mirror of https://github.com/alibaba/MNN.git
412 lines
18 KiB
C++
412 lines
18 KiB
C++
//
|
|
// RasterExecution.cpp
|
|
// MNN
|
|
//
|
|
// Created by MNN on b'2020/04/02'.
|
|
// Copyright © 2018, Alibaba Group Holding Limited
|
|
//
|
|
|
|
#include "RasterExecution.hpp"
|
|
#include "core/OpCommonUtils.hpp"
|
|
#include "core/BufferAllocator.hpp"
|
|
#include "Raster.cuh"
|
|
#include "Transpose.cuh"
|
|
#include "MNNCUDADefine.hpp"
|
|
namespace MNN {
|
|
namespace CUDA {
|
|
|
|
static bool _equalSizeStride(const Tensor::InsideDescribe::Region& slice0, const Tensor::InsideDescribe::Region& slice1) {
|
|
if (slice0.src.stride[0] != slice1.src.stride[0] || slice0.dst.stride[0] != slice1.dst.stride[0]) {
|
|
//MNN_PRINT("Raster total:%d, index:%d, src stride0:%d-%d, , dst stride0:%d-%d\n", mTempInputCopy.size(), i, slice.src.stride[0], slice0.src.stride[0], slice.dst.stride[0], slice0.dst.stride[0]);
|
|
return false;
|
|
}
|
|
if (slice0.src.stride[1] != slice1.src.stride[1] || slice0.dst.stride[1] != slice1.dst.stride[1]) {
|
|
//MNN_PRINT("Raster total:%d, index:%d, src stride1:%d-%d, , dst stride1:%d-%d\n", mTempInputCopy.size(), i, slice.src.stride[1], slice0.src.stride[1], slice.dst.stride[1], slice0.dst.stride[1]);
|
|
return false;
|
|
}
|
|
if (slice0.src.stride[2] != slice1.src.stride[2] || slice0.dst.stride[2] != slice1.dst.stride[2]) {
|
|
//MNN_PRINT("Raster total:%d, index:%d, src stride2:%d-%d, , dst stride2:%d-%d\n", mTempInputCopy.size(), i, slice.src.stride[2], slice0.src.stride[2], slice.dst.stride[2], slice0.dst.stride[2]);
|
|
return false;
|
|
}
|
|
if (slice0.size[0] != slice1.size[0] || slice0.size[1] != slice1.size[1] || slice0.size[2] != slice1.size[2]) {
|
|
//MNN_PRINT("Raster total:%d, index:%d, copy size:%d-%d-%d, %d-%d-%d\n", mTempInputCopy.size(), i, slice.size[0], slice.size[1], slice.size[2], slice0.size[0], slice0.size[1], slice0.size[2]);
|
|
return false;
|
|
}
|
|
if (slice0.dst.stride[0] !=0 && slice0.src.stride[0] != 0 && slice0.src.stride[0] % slice0.dst.stride[0] != 0 && slice0.dst.stride[0] % slice0.src.stride[0] != 0) {
|
|
return false;
|
|
}
|
|
return true;
|
|
}
|
|
|
|
static bool _directBlitC4(const Tensor::InsideDescribe::Region& slice0, const Tensor::InsideDescribe::Region& slice1, Tensor* tensor) {
|
|
if(tensor->dimensions() < 2) {
|
|
return false;
|
|
}
|
|
if(slice0.src.stride[1] == tensor->width() && slice0.src.stride[0] == tensor->width() * tensor->height()) {
|
|
// area pack for fast blit only
|
|
return false;
|
|
}
|
|
if(slice1.src.stride[1] == tensor->width() && slice1.src.stride[0] == tensor->width() * tensor->height()) {
|
|
// area pack for fast blit only
|
|
return false;
|
|
}
|
|
if(slice0.size[1] % PACK_NUMBER != 0 || slice0.size[0] != 1) {
|
|
return false;
|
|
}
|
|
if(slice1.size[1] % PACK_NUMBER != 0 || slice1.size[0] != 1) {
