Enable linux ppc64le

[jeongseok-meta]

Checklist

• Used a personal fork of the feedstock to propose changes
• Bumped the build number (if the version is unchanged)
• Reset the build number to 0 (if the version changed)
• Re-rendered with the latest conda-smithy (Use the phrase @conda-forge-admin, please rerender in a comment in this PR for automated rerendering)
• Ensured the license file is being packaged.

[conda-forge-webservices]

Hi! This is the friendly automated conda-forge-linting service.

I wanted to let you know that I linted all conda-recipes in your PR (recipe/meta.yaml) and found some lint.

Here's what I've got...

For recipe/meta.yaml:

• The conda-forge.yml file is not allowed to have duplicate keys.

[conda-forge-webservices]

Hi! This is the friendly automated conda-forge-linting service.

I just wanted to let you know that I linted all conda-recipes in your PR (recipe/meta.yaml) and found it was in an excellent condition.

[jakirkham]

Thanks Jeongseok! 🙏

This looks like a good set of changes

For the remaining CI jobs, think you will need to accept the ToS, which is pretty similar to other CIs ToS. This amounts to making a PR like this one adding your username to the list like so: Quansight/open-gpu-server#37

Once that is done we can see how CI progresses

[jeongseok-meta]

Done! Quansight/open-gpu-server#39

[jakirkham]

Great, thank you! 🙏

Asked Jaime to take a look as he typically reviews those 🙂

Am wondering if it is worth grabbing this workaround for NumPy builds in PyTorch: #254 (comment)

The reason being we discovered ARM builds likely need that workaround. So think if that is true, it is probably also true for Power

What do you think?

Should add it is ok if you prefer to wait and see how CI goes first. We do now cover that in the test suite after having seen it before. So we will know either way if it is an issue

pytorch-cpu-feedstock/recipe/meta.yaml

Line 332 in 6dd85b3

- python -c "import torch; torch.tensor(1).to('cpu').numpy(); print('numpy support enabled!!!')"

[hmaarrfk]

I suggest adding back the early failure I am suggesting in:
292cd8e

you might be faster at debuging what is going on, but that early test might be more than adequate

[jakirkham]

Agree that sounds like a good plan. Thanks for putting it together Mark! 🙏

Commented over there 🙂

[jeongseok-meta]

@conda-forge-admin, please rerender

[jeongseok-meta]

@conda-forge-admin, please restart ci

[hmaarrfk]

please add:

skip: true  # [py!=310]

to the top level build section

if you are not ready yet to get the GPU enabled, please add an other line with:

skip: true   # [cuda_compiler_version!=None]

and rerender

[hmaarrfk]

@conda-forge-admin please rerender

[hmaarrfk]

sorry about that, lets just skip everything except for ppc64le for now and then re-optimize the builds.

[jeongseok-meta]

Sure, feel free to do anything that makes sense to you or take over this PR. Thank you for helping!

[hmaarrfk]

no i'm struggling with aarch64 already. i won't be able to take over, but this feedstock just hogs the CIs, then you end up building linux64 for 6 hours instead of running ppc64le which you want!

[hmaarrfk]

maybe try rerendering locally, rerendering with cuda is always slow...

[jeongseok-meta]

@conda-forge-admin please rerender

[hmaarrfk]

@conda-forge-admin please rerender

One more rerender. I am allowed to the GPU runners, but you can simply use azure until the 6 hour timeout is hit.

[hmaarrfk]

@conda-forge-admin please rerender

sigh... always one more thing to rerender

[hmaarrfk]

alright, you have the CIs now. happy tuning!

[hmaarrfk]

i'm also assuming that you have access to a powerful linux machine with docker.

To build locally

python build-locally.py

and it should walk you through things.

[hmaarrfk]

While the builds have started, I have a feeling you are hitting the same problems I am with aarch

See:
#256

Depending on what you are trying to prove at this stage (numpy detection vs others), you might want to pull in my patch that causes this to fail loudly.

[hmaarrfk]

Suggested change

	skip: true # [linux64]
	skip: true # [linux64]
	skip: true # [cuda_compiler_version != "None"]

While you are hitting failures in the CPU build, it would be nice to just cancel the cuda builds too ;)

[conda-forge-admin]

Hi! This is the friendly automated conda-forge-linting service.

I just wanted to let you know that I linted all conda-recipes in your PR (recipe/meta.yaml) and found it was in an excellent condition.

I do have some suggestions for making it better though...

For recipe/meta.yaml:

• ℹ️ The recipe is not parsable by parser conda-souschef (grayskull). Your recipe may not receive automatic updates and/or may not be compatible with conda-forge's infrastructure. Please check the logs for more information and ensure your recipe can be parsed.
• ℹ️ The recipe is not parsable by parser conda-recipe-manager. Your recipe may not receive automatic updates and/or may not be compatible with conda-forge's infrastructure. Please check the logs for more information and ensure your recipe can be parsed.

_{This message was generated by GitHub Actions workflow run https://github.com/conda-forge/conda-forge-webservices/actions/runs/12130811287. Examine the logs at this URL for more detail.}

[jakirkham]

Happy New Year! 🥳

Noticed some conflicts crept in due to recent merges

To fix conflicts, would recommend...

1. Check this PR branch locally
2. Attempt merge
3. Resolve conflicts on the directory recipe/ only (git mergetool recipe works well)
4. git rm -rf '.ci_support/linux_*' '.ci_support/osx_*' '.ci_support/win_*' .github/workflows
5. Re-render
6. Finish merge and push changes