区块链跟单合约量化系统是一种基于区块链技术的交易系统，它利用智能合约来自动化交易操作，将交易信息和数据记录在区块链上，保证交易的公开透明和数据的可靠性。
It should be said that data sharing based on blockchain will become the most common application mode of blockchain except for digital assets,and its role will also be more powerful.In reality,people have built various data centers and data nodes.Although some places have started to build larger and stronger data centers under the banner of strengthening data sharing,this model not only requires a lot of resources,but also may not be easy to expand its application.Blockchain based data sharing aims to establish a data sharing network that links large and small data sources scattered in various places through rules,forming a huge data service system.
合约跟单软件系统开发的核心功能：
1、正跟和反跟：正跟可以跟报单（滑点小）反跟跟成交（避免跟单先成交，指引却被撤单）；
2、跟单数量设置，按比例、按最大手数；
3、跟单未成交的处理方式，仓位差异比较和显示，方便用户一目了然的看清跟单是否有差异，同时包含单个合约的同步功能；
4、跟单差异时的处理，同步仓位；
5、数据管理或保存功能，例如账号、跟单设置、日志等；
6、交易功能，报单、行情显示等；
7、账号风控管理、一键清仓、每日账号数据统计和保存等。
int main(int argc,const char*argv[]){
if(argc<4){
DLOG(INFO)<<"Usage:./quantized.out src.mnn dst.mnn preTreatConfig.jsonn";
return 0;
}
const char*modelFile=argv[1];
const char*preTreatConfig=argv[3];
const char*dstFile=argv[2];
DLOG(INFO)<<">>>modelFile:"<<modelFile;
DLOG(INFO)<<">>>preTreatConfig:"<<preTreatConfig;
DLOG(INFO)<<">>>dstFile:"<<dstFile;
//加载待量化的模型
std::unique_ptr<MNN::NetT>netT;
{
std::ifstream input(modelFile);
std::ostringstream outputOs;
outputOs<<input.rdbuf();
netT=MNN::UnPackNet(outputOs.str().c_str());
}
//temp build net for inference
flatbuffers::FlatBufferBuilder builder(1024);
auto offset=MNN::Net::Pack(builder,netT.get());
builder.Finish(offset);
int size=builder.GetSize();
auto ocontent=builder.GetBufferPointer();
//model buffer for creating mnn Interpreter
std::unique_ptr<uint8_t>modelForInference(new uint8_t[size]);
memcpy(modelForInference.get(),ocontent,size);
std::unique_ptr<uint8_t>modelOriginal(new uint8_t[size]);
memcpy(modelOriginal.get(),ocontent,size);
netT.reset();
netT=MNN::UnPackNet(modelOriginal.get());
//quantize model's weight
DLOG(INFO)<<"Calibrate the feature and quantize model...";
//构建Calibration对象，负责量化
std::shared_ptr<Calibration>calibration(
new Calibration(netT.get(),modelForInference.get(),size,preTreatConfig));
//执行量化，更新参数为int8
calibration->runQuantizeModel();
//将量化的参数写入json文件
calibration->dumpTensorScales(dstFile);
DLOG(INFO)<<"Quantize model done!";
//保存量化后的模型
flatbuffers::FlatBufferBuilder builderOutput(1024);
builderOutput.ForceDefaults(true);
auto len=MNN::Net::Pack(builderOutput,netT.get());
builderOutput.Finish(len);
{
std::ofstream output(dstFile);
output.write((const char*)builderOutput.GetBufferPointer(),builderOutput.GetSize());
}
return 0;
}
