* Update dream.py. k_euler_a and k_dpm_2_a M1 fix
Make results reproducible (so runs with the same seed produce the same result).
Implements fix by @wbowling referenced in https://github.com/lstein/stable-diffusion/issues/397#issuecomment-1240679294
* Update dream.py. Remove import torch from dream.py
* generate.py: k_euler_a and k_dpm_2_a M1 fix#579
Co-authored-by: Lincoln Stein <lincoln.stein@gmail.com>
* Refactor generate.py and dream.py
* config file path (models.yaml) is parsed inside Generate() to simplify
API
* Better handling of keyboard interrupts in file loading mode vs
interactive
* Removed oodles of unused variables.
* move nonfunctional inpainting out of the scripts directory
* fix ugly ddim tqdm formatting
* fix embiggen breakage, formatting fixes
* fix web server handling of rel and abs outdir paths
* Can now specify either a relative or absolute path for outdir
* Outdir path does not need to be inside the stable-diffusion directory
* Closes security hole that allowed user to read any file within
stable-diffusion (eek!)
* Closes#536
* revert inadvertent change of conda env name (#528)
* Refactor generate.py and dream.py
* config file path (models.yaml) is parsed inside Generate() to simplify
API
* Better handling of keyboard interrupts in file loading mode vs
interactive
* Removed oodles of unused variables.
* move nonfunctional inpainting out of the scripts directory
* fix ugly ddim tqdm formatting
Code cleanup and attention.py einsum_ops update for M1 16-32GB performance.
Expected: On par with fastest ever from 8 to 128GB for 512x512. Allows large images.
When running on just cpu (intel), a call to torch.layer_norm would error with RuntimeError: expected scalar type BFloat16 but found Float
Fix buggy device handling in model.py.
Tested with scripts/dream.py --full_precision on just cpu on intel laptop. Works but slow at ~10s/it.
* Add Embiggen automation
* Make embiggen_tiles masking more intelligent and count from one (at least for the user), rewrite sections of Embiggen README, fix various typos throughout README
* drop duplicate log message
* This moves the call to half() before model.to(device) to avoid GPU
copy of full model. Improves speed and reduces memory usage dramatically
* This fix contributed by @mh-dm (Mihai)
* Add instructions on how to install alongside pyenv (#393)
Like probably many others, I have a lot of different virtualenvs, one for each project. Most of them are handled by `pyenv`.
After installing according to these instructions I had issues with ´pyenv`and `miniconda` fighting over the $PATH of my system.
But then I stumbled upon this nice solution on SO: https://stackoverflow.com/a/73139031 , upon which I have based my suggested changes.
It runs perfectly on my M1 setup, with the anaconda setup as a virtual environment handled by pyenv.
Feel free to incorporate these instructions as you see fit.
Thanks a million for all your hard work.
* Disabled debug output (#436)
Co-authored-by: Henry van Megen <hvanmegen@gmail.com>
* Add New Logo
Co-authored-by: Håvard Gulldahl <havard@lurtgjort.no>
Co-authored-by: Henry van Megen <h.vanmegen@gmail.com>
Co-authored-by: Henry van Megen <hvanmegen@gmail.com>
Co-authored-by: Lincoln Stein <lincoln.stein@gmail.com>
* start refactoring -not yet functional
* first phase of refactor done - not sure weighted prompts working
* Second phase of refactoring. Everything mostly working.
* The refactoring has moved all the hard-core inference work into
ldm.dream.generator.*, where there are submodules for txt2img and
img2img. inpaint will go in there as well.
* Some additional refactoring will be done soon, but relatively
minor work.
* fix -save_orig flag to actually work
* add @neonsecret attention.py memory optimization
* remove unneeded imports
* move token logging into conditioning.py
* add placeholder version of inpaint; porting in progress
* fix crash in img2img
* inpainting working; not tested on variations
* fix crashes in img2img
* ported attention.py memory optimization #117 from basujindal branch
* added @torch_no_grad() decorators to img2img, txt2img, inpaint closures
* Final commit prior to PR against development
* fixup crash when generating intermediate images in web UI
* rename ldm.simplet2i to ldm.generate
* add backward-compatibility simplet2i shell with deprecation warning
* add back in mps exception, addresses @vargol comment in #354
* replaced Conditioning class with exported functions
* fix wrong type of with_variations attribute during intialization
* changed "image_iterator()" to "get_make_image()"
* raise NotImplementedError for calling get_make_image() in parent class
* Update ldm/generate.py
better error message
Co-authored-by: Kevin Gibbons <bakkot@gmail.com>
* minor stylistic fixes and assertion checks from code review
* moved get_noise() method into img2img class
* break get_noise() into two methods, one for txt2img and the other for img2img
* inpainting works on non-square images now
* make get_noise() an abstract method in base class
* much improved inpainting
Co-authored-by: Kevin Gibbons <bakkot@gmail.com>
* Update README.md with new Anaconda install steps (#347)
pip3 version did not work for me and this is the recommended way to install Anaconda now it seems
* fix save_original flag saving to the same filename
Before this, the `--save_orig` flag was not working. The upscaled/GFPGAN would overwrite the original output image.
Co-authored-by: greentext2 <112735219+greentext2@users.noreply.github.com>
