i++) {
a_arr[i] = nullptr;
platform::SetDeviceId(i);
a_arr[i] = new BuddyAllocator(
std::unique_ptr<detail::SystemAllocator>(new detail::GPUAllocator(i)),
platform::GpuMinChunkSize(), platform::GpuMaxChunkSize());
VLOG(100) << "\n\nNOTE: each GPU device use "
<< FLAGS_fraction_of_gpu_memory_to_use * 100
<< "% of GPU memory.\n"
<< "You can set GFlags environment variable '"
<< "FLAGS_fraction_of_gpu_memory_to_use"
<< "' to change the fraction of GPU usage.\n\n";
}
});
platform::SetDeviceId(gpu_id);
return a_arr[gpu_id];
}
#endif
template <>
size_t Used<platform::CUDAPlace>(const platform::CUDAPlace &place) {
#ifdef PADDLE_WITH_CUDA
return GetGPUBuddyAllocator(place.device)->Used();
#else
PADDLE_THROW("'CUDAPlace' is not supported in CPU only device.");
#endif
}
template <>
void *Alloc<platform::CUDAPlace>(const platform::CUDAPlace &place,
size_t size) {
#ifdef PADDLE_WITH_CUDA
auto *buddy_allocator = GetGPUBuddyAllocator(place.device);
auto *ptr = buddy_allocator->Alloc(size);
if (ptr == nullptr) {
int cur_dev = platform::GetCurrentDeviceId();
platform::SetDeviceId(place.device);
size_t avail, total;
platform::GpuMemoryUsage(&avail, &total);
LOG(WARNING) << "Cannot allocate " << string::HumanReadableSize(size)
<< " in GPU " << place.device << ", available "
<< string::HumanReadableSize(avail);
LOG(WARNING) << "total " << total;
LOG(WARNING) << "GpuMinChunkSize "
<< string::HumanReadableSize(
buddy_allocator->GetMinChunkSize());
LOG(WARNING) << "GpuMaxChunkSize "
<< string::HumanReadableSize(
buddy_allocator->GetMaxChunkSize());
LOG(WARNING) << "GPU memory used: "
<< string::HumanReadableSize(Used<platform::CUDAPlace>(place));
platform::SetDeviceId(cur_dev);
}
if (FLAGS_init_allocated_mem) {
cudaMemset(ptr, 0xEF, size);
}
return ptr;
#else
PADDLE_THROW("'CUDAPlace' is not supported in CPU only device.");
#endif
}
template <>
void Free<platform::CUDAPlace>(const platform::CUDAPlace &place, void *p) {
#ifdef PADDLE_WITH_CUDA
GetGPUBuddyAllocator(place.device)->Free(p);
#else
PADDLE_THROW("'CUDAPlace' is not supported in CPU only device.");
#endif
}
#ifdef PADDLE_WITH_CUDA
BuddyAllocator *GetCUDAPinnedBuddyAllocator() {
static std::once_flag init_flag;
static BuddyAllocator *ba = nullptr;
std::call_once(init_flag, []() {
ba = new BuddyAllocator(std::unique_ptr<detail::SystemAllocator>(
new detail::CUDAPinnedAllocator),
platform::CUDAPinnedMinChunkSize(),
platform::CUDAPinnedMaxChunkSize());
});
return ba;
}
#endif
template <>
size_t Used<platform::CUDAPinnedPlace>(const platform::CUDAPinnedPlace &place) {
#ifdef PADDLE_WITH_CUDA
return GetCUDAPinnedBuddyAllocator()->Used();
#else
PADDLE_THROW("'CUDAPinnedPlace' is not supported in CPU only device.");
#endif
}
template <>
void *Alloc<platform::CUDAPinnedPlace>(const platform::CUDAPinnedPlace &place,
size_t size) {
#ifdef PADDLE_WITH_CUDA
auto *buddy_allocator = GetCUDAPinnedBuddyAllocator();
void *ptr = buddy_allocator->Alloc(size);
if (ptr == nullptr) {
LOG(WARNING) << "cudaMallocHost Cannot allocate " << size
<< " bytes in CUDAPinnedPlace";
}
if (FLAGS_init_allocated_mem) {
memset(ptr, 0xEF, size);
}
return ptr;
#else
PADDLE_THROW("'CUDAPinnedPlace' is not supported in CPU only device.");
#endif
}
template <>
void Free<platform::CUDAPinnedPlace>(const platform::CUDAPinnedPlace &place,
void *p) {
#ifdef PADDLE_WITH_CUDA
GetCUDAPinnedBuddyAllocator()->Free(p);
#else
PADDLE_THROW("'CUDAPinnedPlace' is not supported in CPU only device.");
#endif
}
struct AllocVisitor : public boost::static_visitor<void *> {
inline explicit AllocVisitor(size_t size) : size_(size) {}
