* 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 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>
* 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
* 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
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
