记录完整运行配置
保存环境和配置，确保运行过程完全可复现
记录完整运行配置 是 CoddyKit 上的免费 MLOps Academy 课时。 这是第 4 节课，共 4 节。 你可以在下方免费阅读本课时的完整内容 — 然后在浏览器中使用内置代码编辑器和全天候 AI 导师进行实践。 这是 MLOps Academy 学习路径的一部分，你的进度在网页和 CoddyKit 应用中同步。 MLOps Academy 课程共包含 4 节课。
本课时的部分内容尚未翻译，以英文显示。
Pins Are Only Half the Story
You pinned packages and seeds, but a run also has knobs like learning rate and batch size. Capture the full run config too. 🗂️
Stop Hardcoding Values
Numbers buried inside code are invisible later. Pull every tunable knob into one config you can read at a glance.
A YAML Config File
A small config.yaml holds your hyperparameters in plain, readable text that lives right next to your code.
lr: 0.001
batch_size: 32
epochs: 10
seed: 42Load It in Python
Read the file once at startup with yaml.safe_load and pass the values into your training code.
import yaml
cfg = yaml.safe_load(open('config.yaml'))Capture the Code Version
Config is not enough if the code changed. Record the exact git commit so you know which code produced the run.
git rev-parse HEADCapture the Environment
Save a pip freeze snapshot with each run so you know precisely which library versions were installed.
pip freeze > run_env.txtSnapshot the Data Version
Same code on different data gives different models, so log the data version or hash that fed this run.
Log Config to MLflow
Tools like MLflow store your settings as searchable params, tying config straight to the run's metrics.
mlflow.log_params(cfg)Override From the CLI
Tools like Hydra let you tweak any config value from the command line without editing the file at all.
python train.py lr=0.01 epochs=20Bundle the Run Artifacts
Store the config, env, commit, and seed together as one run record. That bundle is what lets you rebuild a result.
The Reproducibility Test
The real test: hand your run record to a teammate and they get the same model. If not, something went uncaptured.
Quick Check
You saved your config and seed but a rerun still differs. What is most likely missing?
Recap
You now capture the full run config: hyperparameters, git commit, environment, data version, and seed, so any run rebuilds cleanly. 📦
常见问题解答
「记录完整运行配置」课时是免费的吗？
是的 — 「记录完整运行配置」的完整文本可在网页上免费阅读。要进行交互式练习（内置代码编辑器和全天候 AI 导师）并解锁 MLOps Academy 课程的其余内容，请升级到 CoddyKit PRO。 MLOps Academy 课程共包含 4 节课。
「记录完整运行配置」这节课中我会学到什么？
保存环境和配置，确保运行过程完全可复现 你通过在浏览器中直接运行的动手代码来练习 MLOps Academy，全天候 AI 导师会在你学习这节课的过程中回答你的问题。
学习 MLOps Academy 需要有经验吗？
无需任何先前经验。CoddyKit 上的 MLOps Academy 课程适合初学者到高级学习者，你可以从这里开始或从头开始，按照自己的节奏学习。 这是第 4 节课，共 4 节。
「记录完整运行配置」课时需要多长时间？
大多数 CoddyKit 课程大约需要 5–10 分钟。每节课都很精短且互动，所以你能稳步进步，并在网页和应用中从离开的地方继续。
我能在这节 MLOps Academy 课中编写并运行代码吗？
能。每节 MLOps Academy 课都包含内置代码编辑器，你可以在浏览器中直接编写并运行真实代码，并获得即时 AI 反馈 — 无需本地设置。