2 Commits

Include renames

Author	SHA1	Message	Date
dtourolleandClaude Opus 5	39a22875b1	Add the MIGraphX rung for AMD GPUs ... Measured on a Radeon RX 7900 XT against Arch's onnxruntime-rocm 1.29 (docs/inference.md §1.3): MIGraphX fp16 runs the detectors at 2.4–3.4 ms against 10–58 ms on the CPU provider, the inpainter at 8 ms against 514, with a 15–135 s compile per graph the first time and under a second from its cache after. A compiling rung on TensorRT's terms, wired the same way. The ROCm execution provider is gone (removed in ONNX Runtime 1.23), so the AMD ladder is MIGraphX then the CPU, with no non-compiling rung between. MIGraphX is registered through the runtime's generic key/value entry point rather than ort's builder: 1.29 reads the legacy options struct for its precision flags only, and the compiled-program cache directory (`migraphx_model_cache_dir`) only travels the generic way. The provider's cache key omits the precision, so f32 and fp16 programs get their own directories. The probe fingerprint now includes the provider libraries beside the runtime and the ROCm version, since a distribution's CPU and ROCm builds are the same file at the same path. `status().failed` reports only the rungs above the selection, so an AMD desktop's About line says why MIGraphX won rather than that the NVIDIA providers are not in the build. Two examples: `ep_probe` times each provider cold and from cache, and `ladder` drives `init` as the app does to watch the first-run sequence. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>	2026-09-20 19:23:00 +02:00
dtourolle	ecb648818b	Search the user's own runtime directory before the system library ... The reference desktop's only system ONNX Runtime is Arch's onnxruntime-opt-cuda: 1.29, built without TensorRT and against cuDNN 8 on a cuDNN 9 machine. The probe rejects both providers correctly and the app runs on the CPU provider, which is right and not what anyone wants. runtime/ beside the models is now searched ahead of /usr/lib, tools/fetch-desktop-runtime.sh fills it with the four libraries from the current onnxruntime-gpu wheel (cuDNN 9, TensorRT 10), and the About caption lists every rung that lost and why, not only the first. Verified: the app selects TensorRT from that directory with no environment variable set.	2026-09-19 21:15:55 +02:00