- 25 Jul, 2023 1 commit
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YiYi Xu authored
* initial * style * from ...pipelines -> from ..pipeline_util * make style * fix-copies * fix value_guided_sampling oops * style * add test * Show failing test * update from_pipe * fix * add controlnet, additional test and register unused original config * update for controlnet * Apply suggestions from code review Co-authored-by:
Patrick von Platen <patrick.v.platen@gmail.com> * store unused config as private attribute and pass if can * add doc * kandinsky inpaint pipeline does not work with decoder checkpoint * update doc * Apply suggestions from code review Co-authored-by:
Sayak Paul <spsayakpaul@gmail.com> * style * Apply suggestions from code review Co-authored-by:
yiyixuxu <yixu310@gmail,com> Co-authored-by:
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- 20 Jul, 2023 1 commit
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Ruslan Vorovchenko authored
* added AsymmetricAutoencoderKL * fixed copies+dummy * added script to convert original asymmetric vqgan * added docs * updated docs * fixed style * fixes, added tests * update doc * fixed doc * fixed tests * naming Co-authored-by:
Ruslan Vorovchenko <r.vorovchenko@prequelapp.com> Co-authored-by:
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- 17 Jul, 2023 1 commit
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Will Berman authored
* Quick implementation of t2i-adapter Load adapter module with from_pretrained Prototyping generalized adapter framework Writeup doc string for sideload framework(WIP) + some minor update on implementation Update adapter models Remove old adapter optional args in UNet Add StableDiffusionAdapterPipeline unit test Handle cpu offload in StableDiffusionAdapterPipeline Auto correct coding style Update model repo name to "RzZ/sd-v1-4-adapter-pipeline" Refactor MultiAdapter to better compatible with config system Export MultiAdapter Create pipeline document template from controlnet Create dummy objects Supproting new AdapterLight model Fix StableDiffusionAdapterPipeline common pipeline test [WIP] Update adapter pipeline document Handle num_inference_steps in StableDiffusionAdapterPipeline Update definition of Adapter "channels_in" Update documents Apply code style Fix doc typo and merge error Update doc string and example Quality of life improvement Remove redundant code and file from prototyping Remove unused pageage Remove comments Fix title Fix typo Add conditioning scale arg Bring back old implmentation Offload sideload Add supply info on document Update src/diffusers/models/adapter.py Co-authored-by:
Will Berman <wlbberman@gmail.com> Update MultiAdapter constructor Swap out custom checkpoint and update pipeline constructor Update docment Apply suggestions from code review Co-authored-by:
HimariO <dsfhe49854@gmail.com>
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- 05 Jul, 2023 1 commit
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dg845 authored
* initial commit * Improve consistency models sampling implementation. * Add CMStochasticIterativeScheduler, which implements the multi-step sampler (stochastic_iterative_sampler) in the original code, and make further improvements to sampling. * Add Unet blocks for consistency models * Add conversion script for Unet * Fix bug in new unet blocks * Fix attention weight loading * Make design improvements to ConsistencyModelPipeline and CMStochasticIterativeScheduler and add initial version of tests. * make style * Make small random test UNet class conditional and set resnet_time_scale_shift to 'scale_shift' to better match consistency model checkpoints. * Add support for converting a test UNet and non-class-conditional UNets to the consistency models conversion script. * make style * Change num_class_embeds to 1000 to better match the original consistency models implementation. * Add support for distillation in pipeline_consistency_models.py. * Improve consistency model tests: - Get small testing checkpoints from hub - Modify tests to take into account "distillation" parameter of ConsistencyModelPipeline - Add onestep, multistep tests for distillation and distillation + class conditional - Add expected image slices for onestep tests * make style * Improve ConsistencyModelPipeline: - Add initial support for class-conditional generation - Fix initial sigma for onestep generation - Fix some sigma shape issues * make style * Improve ConsistencyModelPipeline: - add latents __call__ argument and prepare_latents method - add check_inputs method - add initial docstrings for ConsistencyModelPipeline.