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Python library for streamlined tracking and management of AI training processes.

Project description

TongSwan

安装

# 进入目录后:
pip install -U .

使用

初始化

import tongWnB

tongWnB.init(
    labHost="http://127.0.0.1:8081",  # tongswanLab 平台
    nodeIP="10.10.10.10",  # 当前节点ip地址,选填。如果不传,工具会自动获取当前节点ip
    gpus=[0],  # 训练用到的 gpu 编号
    company="公司名",  # tongswanLab 平台中公司的名字
    projectName="pythonTest",  # 项目名字
    experimentName="python_package_thirdpart",  # 实验名。如果实验不存在会自动创建该名字
    apiKey="xxx",  # 用户用到的swanKey。请到 tongswanLab 平台个人信息出查看 swanKey
    experimentConfig={"day": "0829", "climate": "rainning"}  # 自定义的配置信息

然后即可上传用户关心的训练指标

tongswan.log({"loss": 0.1, "acc": 0.9})
tongswan.log({"loss": 0.2, "acc": 0.8})
...

完整用例:

import tongWnB

tongWnB.init(
    labHost="http://127.0.0.1:8081",
    nodeIP="YOUR_NODE_IP",
    gpus=[0],
    company="YOUR_COMPANY",
    projectName="YOUR_PROJECT",
    experimentName="YOUR_EXPERIMENT",
    apiKey="YOUR_API_KEY",
    experimentConfig={"day": "0829", "climate": "rainning"}
)

for i in range(11):
    tongWnB.log({"loss": i, "acc": 10 - i})

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