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ai-hub

AI_HUB utils package

  • 0.5.3
  • PyPI
  • Socket score

Maintainers
1

AI_HUB

AI utils for developer. such as notice、send massage when model training is over.Bind WeChat Official Account(AI_HUB) 插入在代码里的小工具,可以在模型训练结束时通过公众号及时发送微信消息给自己,提高科研效率。 inferServer: server your ai model as a API and match the tianchi eval 简单的操作把你训练好的模型变为服务API,并且支持天池大赛的流评测。

INSTALL

pip install ai-hub

SAMPLE

NOTICE

from ai_hub import notice
#到AGIHub微信公众号获取个人openid如(oM8pVuBWl8Rw_vFz7rZNgeO4T8H8),需替换为自己的openid
nc = notice("oM8pVuBWl8Rw_vFz7rZNgeO4T8H8")
#借助AGIHub公众号发送消息给自己
nc.sendmsg("hi,AI_HUB.I am su")

inferServer

'''
依赖:pip install ai-hub #(version>=0.1.7) 
测试用例:
model为y=2*x
请求数据为json:{"img":3}
-----------
post请求:
curl localhost:8080/tccapi -X POST -d '{"img":3}'
返回结果 6
'''
from ai_hub import inferServer
import json

class myInfer(inferServer):
    def __init__(self, model):
       	super().__init__(model)
        print("init_myInfer")

    #数据前处理
    def pre_process(self, data):
        print("my_pre_process")
        #json process
        json_data = json.loads(data.decode('utf-8'))
        img = json_data.get("img")
        print("processed data: ", img)
        return img

    #数据后处理
    def post_process(self, data):
        print("post_process")
        processed_data = data
        return processed_data

    #模型预测:默认执行self.model(preprocess_data),一般不用重写
    #如需自定义,可覆盖重写
    #def pridect(self, data):
    #    ret = self.model(data)
    #    return ret

if __name__ == "__main__":
    mymodel = lambda x: x * 2
    my_infer = myInfer(mymodel)
    my_infer.run(debuge=True) #默认为("127.0.0.1", 80),可自定义端口,如用于天池大赛请默认即可,指定debuge=True可获得更多报错信息

TccProgressBar

from ai_hub import TccProgressBar
#定义progress,显示名为training,在竞赛平台TCC上显示该进度条(tccBar_show=false 不影响本地打印进度条)
progress = TccProgressBar(title="training", tccBar_show=True)
for j in progress(range(100)):
    time.sleep(0.1)

TccTensorboard

from ai_hub import Logger
#Logger用法与tensorboard的logger包一致
info= {
    'loss': loss.data[0],
    'accuracy': accuracy.data[0]
}
for tag, value in info.items():
    logger.scalar_summary(tag, value, step)

获取OPENID

1.扫描关注公众号AGIHub

avatar

2.发送“openid”给公众号 即可获得openid

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