template <typename Place>
inline void *operator()(const Place &place) const {
return Alloc<Place>(place, size_);
}
private:
size_t size_;
};
struct FreeVisitor : public boost::static_visitor<void> {
inline explicit FreeVisitor(void *ptr) : ptr_(ptr) {}
template <typename Place>
inline void operator()(const Place &place) const {
Free<Place>(place, ptr_);
}
private:
void *ptr_;
};
size_t Usage::operator()(const platform::CPUPlace &cpu) const {
return Used(cpu);
}
size_t Usage::operator()(const platform::CUDAPlace &gpu) const {
#ifdef PADDLE_WITH_CUDA
return Used(gpu);
#else
PADDLE_THROW("'CUDAPlace' is not supported in CPU only device.");
#endif
}
size_t Usage::operator()(const platform::CUDAPinnedPlace &cuda_pinned) const {
#ifdef PADDLE_WITH_CUDA
return Used(cuda_pinned);
#else
PADDLE_THROW("'CUDAPinnedPlace' is not supported in CPU only device.");
#endif
}
} // namespace legacy
namespace allocation {
Allocation *LegacyAllocator::AllocateImpl(size_t size, Allocator::Attr attr) {
void *ptr = boost::apply_visitor(legacy::AllocVisitor(size), place_);
return new Allocation(ptr, size, place_);
}
void LegacyAllocator::Free(Allocation *allocation) {
boost::apply_visitor(legacy::FreeVisitor(allocation->ptr()),
allocation->place());
delete allocation;
}
} // namespace allocation
} // namespace memory
} // namespace paddle
// Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
//
// 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 "paddle/fluid/memory/allocation/allocator.h"
#include "paddle/fluid/platform/place.h"
namespace paddle {
namespace memory {
namespace allocation {
class LegacyAllocatorPrivate;
class LegacyAllocator : public Allocator {
public:
explicit LegacyAllocator(const platform::Place &p) : place_(p) {}
protected:
Allocation *AllocateImpl(size_t size, Allocator::Attr attr) override;
void Free(Allocation *allocation) override;
private:
platform::Place place_;
};
} // namespace allocation
} // namespace memory
} // namespace paddle
......@@ -12,305 +12,22 @@ 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. */
#include "paddle/fluid/memory/malloc.h"
#include <string>
#include <vector>
#include "glog/logging.h"
#include "paddle/fluid/memory/allocation/allocator_facade.h"
#include "paddle/fluid/memory/allocation/allocator_strategy.h"
#include "paddle/fluid/memory/detail/buddy_allocator.h"
#include "paddle/fluid/memory/detail/system_allocator.h"
#include "paddle/fluid/memory/malloc.h"
#include "paddle/fluid/platform/gpu_info.h"
#include "paddle/fluid/string/printf.h"
DEFINE_bool(init_allocated_mem, false,
"It is a mistake that the values of the memory allocated by "
"BuddyAllocator are always zeroed in some op's implementation. "
"To find this error in time, we use init_allocated_mem to indicate "
"that initializing the allocated memory with a small value "
"during unit testing.");
DECLARE_double(fraction_of_gpu_memory_to_use);
#include "paddle/fluid/platform/place.h"
namespace paddle {
namespace memory {
namespace legacy {
using BuddyAllocator = detail::BuddyAllocator;
BuddyAllocator* GetCPUBuddyAllocator() {
// We tried thread_local for inference::RNN1 model, but that not works much
// for multi-thread test.
static std::once_flag init_flag;
static detail::BuddyAllocator* a = nullptr;
std::call_once(init_flag, []() {
a = new detail::BuddyAllocator(
std::unique_ptr<detail::SystemAllocator>(new detail::CPUAllocator),
platform::CpuMinChunkSize(), platform::CpuMaxChunkSize());
});
return a;
}
// We compared the NaiveAllocator with BuddyAllocator in CPU memory allocation,
// seems they are almost the same overhead.
