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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