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Re: pytorch and CUDA



Hi,

On 2023-03-14 19:37, M. Zhou wrote:
On Tue, 2023-03-14 at 09:50 +0200, Andrius Merkys wrote:
On 2023-03-14 09:25, Andrius Merkys wrote:
dpkg-shlibdeps: error: no dependency information found for
/lib/x86_64-linux-gnu/libcudnn.so.8 (used by
debian/libtorch1.13/usr/lib/x86_64-linux-gnu/libtorch_python.so.1.13)
Hint: check if the library actually comes from a package.

Right, /lib/x86_64-linux-gnu/libcudnn.so.8 does not come from a package,
it is downloaded and installed without ownership by nvidia-cudnn.

I see that nvidia-cudnn runs the downloader in postinst. Why the
downloaded libraries are not transformed into a source package instead?
It would seem a bit more natural to me, even if the source package would
contain non-rebuilt binaries.

Note this is non-free blob. cudnn has a different EULA than CUDA toolkit or
anything alike. The cudnn is problematic enough to upload onto non-free.
I have already tried to upload the cudnn binaries with the
EULA and without doubt, the binaries are not even suitable for non-free.

And the cudnn binaries for the three architectures, amd64 ppc64el arm64
is a ~3 GB upload. Stripping debugging symbols is forbidden as per EULA.

Ah, I see, thanks for the explanation.

The current solution is the best for me.
Please try to read the cudnn EULA before trying to upload the binaries.

Surely I will not upload anything without consulting with you first. As this is tainted by non-free, absolute caution has to be taken when uploading, and I am not planning to do that in the foreseeable future. All I am interested right now is local Debian packages of CUDA-enabled pytorch.

At the moment I am working on packaging pytorch-geometric which is suitable for main (works with or without CUDA). However, I am seeing test failures which I suspect would not happen with CUDA-enabled pytorch.

Alternatively, dpkg-shlibdeps could be instructed to ignore nvidia-cudnn
libraries, I guess.

Anyway, the installation target is broken and needs a fix. I'll look into
my installer script for nvidia-cudnn, but I'm really unable to work on
the pytorch-cuda install now.

I see. Nevertheless, thanks a lot for your guidance up to this point.

Best,
Andrius


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