[shimmyshimmer]

Qwen-Image-2.1's first VAE decode can spend over 13 minutes benchmarking MIOpen convolution solvers on Radeon 8060S, while the next decode takes about two seconds. Cache isolation traced the delay to solver search: retaining the solver database removes it, but retaining only compiled kernels does not.

Fix

Set MIOPEN_SEARCH_CUTOFF=1 during Studio's existing lazy ROCm hardware detection, before model convolutions. MIOpen can skip excessively slow search candidates while retaining its naive fallback solver.

Enable the default only when every visible Torch GPU reports gfx1151. Preserve explicit environment values, including 0; mixed, unknown and other architectures keep their existing defaults. Users on other ROCm GPUs can opt in with the same environment variable. The setting is process-wide and inherited by workers.

Tests

Live A/B against main at 4e8503e437 on Radeon 8060S / gfx1151, Windows and Linux, PyTorch 2.11 / ROCm 7.13. Each OS runs stock and the actual patch on the same runner with separate empty MIOpen caches. Qwen-Image-2.1 Q4_K_M, Auto memory, 1024x1024, 40 steps, two prompts, seed 42, guidance 1.0 and a 19 GiB Torch allocation cap.

First generation	Main	This PR
Linux VAE decode	800.30 s	19.94 s
Windows VAE decode	939.37 s	23.86 s
Linux full generation	978.47 s	193.40 s
Windows full generation	1249.08 s	239.14 s

All four paired images and decoder input tensors are bit-identical. Cold peak Torch GPU allocation stays 14.92 GiB; warm decode stays around 1.5-2 seconds. The probes confirm that startup sets the flag automatically, with no external override in the patched cases. Load/download time is excluded. Denoiser timing also varied, so the VAE phase is the direct measure of this fix.

Live actual-patch A/B

Separate solver validation passed 468 CPU-reference forward/gradient comparisons across FP32, FP16, BF16, grouped/depthwise/pointwise/3D convolutions and multiple layouts. Solver validation

Rebased onto main at b1c522a4ea; 308 related hardware and startup tests passed, 36 skipped. The live A/B above was run on the stated earlier base and was not repeated after this rebase. Coverage includes explicit overrides, mixed and unknown architectures, probe failures, ROCm SDK version detection, CUDA exclusion and lazy startup. Ruff, formatting and diff checks passed.

Scope

Test hardware is Radeon 8060S / gfx1151 with shared memory. The allocation cap does not emulate a discrete GPU's transfer costs. RX 7900 XT remains untested. This changes cold solver-search behavior, not Auto placement, model-weight memory use or vision-attention correctness.

---

Mirror of unslothai/unsloth#12359 by @oobabooga, opened for review only.
Do not merge here. Fixes agreed on this mirror must be applied to the source PR.
Source description digest at mirror time: 9cefc9690826

[danielhanchen]

@codex review

[danielhanchen]

@codex review

[chatgpt-codex-connector]

Codex Review Summary

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Review	Status	Commit	Review trigger
📝 Code Review	✅ Completed 2026-10-01T09:15:51.322008Z	bbfd543	Manual request

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[chatgpt-codex-connector]

Codex Review: Didn't find any major issues. What shall we delve into next?

Reviewed commit: bbfd543d65

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