struct NaiveAllocator {
void* Alloc(size_t size) { return malloc(size); }
void Free(void* p) {
PADDLE_ENFORCE(p);
free(p);
}
static NaiveAllocator* Instance() {
static NaiveAllocator x;
return &x;
}
private:
std::mutex lock_;
};
template <>
void* Alloc<platform::CPUPlace>(const platform::CPUPlace& place, size_t size) {
VLOG(10) << "Allocate " << size << " bytes on " << platform::Place(place);
void* p = GetCPUBuddyAllocator()->Alloc(size);
if (FLAGS_init_allocated_mem) {
memset(p, 0xEF, size);
}
VLOG(100) << " pointer=" << p;
return p;
}
template <>
void Free<platform::CPUPlace>(const platform::CPUPlace& place, void* p) {
VLOG(10) << "Free pointer=" << p << " on " << platform::Place(place);
GetCPUBuddyAllocator()->Free(p);
}
template <>
size_t Used<platform::CPUPlace>(const platform::CPUPlace& place) {
return GetCPUBuddyAllocator()->Used();
}
#ifdef PADDLE_WITH_CUDA
BuddyAllocator* GetGPUBuddyAllocator(int gpu_id) {
static std::once_flag init_flag;
static detail::BuddyAllocator** a_arr = nullptr;
std::call_once(init_flag, [gpu_id]() {
int gpu_num = platform::GetCUDADeviceCount();
PADDLE_ENFORCE(gpu_id < gpu_num, "gpu_id:%d should < gpu_num:%d", gpu_id,
gpu_num);
a_arr = new BuddyAllocator*[gpu_num];
for (int i = 0; i < gpu_num; i++) {
a_arr[i] = nullptr;
platform::SetDeviceId(i);
a_arr[i] = new BuddyAllocator(
std::unique_ptr<detail::SystemAllocator>(new detail::GPUAllocator(i)),
platform::GpuMinChunkSize(), platform::GpuMaxChunkSize());
VLOG(100) << "\n\nNOTE: each GPU device use "
<< FLAGS_fraction_of_gpu_memory_to_use * 100
<< "% of GPU memory.\n"
<< "You can set GFlags environment variable '"
<< "FLAGS_fraction_of_gpu_memory_to_use"
<< "' to change the fraction of GPU usage.\n\n";
}
});
platform::SetDeviceId(gpu_id);
return a_arr[gpu_id];
}
#endif
template <>
size_t Used<platform::CUDAPlace>(const platform::CUDAPlace& place) {
#ifdef PADDLE_WITH_CUDA
return GetGPUBuddyAllocator(place.device)->Used();
#else
PADDLE_THROW("'CUDAPlace' is not supported in CPU only device.");
#endif
}
template <>
void* Alloc<platform::CUDAPlace>(const platform::CUDAPlace& place,
size_t size) {
#ifdef PADDLE_WITH_CUDA
auto* buddy_allocator = GetGPUBuddyAllocator(place.device);
auto* ptr = buddy_allocator->Alloc(size);
if (ptr == nullptr) {
int cur_dev = platform::GetCurrentDeviceId();
platform::SetDeviceId(place.device);
size_t avail, total;
platform::GpuMemoryUsage(&avail, &total);
LOG(WARNING) << "Cannot allocate " << string::HumanReadableSize(size)
<< " in GPU " << place.device << ", available "
<< string::HumanReadableSize(avail);
LOG(WARNING) << "total " << total;
LOG(WARNING) << "GpuMinChunkSize "
<< string::HumanReadableSize(
buddy_allocator->GetMinChunkSize());
LOG(WARNING) << "GpuMaxChunkSize "
<< string::HumanReadableSize(
buddy_allocator->GetMaxChunkSize());
LOG(WARNING) << "GPU memory used: "
<< string::HumanReadableSize(Used<platform::CUDAPlace>(place));
platform::SetDeviceId(cur_dev);
}
if (FLAGS_init_allocated_mem) {
cudaMemset(ptr, 0xEF, size);
}
return ptr;
#else
PADDLE_THROW("'CUDAPlace' is not supported in CPU only device.");
#endif
}
template <>
void Free<platform::CUDAPlace>(const platform::CUDAPlace& place, void* p) {
#ifdef PADDLE_WITH_CUDA
GetGPUBuddyAllocator(place.device)->Free(p);
#else
PADDLE_THROW("'CUDAPlace' is not supported in CPU only device.");
#endif
}
#ifdef PADDLE_WITH_CUDA
BuddyAllocator* GetCUDAPinnedBuddyAllocator() {
static std::once_flag init_flag;
static BuddyAllocator* ba = nullptr;
std::call_once(init_flag, []() {
ba = new BuddyAllocator(std::unique_ptr<detail::SystemAllocator>(
new detail::CUDAPinnedAllocator),
platform::CUDAPinnedMinChunkSize(),
platform::CUDAPinnedMaxChunkSize());
});
return ba;
}
#endif
template <>
size_t Used<platform::CUDAPinnedPlace>(const platform::CUDAPinnedPlace& place) {
#ifdef PADDLE_WITH_CUDA
