Comments (9)
avx2 is a CPU instruction set. I have no idea what is the binary compatibility to the saved indices across different architectures. Ask the question in the official repository.
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Yep, I have this exact issue. I've deployed to AWS EKS but built the vectorstore on my mac locally and am getting errors. Would be great to get this fixed! @NikhilSehgal123 if you post this issue in the official repository, please post the link here, and i'll +1 and comment! 🙏
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Ya it would be great to fix this issue soon if possible!
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Hey guys @max-addison @jpzhangvincent, I know this issue is causing some pain for many people, so another simple workaround is to just upload your vectorstores to Pinecone or another cloud hosted vector DB to avoid this type of issue.
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I experienced this same issue when using LangChain.
here there is the following code:
Import faiss if available, otherwise raise error.
If FAISS_NO_AVX2 environment variable is set, it will be considered
to load FAISS with no AVX2 optimization.
When I explicitly did not set FAISS_NO_AVX2
this error subsides. Previously I was experiencing the same thing mentioned in this thread. The faiss index that I am working with today, was created on a windows machine and running successfully on a linux machine. So it seems like loading FAISS with AVX2 optimization resolved the issue for me. Not sure this is helpful to everybody, but hopefully it will help somebody 😄
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I was trying FAISS_NO_AVX2
but it does not work inside of docker container for some reason (getting TypeError: IndexFlatCodes.add() missing 1 required positional argument: 'x'
error). I opened issue: langchain-ai/langchain#8857 . Please let me know if you know why I am getting that error.
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@aiakubovich I actually ran into this as well. I am trying to recall what I had done... I know I had troubles with pathing and being able to find the index.faiss
in the faiss_index
folder. I do believe I had to recreate the Faiss_Index on the same type of machine I was trying to inference... for example, originally it was on Windows and trying to be ran on a linux machine, I had to recreate it on a linux machine to run it on the linux machine.
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@Alex-Wenner-FHR Thanks for your response. I thought that FAISS_NO_AVX2
is option that allows to use same embeddings for both Windows and Linux machines. Without this option I indeed have to rerun embeddings on different machines. With this option I unable to run embeddings in Linux container at all. No idea why.
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Same problem to run on linux but not on m2/m1 mac
langchain-ai/chat-langchain#61
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Related Issues (20)
- Segfault in macOS in the presence of other OpenMP dependent packages HOT 2
- faiss-cpu 1.7.4 not working with mkl 2023.1.0 HOT 1
- Running setup.py install for faiss-gpu did not run successfully HOT 2
- inconsistent name: expected 'faiss-gpu', but metadata has 'faiss-cpu' HOT 7
- Faiss-cpu requires numpy, but numpy not installed as a dependency of faiss-cpu
- ERROR: Could not build wheels for faiss-cpu, which is required to install pyproject.toml-based projects in FreeBSD HOT 6
- Support Selector for IDMap HOT 3
- ERROR: Could not build wheels for faiss-cpu, which is required to install pyproject.toml-based projects in linux Alpine HOT 6
- Release v1.7.4 on PyPI HOT 1
- Get a CUDA error when searching in a Faiss index having too small vectors HOT 1
- Release date for faiss-cpu that includes numpy dependency fix? HOT 2
- CPython 3.12 wheels HOT 7
- Cannot install faiss-gpu on Arch Linux HOT 2
- Faiss fails to install on MacOS M2 Macbook HOT 2
- AVX512 support HOT 2
- Refactor third-party dependencies
- Installing `faiss-cpu` via Poetry doesn't install dependencies HOT 2
- Not Installing HOT 7
- Not able to run gpu version on NVIDIA A100/A10 HOT 2
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