MNN/express/Utils.cpp

313 lines
9.6 KiB
C++

//
// Utils.cpp
// MNN
//
// Created by MNN on 2019/07/26.
// Copyright © 2018, Alibaba Group Holding Limited
//
#include "Utils.hpp"
#include <map>
#include <set>
#include <stack>
#include "MNN_generated.h"
#include "core/TensorUtils.hpp"
#include "core/Session.hpp"
#include "core/MNNMemoryUtils.h"
#include "core/Backend.hpp"
#include "core/Execution.hpp"
#include "core/ConvolutionCommon.hpp"
namespace MNN {
namespace Express {
Expr::Inside::Inside(int outputSize) {
mOutputInfos.resize(outputSize);
mOutputTensors.resize(outputSize);
for (int i=0; i<outputSize; ++i) {
mOutputTensors[i] = new Tensor;
TensorUtils::getDescribe(mOutputTensors[i])->memoryType = Tensor::InsideDescribe::MEMORY_HOST;
}
}
Expr::Inside::Inside(Tensor* tensor, bool own) {
mOutputInfos.resize(1);
mOutputTensors.resize(1);
mOutputTensors[0] = tensor;
Utils::copyTensorToInfo(&mOutputInfos[0], tensor);
mOutputInfos[0].syncSize();
mOwnTensor = own;
}
Expr::Inside::~Inside() {
if (mOwnTensor) {
for (auto t : mOutputTensors) {
delete t;
}
}
if (nullptr != mHostTensor) {
delete mHostTensor;
}
}
#define CONVERT(src, dst, f)\
if (f == src) return dst;
int Utils::convertFormat(Dimensionformat format) {
CONVERT(NCHW, MNN_DATA_FORMAT_NCHW, format);
CONVERT(NHWC, MNN_DATA_FORMAT_NHWC, format);
CONVERT(NC4HW4, MNN_DATA_FORMAT_NC4HW4, format);
return MNN_DATA_FORMAT_UNKNOWN;
}
DataType Utils::convertDataType(halide_type_t type) {
if (type.code == halide_type_float) {
return DataType_DT_FLOAT;
}
if (type.code == halide_type_uint && type.bits == 8) {
return DataType_DT_UINT8;
}
if (type.code == halide_type_int && type.bits == 8) {
return DataType_DT_INT8;
}
if (type.code == halide_type_int && type.bits == 32) {
return DataType_DT_INT32;
}
return DataType_DT_INVALID;
}
halide_type_t Utils::revertDataType(DataType dataType) {
CONVERT(DataType_DT_FLOAT, halide_type_of<float>(), dataType);
CONVERT(DataType_DT_INT32, halide_type_of<int32_t>(), dataType);
CONVERT(DataType_DT_INT64, halide_type_of<int32_t>(), dataType);
CONVERT(DataType_DT_UINT8, halide_type_of<uint8_t>(), dataType);
CONVERT(DataType_DT_INT8, halide_type_of<int8_t>(), dataType);
CONVERT(DataType_DT_HALF, halide_type_of<float>(), dataType);
CONVERT(DataType_DT_BFLOAT16, halide_type_t(halide_type_float, 16), dataType);
return halide_type_of<float>();
}
Express::Dimensionformat Utils::revertFormat(int format) {
CONVERT(MNN_DATA_FORMAT_NCHW, Express::NCHW, format);
CONVERT(MNN_DATA_FORMAT_NHWC, Express::NHWC, format);
CONVERT(MNN_DATA_FORMAT_NC4HW4, Express::NC4HW4, format);
return NCHW;
}
void Utils::copyInfoToTensor(Tensor* dest, const Variable::Info* source) {
if (nullptr == source) {
dest->buffer().dimensions = 0;
return;
}
for (int i = 0; i < source->dim.size(); ++i) {
dest->setLength(i, source->dim[i]);
}
dest->buffer().dimensions = (int)source->dim.size();
dest->buffer().type = source->type;
TensorUtils::getDescribe(dest)->dimensionFormat = (MNN_DATA_FORMAT)Utils::convertFormat(source->order);
TensorUtils::setLinearLayout(dest);
}
void Utils::copyTensorToInfo(Variable::Info* shape, const Tensor* tensor) {
shape->type = tensor->getType();
shape->dim = tensor->shape();
shape->size = tensor->elementSize();
shape->order = Utils::revertFormat(TensorUtils::getDescribe(tensor)->dimensionFormat);
}
bool Utils::allocMemoryForHostTensor(Tensor* dest) {
if (nullptr != dest->buffer().host) {
return true;
}
if (TensorUtils::getDescribe(dest)->memoryType != Tensor::InsideDescribe::MEMORY_HOST) {
return false;
}
auto size = dest->size();
if (0 >= size) {
return false;
}
dest->buffer().host = (uint8_t*)MNNMemoryAllocAlign(size, MNN_MEMORY_ALIGN_DEFAULT);
return dest->buffer().host != nullptr;
}
bool Utils::releaseMemoryForHostTensor(Tensor* dest) {
if (nullptr == dest->buffer().host) {
return true;
}
if (TensorUtils::getDescribe(dest)->memoryType != Tensor::InsideDescribe::MEMORY_HOST) {
return false;
}
MNNMemoryFreeAlign(dest->buffer().host);
dest->buffer().host = nullptr;
return true;
}
Tensor* Utils::getTensor(VARP var) {
return (Tensor*)(var->getTensor());
