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build tensorflow on the cirun GPU machine #1238

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@njzjz njzjz commented Dec 18, 2024

Guidelines for marking packages as broken:

  • We prefer to patch the repo data (see here)
    instead of marking packages as broken. This alternative workflow makes environments more reproducible.
  • Packages with requirements/metadata that are too strict but otherwise work are
    not technically broken and should not be marked as such.
  • Packages with missing metadata can be marked as broken on a temporary basis
    but should be patched in the repo data and be marked unbroken later.
  • In some cases where the number of users of a package is small or it is used by
    the maintainers only, we can allow packages to be marked broken more liberally.
  • We (conda-forge/core) try to make a decision on these requests within 24 hours.

What will happen when a package is marked broken?

  • Our bots will add the broken label to the package. The main label will remain on the package and this is normal.
  • Our bots will rebuild our repodata patches to remove this package from the repodata.
  • In a few hours after the anaconda.org CDN picks up the new patches, you will no longer be able to install the package from the main channel.

Checklist:

  • I want to mark a package as broken (or not broken):

    • Added a description of the problem with the package in the PR description.
    • Pinged the team for the package for their input.
  • I want to archive a feedstock:

    • Pinged the team for that feedstock for their input.
    • Make sure you have opened an issue on the feedstock explaining why it was archived.
    • Linked that issue in this PR description.
    • Added links to any other relevant issues/PRs in the PR description.
  • I want to request (or revoke) access to an opt-in CI resource:

    • Pinged the relevant feedstock team(s)
    • Added a small description explaining why access is needed
  • I want to copy an artifact following CFEP-3:

    • Pinged the relevant feedstock team(s)
    • Added a reference to the original PR
    • Posted a link to the conda artifacts
    • Posted a link to the build logs
  • I want to add a package output to a feedstock:

    • Pinged the relevant feedstock team(s)
    • Added a small description of why the output is being added.

See conda-forge/tensorflow-feedstock#408 (comment). TensorFlow starts to link libcuda.so.1 which can be accessible on a GPU machine and inside its docker. This is a runtime requirement. I've validated locally and confirmed this can pass the GPU builds. I think this is the easiest way.

I am not sure whether the memory on cirun-openstack-gpu-xlarge is enough so I also request cirun-openstack-gpu-2xlarge.

cc @conda-orge/tensorflow

@jaimergp
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Replied in the linked PR.

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