v0.3.0 — GPU acceleration + Windows launch fix

GPU acceleration, and a fix for a Windows crash that stopped the app launching at all.

Windows launch crash — fixed

If you double-clicked nam-a2a1-converter.exe and it flashed and disappeared, that was a real bug, not your machine.

The windowed build starts with no stdout, and the web server died while configuring its logger — before it could open a port. Launching through PowerShell with | Out-Host worked around it by handing the process a real output pipe.

This release fixes the cause. No wrapper script or .bat needed. Thanks to the person who reported it on reddit.

GPU acceleration

Training is much faster on a GPU. What you need depends on your machine:

Machine	What to do
Apple silicon (M1/M2/M3/M4)	Nothing. The macOS build already trains on the GPU via Metal (MPS), and always has. No extra download, no setting, no opt-in.
Windows + NVIDIA	Grab the CUDA build below.
Intel Mac, AMD / Intel GPUs	CPU only — no GPU path today.

You don't have to work out which row you're in. The standard build now checks on launch: if it finds an NVIDIA card it can't use, it shows a banner linking to the CUDA build. No banner means you're already as fast as this tool gets.

Downloads

Platform	File
macOS (signed + notarized)	nam-a2a1-converter-macos.dmg
Windows	nam-a2a1-converter-windows.zip
Windows + NVIDIA	nam-a2a1-converter-windows-cuda.zip.001 and .002 — see below
Linux x86_64	nam-a2a1-converter-linux-x86_64.tar.gz

Getting the CUDA build

It's ~2.6 GiB, and GitHub caps a single release file at 2 GiB, so it ships as two parts you rejoin.

Easiest — download get-cuda-build.ps1 and run:

powershell -ExecutionPolicy Bypass -File get-cuda-build.ps1

It fetches both parts, verifies them against the published SHA256, rejoins them and unpacks the app. (-ExecutionPolicy Bypass is needed because the script is unsigned; it only ever downloads from this repo's releases.)

By hand — the parts are a plain byte split, so copy /b rebuilds the zip with no extra software:

copy /b nam-a2a1-converter-windows-cuda.zip.001 + nam-a2a1-converter-windows-cuda.zip.002 nam-a2a1-converter-windows-cuda.zip

Then unzip as usual. nam-a2a1-converter-windows-cuda.zip.sha256 lists the expected hash for the assembled zip and for each part — check against it if a convert later fails oddly, since a truncated part is the usual cause.

Requires an NVIDIA card of compute capability 5.0+ (GTX 900-series / 2014 or newer) with a current driver. CUDA itself is inside the bundle; there's nothing else to install.

Notes

• Windows and macOS are both unsigned/notarized as before: macOS opens clean, Windows SmartScreen still warns — More info → Run anyway.
• macOS is tested end-to-end, and Windows has now had a real conversion run on it by a user. Linux compiles and passes automated checks in CI but is still untested on real hardware — please open an issue if something breaks.