473eab8763
Round 2 of follow-up review surfaced three usability issues: - model-defaults.ts: switching to a model whose backend YAML omits vision_image_size now explicitly resets the store value to null. Pre-fix, a stale 2048 from a previous model would silently apply to the new run because every checked-in model-default file omits the key. - training-section.tsx: handleSaveConfig now includes vision fields unless isDatasetImage is definitively false. isDatasetImage is null during dataset checks, after dataset edits, and on import; treating unknown as "drop" would silently lose the user's selection in those windows. Confirmed-text-only datasets still drop the value. - worker.py: _mlx_vlm_max_resized_size now mirrors the Torch collator's integer formula (w * size + size_func // 2) // size_func instead of Python round(), which uses banker's rounding and disagreed by 1px on half-pixel inputs like 333x1000 with target 500 (was 166, now 167). Test_mlx_training_worker_config gains parity assertions. |
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| assets | ||
| auth | ||
| core | ||
| loggers | ||
| models | ||
| plugins | ||
| requirements | ||
| routes | ||
| state | ||
| storage | ||
| tests | ||
| utils | ||
| __init__.py | ||
| _platform_compat.py | ||
| colab.py | ||
| main.py | ||
| run.py | ||
| startup_banner.py | ||