* Add properties and `IPAdapterTesterMixin` tests for `StableDiffusionPanoramaPipeline`
* Fix variable name typo and update comments
* Update deprecated `output_type="numpy"` to "np" in test files
* Discard changes to src/diffusers/pipelines/stable_diffusion_panorama/pipeline_stable_diffusion_panorama.py
* Update test_stable_diffusion_panorama.py
* Update numbers in README.md
* Update get_guidance_scale_embedding method to use timesteps instead of w
* Update number of checkpoints in README.md
* Add type hints and fix var name
* Fix PyTorch's convention for inplace functions
* Fix a typo
* Revert "Fix PyTorch's convention for inplace functions"
This reverts commit 74350cf65b.
* Fix typos
* Indent
* Refactor get_guidance_scale_embedding method in LEditsPPPipelineStableDiffusionXL class
* fix test
* initial commit
* change test
* updates:
* fix tests
* test fix
* test fix
* fix tests
* make test faster
* clean up
* fix precision in test
* fix precision
* Fix tests
* Fix logging test
* fix test
* fix test
---------
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* up
* fix more
* Apply suggestions from code review
* fix more
* fix more
* Check it
* Remove 16:8
* fix more
* fix more
* fix more
* up
* up
* Test only stable diffusion
* Test only two files
* up
* Try out spinning up processes that can be killed
* up
* Apply suggestions from code review
* up
* up
* ⚙️chore(train_controlnet) fix typo in logger message
* ⚙️chore(models) refactor modules order; make them the same as calling order
When printing the BasicTransformerBlock to stdout, I think it's crucial that the attributes order are shown in proper order. And also previously the "3. Feed Forward" comment was not making sense. It should have been close to self.ff but it's instead next to self.norm3
* correct many tests
* remove bogus file
* make style
* correct more tests
* finish tests
* fix one more
* make style
* make unclip deterministic
* ⚙️chore(models/attention) reorganize comments in BasicTransformerBlock class
---------
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* make tests deterministic
* run slow tests
* prepare for testing
* finish
* refactor
* add print statements
* finish more
* correct some test failures
* more fixes
* set up to correct tests
* more corrections
* up
* fix more
* more prints
* add
* up
* up
* up
* uP
* uP
* more fixes
* uP
* up
* up
* up
* up
* fix more
* up
* up
* clean tests
* up
* up
* up
* more fixes
* Apply suggestions from code review
Co-authored-by: Suraj Patil <surajp815@gmail.com>
* make
* correct
* finish
* finish
Co-authored-by: Suraj Patil <surajp815@gmail.com>
* added dit model
* import
* initial pipeline
* initial convert script
* initial pipeline
* make style
* raise valueerror
* single function
* rename classes
* use DDIMScheduler
* timesteps embedder
* samples to cpu
* fix var names
* fix numpy type
* use timesteps class for proj
* fix typo
* fix arg name
* flip_sin_to_cos and better var names
* fix C shape cal
* make style
* remove unused imports
* cleanup
* add back patch_size
* initial dit doc
* typo
* Update docs/source/api/pipelines/dit.mdx
Co-authored-by: Suraj Patil <surajp815@gmail.com>
* added copyright license headers
* added example usage and toc
* fix variable names asserts
* remove comment
* added docs
* fix typo
* upstream changes
* set proper device for drop_ids
* added initial dit pipeline test
* update docs
* fix imports
* make fix-copies
* isort
* fix imports
* get rid of more magic numbers
* fix code when guidance is off
* remove block_kwargs
* cleanup script
* removed to_2tuple
* use FeedForward class instead of another MLP
* style
* work on mergint DiTBlock with BasicTransformerBlock
* added missing final_dropout and args to BasicTransformerBlock
* use norm from block
* fix arg
* remove unused arg
* fix call to class_embedder
* use timesteps
* make style
* attn_output gets multiplied
* removed commented code
* use Transformer2D
* use self.is_input_patches
* fix flags
* fixed conversion to use Transformer2DModel
* fixes for pipeline
* remove dit.py
* fix timesteps device
* use randn_tensor and fix fp16 inf.
* timesteps_emb already the right dtype
* fix dit test class
* fix test and style
* fix norm2 usage in vq-diffusion
* added author names to pipeline and lmagenet labels link
* fix tests
* use norm_type as string
* rename dit to transformer
* fix name
* fix test
* set norm_type = "layer" by default
* fix tests
* do not skip common tests
* Update src/diffusers/models/attention.py
Co-authored-by: Suraj Patil <surajp815@gmail.com>
* revert AdaLayerNorm API
* fix norm_type name
* make sure all components are in eval mode
* revert norm2 API
* compact
* finish deprecation
* add slow tests
* remove @
* refactor some stuff
* upload
* Update src/diffusers/pipelines/dit/pipeline_dit.py
* finish more
* finish docs
* improve docs
* finish docs
Co-authored-by: Suraj Patil <surajp815@gmail.com>
Co-authored-by: William Berman <WLBberman@gmail.com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