|
|
return false;
|
|
}
|
|
if(slice0.dst.offset % (slice0.size[1] * slice0.size[2]) != 0) {
|
|
return false;
|
|
}
|
|
if(slice1.dst.offset % (slice1.size[1] * slice1.size[2]) != 0) {
|
|
return false;
|
|
}
|
|
if(slice0.src.offset % (slice0.size[1] * slice0.size[2]) != 0) {
|
|
return false;
|
|
}
|
|
if(slice1.src.offset % (slice1.size[1] * slice1.size[2]) != 0) {
|
|
return false;
|
|
}
|
|
if(slice0.src.stride[2] != 1 || slice0.dst.stride[2] != 1) {
|
|
return false;
|
|
}
|
|
if(slice1.src.stride[2] != 1 || slice1.dst.stride[2] != 1) {
|
|
return false;
|
|
}
|
|
return _equalSizeStride(slice0, slice1);
|
|
}
|
|
|
|
static void _turnToNewRegion(const Tensor::InsideDescribe::Region& region, Tensor::InsideDescribe::Region& newRegion, const int srcStep, const int dstStep) {
|
|
newRegion.size[0] = region.size[0];
|
|
newRegion.size[1] = region.size[2];
|
|
newRegion.size[2] = region.size[1];
|
|
|
|
newRegion.src.stride[0] = region.src.stride[0];
|
|
newRegion.src.stride[1] = region.src.stride[2] * region.size[1] * srcStep;
|
|
newRegion.src.stride[2] = region.src.stride[1] / region.size[2];
|
|
|
|
newRegion.dst.stride[0] = region.dst.stride[0] * dstStep;
|
|
newRegion.dst.stride[1] = region.dst.stride[2] * region.size[1] * dstStep;
|
|
newRegion.dst.stride[2] = region.dst.stride[1] / region.size[2];
|
|
|
|
newRegion.src.offset = region.src.offset / region.size[2];
|
|
newRegion.dst.offset = region.dst.offset / region.size[2];
|
|
}
|
|
|
|
ErrorCode RasterExecution::onResize(const std::vector<Tensor *> &____inputs, const std::vector<Tensor *> &outputs) {
|
|
MNN_ASSERT(outputs.size() == 1);
|
|
auto input = outputs[0];
|
|
auto output = outputs[0];
|
|
OpCommonUtils::rasterInputReset(____inputs, outputs[0]);
|
|
mSingleConvert.type = 0;
|
|
|
|
auto des = TensorUtils::getDescribe(input);
|
|
auto outputDes = TensorUtils::getDescribe(output);
|
|
mNeedZero = !TensorUtils::regionIsFull(input);
|
|
mTempInputCopy.clear();
|
|
mTempInput.clear();
|
|
|
|
mTempOutput = nullptr;
|
|
mOutputPtr = output;
|
|
|
|
mFast = false;
|
|
int pack = PACK_NUMBER;
|
|
// all_srcFormat == dstFormat == NC4HW4 : Fast Exe
|
|
if (outputDes->dimensionFormat == MNN_DATA_FORMAT_NC4HW4) {
|
|
mFast = true;
|
|
auto& slice0 = des->regions[0];
|
|
for (int i=0; i< des->regions.size(); ++i) {
|
|
auto& slice = des->regions[i];
|
|
// MNN_PRINT("%d-%d-%d-%d-%d\n", ____inputs[i]->batch(), ____inputs[i]->height(), ____inputs[i]->width(), ____inputs[i]->channel(), outputs[0]->channel());
|
|
// MNN_PRINT("%d-%d-%d, %d-%d-%d, %d-%d-%d, %d-%d\n\n", slice.size[0], slice.size[1], slice.size[2], slice.src.stride[0], slice.src.stride[1], slice.src.stride[2], slice.dst.stride[0], slice.dst.stride[1], slice.dst.stride[2], slice.src.offset, slice.dst.offset);
|
|
if (TensorUtils::getDescribe(slice.origin)->dimensionFormat != MNN_DATA_FORMAT_NC4HW4) {
