c2b25feaee
Teach the chat and image load guards about an active diffusion (SDXL) LoRA job: a chat load is refused (its footprint cannot be fit-checked against the trainer) and an image load is refused outright, mirroring the existing LLM training guards, so a load can no longer allocate GPU memory alongside the trainer and undo the pre-start cleanup. Bind the diffusion trainer subprocess to the parent's lifetime and scrub the native path lease secret from it by running the child through run_without_native_path_secret, matching the inference/export/LLM workers, so a Studio crash or kill no longer leaves the trainer holding the GPU. Reset in_model_load on the complete and error terminal events: a stop or failure during model loading otherwise leaves the status reporting a stale loading indicator after the job has ended. |
||
|---|---|---|
| .. | ||
| __init__.py | ||
| diffusion_lora_trainer.py | ||
| diffusion_training_service.py | ||
| resume.py | ||
| s3_dataset.py | ||
| trainer.py | ||
| training.py | ||
| worker.py | ||