Experiment tracking with sacred and mlflow
Project description
Observe your sacred experiments with mlflow.
Writing experiments with sacred is great.
mlflow provides a nice UI that can be used to get a quick overview of your runs and analyze the results.
Usage
In your code, add the observer:
from sacred import Experiment
from mlflow_observer import MlflowObserver
from _paths import MY_TRACKING_URI
ex = Experiment('MyExperiment')
ex.observers.append(MlflowObserver(MY_TRACKING_URI))
In the commandline, you can pass a run name through sacred’s comment flag:
python train.py -c "My sacred run"
Otherwise the run name will be of the form run_[datetime].
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