46daf0a9a7
Add debug options to force on and off attention upcasting.
2024-05-16 04:09:41 -04:00
ec6f16adb6
Fix SAG.
2024-05-14 18:02:27 -04:00
bb4940d837
Only enable attention upcasting on models that actually need it.
2024-05-14 17:00:50 -04:00
b0ab31d06c
Refactor attention upcasting code part 1.
2024-05-14 12:47:31 -04:00
2aed53c4ac
Workaround xformers bug.
2024-04-30 21:23:40 -04:00
d7897fff2c
Move cascade scale factor from stage_a to latent_formats.py
2024-03-16 14:49:35 -04:00
2a813c3b09
Switch some more prints to logging.
2024-03-11 16:34:58 -04:00
5f60ee246e
Support loading the sr cascade controlnet.
2024-03-07 01:22:48 -05:00
03e6e81629
Set upscale algorithm to bilinear for stable cascade controlnet.
2024-03-06 02:59:40 -05:00
03e83bb5d0
Support stable cascade canny controlnet.
2024-03-06 02:25:42 -05:00
cb7c3a2921
Allow image_only_indicator to be None.
2024-02-29 13:11:30 -05:00
b3e97fc714
Koala 700M and 1B support.
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Use the UNET Loader node to load the unet file to use them.
2024-02-28 12:10:11 -05:00
e93cdd0ad0
Remove print.
2024-02-19 11:47:26 -05:00
a7b5eaa7e3
Forgot to commit this.
2024-02-19 04:25:46 -05:00
6bcf57ff10
Fix attention masks properly for multiple batches.
2024-02-17 16:15:18 -05:00
11e3221f1f
fp8 weight support for Stable Cascade.
2024-02-17 15:27:31 -05:00
f8706546f3
Fix attention mask batch size in some attention functions.
2024-02-17 15:22:21 -05:00
3b9969c1c5
Properly fix attention masks in CLIP with batches.
2024-02-17 12:13:13 -05:00
805c36ac9c
Make Stable Cascade work on old pytorch 2.0
2024-02-17 00:42:30 -05:00
667c92814e
Stable Cascade Stage B.
2024-02-16 13:02:03 -05:00
f83109f09b
Stable Cascade Stage C.
2024-02-16 10:55:08 -05:00
5e06baf112
Stable Cascade Stage A.
2024-02-16 06:30:39 -05:00
c661a8b118
Don't use numpy for calculating sigmas.
2024-02-07 18:52:51 -05:00
89507f8adf
Remove some unused imports.
2024-01-25 23:42:37 -05:00
2395ae740a
Make unclip more deterministic.
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Pass a seed argument note that this might make old unclip images different.
2024-01-14 17:28:31 -05:00
6a7bc35db8
Use basic attention implementation for small inputs on old pytorch.
2024-01-09 13:46:52 -05:00
c6951548cf
Update optimized_attention_for_device function for new functions that
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support masked attention.
2024-01-07 13:52:08 -05:00
aaa9017302
Add attention mask support to sub quad attention.
2024-01-07 04:13:58 -05:00
0c2c9fbdfa
Support attention mask in split attention.
2024-01-06 13:16:48 -05:00
3ad0191bfb
Implement attention mask on xformers.
2024-01-06 04:33:03 -05:00
8c6493578b
Implement noise augmentation for SD 4X upscale model.
2024-01-03 14:27:11 -05:00
79f73a4b33
Remove useless code.
2024-01-02 01:50:29 -05:00
61b3f15f8f
Fix lowvram mode not working with unCLIP and Revision code.
2023-12-26 05:02:02 -05:00
d0165d819a
Fix SVD lowvram mode.
2023-12-24 07:13:18 -05:00
261bcbb0d9
A few missing comfy ops in the VAE.
2023-12-22 04:05:42 -05:00
a5056cfb1f
Remove useless code.
