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Hi All,
I've installed CUDA v8 from the AUR for use with Tensorflow.
This version is one down from the latest release (CUDA v9).
To use Tensorflow, I also need cuDNN v6. (also one down from the latest release cuDNN v7)
There is a version 6 cuDNN in the AUR (thanks petronny) but it is built to be dependent on CUDA v9, the latest release, and not CUDA v8, the version I have to use with Tensorflow.
Can anyone advise? is it possible to override the versioning on install? Would that be the preferred method or should I have a go at repacking cuDNN v6 separately this time dependent on CUDA v8?
(I know cuDNN v6 works fine with both CUDA v8 and CUDA v9).
Simon
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As far as I can tell, cuDNN depends on cuda, not any versioned cuda. If it isn't working for you, you might want to leave a comment on the aur page asking the maintainer if there are options.
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[Community] repo has a tensorflow-cuda package that looks like it should work with latest cuda and cudnn , have you tried that ?
Disliking systemd intensely, but not satisfied with alternatives so focusing on taming systemd.
(A works at time B) && (time C > time B ) ≠ (A works at time C)
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Hey circleface/ Lone_Wolf,
Thanks for getting back.
circleface: agreed, I've left a message with them and we'll see what they think. Honestly, it actually boils down to copying three files from the cuDNN package to the right CUDA directories. I can do it manually but wanted to get it right.
Lone_Wolf: the issue is that I'm installing from within Anaconda - Tensorflow would have to be inside the right environment and CUDA is outside that in /opt.
I'll update when I hear back.
Thanks again.
Simon
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