* start printing the tensors.
* print full throttle
* set static slices for 7 tests.
* remove printing.
* flatten
* disable test for controlnet
* what happens when things are seeded properly?
* set the right value
* style./
* make pia test fail to check things
* print.
* fix pia.
* checking for animatediff.
* fix: animatediff.
* video synthesis
* final piece.
* style.
* print guess.
* fix: assertion for control guess.
---------
Co-authored-by: Dhruv Nair <dhruv.nair@gmail.com>
* speed up test_vae_slicing in animatediff
* speed up test_karras_schedulers_shape for attend and excite.
* style.
* get the static slices out.
* specify torch print options.
* modify
* test run with controlnet
* specify kwarg
* fix: things
* not None
* flatten
* controlnet img2img
* complete controlet sd
* finish more
* finish more
* finish more
* finish more
* finish the final batch
* add cpu check for expected_pipe_slice.
* finish the rest
* remove print
* style
* fix ssd1b controlnet test
* checking ssd1b
* disable the test.
* make the test_ip_adapter_single controlnet test more robust
* fix: simple inpaint
* multi
* disable panorama
* enable again
* panorama is shaky so leave it for now
* remove print
* raise tolerance.
* 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
* move model helper function in pipeline to EfficiencyMixin
---------
Co-authored-by: YiYi Xu <yixu310@gmail.com>
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
* utils and test modifications to enable device agnostic testing
* device for manual seed in unet1d
* fix generator condition in vae test
* consistency changes to testing
* make style
* add device agnostic testing changes to source and one model test
* make dtype check fns private, log cuda fp16 case
* remove dtype checks from import utils, move to testing_utils
* adding tests for most model classes and one pipeline
* fix vae import
* fix ddim inverse scheduler
* update test of ddim inverse scheduler
* update test of pix2pix_zero
* update test of diffedit
* fix typo
---------
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* 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>
* [Draft] Refactor model offload
* [Draft] Refactor model offload
* Apply suggestions from code review
* cpu offlaod updates
* remove model cpu offload from individual pipelines
* add hook to offload models to cpu
* clean up
* model offload
* add model cpu offload string
* make style
* clean up
* fixes for offload issues
* fix tests issues
* resolve merge conflicts
* update src/diffusers/pipelines/pipeline_utils.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* make style
* Update src/diffusers/pipelines/latent_diffusion/pipeline_latent_diffusion.py
---------
Co-authored-by: Dhruv Nair <dhruv.nair@gmail.com>
* proposal for flaky tests
* more precision fixes
* move more tests to use cosine distance
* more test fixes
* clean up
* use default attn
* clean up
* update expected value
* make style
* make style
* Apply suggestions from code review
* Update src/diffusers/pipelines/stable_diffusion/pipeline_onnx_stable_diffusion_img2img.py
* make style
* fix failing tests
---------
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* refactoring of encode_prompt()
* better handling of device.
* fix: device determination
* fix: device determination 2
* handle num_images_per_prompt
* revert changes in loaders.py and give birth to encode_prompt().
* minor refactoring for encode_prompt()/
* make backward compatible.
* Apply suggestions from code review
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* fix: concatenation of the neg and pos embeddings.
* incorporate encode_prompt() in test_stable_diffusion.py
* turn it into big PR.
* make it bigger
* gligen fixes.
* more fixes to fligen
* _encode_prompt -> encode_prompt in tests
* first batch
* second batch
* fix blasphemous mistake
* fix
* fix: hopefully for the final time.
---------
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* move audioldm tests to nightly
* move kandinsky im2img ddpm test to nightly
* move flax dpm test to nightly
* move diffedit dpm test to nightly
* move fp16 slow tests to nightly
* update expected slice so img2img compile tests pass
* use default attn processor
* use default attn processor and update expected slice value to pass test
* use default attn processor
* set default attn processor and update expected slice
* set default attn processor and change precision for check
* set unet to use default attn processor
* Add Recent Timestep Scheduling Improvements to DDIM Inverse Scheduler
Roll timesteps by one to reflect origin-destination semantic discrepancy
Restore `set_alpha_to_one` option to handle negative initial timesteps
Remove `set_alpha_to_zero` option not used due to previous truncation
* Bugfix
* Remove unnecessary calls to `detach()`
Use `self.image_processor.preprocess` in DiffEdit pipeline functions
* Preprocess list input for inverted image latents in diffedit pipeline
* Add `timestep_spacing` and `steps_offset` to `DPMSolverMultistepInverseScheduler`
* Update expected test results to account for inverting last forward diffusion step
* Fix inversion progress bar bug
* Add first draft for proper fast tests for DDIMInverseScheduler
* Add deprecated DDIMInverseScheduler kwarg to ConfigMixer registry
* Fix test failure in DPMMultistepInverseScheduler
Invert step specification leads to negative noise variance in SDE-based algs
Add first draft for proper fast tests for DPMMultistepInverseScheduler
* Update expected test results to account for inverting last forward diffusion step
Clean up diffedit fast test
* Correct controlnet out of list error
* Apply suggestions from code review
* correct tests
* correct tests
* fix
* test all
* Apply suggestions from code review
* test all
* test all
* Apply suggestions from code review
* Apply suggestions from code review
* fix more tests
* Fix more
* Apply suggestions from code review
* finish
* Apply suggestions from code review
* Update src/diffusers/schedulers/scheduling_k_dpm_2_ancestral_discrete.py
* finish
* Implement option for rescaling betas to zero terminal SNR
* Implement rescale classifier free guidance in pipeline_stable_diffusion.py
* focus on DDIM
* make style
* make style
* make style
* make style
* Apply suggestions from Peter Lin
* Apply suggestions from Peter Lin
* make style
* Apply suggestions from code review
* Apply suggestions from code review
* make style
* make style
---------
Co-authored-by: MaxWe00 <gitlab.9v1lq@slmail.me>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
VaeImageProcessor.preprocess refactor
* refactored VaeImageProcessor
- allow passing optional height and width argument to resize()
- add convert_to_rgb
* refactored prepare_latents method for img2img pipelines so that if we pass latents directly as image input, it will not encode it again
* added a test in test_pipelines_common.py to test latents as image inputs
* refactored img2img pipelines that accept latents as image:
- controlnet img2img, stable diffusion img2img , instruct_pix2pix
---------
Co-authored-by: yiyixuxu <yixu310@gmail,com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
Co-authored-by: Sayak Paul <spsayakpaul@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
* enable deterministic pytorch and cuda operations.