2023-12-15 01:28:16 -05:00
77755ab8db
Refactor comfy.ops
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comfy.ops -> comfy.ops.disable_weight_init
This should make it more clear what they actually do.
Some unused code has also been removed.
2023-12-11 23:27:13 -05:00
fbdb14d4c4
Cleaner CLIP text encoder implementation.
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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
1bbd65ab30
Missed this one.
2023-12-05 12:48:41 -05:00
31b0f6f3d8
UNET weights can now be stored in fp8.
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--fp8_e4m3fn-unet and --fp8_e5m2-unet are the two different formats
supported by pytorch.
2023-12-04 11:10:00 -05:00
af365e4dd1
All the unet ops with weights are now handled by comfy.ops
2023-12-04 03:12:18 -05:00
39e75862b2
Fix regression from last commit.
2023-11-26 03:43:02 -05:00
50dc39d6ec
Clean up the extra_options dict for the transformer patches.
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Now everything in transformer_options gets put in extra_options.
2023-11-26 03:13:56 -05:00
3e5ea74ad3
Make buggy xformers fall back on pytorch attention.
2023-11-24 03:55:35 -05:00
871cc20e13
Support SVD img2vid model.
2023-11-23 19:41:33 -05:00
72741105a6
Remove useless code.
2023-11-21 17:27:28 -05:00
7e3fe3ad28
Make deep shrink behave like it should.
2023-11-16 15:26:28 -05:00
7ea6bb038c
Print warning when controlnet can't be applied instead of crashing.
2023-11-16 12:57:12 -05:00
94cc718e9c
Add a way to add patches to the input block.
2023-11-14 00:08:12 -05:00
794dd2064d
Fix typo.
2023-11-07 23:41:55 -05:00
a527d0c795
Code refactor.
2023-11-07 19:33:40 -05:00
2a23ba0b8c
Fix unet ops not entirely on GPU.
2023-11-07 04:30:37 -05:00
a268a574fa
Remove a bunch of useless code.
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DDIM is the same as euler with a small difference in the inpaint code.
DDIM uses randn_like but I set a fixed seed instead.
I'm keeping it in because I'm sure if I remove it people are going to
complain.
2023-10-31 18:11:29 -04:00
c837a173fa
Fix some memory issues in sub quad attention.
2023-10-30 15:30:49 -04:00
125b03eead
Fix some OOM issues with split attention.
2023-10-30 13:14:11 -04:00
6ec3f12c6e
Support SSD1B model and make it easier to support asymmetric unets.
2023-10-27 14:45:15 -04:00
a373367b0c
Fix some OOM issues with split and sub quad attention.
2023-10-25 20:17:28 -04:00
8b65f5de54
attention_basic now works with hypertile.
2023-10-22 03:59:53 -04:00
e6bc42df46
Make sub_quad and split work with hypertile.
2023-10-22 03:51:29 -04:00
9906e3efe3
Make xformers work with hypertile.
2023-10-21 13:23:03 -04:00
d44a2de49f
Make VAE code closer to sgm.
2023-10-17 15:18:51 -04:00
23680a9155
Refactor the attention stuff in the VAE.
2023-10-17 03:19:29 -04:00
bb064c9796
Add a separate optimized_attention_masked function.
2023-10-16 02:31:24 -04:00
9a55dadb4c
Refactor code so model can be a dtype other than fp32 or fp16.
2023-10-13 14:41:17 -04:00
88733c997f
pytorch_attention_enabled can now return True when xformers is enabled.
2023-10-11 21:30:57 -04:00
ac7d8cfa87
Allow attn_mask in attention_pytorch.
2023-10-11 20:38:48 -04:00
1a4bd9e9a6
Refactor the attention functions.
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There's no reason for the whole CrossAttention object to be repeated when
only the operation in the middle changes.
2023-10-11 20:38:48 -04:00
fff491b032
Model patches can now know which batch is positive and negative.
2023-09-27 12:04:07 -04:00
446caf711c
Sampling code refactor.
