Comments (5)
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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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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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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@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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Closing out old issues with no activity in preparation for migration to the next
branch.
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