|
|
mFast = false;
|
|
break;
|
|
}
|
|
if(!_directBlitC4(slice0, slice, output)) {
|
|
mFast = false;
|
|
break;
|
|
}
|
|
if (!OpCommonUtils::canBlitFast(slice, output, pack, false, true)) {
|
|
mFast = false;
|
|
break;
|
|
}
|
|
}
|
|
//MNN_PRINT("raster fast:%d regionNum:%d\n\n\n", mFast, des->regions.size());
|
|
if (mFast) {
|
|
for (int i=0; i< des->regions.size(); ++i) {
|
|
int srcStep = 1;
|
|
int dstStep = 1;
|
|
auto& slice = des->regions[i];
|
|
if(slice.dst.offset / (slice.size[2] * slice.size[1]) >= 1) {
|
|
int batchChannel = slice.dst.offset / (slice.size[1] * slice.size[2]) + 1;
|
|
dstStep = dstStep > batchChannel ? dstStep : batchChannel;
|
|
}
|
|
if(slice.src.stride[0] != 0 && slice.dst.stride[0] / slice.src.stride[0] > 1) {
|
|
int tmp = slice.dst.stride[0] / slice.src.stride[0];
|
|
dstStep = dstStep > tmp ? dstStep : tmp;
|
|
}
|
|
if(slice.src.offset / (slice.size[2] * slice.size[1]) >= 1) {
|
|
int batchChannel = slice.src.offset / (slice.size[1] * slice.size[2]) + 1;
|
|
srcStep = srcStep > batchChannel ? srcStep : batchChannel;
|
|
}
|
|
if(slice.dst.stride[0] != 0 && slice.src.stride[0] / slice.dst.stride[0] > 1) {
|
|
int tmp = slice.src.stride[0] / slice.dst.stride[0];
|
|
srcStep = srcStep > tmp ? srcStep : tmp;
|
|
}
|
|
if(____inputs[i]->channel() > slice.size[1]) {
|
|
int tmp = ____inputs[i]->channel() / slice.size[1];
|
|
srcStep = srcStep > tmp ? srcStep : tmp;
|
|
}
|
|
|
|
if (slice.origin == nullptr) {
|
|
continue;
|
|
}
|
|
Tensor::InsideDescribe::Region newRegion;
|
|
// [N, C, HW] --> [N, HW, C]
|
|
_turnToNewRegion(slice, newRegion, srcStep, dstStep);
|
|
mFastBlit.emplace_back(std::make_pair(slice.origin, std::move(newRegion)));
|
|
// MNN_PRINT("new step %d-%d:%d-%d-%d, %d-%d-%d, %d-%d-%d, %d-%d\n\n", srcStep, dstStep, newRegion.size[0], newRegion.size[1], newRegion.size[2], newRegion.src.stride[0], newRegion.src.stride[1], newRegion.src.stride[2], newRegion.dst.stride[0], newRegion.dst.stride[1], newRegion.dst.stride[2], newRegion.src.offset, newRegion.dst.offset);
|
|
}
|
|
return NO_ERROR;
|
|
}
|
|
}
|
|
|
|
// srcNum == 1 && srcFormat != dstFormat : Single Convert
|
|
if (des->regions.size() == 1) {
|
|
OpCommonUtils::turnRegion2Convert(des->regions[0], output, mSingleConvert);
|
|
if (mSingleConvert.type > 0) {
|
|
return NO_ERROR;
|
|
}
|
|
}
|
|
|
|
std::vector<Tensor*> forRelease;
|
|
for(int i = 0; i < des->regions.size(); i++) {
|
|
auto& slice = des->regions[i];
|
|
auto origin = slice.origin;
|
|
if (TensorUtils::getDescribe(origin)->dimensionFormat != MNN_DATA_FORMAT_NC4HW4) {
|
|
mTempInputCopy.emplace_back(std::make_pair(origin, &slice));
|
|
continue;
|
|
}
|
|
auto cache = static_cast<CUDABackend*>(backend())->getCache();
|
|
auto tempTensor = cache->findCacheTensor(origin, MNN_DATA_FORMAT_NCHW);
|
|