2023-09-26 13:45:15 -04:00
afa2399f79
Add a way to set output block patches to modify the h and hsp.
2023-09-22 20:26:47 -04:00
94e4fe39d8
This isn't used anywhere.
2023-09-15 12:03:03 -04:00
1938f5c5fe
Add a force argument to soft_empty_cache to force a cache empty.
2023-09-04 00:58:18 -04:00
2da73b7073
Revert changes in comfy/ldm/modules/diffusionmodules/util.py, which is unused.
2023-09-02 20:07:52 -07:00
4a0c4ce4ef
Some fixes to generalize CUDA specific functionality to Intel or other GPUs.
2023-09-02 18:22:10 -07:00
0e3b641172
Remove xformers related print.
2023-09-01 02:12:03 -04:00
bed116a1f9
Remove optimization that caused border.
2023-08-29 11:21:36 -04:00
1c794a2161
Fallback to slice attention if xformers doesn't support the operation.
2023-08-27 22:24:42 -04:00
d935ba50c4
Make --bf16-vae work on torch 2.0
2023-08-27 21:33:53 -04:00
cf5ae46928
Controlnet/t2iadapter cleanup.
2023-08-22 01:06:26 -04:00
b80c3276dc
Fix issue with gligen.
2023-08-18 16:32:23 -04:00
d6e4b342e6
Support for Control Loras.
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Control loras are controlnets where some of the weights are stored in
"lora" format: an up and a down low rank matrice that when multiplied
together and added to the unet weight give the controlnet weight.
This allows a much smaller memory footprint depending on the rank of the
matrices.
These controlnets are used just like regular ones.
2023-08-18 11:59:51 -04:00
2b13939044
Remove some useless code.
2023-07-30 14:13:33 -04:00
95d796fc85
Faster VAE loading.
2023-07-29 16:28:30 -04:00
4b957a0010
Initialize the unet directly on the target device.
2023-07-29 14:51:56 -04:00
9ba440995a
It's actually possible to torch.compile the unet now.
2023-07-18 21:36:35 -04:00
3ded1a3a04
Refactor of sampler code to deal more easily with different model types.
2023-07-17 01:22:12 -04:00
ddc6f12ad5
Disable autocast in unet for increased speed.
2023-07-05 21:58:29 -04:00
103c487a89
Cleanup.
2023-07-02 11:58:23 -04:00
c71a7e6b20
Fix ddim + inpainting not working.
2023-06-26 00:48:48 -04:00
78d8035f73
Fix bug with controlnet.
2023-06-24 11:02:38 -04:00
05676942b7
Add some more transformer hooks and move tomesd to comfy_extras.
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Tomesd now uses q instead of x to decide which tokens to merge because
it seems to give better results.
2023-06-24 03:30:22 -04:00
fa28d7334b
Remove useless code.
2023-06-23 12:35:26 -04:00
f87ec10a97
Support base SDXL and SDXL refiner models.
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Large refactor of the model detection and loading code.
2023-06-22 13:03:50 -04:00
9fccf4aa03
Add original_shape parameter to transformer patch extra_options.
2023-06-21 13:22:01 -04:00
8883cb0f67
Add a way to set patches that modify the attn2 output.
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Change the transformer patches function format to be more future proof.
2023-06-18 22:58:22 -04:00
45be2e92c1
Fix DDIM v-prediction.
2023-06-17 20:48:21 -04:00
ae43f09ef7
All the unet weights should now be initialized with the right dtype.
2023-06-15 18:42:30 -04:00
7bf89ba923
Initialize more unet weights as the right dtype.
2023-06-15 15:00:10 -04:00
e21d9ad445
Initialize transformer unet block weights in right dtype at the start.
2023-06-15 14:29:26 -04:00
21f04fe632
Disable default weight values in unet conv2d for faster loading.
2023-06-14 19:46:08 -04:00
comfyanonymous
Simon Lui