Disable mlflow autologging in a helper notebook

[invalidargument]

We have a helper function that uses a sklearn estimator. We don't want to to be logged to mlflow.

I can do

def myfunc():
    import mlflow
    with mlflow.autolog.ignore:
        # train model
        # use model
    return predictions
But 

I get info prints:
2024/11/29 08:33:05 INFO mlflow.tracking.fluent: Autologging successfully enabled for statsmodels.
2024/11/29 08:33:06 INFO mlflow.tracking.fluent: Autologging successfully enabled for sklearn.
2. I will change the state of autologging to True, even if the user had it to autologging = False before calling myfunc()

How can I solve this? Can I get state of autologging somehow so I can set it back? How to supress info prints?

It would be nice if something like this would be supported, but I cant find anything
def myfunc():
    import mlflow
    with mlflow.autolog.ignore:
        # train model
        # use model
    return predictions

[MuthuLakshmi]

@invalidargument 
Please refer to the below doc. 
https://docs.databricks.com/en/mlflow/databricks-autologging.html#disable-databricks-autologging

[invalidargument]

mlflow.autolog(disable=True, silent=True) fixes the printing. But my other problem with setting autologging back to previous state is still unsolved. I can't find any information about that problem in the docs.