if (nullptr == tempTensor) {
|
|
std::shared_ptr<Tensor> newTensor(new Tensor);
|
|
TensorUtils::copyShape(origin, newTensor.get());
|
|
TensorUtils::getDescribe(newTensor.get())->dimensionFormat = MNN_DATA_FORMAT_NCHW;
|
|
newTensor->buffer().type = origin->getType();
|
|
TensorUtils::setLinearLayout(newTensor.get());
|
|
// Propagate quant info if necessary
|
|
auto des = TensorUtils::getDescribe(newTensor.get());
|
|
auto originDes = TensorUtils::getDescribe(origin);
|
|
if (originDes->quantAttr != nullptr) {
|
|
des->quantAttr.reset(new QuantAttr);
|
|
*des->quantAttr = *originDes->quantAttr;
|
|
des->type = static_cast<CUDABackend*>(backend())->getDataType(origin);
|
|
}
|
|
|
|
auto res = backend()->onAcquireBuffer(newTensor.get(), Backend::DYNAMIC);
|
|
if (!res) {
|
|
return OUT_OF_MEMORY;
|
|
}
|
|
tempTensor = newTensor.get();
|
|
TensorUtils::getDescribe(tempTensor)->useCount = TensorUtils::getDescribe(origin)->useCount;
|
|
cache->pushCacheTensor(newTensor, origin, MNN_DATA_FORMAT_NCHW);
|
|
mTempInput.insert(std::make_pair(origin, tempTensor));
|
|
}
|
|
if (--TensorUtils::getDescribe(tempTensor)->useCount == 0) {
|
|
forRelease.emplace_back(tempTensor);
|
|
}
|
|
mTempInputCopy.emplace_back(std::make_pair(tempTensor, &slice));
|
|
}
|
|
|
|
if (MNN_DATA_FORMAT_NC4HW4 == outputDes->dimensionFormat) {
|
|
mTempOutput.reset(new Tensor);
|
|
TensorUtils::setupTensorInfo(output, mTempOutput.get(), MNN_DATA_FORMAT_NCHW);
|
|
|
|
// Propagate quant info if necessary
|
|
auto des = TensorUtils::getDescribe(mTempOutput.get());
|
|
auto originDes = TensorUtils::getDescribe(output);
|
|
if (originDes->quantAttr != nullptr) {
|
|
des->quantAttr.reset(new QuantAttr);
|
|
*des->quantAttr = *originDes->quantAttr;
|
|
des->type = static_cast<CUDABackend*>(backend())->getDataType(output);
|
|
}
|
|
|
|
auto res = backend()->onAcquireBuffer(mTempOutput.get(), Backend::DYNAMIC);
|
|
if (!res) {
|
|
return OUT_OF_MEMORY;
|
|
}
|
|
mOutputPtr = mTempOutput.get();
|
|
}
|
|
|
|
//MNN_PRINT("Raster copy size:%d\n", mTempInputCopy.size());
|
|
if(mTempInputCopy.size() > 1) {
|
|
mFuseRaster.first = 1;
|
|
mFuseRaster.second = mTempInputCopy.size();
|
|
auto& slice0 = *mTempInputCopy[0].second;
|
|
for (int i = 1; i < mTempInputCopy.size(); ++i) {
|
|
auto& slice = *mTempInputCopy[i].second;
|
|
if (mTempInputCopy[i].first != mTempInputCopy[0].first) {
|
|
mFuseRaster.first = 0;
|
|
//MNN_PRINT("Raster total:%d, index:%d, origin:%p-%p\n", mTempInputCopy.size(), i, mTempInputCopy[i].first, mTempInputCopy[0].first);
|
|
break;
|
|
}
|
|
if(!_equalSizeStride(slice0, slice)) {
|
|
mFuseRaster.first = 0;
|
|
}
|
|
}
|
|
}
|
|
if(mFuseRaster.first > 0) {
|
|
auto& slice0 = *mTempInputCopy[0].second;
|
|
auto tensor = mTempInputCopy[0].first;
|
|
int regionSize = mTempInputCopy.size();
|
|
std::vector<int32_t> temp(2*regionSize, 0);
