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MNN/source/backend/cpu/CPUBackend.cpp

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//
// CPUBackend.cpp
// MNN
//
// Created by MNN on 2018/07/06.
// Copyright © 2018, Alibaba Group Holding Limited
//
#include "backend/cpu/CPUBackend.hpp"
#include <cmath>
#include <mutex>
#include "core/BufferAllocator.hpp"
#include "backend/cpu/CPUConcat.hpp"
#include "backend/cpu/CPUTensorConvert.hpp"
#include "backend/cpu/compute/CommonOptFunction.h"
#include "core/TensorUtils.hpp"
#include "backend/cpu/ThreadPool.hpp"
#include "core/SizeComputer.hpp"
#ifdef _OPENMP
#include <omp.h>
#endif // _OPENMP
#include "backend/cpu/CPURuntime.hpp"
#define MAX_THREAD_NUMBER 32
//#define MNN_DUMP_MEMORY_USAGE
#define MNN_CPU_CHECK_NAN 1
namespace MNN {
#ifdef MNN_CODEGEN_REGISTER
void registerCPUOps();
#endif
static inline std::map<OpType, CPUBackend::Creator*>* getCreatorMap() {
static std::once_flag of;
static std::map<OpType, CPUBackend::Creator*>* ret = nullptr;
std::call_once(of, [&]() { ret = new std::map<OpType, CPUBackend::Creator*>; });
return ret;
}
bool CPUBackend::addCreator(OpType t, Creator* c) {
auto map = getCreatorMap();
if (map->find(t) != map->end()) {
MNN_PRINT("Error: %d type has be added\n", t);
return false;
}
map->insert(std::make_pair(t, c));
return true;
}
CPUBackend::CPUBackend(int numberThread, BackendConfig::MemoryMode memory, BackendConfig::PowerMode power, size_t flags)
: Backend(MNN_FORWARD_CPU), mThreadNumber(numberThread), mMemory(memory), mPower(power) {
mThreadNumber = std::max(1, mThreadNumber);
mThreadNumber = std::min(mThreadNumber, MAX_THREAD_NUMBER);
mDynamicAllocator.reset(new BufferAllocator);
mStaticAllocator.reset(new BufferAllocator);
mCheckNAN = flags == MNN_CPU_CHECK_NAN;
#ifdef _OPENMP
switch (power) {
case BackendConfig::Power_Low:
MNNSetCPUThreadsMode(MNN_CPU_MODE_LITTLE);
break;
case BackendConfig::Power_High:
MNNSetCPUThreadsMode(MNN_CPU_MODE_POWER_FRI);
break;
default:
break;
}
#endif
#ifdef MNN_USE_THREAD_POOL
mThreadNumber = ThreadPool::init(mThreadNumber);
if (mThreadNumber > 1) {
mTaskIndex = ThreadPool::acquireWorkIndex();
} else {
mTaskIndex = -1;
}
if (mTaskIndex >= 0 && mPower == BackendConfig::Power_High) {
ThreadPool::active();
}
#endif
mFlops = MNNGetCPUFlops(mThreadNumber);
}
CPUBackend::~CPUBackend() {
#ifdef MNN_USE_THREAD_POOL
if (mTaskIndex >= 0 && mPower == BackendConfig::Power_High) {
ThreadPool::deactive();
}
ThreadPool::releaseWorkIndex(mTaskIndex);
#endif
}
void CPUBackend::onExecuteBegin() const {
#ifdef MNN_DUMP_MEMORY_USAGE
{
auto dynamicMemoryInMB = mDynamicAllocator->totalSize() / 1024.0f / 1024.0f;
FUNC_PRINT_ALL(dynamicMemoryInMB, f);
auto staticMemoryInMB = mStaticAllocator->totalSize() / 1024.0f / 1024.0f;
FUNC_PRINT_ALL(staticMemoryInMB, f);
}
#endif
#ifdef MNN_USE_THREAD_POOL
if (mTaskIndex >= 0 && mPower != BackendConfig::Power_High) {
ThreadPool::active();
}
#else
#ifdef _OPENMP
omp_set_dynamic(0);
omp_set_num_threads(mThreadNumber);
#endif
#endif
}
void CPUBackend::onExecuteEnd() const {
#ifdef MNN_USE_THREAD_POOL
if (mTaskIndex >= 0 && mPower != BackendConfig::Power_High) {
ThreadPool::deactive();
}
#endif
}
bool CPUBackend::onAcquireBuffer(const MNN::Tensor* nativeTensorConst, StorageType storageType) {
if (nativeTensorConst == nullptr) {
return false;
}
auto nativeTensor = (Tensor*)nativeTensorConst;
auto& buffer = nativeTensor->buffer();
auto size = nativeTensor->size();
// MNN_PRINT("Acquire size = %d\n", size);
if (size <= 0) {
MNN_ASSERT(false);
return false;
}
switch (storageType) {
case STATIC: {
buffer.host = (uint8_t*)mStaticAllocator->alloc(size, false);
break;
}
case DYNAMIC: {
buffer.host = (uint8_t*)(mDynamicAllocator->alloc(size, false));
break;
}
case DYNAMIC_SEPERATE: {
buffer.host = (uint8_t*)(mDynamicAllocator->alloc(size, true));
break;
}
default:
break;
}
if (nullptr == buffer.host) {
MNN_ERROR("Alloc buffer error for cpu backend\n");
return false;
}
if (buffer.type.code == halide_type_handle) {
::memset(buffer.host, 0, size);
}
return true;
}
bool CPUBackend::onReleaseBuffer(const MNN::Tensor* nativeTensor, StorageType storageType) {
if (nativeTensor == nullptr) {
return false;
}
