Publish CUDA wheels so a GPU user does not build from source - #21569
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shoumikhin wants to merge 16 commits into
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Publish CUDA wheels so a GPU user does not build from source#21569shoumikhin wants to merge 16 commits into
shoumikhin wants to merge 16 commits into
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🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/21569
Note: Links to docs will display an error until the docs builds have been completed. ❌ 16 New Failures, 340 Pending, 40 Unrelated Failures, 31 Unclassified FailuresAs of commit fc8b4e3 with merge base ad3a71f ( NEW FAILURES - The following jobs have failed:
UNCLASSIFIED FAILURES - DrCI could not classify the following jobs because the workflow did not run on the merge base. The failures may be pre-existing on trunk or introduced by this PR:
FLAKY - The following jobs failed but were likely due to flakiness present on trunk:
BROKEN TRUNK - The following jobs failed but were present on the merge base:👉 Rebase onto the `viable/strict` branch to avoid these failures
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This was referenced Aug 4, 2026
This was referenced Aug 4, 2026
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Right now
pip install executorchalways gives you a CPU-only wheel.The CUDA delegate is built and tested from source, but no published wheel contains it, so anyone
who wants GPU support has to clone the repository and build.
This turns on the GPU wheel rows so a plain install can bring the delegate with it:
Two things make those wheels correct rather than merely present
The GPU generations to compile for. Without being told, the build compiles device code only
for the GPU in the build machine. The wheel then installs fine on every machine the row claims
and fails when a model actually runs on a different generation, which looks like a model bug
rather than a packaging one. Each row now names its architectures explicitly:
The CUDA libraries the wheel needs. The delegate links the CUDA runtime but does not bundle
it, so the wheel now declares those libraries as dependencies and one install brings what it
needs. The build variant is read from the release environment rather than guessed from whether a
CUDA compiler happens to be installed, because a CPU wheel built on a machine that has one must
not declare them.
Tested
Built a GPU wheel for each supported CUDA version on Linux x86_64 and on two Jetson devices,
then confirmed the built wheel carries device code for every architecture its row claims and
declares the matching CUDA packages. A CPU wheel is unchanged: no architectures named, no CUDA
dependencies declared.