|
|
// TODO: Reduce logic for these code
|
|
mFuseRaster.first = 4;
|
|
for (int i = 0; i < regionSize; ++i) {
|
|
auto& slice = *mTempInputCopy[i].second;
|
|
temp[i] = slice.src.offset;
|
|
temp[regionSize+i] = slice.dst.offset;
|
|
if (temp[i] % 4 != 0 || temp[regionSize+i] % 4 != 0) {
|
|
mFuseRaster.first = 1;
|
|
}
|
|
//MNN_PRINT("%d-%d-%d\n", regionSize, temp[i], temp[regionSize+i]);
|
|
}
|
|
//save srcOffset/dstOffset to Device
|
|
mOffsetTensor.reset(Tensor::createDevice<int32_t>({2*regionSize}));
|
|
backend()->onAcquireBuffer(mOffsetTensor.get(), Backend::STATIC);
|
|
mOffset = (void *)mOffsetTensor.get()->buffer().device;
|
|
cuda_check(cudaMemcpy(mOffset, temp.data(), 2*regionSize*sizeof(int32_t), cudaMemcpyHostToDevice));
|
|
mTempInputCopy.clear();
|
|
mTempInputCopy.emplace_back(std::make_pair(tensor, &slice0));
|
|
}
|
|
for (auto t : forRelease) {
|
|
backend()->onReleaseBuffer(t, Backend::DYNAMIC);
|
|
}
|
|
if (nullptr != mTempOutput) {
|
|
backend()->onReleaseBuffer(mTempOutput.get(), Backend::DYNAMIC);
|
|
}
|
|
return NO_ERROR;
|
|
}
|
|
|
|
void RasterExecution::executeFaster(const std::vector<Tensor *> &inputs, const std::vector<Tensor *> &outputs) const {
|
|
auto bn = static_cast<CUDABackend*>(backend());
|
|
auto input = outputs[0];
|
|
auto output = outputs[0];
|
|
auto bytes = bn->getBytes(output);
|
|
auto runtime = static_cast<CUDABackend*>(backend())->getCUDARuntime();
|
|
if (mNeedZero) {
|
|
auto size = static_cast<CUDABackend*>(backend())->realSize(output) * bytes;
|
|
cudaMemset((uint8_t*)output->deviceId(), 0, size);
|
|
checkKernelErrors;
|
|
}
|
|
// Use mFastBlit
|
|
for (auto& iter : mFastBlit) {
|
|
auto srcPtr = (uint8_t*)iter.first->deviceId() + iter.second.src.offset * bytes;
|
|
auto dstPtr = (uint8_t*)output->deviceId() + iter.second.dst.offset * bytes;
|
|
RasterBlit(dstPtr, srcPtr, iter.second.size, iter.second.src.stride, iter.second.dst.stride, bytes, runtime);
|
|
checkKernelErrors;
|
|
}
|
|
}
|
|
|
|
ErrorCode RasterExecution::onExecute(const std::vector<Tensor *> &inputs, const std::vector<Tensor *> &outputs) {
|
|
if (mFast) {
|
|
executeFaster(inputs, outputs);
|
|
return NO_ERROR;
|
|
}
|
|
auto bn = static_cast<CUDABackend*>(backend());
|
|
auto input = outputs[0];
|
|
auto output = outputs[0];
|
|
auto bytes = bn->getBytes(output);
|
|
auto runtime = static_cast<CUDABackend*>(backend())->getCUDARuntime();
|
|
// MNN_PRINT("raster format:%d -> %d, addr:%p %p bytes:%d\n", TensorUtils::getDescribe(input)->dimensionFormat, \
|
|
// TensorUtils::getDescribe(output)->dimensionFormat, \
|
|
// input->deviceId(), output->deviceId(), bytes);
|
|
|
|
if (mSingleConvert.type > 0) {
|
|
auto realInput = TensorUtils::getDescribe(input)->regions[0].origin;
|
|
int srcBatch = mSingleConvert.batch, srcChannel = mSingleConvert.channel, srcArea = mSingleConvert.area;
