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Hi, We Are Trying To Understand When The Auto-Logging Parameters Configuration. From The

We are trying to understand when the auto-logging parameters configuration.
from the https://github.com/allegroai/clearml/blob/master/examples/frameworks/scikit-learn/sklearn_matplotlib_example.py - we can see that none of the parameters are logged.
e.g. we would like to log the ShuffleSplit parameters in addition to the https://github.com/allegroai/clearml/blob/master/examples/frameworks/scikit-learn/sklearn_matplotlib_example.py#L150
Is there any auto-logging for such parameters or should we manually use the https://clear.ml/docs/latest/docs/references/sdk/task/#connect_configuration to log the parameters?

Posted 2 years ago
Votes Newest

Answers 5

Hi, it does not log the internal sklearn configuration, that is correct.
I think the problem is finding a standard way to allow you both log and change it later from the UI. But I think you can still connect it directly as a configuration and that should work 🙂

Posted 2 years ago

Hi OutrageousSheep60 , I think the connect_configuration is your solution for this one (or connect)

Posted 2 years ago

Thx CostlyOstrich36 for your input -
So I guess that if we try to always work with https://clear.ml/docs/latest/docs/fundamentals/hyperparameters (even if there is only have 1 parameter), we will consistently log our parameters.
Do you have a suggested different workflow?

Posted 2 years ago

Not one known to me, also, it's a good practice to implement (Think of automation) 🙂

Posted 2 years ago

Great - Thx TimelyPenguin76 for your input

Posted 2 years ago
5 Answers
2 years ago
one year ago
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