6bd3e87c6f
- normalized() + family_train_infos() mirror the inference fp8 deny for Qwen-Image (activation outliers exceed fp8's range and corrupt the trained result); int8 stays allowed and the UI no longer advertises fp8 for it. - _resolve_base_precision() gates an explicit int8 on a FUNCTIONAL torchao, the same gate auto and /info already apply, so a missing/stub torchao fails fast instead of silently loading dense with compile disabled. - train_precision_modes() gates the dense modes (bf16/int8/fp8/auto) on torch.cuda.is_bf16_supported(), so a non-bf16 CUDA GPU (T4/V100/RTX 20xx) is offered only nf4 instead of a start that evicts resident models and then fails. - start_diffusion_training preflights bf16 support for the DiT families BEFORE _free_gpu_for_diffusion_training(), so any DiT start (nf4 included, since the trainer requires bf16 unconditionally on CUDA) fails fast without eviction. |
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| .. | ||
| assets | ||
| auth | ||
| core | ||
| hub | ||
| loggers | ||
| models | ||
| plugins | ||
| requirements | ||
| routes | ||
| state | ||
| storage | ||
| tests | ||
| utils | ||
| __init__.py | ||
| _platform_compat.py | ||
| cloudflare_tunnel.py | ||
| colab.py | ||
| main.py | ||
| run.py | ||
| startup_banner.py | ||