Standardize use of n_jobs and reporting of computation time #1038
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tests/test_extensions/test_sklearn_extension/test_sklearn_extension.py
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Hey, I think the example is really getting along well. Based on the current status I'm wondering three things:
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Do you mean their interaction and behaviour? It would be useful I guess, but the only concern or question is what (exactly) to summarize I guess.
Though we could, from the OpenML API standpoint, we can also ignore it. If the duty of parallelization is delegated to scikit-learn or OpenML (as we show in the example), I feel it is likely that the user may not set the backend with a On second thought, this might necessitate the mention of how the backends change in the entire stack of function calls going through OpenML to scikit-learn pipelines. This is obviously quite complicated.
In the latest SGDClassifier documentation, the parallelization happens through |
I think the main caveats to pay attention to, like the gist of #895
Probably I mixed up something. But an example on how this can be changed might be a good idea!
Yes, but that's for fitting multiple classifiers for a "one vs all" scheme. I was more thinking about something like the neural network where the number of used cores can't be set via the API. |
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| # Summmary | ||
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| # OpenML records model runtimes for the CPU-clock and the wall-clock times. The above |
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Hm, should we explicitly say "the scikit-learn extension"? Everything we're writing here is exclusive about the scikit-learn extension, so it could be confusing otherwise.
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I still can't annotate all my comments... anyway, linear SVM also releases the GIL: https://github.com/scikit-learn/scikit-learn/blob/main/sklearn/svm/_liblinear.pyx#L61 Maybe naive bayes doesn't release the GIL? |
* Minor reshuffling * Update examples/30_extended/fetch_runtimes_tutorial.py Co-authored-by: Neeratyoy Mallik <neeratyoy@gmail.com> Co-authored-by: Neeratyoy Mallik <neeratyoy@gmail.com>
) * Unit test to test existence of refit time * Measuring runtime always * Removing redundant check in unit test * Updating docs with runtimes * Adding more utilities to new example * Removing refit_time + fetching trace runtime in example * rename example * Reiterating with changes to example from @mfeurer suggestions * Including refit time and other minor formatting * Adding more cases + a concluding summary * Cosmetic changes * Adding 5th case with no release of GIL * Removing debug code * Runtime measurement example updates (openml#1052) * Minor reshuffling * Update examples/30_extended/fetch_runtimes_tutorial.py Co-authored-by: Neeratyoy Mallik <neeratyoy@gmail.com> Co-authored-by: Neeratyoy Mallik <neeratyoy@gmail.com> Co-authored-by: Matthias Feurer <feurerm@informatik.uni-freiburg.de>
Reference Issue
Addresses #895.