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use joblib for multiprocessing #1

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remiadon opened this issue Mar 26, 2019 · 0 comments · Fixed by #2
Closed

use joblib for multiprocessing #1

remiadon opened this issue Mar 26, 2019 · 0 comments · Fixed by #2

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@remiadon
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remiadon commented Mar 26, 2019 •
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The current TransformerScheduler class uses a multiprocess version of pandas apply, imported from melusine.utils.multiprocessing

Actually scikit-learn already provides a high level interface for multiprocess/multithread processing over numpy/pandas, accessible from the external namespace

from sklearn.externals import joblib

using joblib would reduce the code base and improve compatibility with the sklearn ecosystem
@remiadon remiadon mentioned this issue Apr 2, 2019
Merged
@FDJFDJ FDJFDJ closed this as completed in #2 Apr 4, 2019
hugo-quantmetry added a commit that referenced this issue Jul 24, 2019
@hugo-quantmetry
Merge pull request #1 from MAIF/master
4a6c073 
Update Fork Hugo to the most recent Melusine version
hugo-quantmetry pushed a commit that referenced this issue Aug 28, 2019
@milidris
Merge pull request #1 from MAIF/master
537736c 
Update to current image before pull requesting changes
hugo-quantmetry pushed a commit that referenced this issue Sep 23, 2019
Merge pull request #1 from BenoitLebreton/regex
9a38adb 
Regex
FDJFDJ pushed a commit that referenced this issue Oct 14, 2019
@farthur
Merge pull request #1 from MAIF/master
e6b6768 
Maj fork farthur
TFA-MAIF pushed a commit that referenced this issue Oct 30, 2020
@victorBigand
Merge pull request #1 from MAIF/master
27bdaa1 
Update forked repo
TFA-MAIF added a commit that referenced this issue Jun 28, 2022
@TFA-MAIF
Merge pull request #1 from TFA-MAIF/feature/contributing
9a5db62 
Upgrade version
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joblib as backend to apply_by_multiprocessing
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@remiadon