Comments (7)
ahmadia
commented on May 24, 2024
changes needed in Elemental are raised as an issue here: elemental/Elemental#149
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ahmadia
commented on May 24, 2024
make -j 4 seems to be safe.
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ahmadia
commented on May 24, 2024
This is a C1 proxy problem.
qmj240@f45c899d5ff9 ~/Elemental/build master $ cd source/
qmj240@f45c899d5ff9 ~/Elemental/build/source master $ git clone https://github.com/scibuilder/parmetis.git
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ahmadia
commented on May 24, 2024
Also much needed:
-D CMAKE_INSTALL_PREFIX="~/anaconda3/envs/elemental"
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ahmadia
commented on May 24, 2024
Still to do, get a proper conda build recipe for elemental so that we can just build this correctly once and never again. Currently stuck at Python 2 but shouldn't be hard to fix to Python 3 compatibility.
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jcrist
commented on May 24, 2024
The scope of this project has been reduced to just model parallelism (e.g. grid-search) over small-medium data. It'd still be nice to get this working ,but I'm closing for now, as this is unrelated to this project.
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mrocklin
commented on May 24, 2024
@ahmadia if you still have an interest in this I've been building a variety of dask-other projects recently where other is a distributed system. I'd be happy to collaborate here if handing off data between systems is still of value to you all and you have someone on the elemental side that is interested in taking this on.
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Related Issues (20)
- Efficiency for GridSearchCV on large graphs HOT 46
- re Custom Sklearn Transforms with Dask Apply inside HOT 4
- Asynchronous algorithms and "Good enough" RandomSearchCV HOT 7
- Memory Error when number of worker increase in daskgridsearch HOT 13
- pip installable HOT 4
- Works with stock Pipeline now? HOT 4
- Maybe add verbose parameter to "RandomizedSearchCV" ? HOT 9
- Wish: support multiple metric scoring as in scikit-learn 0.19
- Compatibility with scikit-learn 0.19 HOT 6
- TypeError: can't pickle NotImplementedType objects on sklearn.metrics.make_scorer and FeatureUnion HOT 8
- Failure on model pipeline that succeeds using stock scikit-learn HOT 7
- bayesian optimization for hyperparameter tuning HOT 1
- COMPAT: /Users/taugspurger/Envs/dask-dev/lib/python3.6/site-packages/scikit-learn/sklearn/base.py:114: DeprecationWarning: Estimator Pipeline modifies parameters in __init__. HOT 1
- AttributeError: 'unicode' object has no attribute 'version' - LooseVersion with Py 2.7 HOT 6
- Incompatibility With Keras Scikit-Learn Wrapper HOT 6
- Multi-threading or -processing doesn't work for simple sklearn Pipeline HOT 12
- Fold dask-searchcv into Dask-ML HOT 11
- BaseSearchCV throws IndexError for particular sized optional arguments to BaseSearchCV.fit HOT 2
- Implement partial_fit support in DaskBaseSearchCV HOT 2
- dask-searchcv incompatible with Dask v0.18 HOT 7
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