* fix an issue that ipex occupy too much memory, it will not impact performance
* make style
---------
Co-authored-by: root <jun.chen@intel.com>
Co-authored-by: Meng Guoqing <guoqing.meng@intel.com>
* Fix the pipeline name in the examples for LMD+ pipeline
* Add LMD+ colab link
* Apply code formatting
---------
Co-authored-by: Sayak Paul <spsayakpaul@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>
* SDXL microconditioning documentation should indicate the correct default order of parameters, so that developers know
* SDXL microconditioning documentation should indicate the correct default order of parameters, so that developers know
* empty
---------
Co-authored-by: bghira <bghira@users.github.com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Fixed `get_word_inds` mistake/typo in P2P community pipeline
The function `get_word_inds` was taking a string of text and either a word (str) or a word index (int) and returned the indices of token(s) the word would be encoded to.
However, there was a typo, in which in the second `if` branch the word was checked to be a `str` **again**, not `int`, which resulted in an [example code from the docs](https://github.com/huggingface/diffusers/tree/main/examples/community#prompt2prompt-pipeline) to result in an error
* Initial commit P2P
* Replaced CrossAttention, added test skeleton
* bug fixes
* Updated docstring
* Removed unused function
* Created tests
* improved tests
- made fast inference tests faster
- corrected image shape assertions
* Corrected expected output shape in tests
* small fix: test inputs
* Update tests
- used conditional unet2d
- set expected image slices
- edit_kwargs are now not popped, so pipe can be run multiple times
* Fixed bug in int tests
* Fixed tests
* Linting
* Create prompt2prompt.md
* Added to docs toc
* Ran make fix-copies
* Fixed code blocks in docs
* Using same interface as StableDiffusionPipeline
* Fixed small test bug
* Added all options SDPipeline.__call_ has
* Fixed docstring; made __call__ like in SD
* Linting
* Added test for multiple prompts
* Improved docs
* Incorporated feedback
* Reverted formatting on unrelated files
* Moved prompt2prompt to community
- Moved prompt2prompt pipeline from main to community
- Deleted tests
- Moved documentation to community and shorted it
* Update src/diffusers/utils/dummy_torch_and_transformers_objects.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
---------
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Fix potential type conversion errors in SDXL pipelines
* make sure vae stays in fp16
---------
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* empty PR
* init
* changes
* starting with the pipeline
* stable diff
* prev
* more things, getting started
* more functions
* makeing it more readable
* almost done testing
* var changes
* testing
* device
* device support
* maybe
* device malfunctions
* new new
* register
* testing
* exec does not work
* float
* change info
* change of architecture
* might work
* testing with colab
* more attn atuff
* stupid additions
* documenting and testing
* writing tests
* more docs
* tests and docs
* remove test
* empty PR
* init
* changes
* starting with the pipeline
* stable diff
* prev
* more things, getting started
* more functions
* makeing it more readable
* almost done testing
* var changes
* testing
* device
* device support
* maybe
* device malfunctions
* new new
* register
* testing
* exec does not work
* float
* change info
* change of architecture
* might work
* testing with colab
* more attn atuff
* stupid additions
* documenting and testing
* writing tests
* more docs
* tests and docs
* remove test
* change cross attention
* revert back
* tests
* reverting back to orig
* changes
* test passing
* pipeline changes
* before quality
* quality checks pass
* remove print statements
* doc fixes
* __init__ error something
* update docs, working on dim
* working on encoding
* doc fix
* more fixes
* no more dependent on 512*512
* update docs
* fixes
* test passing
* remove comment
* fixes and migration
* simpler tests
* doc changes
* green CI
* changes
* more docs
* changes
* new images
* to community examples
* selete
* more fixes
* changes
* fix
---------
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
* Add SDXL long weighted prompt pipeline
* Add SDXL long weighted prompt pipeline usage sample in the readme document
* Add SDXL long weighted prompt pipeline usage sample in the readme document, add result image
* add zero123 pipeline to community
* add community doc
* reformat
* update zero123 pipeline, including cc_projection within diffusers; add convert ckpt scripts; support diffusers weights
* added StableDiffusionCanvasPipeline pipeline
* Added utils codes to pipe_utils file.
* make style
* delete mixture.py and Text2ImageRegion class
* make style
* Added the codes to the readme.md file.
* Moved functions from pipeline_utils to mix_canvas
