c1909f350f
Better argument handling of front-end-root ( #7043 )
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* Better argument handling of front-end-root
Improves handling of front-end-root launch argument. Several instances where users have set it and ComfyUI launches as normal and completely disregards the launch arg which doesn't make sense. Better to indicate to user that something is incorrect.
* Removed unused import
There was no real reason to use "Optional" typing in ther front-end-root argument.
2025-03-05 15:34:22 -05:00
52b3469606
[NodeDef] Explicitly add control_after_generate to seed/noise_seed ( #7059 )
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* [NodeDef] Explicitly add control_after_generate to seed/noise_seed
* Update comfy/comfy_types/node_typing.py
Co-authored-by: filtered <176114999+webfiltered@users.noreply.github.com >
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Co-authored-by: filtered <176114999+webfiltered@users.noreply.github.com >
2025-03-05 15:33:23 -05:00
369b079ff6
Fix lowvram issue with ltxv vae.
2025-03-05 05:26:08 -05:00
9c9a7f012a
Adjust ltxv memory factor.
2025-03-05 05:16:05 -05:00
93fedd92fe
Support LTXV 0.9.5.
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Credits: Lightricks team.
2025-03-05 00:13:49 -05:00
65042f7d39
Make it easier to set a custom template for hunyuan video.
2025-03-04 09:26:05 -05:00
7c7c70c400
Refactor skyreels i2v code.
2025-03-04 00:15:45 -05:00
f86c724ef2
Temporal area composition.
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New ConditioningSetAreaPercentageVideo node.
2025-03-03 06:50:31 -05:00
9af6320ec9
Make 2d area composition nodes work on video models.
2025-03-02 08:19:16 -05:00
4dc6709307
Rename argument in last commit and document the options.
2025-03-01 02:43:49 -05:00
4d55f16ae8
Use enum list for --fast options ( #7024 )
2025-03-01 02:37:35 -05:00
cf0b549d48
--fast now takes a number as argument to indicate how fast you want it.
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The idea is that you can indicate how much quality vs speed you want.
At the moment:
--fast 2 enables fp16 accumulation if your pytorch supports it.
--fast 5 enables fp8 matrix mult on fp8 models and the optimization above.
--fast without a number enables all optimizations.
2025-02-28 02:48:20 -05:00
eb4543474b
Use fp16 for intermediate for fp8 weights with --fast if supported.
2025-02-28 02:17:50 -05:00
1804397952
Use fp16 if checkpoint weights are fp16 and the model supports it.
2025-02-27 16:39:57 -05:00
f4dac8ab6f
Wan code small cleanup.
2025-02-27 07:22:42 -05:00
89253e9fe5
Support Cambricon MLU ( #6964 )
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Co-authored-by: huzhan <huzhan@cambricon.com >
2025-02-26 20:45:13 -05:00
3ea3bc8546
Fix wan issues when prompt length is long.
2025-02-26 20:34:02 -05:00
0270a0b41c
Reduce artifacts on Wan by doing the patch embedding in fp32.
2025-02-26 16:59:26 -05:00
c37f15f98e
Add fast preview support for Wan models.
2025-02-26 08:56:23 -05:00
4bca7367f3
Don't try to use clip_fea on t2v model.
2025-02-26 08:38:09 -05:00
b6fefe686b
Better wan memory estimation.
2025-02-26 07:51:22 -05:00
fa62287f1f
More code reuse in wan.
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Fix bug when changing the compute dtype on wan.
2025-02-26 05:22:29 -05:00
0844998db3
Slightly better wan i2v mask implementation.
2025-02-26 03:49:50 -05:00
4ced06b879
WIP support for Wan I2V model.
2025-02-26 01:49:43 -05:00
cb06e9669b
Wan seems to work with fp16.
2025-02-25 21:37:12 -05:00
9a66bb972d
Make wan work with all latent resolutions.
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Cleanup some code.
2025-02-25 19:56:04 -05:00
ea0f939df3
Fix issue with wan and other attention implementations.
2025-02-25 19:13:39 -05:00
f37551c1d2
Change wan rope implementation to the flux one.
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Should be more compatible.
2025-02-25 19:11:14 -05:00
63023011b9
WIP support for Wan t2v model.
2025-02-25 17:20:35 -05:00
f40076096e
Cleanup some lumina te code.
2025-02-25 04:10:26 -05:00
96d891cb94
Speedup on some models by not upcasting bfloat16 to float32 on mac.
2025-02-24 05:41:32 -05:00
ace899e71a
Prioritize fp16 compute when using allow_fp16_accumulation
2025-02-23 04:45:54 -05:00
aff16532d4
Remove some useless code.
2025-02-22 04:45:14 -05:00
072db3bea6
Assume the mac black image bug won't be fixed before v16.
2025-02-21 20:24:07 -05:00
a6deca6d9a
Latest mac still has the black image bug.
2025-02-21 20:14:30 -05:00
41c30e92e7
Let all model memory be offloaded on nvidia.
2025-02-21 06:32:21 -05:00
12da6ef581
Apparently directml supports fp16.
2025-02-20 09:30:24 -05:00
c5be423d6b
Fix link pointing to non-exisiting docs ( #6891 )
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* Fix link pointing to non-exisiting docs
The current link is pointing to a path that does not exist any longer.
I changed it to point to the currect correct path for custom nodes datatypes.
* Update node_typing.py
2025-02-20 07:07:07 -05:00
5715be2ca9
Fix Hunyuan unet config detection for some models. ( #6877 )
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The change to support 32 channel hunyuan models is missing the `key_prefix` on the key.
This addresses a complain in the comments of acc152b674
2025-02-19 07:14:45 -05:00
afc85cdeb6
Add Load Image Output node ( #6790 )
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* add LoadImageOutput node
* add route for input/output/temp files
* update node_typing.py
* use literal type for image_folder field
* mark node as beta
2025-02-18 17:53:01 -05:00
acc152b674
Support loading and using SkyReels-V1-Hunyuan-I2V ( #6862 )
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* Support SkyReels-V1-Hunyuan-I2V
* VAE scaling
* Fix T2V
oops
* Proper latent scaling
2025-02-18 17:06:54 -05:00
b07258cef2
Fix typo.
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Let me know if this slows things down on 2000 series and below.
2025-02-18 07:28:33 -05:00
31e54b7052
Improve AMD arch detection.
2025-02-17 04:53:40 -05:00
8c0bae50c3
bf16 manual cast works on old AMD.
2025-02-17 04:42:40 -05:00
530412cb9d
Refactor torch version checks to be more future proof.
2025-02-17 04:36:45 -05:00
e2919d38b4
Disable bf16 on AMD GPUs that don't support it.
2025-02-16 05:46:10 -05:00
1cd6cd6080
Disable pytorch attention in VAE for AMD.
2025-02-14 05:42:14 -05:00
d7b4bf21a2
Auto enable mem efficient attention on gfx1100 on pytorch nightly 2.7
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I'm not not sure which arches are supported yet. If you see improvements in
memory usage while using --use-pytorch-cross-attention on your AMD GPU let
me know and I will add it to the list.
2025-02-14 04:18:14 -05:00
019c7029ea
Add a way to set a different compute dtype for the model at runtime.
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Currently only works for diffusion models.
2025-02-13 20:34:03 -05:00
8773ccf74d
Better memory estimation for ROCm that support mem efficient attention.
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There is no way to check if the card actually supports it so it assumes
that it does if you use --use-pytorch-cross-attention with yours.
2025-02-13 08:32:36 -05:00
