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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| .. | ||
| __init__.py | ||
| diffusion_dit_trainer.py | ||
| diffusion_lora_trainer.py | ||
| diffusion_train_common.py | ||
| diffusion_training_service.py | ||
| resume.py | ||
| s3_dataset.py | ||
| trainer.py | ||
| training.py | ||
| worker.py | ||