}
EXPRP Utils::makeRaster(const std::vector<VARP>& vars, const std::vector<int>& regions, const std::vector<int>& shape, halide_type_t dataType, MNN_DATA_FORMAT format) {
std::unique_ptr<MNN::OpT> op(new MNN::OpT);
op->type = OpType_Raster;
auto extra = new ExtraT;
// set shape
std::unique_ptr<AttributeT> shapeAttr(new AttributeT);
shapeAttr->key = "shape";
shapeAttr->list.reset(new ListValueT);
shapeAttr->list->i = shape;
extra->attr.push_back(std::move(shapeAttr));
// set region
std::unique_ptr<AttributeT> regionAttr(new AttributeT);
regionAttr->key = "region";
regionAttr->list.reset(new ListValueT);
regionAttr->list->i = regions;
extra->attr.push_back(std::move(regionAttr));
// set data type
if (format != MNN_DATA_FORMAT_UNKNOWN) {
{
std::unique_ptr<AttributeT> attr(new AttributeT);
attr->key = "code";
attr->i = dataType.code;
extra->attr.push_back(std::move(attr));
}
{
std::unique_ptr<AttributeT> attr(new AttributeT);
attr->key = "bits";
attr->i = dataType.bits;
extra->attr.push_back(std::move(attr));
}
{
std::unique_ptr<AttributeT> attr(new AttributeT);
attr->key = "format";
attr->i = (int)format;
extra->attr.push_back(std::move(attr));
}
}
op->main.type = OpParameter_Extra;
op->main.value = extra;
auto expr = Expr::create(std::move(op), vars);
return expr;
}
void* Executor::ComputeCache::mapOutput(int offset, Tensor* dest) {
auto tensor = mSession->getTensor(offset);
auto des = TensorUtils::getDescribe(tensor);
if (0 == tensor->deviceId() && des->quantAttr.get() == nullptr) {
auto ptr = tensor->host<void>();
Utils::releaseMemoryForHostTensor(dest);
TensorUtils::getDescribe(dest)->memoryType = Tensor::InsideDescribe::MEMORY_BACKEND;
dest->buffer().host = (uint8_t*)ptr;
//MNN_ASSERT(nullptr != ptr);
return ptr;
}
Utils::allocMemoryForHostTensor(dest);
tensor->copyToHostTensor(dest);
MNN_ASSERT(nullptr != dest->host<void>());
return dest->host<void>();
}
void Executor::ComputeCache::setShapeDirty() {
mShapeDirty = true;
}
void Executor::ComputeCache::setContentDirty() {
mContentDirty = true;
}
Executor::ComputeCache::~ComputeCache() {
mSession = nullptr;
#ifdef MNN_EXPRESS_MEMLEAK_DEBUG
gInstanceCount--;
FUNC_PRINT(gInstanceCount);
#endif
}
ErrorCode Executor::ComputeCache::compute() {
std::stack<ComputeCache*> dfsStack;
std::set<ComputeCache*> visited;
dfsStack.push(this);
while (!dfsStack.empty()) {
//printf("stcak = %d\n", dfsStack.size());
auto cache = dfsStack.top();
for (auto& c : cache->mInputInside) {
if (c->mContentDirty) {
return CALL_BACK_STOP;
}
}
if (cache->mShapeDirty) {
auto code = cache->resize();
if (NO_ERROR != code) {
cache->mShapeDirty = true;
return code;
}
}
if (!cache->mContentDirty) {
visited.insert(cache);
dfsStack.pop();
continue;
}
auto hasUnvisitInput = [&] () {
for (auto c : cache->mInputs) {
if (visited.find(c.get()) == visited.end()) {
return true;
}
}
return false;
};
if (hasUnvisitInput()) {
for (auto c : cache->mInputs) {
dfsStack.push(c.get());
}
} else {
visited.insert(cache);
dfsStack.pop();
cache->mSession->run();
cache->mContentDirty = false;
}
}
return NO_ERROR;
}
ErrorCode Executor::ComputeCache::resizeImpl() {
mShapeDirty = false;
mSession->setNeedResize();
mSession->resize();
mContentDirty = true;
return NO_ERROR;
}
ErrorCode Executor::ComputeCache::resize() {
std::stack<ComputeCache*> dfsStack;
std::set<ComputeCache*> visited;
dfsStack.push(this);
while (!dfsStack.empty()) {
auto cache = dfsStack.top();
if (!cache->mShapeDirty) {
visited.insert(cache);
dfsStack.pop();
continue;
}
for (auto& c : cache->mInputInside) {
if (c->mInfoDirty) {
return CALL_BACK_STOP;
}
}
auto hasUnvisitInput = [&] () {
for (auto c : cache->mInputs) {
if (visited.find(c.get()) == visited.end()) {
return true;
}
}
return false;
};
if (hasUnvisitInput()) {
for (auto c : cache->mInputs) {
dfsStack.push(c.get());
}
} else {
visited.insert(cache);
dfsStack.pop();
auto code = cache->resizeImpl();
if (code != NO_ERROR) {
return code;
}
}
}
return NO_ERROR;
}
#ifdef MNN_EXPRESS_MEMLEAK_DEBUG
int Executor::ComputeCache::gInstanceCount = 0;
#endif
} // namespace Express
} // namespace MNN