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
1d5d6586f3
Fix ruff.
2025-02-12 06:49:16 -05:00
35740259de
mix_ascend_bf16_infer_err ( #6794 )
2025-02-12 06:48:11 -05:00
ab888e1e0b
Add add_weight_wrapper function to model patcher.
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Functions can now easily be added to wrap/modify model weights.
2025-02-12 05:55:35 -05:00
d9f0fcdb0c
Cleanup.
2025-02-11 17:17:03 -05:00
b124256817
Fix for running via DirectML ( #6542 )
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* 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
af4b7c91be
Make --force-fp16 actually force the diffusion model to be fp16.
2025-02-11 08:33:09 -05:00
4027466c80
Make lumina model work with any latent resolution.
2025-02-10 00:24:20 -05:00
095d867147
Remove useless function.
2025-02-09 07:02:57 -05:00
caeb27c3a5
res_multistep: Fix cfgpp and add ancestral samplers ( #6731 )
2025-02-08 19:39:58 -05:00
3d06e1c555
Make error more clear to user.
2025-02-08 18:57:24 -05:00
43a74c0de1
Allow FP16 accumulation with `--fast` ( #6453 )
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Currently only applies to PyTorch nightly releases. (>=20250208)
2025-02-08 17:00:56 -05:00
079eccc92a
Don't compress http response by default.
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Remove argument to disable it.
Add new --enable-compress-response-body argument to enable it.
2025-02-07 03:29:21 -05:00
14880e6dba
Remove some useless code.
2025-02-06 05:00:37 -05:00
37cd448529
Set the shift for Lumina back to 6.
2025-02-05 14:49:52 -05:00
94f21f9301
Upcasting rope to fp32 seems to make no difference in this model.
2025-02-05 04:32:47 -05:00
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