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02-10-2023 09:48 AM
I am running some code to smooth columns of data and fill in missing values. The algorithms being used are automatically logged to an experiment using MLFlow which makes a 15 second job take 9 minutes and causes out of memory errors in another instance. I have not even imported the MLFlow package in the notebook. How do I avoid logging results?
- Labels:
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Experiments
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LogRuns
-
Using MLflow
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02-10-2023 12:06 PM
I think I figured it out. Autologing must have been enabled from a previous run. Pretty easy to solve. Posting this to help anyone else in this situation.
https://mlflow.org/docs/latest/tracking.html#automatic-logging
To disable just run the appropriate command for the library being logged as per below.
import mlflow
mlflow.sklearn.autolog(disable=True)
mlflow.xgboost.autolog(disable=True)
mlflow.statsmodels.autolog(disable=True)
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02-10-2023 12:06 PM
I think I figured it out. Autologing must have been enabled from a previous run. Pretty easy to solve. Posting this to help anyone else in this situation.
https://mlflow.org/docs/latest/tracking.html#automatic-logging
To disable just run the appropriate command for the library being logged as per below.
import mlflow
mlflow.sklearn.autolog(disable=True)
mlflow.xgboost.autolog(disable=True)
mlflow.statsmodels.autolog(disable=True)
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06-28-2023 07:32 AM
You can even us a general command without noting which library will be used:

