“量化交易”有着两层含义：一是从狭义上来讲，是指量化交易的内容，将交易条件转变成为程序，自动下单；二是从广义上来讲，是指系统交易方法，就是一个整合的交易系统。即为根据一系列交易条件，智能化辅助决策体系，Combine rich professional experience with trading conditions to manage and control risks during the trading process. 量化交易是根据量化分析得出交易策略的一种交易技术，它通过数学计算和数值分析来识别交易机会。以往的完整数据是量化分析的基础，价格和数量是建立数学模型中的主要变量。 //wrapping input tensor,convert nhwc to nchw std::vector<int>dims{1,INPUT_SIZE,INPUT_SIZE,3}; auto nhwc_Tensor=MNN::Tensor::create<float>(dims,NULL,MNN::Tensor::TENSORFLOW); auto nhwc_data=nhwc_Tensor->host<float>(); auto nhwc_size=nhwc_Tensor->size(); ::memcpy(nhwc_data,image.data,nhwc_size); std::string input_tensor=data; auto inputTensor=net->getSessionInput(session,nullptr); inputTensor->copyFromHostTensor(nhwc_Tensor); //run network net->runSession(session); //get output data std::string output_tensor_name0=conv5_fwd; MNN::Tensor*tensor_lmks=net->getSessionOutput(session,output_tensor_name0.c_str()); MNN::Tensor tensor_lmks_host(tensor_lmks,tensor_lmks->getDimensionType()); tensor_lmks->copyToHostTensor(&tensor_lmks_host); //load and config mnn model auto revertor=std::unique_ptr<Revert>(new Revert(model_name.c_str())); revertor->initialize(); auto modelBuffer=revertor->getBuffer(); const auto bufferSize=revertor->getBufferSize(); auto net=std::shared_ptr<MNN::Interpreter>(MNN::Interpreter::createFromBuffer(modelBuffer,bufferSize)); revertor.reset(); MNN::ScheduleConfig config; config.numThread=threads; config.type=static_cast<MNNForwardType>(forward); MNN::BackendConfig backendConfig; config.backendConfig=&backendConfig; auto session=net->createSession(config); net->releaseModel();
