Commit Graph

17 Commits

Author SHA1 Message Date
comfyanonymous
d9f0fcdb0c Cleanup. 2025-02-11 17:17:03 -05:00
HishamC
b124256817
Fix for running via DirectML (#6542)
* Fix for running via DirectML

Fix DirectML empty image generation issue with Flux1. add CPU fallback for unsupported path. Verified the model works on AMD GPUs

* fix formating

* update casual mask calculation
2025-02-11 17:11:32 -05:00
comfyanonymous
44e19a28d3 Use maximum negative value instead of -inf for masks in text encoders.
This is probably more correct.
2025-02-02 09:46:00 -05:00
comfyanonymous
8f0009aad0 Support new flux model variants. 2024-11-21 08:38:23 -05:00
comfyanonymous
d1a6bd6845 Support loading long clipl model with the CLIP loader node. 2024-08-20 10:46:36 -04:00
comfyanonymous
83dbac28eb Properly set if clip text pooled projection instead of using hack. 2024-08-20 10:46:36 -04:00
comfyanonymous
2c038ccef0 Lower CLIP memory usage by a bit. 2024-07-31 01:32:35 -04:00
comfyanonymous
82cae45d44 Fix potential issue with non clip text embeddings. 2024-07-30 14:41:13 -04:00
comfyanonymous
c2cb8e889b Always return unprojected pooled output for gligen. 2024-02-25 07:33:13 -05:00
comfyanonymous
1cb3f6a83b Move text projection into the CLIP model code.
Fix issue with not loading the SSD1B clip correctly.
2024-02-25 01:41:08 -05:00
comfyanonymous
3b9969c1c5 Properly fix attention masks in CLIP with batches. 2024-02-17 12:13:13 -05:00
comfyanonymous
6c875d846b Fix clip attention mask issues on some hardware. 2024-02-17 07:53:52 -05:00
comfyanonymous
c6951548cf Update optimized_attention_for_device function for new functions that
support masked attention.
2024-01-07 13:52:08 -05:00
comfyanonymous
c782144433 Fix clip vision lowvram mode not working. 2023-12-27 13:50:57 -05:00
comfyanonymous
174eba8e95 Use own clip vision model implementation. 2023-12-09 11:56:31 -05:00
comfyanonymous
efb704c758 Support attention masking in CLIP implementation. 2023-12-07 02:51:02 -05:00
comfyanonymous
fbdb14d4c4 Cleaner CLIP text encoder implementation.
Use a simple CLIP model implementation instead of the one from
transformers.

This will allow some interesting things that would too hackish to implement
using the transformers implementation.
2023-12-06 23:50:03 -05:00