人工智能（Artificial Intelligence，簡(jiǎn)稱AI）是指計(jì)算機(jī)系統(tǒng)在完成類似人類智力所需的任務(wù)時(shí)所表現(xiàn)出來(lái)的能力。它是一種復(fù)雜的技術(shù)，通過(guò)將大量的數(shù)據(jù)輸入到算法中進(jìn)行學(xué)習(xí)，不斷調(diào)整和改進(jìn)自己的算法，從而不斷優(yōu)化其性能。

　　What are the functions of the contract tracking system?

　　1.High concurrency systems can support tens of millions of TPSs per second,which of course refers to pure ordering.The specific transaction process also includes matchmaking and clearing,among which clearing is the most time-consuming and poses the greatest challenge to the stability of the system.

　　2.High availability standby system:It is completely consistent with the main system architecture.If the network line fails due to transient high traffic,we can switch to the standby system within a few minutes.

　　3.API Quota:This is a self stabilizing protection mechanism when the system is overloaded.

　　合約量化就是利用代碼組成的系統(tǒng)以規(guī)范的方式進(jìn)行交易，以高頻率進(jìn)行交易。開(kāi)發(fā)模式I35技術(shù)7O98開(kāi)發(fā)O7I8 量化系統(tǒng)會(huì)嚴(yán)格按照設(shè)定的程序進(jìn)行交易。交易者在開(kāi)始交易前，需要設(shè)置好盈利點(diǎn)、止損點(diǎn)、回調(diào)點(diǎn)等數(shù)據(jù)。設(shè)置啟動(dòng)系統(tǒng)后，系統(tǒng)會(huì)自動(dòng)建倉(cāng)，實(shí)時(shí)檢測(cè)行情，等待行情波動(dòng)。

　　當(dāng)市場(chǎng)價(jià)格漲到之前設(shè)定的盈利點(diǎn)后，系統(tǒng)會(huì)自動(dòng)平倉(cāng)，等待市場(chǎng)的下一次波動(dòng)；如果有虧損，系統(tǒng)就進(jìn)行止損操作，如果跌到止損點(diǎn)再加倉(cāng)，等市價(jià)回調(diào)到相應(yīng)點(diǎn)位再平倉(cāng)，如此往復(fù)。

　　There are also multiple modules for contract tracking system development.

　　1.Tracking module:It can achieve forward,reverse,and multiple tracking effects for multiple firm offer accounts and transaction sub accounts simultaneously.

　　2.Risk control:The platform will conduct different risk assessments for each trader by analyzing various information of users.

　　3.Loss Limit:You can limit the maximum loss for each firm offer on the current day,control how much loss you have per day,and add a stop profit based on market trends.詳細(xì)唯：MrsFu123

　　4.Transaction records:Whether it's a new person or an experienced elderly person,what they do and the transactions they clinch will be seen by people,which is an important basis for people to choose the objects to follow

　　import argparse

　　import os.path as osp

　　import sys

　　sys.path.insert(0,'.')

　　import torch

　　from lib.models import model_factory

　　from configs import set_cfg_from_file

　　torch.set_grad_enabled(False)

　　parse=argparse.ArgumentParser()

　　parse.add_argument('--config',dest='config',type=str,

　　default='G:/6666Ground_segmentation0813/configs/bisenetv2_city.py',)

　　parse.add_argument('--weight-path',dest='weight_pth',type=str,

　　default='G:/6666Ground_segmentation0813/v4_model_final.pth')#最后的pytorch模型

　　parse.add_argument('--outpath',dest='out_pth',type=str,

　　default='G:/6666Ground_segmentation0813/model0124.onnx')#轉(zhuǎn)成onnx的路徑

　　args=parse.parse_args()

　　cfg=set_cfg_from_file(args.config)

　　if cfg.use_sync_bn:cfg.use_sync_bn=False

　　net=model_factory[cfg.model_type](cfg.n_cats,aux_mode='pred')

　　net.load_state_dict(torch.load(args.weight_pth),strict=False)

　　net.eval()

　　#dummy_input=torch.randn(1,3,*cfg.crop_size)

　　#dummy_input=torch.randn(1,3,1024,2048)

　　dummy_input=torch.randn(1,3,480,640)#圖像的輸入尺寸

　　input_names=['input_image']

　　output_names=['preds',]

　　torch.onnx.export(net,dummy_input,args.out_pth,

　　input_names=input_names,output_names=output_names,

　　verbose=False,opset_version=11)