NVIDIA / NVIDIA/TransformerEngine
[Build] Restore CUDA 13 Linux aarch64 core wheels
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- Python
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Description
Describe the bug
transformer-engine-cu13 stopped publishing Linux aarch64 wheels after v2.16.0.
PyPI contains both platforms for v2.16.0:
transformer_engine_cu13-2.16.0-py3-none-manylinux_2_28_aarch64.whltransformer_engine_cu13-2.16.0-py3-none-manylinux_2_28_x86_64.whl
For v2.16.1 and v2.17.0, PyPI contains only the x86_64 wheel. This makes installation on GB200/aarch64 fall back to a resource-intensive native build.
Steps to reproduce
Inspect published files for:
- https://pypi.org/project/transformer-engine-cu13/2.16.0/#files
- https://pypi.org/project/transformer-engine-cu13/2.16.1/#files
- https://pypi.org/project/transformer-engine-cu13/2.17.0/#files
Or attempt an ARM64 binary-only download:
python -m pip download \
--only-binary=:all: \
--platform manylinux_2_28_aarch64 \
--python-version 3.12 \
--implementation cp \
--abi cp312 \
--no-deps \
transformer-engine-cu13==2.17.0
Expected behavior
Publish transformer_engine_cu13-<version>-py3-none-manylinux_2_28_aarch64.whl alongside the x86_64 core wheel for CUDA 13 releases.
ARM64 release automation also appears unhealthy:
- v2.16.1 ARM wheel job failed after exhausting runner disk space: https://github.com/NVIDIA/TransformerEngine/actions/runs/28210514784/job/83570631411
- v2.17 ARM wheel job failed before publishing an asset: https://github.com/NVIDIA/TransformerEngine/actions/runs/30397388710/job/90403758771
The v2.16.1 runner reported No space left on device while writing its diagnostic log. This may be separate from the core-wheel publishing path, but it shows the release currently lacks reliable ARM64 coverage.
Environment overview
- Platform: Linux aarch64
- Hardware: NVIDIA GB200
- Python: 3.12
- CUDA: 13.0
- Transformer Engine: 2.16.1 and 2.17.0
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start by inspecting the CUDA 13 release automation and the failed ARM wheel jobs linked in the issue; use the listed pip download command to reproduce the missing artifact. Trace why v2.16.1 and v2.17.0 ARM jobs did not publish, including the reported runner disk-space failure. Done means later CUDA 13 releases publish matching manylinux_2_28_aarch64 and x86_64 core wheels.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- github-actions, python
- Domain
- build-system, ci-cd, release
- Issue type
- Bug
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Quiet
- Clarity
- Mostly clear
- Newbie friendliness
- 48/100