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mrobakowski avatar mrobakowski commented on September 3, 2024 2

I had the same thing happen. For now, I just worked around this by running

NIXPKGS_ALLOW_UNFREE=1 nix-shell

instead of just nix-shell.

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tbenst avatar tbenst commented on September 3, 2024

I think https://github.com/tweag/jupyterWith/blob/b12e8296a736725690ba73831cc987ce1c016275/default.nix#L2 is the culprit--not sure this is needed...or at least should default to ~/.config/nixpkgs/config.nix. I understand why ignoring overlays unless user opts in may be a good thing for reproducibility / cachix, but don't see the same benefit for config.nix

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guaraqe avatar guaraqe commented on September 3, 2024

The Nixpkgs used by JupyterWith is overrided, and pinned by the commit used in the repo. Since the configuration is defined for each Nixpkgs, it has to be set up manually. The nixpkgs/config.nix file is some magic that only works with the main channel.

For the unfree problem, you can set: { config = { allowUnfree = true; }; } so that MKL builds without using environment variables.

For the problem of having MKL in the dependency graph, did you manage to track which dependency brings with JupyterWith?

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alexvorobiev avatar alexvorobiev commented on September 3, 2024

@tbenst This could be off-topic but we configured numpy with MKL in an overlay and so far haven't had any complaints about scikit-learn. Could you please share what is broken?

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djacu avatar djacu commented on September 3, 2024

Closing out old issues with no activity in preparation for migration to the next branch.

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