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Mac M1/M2/M? support #13
Description
Hiya! Mac M1/M2/... are not compatible with CUDA, and so KeOps does not work. I keep getting
[KeOps] Warning : Cuda libraries were not detected on the system or could not be loaded ; using cpu only mode
[pyKeOps] Compiling pykeops cpp 25c52bb6f5 module ...
[KeOps] Warning : There were warnings or errors :
g++: error: unrecognized command-line option '-Xclang'
OK
when I run
points = mp.data.three_annulus(5000,5000)
grades = - KDE(bandwidth=.1, return_log=True).fit(points).score_samples(points)
in the function_delaunay_test.ipynb notebook.
Activity
DavidLapous commentedon Jul 5, 2024
Hey @yossibokorbleile, thanks for pointing that out;
First (unrelated) thing, I'm not really maintaining the notebooks in the tutorial folder anymore, as IIRC, they are all in the documentation in the docs/notebooks folder. I'm planning to remove this folder after checking that everything is in the doc.
For PyKeops on ARM + macOS, this is not linked with cuda and should work fine, but I opened an issue for a very similar problem (cf getkeops/keops#332) which was solved then, I hope what's in there helps you fix this.
Otherwise, feel free to open an issue there, I don't own a mac anymore, so it's hard for me to debug this.
You can also try to launch this with the
conda install cxx-compilerinstalled.In the meantime, the
KDEcan be completely replaced byThis will be slower and not pytorch-auto-differentiable, but should work fine otherwise.
yossibokorbleile commentedon Jul 5, 2024
Thanks!
Replacing KDE worked initially, until I tried
in
multipers_intro.ipynb.I will just continue with testing functionality, and ignore anything
KeOpsrelated.DavidLapous commentedon Jul 5, 2024
Yes, this specific pipeline doesn't really have a non-keops alternative, but you can replace
bandwidthsbymasses, which doesn't require keops, and should produce somehow similar pictures. This basically replaces a Gaussian Kernel Density Estimation (KDE) by the Distance To Measure (DTM), c.f., e.g., this tda paper.I also forgot to mention that the GitHub workflow tests this pipeline on a mac with an M1 chip, and works fine with pykeops, with the default apple clang compiler. Can you try using the default compiler instead of
gcc?