31b0f6f3d8
UNET weights can now be stored in fp8.
...
--fp8_e4m3fn-unet and --fp8_e5m2-unet are the two different formats
supported by pytorch.
2023-12-04 11:10:00 -05:00
61a123a1e0
A different way of handling multiple images passed to SVD.
...
Previously when a list of 3 images [0, 1, 2] was used for a 6 frame video
they were concated like this:
[0, 1, 2, 0, 1, 2]
now they are concated like this:
[0, 0, 1, 1, 2, 2]
2023-12-03 03:31:47 -05:00
13fdee6abf
Try to free memory for both cond+uncond before inference.
2023-11-27 14:55:40 -05:00
be71bb5e13
Tweak memory inference calculations a bit.
2023-11-27 14:04:16 -05:00
871cc20e13
Support SVD img2vid model.
2023-11-23 19:41:33 -05:00
ce67dcbcda
Make it easy for models to process the unet state dict on load.
2023-11-20 23:17:53 -05:00
4781819a85
Make memory estimation aware of model dtype.
2023-11-12 04:28:26 -05:00
dd4ba68b6e
Allow different models to estimate memory usage differently.
2023-11-12 04:03:52 -05:00
064d7583eb
Add a CONDConstant for passing non tensor conds to unet.
2023-11-08 01:59:09 -05:00
1ffa8858e7
Move model sampling code to comfy/model_sampling.py
2023-11-04 01:32:23 -04:00
ecb80abb58
Allow ModelSamplingDiscrete to be instantiated without a model config.
2023-11-01 19:13:03 -04:00
111f1b5255
Fix some issues with sampling precision.
2023-10-31 23:49:29 -04:00
7c0f255de1
Clean up percent start/end and make controlnets work with sigmas.
2023-10-31 22:14:32 -04:00
1777b54d02
Sampling code changes.
...
apply_model in model_base now returns the denoised output.
This means that sampling_function now computes things on the denoised
output instead of the model output. This should make things more consistent
across current and future models.
2023-10-31 17:33:43 -04:00
d1d2fea806
Pass extra conds directly to unet.
2023-10-25 00:07:53 -04:00
036f88c621
Refactor to make it easier to add custom conds to models.
2023-10-24 23:31:12 -04:00
e6962120c6
Make sure cond_concat is on the right device.
2023-10-19 01:14:25 -04:00
782a24fce6
Refactor cond_concat into model object.
2023-10-18 16:48:37 -04:00
492db2de8d
Allow having a different pooled output for each image in a batch.
2023-09-21 01:14:42 -04:00
7931ff0fd9
Support SDXL inpaint models.
2023-09-01 15:22:52 -04:00
1c012d69af
It doesn't make sense for c_crossattn and c_concat to be lists.
2023-08-31 13:25:00 -04:00
15adc3699f
Move beta_schedule to model_config and allow disabling unet creation.
2023-08-29 14:22:53 -04:00
a57b0c797b
Fix lowvram model merging.
2023-08-26 11:52:07 -04:00
39ac856a33
ReVision support: unclip nodes can now be used with SDXL.
2023-08-18 11:59:36 -04:00
a2ce9655ca
Refactor unclip code.
2023-08-14 23:48:47 -04:00
9cc12c833d
CLIPVisionEncode can now encode multiple images.
2023-08-14 16:54:05 -04:00
4b957a0010
Initialize the unet directly on the target device.
2023-07-29 14:51:56 -04:00
68be24eead
Remove some prints.
2023-07-27 16:12:43 -04:00
51d5477579
Add key to indicate checkpoint is v_prediction when saving.
2023-07-18 00:25:53 -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
fcef47f06e
Fix bug.
2023-06-28 00:38:07 -04:00
9b93b920be
Add CheckpointSave node to save checkpoints.
...
The created checkpoints contain workflow metadata that can be loaded by
dragging them on top of the UI or loading them with the "Load" button.
Checkpoints will be saved in fp16 or fp32 depending on the format ComfyUI
is using for inference on your hardware. To force fp32 use: --force-fp32
Anything that patches the model weights like merging or loras will be
saved.
The output directory is currently set to: output/checkpoints but that might
change in the future.
2023-06-26 12:22:27 -04:00
8607c2d42d
Move latent scale factor from VAE to model.
2023-06-23 02:33:31 -04:00
f87ec10a97
Support base SDXL and SDXL refiner models.
...
Large refactor of the model detection and loading code.
2023-06-22 13:03:50 -04:00
c64ca8c0b2
Refactor unCLIP noise augment out of samplers.py
2023-06-11 04:01:18 -04:00
de142eaad5
Simpler base model code.
2023-06-09 12:31:16 -04:00
comfyanonymous