|
|
auto sourceFormat = TensorUtils::getDescribe(realInput)->dimensionFormat;
|
|
PackInfo pack;
|
|
pack.inside = srcArea;
|
|
pack.axis = srcChannel;
|
|
pack.unit = PACK_NUMBER;
|
|
pack.outside = srcBatch;
|
|
if (mSingleConvert.type == 1) {
|
|
pack.axisStride = srcArea;
|
|
pack.insideStride = 1;
|
|
} else if (mSingleConvert.type == 2) {
|
|
pack.axisStride = 1;
|
|
pack.insideStride = srcChannel;
|
|
}
|
|
auto srcPtr = (void*)realInput->deviceId();
|
|
auto dstPtr = (void*)output->deviceId();
|
|
if (MNN_DATA_FORMAT_NC4HW4 == sourceFormat) {
|
|
if (realInput->dimensions() <= 1) {
|
|
cudaMemcpy(dstPtr, srcPtr, bn->realSize(realInput) * bytes, cudaMemcpyDeviceToDevice);
|
|
return NO_ERROR;
|
|
}
|
|
UnpackBuffer(dstPtr, srcPtr, &pack, bytes, runtime);
|
|
checkKernelErrors;
|
|
} else {
|
|
if (output->dimensions() <= 1) {
|
|
cudaMemcpy(dstPtr, srcPtr, bn->realSize(realInput) * bytes, cudaMemcpyDeviceToDevice);
|
|
return NO_ERROR;
|
|
}
|
|
PackBuffer(dstPtr, srcPtr, &pack, bytes, runtime);
|
|
checkKernelErrors;
|
|
}
|
|
return NO_ERROR;
|
|
}
|
|
|
|
if (mNeedZero) {
|
|
auto size = static_cast<CUDABackend*>(backend())->realSize(mOutputPtr) * bytes;
|
|
cudaMemset((uint8_t*)mOutputPtr->deviceId(), 0, size);
|
|
checkKernelErrors;
|
|
}
|
|
for (auto& iter : mTempInput) {
|
|
backend()->onCopyBuffer(iter.first, iter.second);
|
|
checkKernelErrors;
|
|
}
|
|
//MNN_PRINT("\n%d\n", mFuseRaster.first);
|
|
if(mFuseRaster.first > 0) {
|
|
MNN_ASSERT(mTempInputCopy.size() == 1);
|
|
auto& iter = mTempInputCopy[0];
|
|
auto& slice = *(iter.second);
|
|
auto srcPtr = (uint8_t*)iter.first->deviceId();
|
|
auto dstPtr = (uint8_t*)mOutputPtr->deviceId();
|
|
//MNN_PRINT("fuseRaster:%p-%p\n", mSrcOffset, mDstOffset);
|
|
|
|
FuseRasterBlit(dstPtr, srcPtr, slice.size, slice.src.stride, slice.dst.stride, mFuseRaster.second, mOffset, bytes, runtime, mFuseRaster.first);
|
|
checkKernelErrors;
|
|
} else {
|
|
for (auto& iter : mTempInputCopy) {
|
|
auto srcPtr = (uint8_t*)iter.first->deviceId() + iter.second->src.offset * bytes;
|
|
auto dstPtr = (uint8_t*)mOutputPtr->deviceId() + iter.second->dst.offset * bytes;
|
|
RasterBlit(dstPtr, srcPtr, iter.second->size, iter.second->src.stride, iter.second->dst.stride, bytes, runtime);
|
|
checkKernelErrors;
|
|
}
|
|
}
|
|
|
|
if (nullptr != mTempOutput) {
|
|
backend()->onCopyBuffer(mTempOutput.get(), output);
|
|
checkKernelErrors;
|
|
}
|
|
return NO_ERROR;
|
|
}
|
|
|
|
class RasterExecutionFactory : public CUDABackend::Creator {
|
|
public:
|
|
virtual Execution* onCreate(const std::vector<Tensor*>& inputs, const std::vector<Tensor*>& outputs,
|
|
const MNN::Op* op, Backend* backend) const {
|
|
return new RasterExecution(backend);
|
|
}
|
|
};
|
|
|
|
static CUDACreatorRegister<RasterExecutionFactory> __init(OpType_Raster);
|
|
|
|
}
|
|
}
|