try to downgrade the sklearn version and rise a strange error #19699
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my currently scikit-learn version is 0.24.1 |
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Replies: 4 comments
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Sorry to ask but have you tried the suggestions in the error message above? If you have, please report the issues you found. In particular for export SKLEARN_NO_OPENMP=1
pip install scikit-learn==0.21.3 Also why do you need 0.21, and what arch are you building on? |
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I try your suggestion
before that there is a lot of red warning and error sorry for throw another error again and the reason I want to use 0.21.3 is because I want to run a project code called Plasclass |
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I think it is unlikely that this is a problem with scikit-learn. I feel this is more a general "how do I get out of weird issues when installing something with Python" question or maybe an installation question for https://github.com/Shamir-Lab/PlasClass (it that is the PlasClass package you are trying to use). As a general recommendation it is a very bad idea to mix I would first try to create a separate First approach: the "conda for environments + full pip" wayProbably preferable here because PassClass insists on very specific version of scikit-learn (also numpy and scipy) in its setup.py.
Alternative: the "conda for most packages + pip on top of it when you absolutely need it" way
Miscnot sure why from your logs, pip is trying to build from source rather than use a wheel, maybe someone else will have a better idea about this ... |
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Migrating this to a discussion, which it should probably have been in the first place ... |
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I think it is unlikely that this is a problem with scikit-learn. I feel this is more a general "how do I get out of weird issues when installing something with Python" question or maybe an installation question for https://github.com/Shamir-Lab/PlasClass (it that is the PlasClass package you are trying to use).
As a general recommendation it is a very bad idea to mix
conda
andpip
for the same package. This can happen without realising, e.g.conda install scikit-learn
+pip install PassClass
will replace a conda-installed scikit-learn with a pip-installed one and weird things can happen. This is because PassClass insists on very specific version of scikit-learn (also numpy and scipy) in its