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alessandrofasse avatar alessandrofasse commented on September 16, 2024

I think upgrading is a good idea. There we a lot of changes. With respect to pytorch such a table does not exists right away. However, I checked on both websites.

If use the image

11.8.0-cudnn8-runtime-ubuntu22.04

we could install the most recent versions of tensorflow in version 2.14.0 and pytorch in version 2.1.0 (https://pytorch.org/get-started/locally/)

How does that sound?

from jupyter-machine-learning.

elisabettai avatar elisabettai commented on September 16, 2024

It sounds good @alessandrofasse, thanks. The biggest question a think is to figure out if users that have scripts running with the current versions will be able to use them as they are if we upgrade.

Once we answer that, we can decide if we go with a new patch service version or a minor/major one.

from jupyter-machine-learning.

alessandrofasse avatar alessandrofasse commented on September 16, 2024

But I think all our containers are version controlled? I.e. others can still use their scripts and if they update they need to fix the scripts

Yes. How it works for updating services in oSPARC is the following:

  • We update the patch version of the service -> Users can update their containers in one click and they should expect to be able to run their scripts as they were before.
  • We update minor/major version of the service -> Users cannot expect that their scripts will still work.

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