torch DataLoader's pin_memory was never set, defaulting to False. Setting
pin_memory=True allocates batch tensors in page-locked memory, which lets
PyTorch issue async cuda host->device copies via DMA - typically 10-30%
faster transfer for image/video training tensors and can reduce per-step
overhead noticeably on Windows where num_workers is forced to 0 (see
6d31c6db / #770) and the main process pays the full transfer cost.
pin_memory is orthogonal to num_workers and is safe with num_workers=0,
so this benefits Windows/macOS users (who currently can't use multi-worker
loading due to pickling constraints) without changing any other behavior.
Gated on torch.cuda.is_available() so it's a no-op on CPU/MPS/ROCm-without
-CUDA-API setups.
Refs #758.
* Base ace step 1.5 xl added. Generating, still wip on training and ui
* Base training code done
* Fix some issues with caching text embeddings. Update sample cards to show audio
* Fix issue with quantizing ace step
* Add album artwork to samples with waveform.
* Cleanup logs
* Add album art endpoint to speed up album art loading
* Made an make video with artwork script
* Make ui handle basic audio models. Make multi line adjustments to the editor and better syntax hilighting.
* Add prompt tagging system for special tagged models.
* prompt tagging processing for ui working.
* Moved default samples to a special file so we can add more when needed and they can be adjusted for a specific model
* Add a captioner job with music captioner that is prepped for use with the ui
* Add basit ui setup for captioning modal and handeling captioning jobs
* Starting captioning job from ui working. Still better management for it.
* Better filtering of job options in the job view for captioning jobs
* Added qwen3 vl as a captioner for images
* Have an indicator when a dataset is being captioned.
* Adjust the way caption jobs look in the queue
* Fix a few issues. Adjust defaults.
* Version bump
* Added ace step to the readme.
Booyaka101
Jaret Burkett
Asaf Agami