Re: alphafold Debian packaging ?
Even more complicated is the underlying software dependency tree.
alphafold depends on dm-haiku, jax, tensorflow.
dm-haiku depends on jax.
jax depends on XLA from tensorflow.
tensorflow still in NEW.
Long way to go. Mhhh.
What's also complicated is the GPU support. Currently the only
working modern deep learning framework in our archive is pytorch,
which is only compiled with cpu support.
pytorch-cuda requires cudnn. I gave up cudnn packaging a few
times and I eventually realized that I dislike working on
nvidia stuff even if I have to use it.
pytorch-rocm is a good way to go. As you can see on debian-ai@
people are still working hard to get ROCm into debian.
Intel GPU support is too new to evaluate.
On Wed, 2022-01-12 at 16:54 +0100, Gard Spreemann wrote:
> Andrius Merkys <firstname.lastname@example.org> writes:
> > On 2022-01-12 17:34, Gard Spreemann wrote:
> > > And their code repository is Apache. Or did you find the actual
> > > pretrained models somewhere under CC-BY-NC?
> > Interesting. Maybe I am looking at some other source. Am I right to
> > assume we are talking about ? If so, it says that the parameters
> > are
> > CC-BY-NC here: .
> >  https://github.com/deepmind/alphafold
> >  https://github.com/deepmind/alphafold#model-parameters
> Interesting indeed! So we have:
> – Training data: A plethora of different licenses.
> – Code: Apache
> – Trained model: CC-BY-NC-4.0
> – Output of said trained model: CC-BY-4.0 
>  See under "license and attributions" on https://alphafold.com
> -- Gard