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build(windows): don't bundle CUDA torch in the NVIDIA package (revert #318) #320

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Merged
thcp merged 1 commit into from
Jul 18, 2026
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build(windows): don't bundle CUDA torch in the NVIDIA package (revert #318) #320

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21 changes: 8 additions & 13 deletions scripts/windows/make-portable.ps1
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Original file line number Diff line number Diff line change
Expand Up @@ -202,25 +202,20 @@ if ($PackageVersion) {
& $PythonExe -m pip install "$Root"

if ($CpuOnly) {
# Force the CPU wheel explicitly. On Windows the default PyPI torch wheel is
# Force the slim CPU-only wheel. On Windows the default PyPI torch wheel is
# already CPU-only, but this also downgrades a build host that resolved a CUDA
# wheel (e.g. via a cu124 index in the runner's pip config), so the CPU package
# wheel (e.g. via a cuXXX index in the runner's pip config), so the CPU package
# is deterministic regardless of the host.
& $PythonExe -m pip install torch==2.6.0+cpu torchaudio==2.6.0+cpu `
--index-url https://download.pytorch.org/whl/cpu `
--force-reinstall --no-deps
} else {
# Force the CUDA wheel explicitly. Unlike Linux (whose default PyPI torch wheel
# bundles CUDA), the Windows PyPI torch wheel is CPU-only, so `pip install`
# above yields a CPU torch. Without this step the "NVIDIA" package's GPU support
# would depend on the build host happening to resolve a CUDA wheel -- silently
# regressing to CPU if that host's pip config ever changes. The Windows CUDA
# wheel is self-contained (bundles the CUDA DLLs; no separate nvidia-* deps like
# Linux), so --no-deps is correct here. (#316)
& $PythonExe -m pip install torch==2.6.0+cu124 torchaudio==2.6.0+cu124 `
--index-url https://download.pytorch.org/whl/cu124 `
--force-reinstall --no-deps
}
# Do NOT bundle CUDA torch into the NVIDIA (non-CpuOnly) package. It ships base
# torch and the desktop app installs the CUDA build on first run via
# ensure_torch_device, which picks the cuXXX index matching the detected GPU's
# compute capability / driver. Bundling the CUDA wheel here (~2.5 GB installed)
# pushes the zip past GitHub's 2 GiB release-asset cap and loses that adaptive
# versioning. (Reverts #318; the real GPU-detection fix is #317.)

& $PythonExe -c "import fastapi, uvicorn, yt_dlp, demucs, torch, torchaudio, librosa, pyloudnorm, soundfile"

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