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Machine Learning
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Avoid Using MLFlow to log runs

Evan_MCK
Contributor

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?

1 ACCEPTED SOLUTION

Accepted Solutions

Evan_MCK
Contributor

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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2 REPLIES 2

Evan_MCK
Contributor

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)

Evan_MCK
Contributor

You can even us a general command without noting which library will be used:

import mlflow
mlflow.autolog(disable=True)

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