Publish CUDA wheels so a GPU user does not build from source - #21570
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shoumikhin wants to merge 1 commit into
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Publish CUDA wheels so a GPU user does not build from source#21570shoumikhin wants to merge 1 commit into
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🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/21570
Note: Links to docs will display an error until the docs builds have been completed. ❗ 1 Active SEVsThere are 1 currently active SEVs. If your PR is affected, please view them below: This comment was automatically generated by Dr. CI and updates every 15 minutes. |
This was referenced Aug 4, 2026
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Superseded by #21569, which carries this change. A missing |
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Today
pip install executorchonly ever gives a CPU wheel. The CUDA delegate isbuilt and tested from source in CI, but no published wheel contains it, so anyone
who wants GPU support has to clone the repository and build.
Turn on the accelerator rows in the two Linux wheel workflows. The shared matrix
generator then emits one cell per supported CUDA train, each with its own local
version label, so the CPU and accelerator artifacts stay distinguishable. A plain
install still resolves the CPU wheel from the default index:
Two things are needed to make those artifacts correct rather than merely present.
First, device code. CMake otherwise compiles for whichever GPU the build machine
has, so a wheel built on one generation installs everywhere the row claims and
then fails when a model runs on a different GPU. Each row now names its
architectures explicitly, chosen for the hardware that row supports.
Second, the CUDA runtime. The delegate links it but does not bundle it, so the
wheel now declares those libraries as dependencies. The build variant is read
from the wheel build environment rather than detected from an installed compiler,
because a CPU wheel built on a machine that happens to have a CUDA toolkit must
not declare them.