* I added a new doc string to the class. This is more flexible to understanding other developers what are doing and where it's using.
* Update src/diffusers/models/unet_2d_blocks.py
This changes suggest by maintener.
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
* Update src/diffusers/models/unet_2d_blocks.py
Add suggested text
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
* Update unet_2d_blocks.py
I changed the Parameter to Args text.
* Update unet_2d_blocks.py
proper indentation set in this file.
* Update unet_2d_blocks.py
a little bit of change in the act_fun argument line.
* I run the black command to reformat style in the code
* Update unet_2d_blocks.py
similar doc-string add to have in the original diffusion repository.
* I removed the dummy variable defined in both the encoder and decoder.
* Now, I run black package to reformat my file
---------
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
Co-authored-by: Dhruv Nair <dhruv.nair@gmail.com>
* Update final model offload for more pipelines
Add test to ensure all pipeline components are returned to CPU after
execution with model offloading
* Add comment to explain early UNet offload in Text-to-Video pipeline
* Style
* stabilize dpmpp for sdxl by using euler at the final step
* add lu's uniform logsnr time steps
* add test
* fix check_copies
* fix tests
---------
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* fix error reported 'find_unused_parameters' running in mutiple GPUs or NPUs
* fix code check of importing module by its alphabetic order
---------
Co-authored-by: jiaqiw <wangjiaqi50@huawei.com>
Co-authored-by: Dhruv Nair <dhruv.nair@gmail.com>
* I added a new doc string to the class. This is more flexible to understanding other developers what are doing and where it's using.
* Update src/diffusers/models/unet_2d_blocks.py
This changes suggest by maintener.
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
* Update src/diffusers/models/unet_2d_blocks.py
Add suggested text
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
* Update unet_2d_blocks.py
I changed the Parameter to Args text.
* Update unet_2d_blocks.py
proper indentation set in this file.
* Update unet_2d_blocks.py
a little bit of change in the act_fun argument line.
* I run the black command to reformat style in the code
* Update unet_2d_blocks.py
similar doc-string add to have in the original diffusion repository.
* I use a lower method in the activation function.
* Replace multiple if-else statements with a dictionary of activation functions, and call one if statement to retrieve the appropriate function.
* I am using black package to reforamted my file
* I defined the ACTIVATION_FUNCTIONS variable outside of the function
* activation function variable convert to lower case
* First, I resolved the conflict issue. Then, I ran the Black package to reformat my file.
---------
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
* improvement: add typehints and docs to src/diffusers/models/attention_processor.py
* improvement: add typehints and docs to src/diffusers/models/vae.py
* improvement: add missing docs in src/diffusers/models/vq_model.py
* improvement: add typehints and docs to src/diffusers/models/transformer_temporal.py
* improvement: add typehints and docs to src/diffusers/models/t5_film_transformer.py
* improvement: add type hints to src/diffusers/models/unet_1d_blocks.py
* improvement: add missing type hints to src/diffusers/models/unet_2d_blocks.py
* fix: CI error (make fix-copies required)
* fix: CI error (make fix-copies required again)
---------
Co-authored-by: Dhruv Nair <dhruv.nair@gmail.com>
* Add a new community pipeline
examples/community/latent_consistency_img2img.py
which can be called like this
import torch
from diffusers import DiffusionPipeline
pipe = DiffusionPipeline.from_pretrained(
"SimianLuo/LCM_Dreamshaper_v7", custom_pipeline="latent_consistency_txt2img", custom_revision="main")
# To save GPU memory, torch.float16 can be used, but it may compromise image quality.
pipe.to(torch_device="cuda", torch_dtype=torch.float32)
img2img=LatentConsistencyModelPipeline_img2img(
vae=pipe.vae,
text_encoder=pipe.text_encoder,
tokenizer=pipe.tokenizer,
unet=pipe.unet,
#scheduler=pipe.scheduler,
scheduler=None,
safety_checker=None,
feature_extractor=pipe.feature_extractor,
requires_safety_checker=False,
)
img = Image.open("thisismyimage.png")
result = img2img(prompt,img,strength,num_inference_steps=4)
* Apply suggestions from code review
Fix name formatting for scheduler
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* update readme (and run formatter on latent_consistency_img2img.py)
---------
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