* disable manual seeding.
* make style && make quality for unet_2d tests.
* enable determinism for the unet2dconditional model.
* add CUBLAS_WORKSPACE_CONFIG for better reproducibility.
* relax tolerance (very weird issue, though).
* revert to torch manual_seed() where needed.
* relax more tolerance.
* better placement of the cuda variable and relax more tolerance.
* enable determinism for 3d condition model.
* relax tolerance.
* add: determinism to alt_diffusion.
* relax tolerance for alt diffusion.
* dance diffusion.
* dance diffusion is flaky.
* test_dict_tuple_outputs_equivalent edit.
* fix two more tests.
* fix more ddim tests.
* fix: argument.
* change to diff in place of difference.
* fix: test_save_load call.
* test_save_load_float16 call.
* fix: expected_max_diff
* fix: paint by example.
* relax tolerance.
* add determinism to 1d unet model.
* torch 2.0 regressions seem to be brutal
* determinism to vae.
* add reason to skipping.
* up tolerance.
* determinism to vq.
* determinism to cuda.
* determinism to the generic test pipeline file.
* refactor general pipelines testing a bit.
* determinism to alt diffusion i2i
* up tolerance for alt diff i2i and audio diff
* up tolerance.
* determinism to audioldm
* increase tolerance for audioldm lms.
* increase tolerance for paint by paint.
* increase tolerance for repaint.
* determinism to cycle diffusion and sd 1.
* relax tol for cycle diffusion 🚲
* relax tol for sd 1.0
* relax tol for controlnet.
* determinism to img var.
* relax tol for img variation.
* tolerance to i2i sd
* make style
* determinism to inpaint.
* relax tolerance for inpaiting.
* determinism for inpainting legacy
* relax tolerance.
* determinism to instruct pix2pix
* determinism to model editing.
* model editing tolerance.
* panorama determinism
* determinism to pix2pix zero.
* determinism to sag.
* sd 2. determinism
* sd. tolerance
* disallow tf32 matmul.
* relax tolerance is all you need.
* make style and determinism to sd 2 depth
* relax tolerance for depth.
* tolerance to diffedit.
* tolerance to sd 2 inpaint.
* up tolerance.
* determinism in upscaling.
* tolerance in upscaler.
* more tolerance relaxation.
* determinism to v pred.
* up tol for v_pred
* unclip determinism
* determinism to unclip img2img
* determinism to text to video.
* determinism to last set of tests
* up tol.
* vq cumsum doesn't have a deterministic kernel
* relax tol
* relax tol
* Update Pix2PixZero Auto-correlation Loss
* Add Stable Diffusion DiffEdit pipeline
* Add draft documentation and import code
* Bugfixes and refactoring
* Add option to not decode latents in the inversion process
* Harmonize preprocessing
* Revert "Update Pix2PixZero Auto-correlation Loss"
This reverts commit b218062fed.
* Update annotations
* rename `compute_mask` to `generate_mask`
* Update documentation
* Update docs
* Update Docs
* Fix copy
* Change shape of output latents to batch first
* Update docs
* Add first draft for tests
* Bugfix and update tests
* Add `cross_attention_kwargs` support for all pipeline methods
* Fix Copies
* Add support for PIL image latents
Add support for mask broadcasting
Update docs and tests
Align `mask` argument to `mask_image`
Remove height and width arguments
* Enable MPS Tests
* Move example docstrings
* Fix test
* Fix test
* fix pipeline inheritance
* Harmonize `prepare_image_latents` with StableDiffusionPix2PixZeroPipeline
* Register modules set to `None` in config for `test_save_load_optional_components`
* Move fixed logic to specific test class
* Clean changes to other pipelines
* Update new tests to coordinate with #2953
* Update slow tests for better results
* Safety to avoid potential problems with torch.inference_mode
* Add reference in SD Pipeline Overview
* Fix tests again
* Enforce determinism in noise for generate_mask
* Fix copies
* Widen test tolerance for fp16 based on `test_stable_diffusion_upscale_pipeline_fp16`
* Add LoraLoaderMixin and update `prepare_image_latents`
* clean up repeat and reg
* bugfix
* Remove invalid args from docs
Suppress spurious warning by repeating image before latent to mask gen
* ⚙️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>
