Combined updates for 2.10.x

[mgorny]

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.

Combined updates for 2.10.x. So far with [ci skip] on top, we'll run it when the next RC or final is available.

[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• ℹ️ The magma output has been superseded by libmagma-devel.
• ℹ️ The recipe is not parsable by parser conda-souschef (grayskull). This parser is not currently used by conda-forge, but may be in the future. We are collecting information to see which recipes are compatible with grayskull.
• ℹ️ The recipe is not parsable by parser conda-recipe-manager. The recipe can only be automatically migrated to the new v1 format if it is parseable by conda-recipe-manager.

_{This message was generated by GitHub Actions workflow run https://github.com/conda-forge/conda-forge-webservices/actions/runs/21220733650. Examine the logs at this URL for more detail.}

[mgorny]

@h-vetinari, do we want to include CUDA 13 migration for when the final is released?

[h-vetinari]

@h-vetinari, do we want to include CUDA 13 migration for when the final is released?

As long as you use a development install of smithy (combined with the skip from #332, so that CPU builds run on non-GPU agents), that's OK for me. We also won't be able to test the GPU paths for CUDA 13, but I guess running the test suite on CUDA 12.x only is good enough.

[mgorny]

@h-vetinari, do we want to include CUDA 13 migration for when the final is released?

As long as you use a development install of smithy (combined with the skip from #332, so that CPU builds run on non-GPU agents), that's OK for me. We also won't be able to test the GPU paths for CUDA 13, but I guess running the test suite on CUDA 12.x only is good enough.

I suppose new conda-smithy will be released before the final version.

[mgorny]

The aarch64 build hit the "exec format error" problem again, and the mkl/CUDA x86-64 build seems to have hit some builder issue — the logs are cut short, and GitHub seemed to be confused over whether it actually failed or was still running.

[mgorny]

Uh, aarch64 keeps failing with that "Exec format error". I wonder how it is that it happens only in some runs.

And then mkl run timed out. FWICS the non-mkl build took over 19 hours anyway, so we probably need to consider increasing timeouts again.

[h-vetinari]

One test failure on osx-arm64; I can add a skip for that while merging (assuming the rest doesn't blow up)

=========================== short test summary info ============================
FAILED [0.3161s] test/test_nn.py::TestNNDeviceTypeMPS::test_LayerNorm_numeric_mps - AssertionError: Tensor-likes are not close!

Mismatched elements: 9437063 / 18874368 (50.0%)
Greatest absolute difference: 0.7128685712814331 at index (0, 8, 24, 54) (up to 1e-05 allowed)
Greatest relative difference: 0.7136273980140686 at index (0, 69, 57, 29) (up to 0 allowed)

To execute this test, run the following from the base repo dir:
    python test/test_nn.py TestNNDeviceTypeMPS.test_LayerNorm_numeric_mps

This message can be suppressed by setting PYTORCH_PRINT_REPRO_ON_FAILURE=0
= 1 failed, 8672 passed, 4907 skipped, 57 xfailed, 65984 warnings in 462.48s (0:07:42) =