if (nullptr == nativeTensor->buffer().host) {
return false;
}
if (STATIC == storageType) {
mStaticAllocator->free(nativeTensor->buffer().host);
return true;
}
if (DYNAMIC_SEPERATE == storageType) {
return true;
}
mDynamicAllocator->free(nativeTensor->buffer().host);
return true;
}
std::pair<float, bool> CPUBackend::onMeasure(const std::vector<Tensor*>& inputs, const std::vector<Tensor*>& outputs,
const MNN::Op* op) {
auto map = getCreatorMap();
auto iter = map->find(op->type());
if (iter == map->end()) {
MNN_PRINT("Don't support type %d, %s\n", op->type(), op->name()->c_str());
return std::make_pair(0.0f, false);
}
auto computeFlops = SizeComputer::computeFlops(op, inputs, outputs);
return std::make_pair(computeFlops / mFlops * 1000.0f, true);
}
/// get execution
Execution* CPUBackend::onCreate(const std::vector<Tensor*>& inputs, const std::vector<Tensor*>& outputs,
const MNN::Op* op) {
auto map = getCreatorMap();
auto iter = map->find(op->type());
if (iter == map->end()) {
MNN_PRINT("Don't support type %d, %s\n", op->type(), op->name()->c_str());
return nullptr;
}
auto exe = iter->second->onCreate(inputs, outputs, op, this);
if (nullptr == exe) {
MNN_PRINT("The Creator Don't support type %d, %s\n", op->type(), op->name()->c_str());
return nullptr;
}
if (mCheckNAN) {
class CheckNANExecution : public Execution {
public:
CheckNANExecution(Execution* exe) : Execution(exe->backend()) {
mExecution.reset(exe);
mValid = exe->valid();
}
virtual ~CheckNANExecution() {
// Do nothing
}
virtual ErrorCode onResize(const std::vector<Tensor*>& inputs,
const std::vector<Tensor*>& outputs) override {
return mExecution->onResize(inputs, outputs);
}
virtual ErrorCode onReleaseCache() override {
return mExecution->onReleaseCache();
}
virtual ErrorCode onExecute(const std::vector<Tensor*>& inputs,
const std::vector<Tensor*>& outputs) override {
for (auto tensor : inputs) {
if (halide_type_float != tensor->getType().code) {
return NO_ERROR;
}
auto size = tensor->elementSize();
auto ptr = tensor->host<float>();
for (int i = 0; i < size; ++i) {
auto value = ptr[i];
if (std::isnan(value) || std::isinf(value)) {
return INVALID_VALUE;
}
}
}
auto code = mExecution->onExecute(inputs, outputs);
if (NO_ERROR != code) {
return code;
}
for (auto tensor : outputs) {
if (halide_type_float != tensor->getType().code) {
return NO_ERROR;
}
auto size = tensor->elementSize();
auto ptr = tensor->host<float>();
for (int i = 0; i < size; ++i) {
auto value = ptr[i];
if (std::isnan(value) || std::isinf(value)) {
return INVALID_VALUE;
}
}
}
return NO_ERROR;
}
private:
std::unique_ptr<Execution> mExecution;
};
return new CheckNANExecution(exe);
}
return exe;
}
bool CPUBackend::onAllocateBuffer() {
mStaticAllocator->release(false);
return true;
}
bool CPUBackend::onClearBuffer() {
mDynamicAllocator->release(true);
mStaticAllocator->release(false);
return true;
}
void CPUBackend::onCopyBuffer(const Tensor* srcTensor, const Tensor* dstTensor) const {
auto& srcBuffer = srcTensor->buffer();
auto& dstBuffer = dstTensor->buffer();
MNN_ASSERT(srcBuffer.dimensions == dstBuffer.dimensions);
MNN_ASSERT(srcBuffer.type == dstBuffer.type);
if (srcTensor->getDimensionType() == dstTensor->getDimensionType()) {
for (int i = 0; i < srcBuffer.dimensions; ++i) {
MNN_ASSERT(srcBuffer.dim[i].extent <= dstBuffer.dim[i].extent);
}
}
if (nullptr == srcBuffer.host || nullptr == dstBuffer.host) {
return;
}
auto code = CPUTensorConverter::convert(srcTensor, dstTensor);
if (NO_ERROR != code) {
MNN_ERROR("Error in CPUBackend::onCopyBuffer\n");
}
}
struct CPUBackendCreator : BackendCreator {
Backend* onCreate(const Backend::Info& info) const override {
auto power = BackendConfig::Power_Normal;
auto memory = BackendConfig::Memory_Normal;
size_t flags = 0;
if (nullptr != info.user) {
power = info.user->power;
memory = info.user->memory;
flags = info.user->flags;
}
#ifdef MNN_CODEGEN_REGISTER
static std::once_flag s_flag;
std::call_once(s_flag, [&]() { registerCPUOps(); });
#endif
return new CPUBackend(info.numThread, memory, power, flags);
}
};
void registerCPUBackendCreator() {
MNNInsertExtraBackendCreator(MNN_FORWARD_CPU, new CPUBackendCreator);
};
} // namespace MNN
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