kaivalnp commented on PR #14178:
URL: https://github.com/apache/lucene/pull/14178#issuecomment-2835496582

   > One big part of the complexity of building these packages is the low-level 
optimizations based on which "bare metal" you are running on
   
   > but how do I know whichever I pick is optimized properly for my particular 
env?
   
   These artifacts are created by the scripts in [this 
folder](https://github.com/facebookresearch/faiss/tree/main/conda/faiss) which 
are separate based on CPU architecture (like OSX, Windows, Arm, Intel, etc. -- 
see [these files](https://anaconda.org/pytorch/faiss-cpu/files) for different 
artifacts in Conda)
   
   All builds enable standard [release 
flags](https://github.com/facebookresearch/faiss/blob/ea1cdf0fb28f31ab36ea95d8d65abfcc184d1b8f/conda/faiss/build-lib.sh#L20),
 and produce libraries with optimized instructions like AVX2, AVX512, etc. as 
well (in this PR we're not using the optimized libraries yet, but I've added a 
TODO -- it's a matter of picking the library with the highest optimization 
level available at runtime)
   
   > maybe we can help debug those builds to nudge things forwards!
   
   Would be great to have everything on `conda-forge`!
   
   As for the build issues there, looks like some of [these 
patches](https://github.com/conda-forge/faiss-split-feedstock/tree/main/recipe/patches)
 are outdated -- I could try to modify those for the latest version but I'm not 
sure if some of those aren't required / some others are missing (not super 
familiar with build intricacies of Faiss / `conda-forge`)
   
   Taking a step back, I wonder if having everything on `conda-forge` is 
good-to-have, but the libraries on `pytorch` are still usable in the short term?


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