return GetCUDAPinnedBuddyAllocator()->Used();
#else
PADDLE_THROW("'CUDAPinnedPlace' is not supported in CPU only device.");
#endif
}
template <>
void* Alloc<platform::CUDAPinnedPlace>(const platform::CUDAPinnedPlace& place,
size_t size) {
#ifdef PADDLE_WITH_CUDA
auto* buddy_allocator = GetCUDAPinnedBuddyAllocator();
void* ptr = buddy_allocator->Alloc(size);
if (ptr == nullptr) {
LOG(WARNING) << "cudaMallocHost Cannot allocate " << size
<< " bytes in CUDAPinnedPlace";
}
if (FLAGS_init_allocated_mem) {
memset(ptr, 0xEF, size);
}
return ptr;
#else
PADDLE_THROW("'CUDAPinnedPlace' is not supported in CPU only device.");
#endif
}
template <>
void Free<platform::CUDAPinnedPlace>(const platform::CUDAPinnedPlace& place,
void* p) {
#ifdef PADDLE_WITH_CUDA
GetCUDAPinnedBuddyAllocator()->Free(p);
#else
PADDLE_THROW("'CUDAPinnedPlace' is not supported in CPU only device.");
#endif
}
struct AllocVisitor : public boost::static_visitor<void*> {
inline explicit AllocVisitor(size_t size) : size_(size) {}
template <typename Place>
inline void* operator()(const Place& place) const {
return Alloc<Place>(place, size_);
}
private:
size_t size_;
};
struct FreeVisitor : public boost::static_visitor<void> {
inline explicit FreeVisitor(void* ptr) : ptr_(ptr) {}
template <typename Place>
inline void operator()(const Place& place) const {
Free<Place>(place, ptr_);
}
private:
void* ptr_;
};
size_t Usage::operator()(const platform::CPUPlace& cpu) const {
return Used(cpu);
}
size_t Usage::operator()(const platform::CUDAPlace& gpu) const {
#ifdef PADDLE_WITH_CUDA
return Used(gpu);
#else
PADDLE_THROW("'CUDAPlace' is not supported in CPU only device.");
#endif
}
size_t Usage::operator()(const platform::CUDAPinnedPlace& cuda_pinned) const {
#ifdef PADDLE_WITH_CUDA
return Used(cuda_pinned);
#else
PADDLE_THROW("'CUDAPinnedPlace' is not supported in CPU only device.");
#endif
}
class LegacyAllocation : public Allocation {
public:
using Allocation::Allocation;
~LegacyAllocation() final {
boost::apply_visitor(FreeVisitor(this->ptr()), this->place());
}
};
} // namespace legacy
std::shared_ptr<Allocation> AllocShared(const platform::Place& place,
size_t size, Allocator::Attr attr) {
if (allocation::GetAllocatorStrategy() ==
allocation::AllocatorStrategy::kLegacy) {
void* p = boost::apply_visitor(legacy::AllocVisitor(size), place);
return std::shared_ptr<Allocation>(
new legacy::LegacyAllocation(p, size, place));
} else {
return allocation::AllocatorFacade::Instance().AllocShared(place, size,
attr);
}
return allocation::AllocatorFacade::Instance().AllocShared(place, size, attr);
}
AllocationPtr Alloc(const platform::Place& place, size_t size,
Allocator::Attr attr) {
if (allocation::GetAllocatorStrategy() ==
allocation::AllocatorStrategy::kLegacy) {
void* p = boost::apply_visitor(legacy::AllocVisitor(size), place);
return AllocationPtr(new legacy::LegacyAllocation(p, size, place));
} else {
return allocation::AllocatorFacade::Instance().Alloc(place, size, attr);
}
}
} // namespace memory
......
......@@ -30,26 +30,5 @@ extern std::shared_ptr<Allocation> AllocShared(
extern AllocationPtr Alloc(const platform::Place& place, size_t size,
Allocator::Attr attr = Allocator::kDefault);
namespace legacy {
template <typename Place>
void* Alloc(const Place& place, size_t size);
template <typename Place>
void Free(const Place& place, void* p);
template <typename Place>
size_t Used(const Place& place);
struct Usage : public boost::static_visitor<size_t> {
size_t operator()(const platform::CPUPlace& cpu) const;
size_t operator()(const platform::CUDAPlace& gpu) const;
size_t operator()(const platform::CUDAPinnedPlace& cuda_pinned) const;
};
size_t memory_usage(const platform::Place& p);
} // namespace legacy
} // namespace memory
} // namespace paddle
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