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chore(ml): downgrade to cuda 12.2 (#12587) 

* downgrade to cuda 12.2

* update docs
pull/12589/head
Mert 2024-09-11 20:25:57 +07:00 committed by GitHub
parent 01c7adc24d
commit ad58d7e23e
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2 changed files with 7 additions and 2 deletions
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docs/docs/features/ml-hardware-acceleration.md
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@ -38,7 +38,7 @@ You do not need to redo any machine learning jobs after enabling hardware accele
- The GPU must have compute capability 5.2 or greater.
- The server must have the official NVIDIA driver installed.
- The installed driver must be >= 545 (it must support CUDA 12.3.2).
- The installed driver must be >= 535 (it must support CUDA 12.2).
- On Linux (except for WSL2), you also need to have [NVIDIA Container Toolkit][nvct] installed.
#### OpenVINO

7
machine-learning/Dockerfile
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@ -49,7 +49,12 @@ RUN apt-get update && \
apt-get remove wget -yqq && \
rm -rf /var/lib/apt/lists/*
FROM nvidia/cuda:12.3.2-cudnn9-runtime-ubuntu22.04@sha256:fa44193567d1908f7ca1f3abf8623ce9c63bc8cba7bcfdb32702eb04d326f7a8 AS prod-cuda
FROM nvidia/cuda:12.2.2-runtime-ubuntu22.04@sha256:94c1577b2cd9dd6c0312dc04dff9cb2fdce2b268018abc3d7c2dbcacf1155000 AS prod-cuda
RUN apt-get update && \
apt-get install --no-install-recommends -yqq libcudnn9-cuda-12 && \
apt-get clean && \
rm -rf /var/lib/apt/lists/*
COPY --from=builder-cuda /usr/local/bin/python3 /usr/local/bin/python3
COPY --from=builder-cuda /usr/local/lib/python3.11 /usr/local/lib/python3.11