__call__ * make style * Fix bug when randomly generating class labels for class-conditional generation. * Switch CMStochasticIterativeScheduler to configuring a sigma schedule and make related changes to the pipeline and tests. * Remove some unused code and make style. * Fix small bug in CMStochasticIterativeScheduler. * Add expected slices for multistep sampling tests and make them pass. * Work on consistency model fast tests: - in pipeline, call self.scheduler.scale_model_input before denoising - get expected slices for Euler and Heun scheduler tests - make Euler test pass - mark Heun test as expected fail because it doesn't support prediction_type "sample" yet - remove DPM and Euler Ancestral tests because they don't support use_karras_sigmas * make style * Refactor conversion script to make it easier to add more model architectures to convert in the future. * Work on ConsistencyModelPipeline tests: - Fix device bug when handling class labels in ConsistencyModelPipeline.__call__ - Add slow tests for onestep and multistep sampling and make them pass - Refactor fast tests - Refactor ConsistencyModelPipeline.__init__ * make style * Remove the add_noise and add_noise_to_input methods from CMStochasticIterativeScheduler for now. * Run python utils/check_copies.py --fix_and_overwrite python utils/check_dummies.py --fix_and_overwrite to make dummy objects for new pipeline and scheduler. * Make fast tests from PipelineTesterMixin pass. * make style * Refactor consistency models pipeline and scheduler: - Remove support for Karras schedulers (only support CMStochasticIterativeScheduler) - Move sigma manipulation, input scaling, denoising from pipeline to scheduler - Make corresponding changes to tests and ensure they pass * make style * Add docstrings and further refactor pipeline and scheduler. * make style * Add initial version of the consistency models documentation. * Refactor custom timesteps logic following DDPMScheduler/IFPipeline and temporarily add torch 2.0 SDPA kernel selection logic for debugging. * make style * Convert current slow tests to use fp16 and flash attention. * make style * Add slow tests for normal attention on cuda device. * make style * Fix attention weights loading * Update consistency model fast tests for new test checkpoints with attention fix. * make style * apply suggestions * Add add_noise method to CMStochasticIterativeScheduler (copied from EulerDiscreteScheduler). * Conversion script now outputs pipeline instead of UNet and add support for LSUN-256 models and different schedulers. * When both timesteps and num_inference_steps are supplied, raise warning instead of error (timesteps take precedence). * make style * Add remaining diffusers model checkpoints for models in the original consistency model release and update usage example. * apply suggestions from review * make style * fix attention naming * Add tests for CMStochasticIterativeScheduler. * make style * Make CMStochasticIterativeScheduler tests pass. * make style * Override test_step_shape in CMStochasticIterativeSchedulerTest instead of modifying it in SchedulerCommonTest. * make style * rename some models * Improve API * rename some models * Remove duplicated block * Add docstring and make torch compile work * More fixes * Fixes * Apply suggestions from code review * Apply suggestions from code review * add more docstring * update consistency conversion script --------- Co-authored-by:
ayushmangal <ayushmangal@microsoft.com> Co-authored-by:
Ayush Mangal <43698245+ayushtues@users.noreply.github.com> Co-authored-by:
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- 20 Jun, 2023 1 commit
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Andy Shih authored
* add paradigms parallel sampling pipeline * linting * ran make fix-copies * add paradigms parallel sampling pipeline * linting * ran make fix-copies * Apply suggestions from code review Co-authored-by:
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- 16 May, 2023 1 commit
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clarencechen authored
* Add DPM-Solver Multistep Inverse Scheduler * Add draft tests for DiffEdit * Add inverse sde-dpmsolver steps to tune image diversity from inverted latents * Fix tests --------- Co-authored-by:
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- 23 Mar, 2023 1 commit
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Kashif Rasul authored
* initial TokenEncoder and ContinuousEncoder * initial modules * added ContinuousContextTransformer * fix copy paste error * use numpy for get_sequence_length * initial terminal relative positional encodings * fix weights keys * fix assert * cross attend style: concat encodings * make style * concat once * fix formatting * Initial SpectrogramPipeline * fix input_tokens * make style * added mel output * ignore weights for config * move mel to numpy * import pipeline * fix class names and import * moved models to models folder * import ContinuousContextTransformer and SpectrogramDiffusionPipeline * initial spec diffusion converstion script * renamed config to t5config * added weight loading * use arguments instead of t5config * broadcast noise time to batch dim * fix call * added scale_to_features * fix weights * transpose laynorm weight * scale is a vector * scale the query outputs * added comment * undo scaling * undo depth_scaling * inital get_extended_attention_mask * attention_mask is none in self-attention * cleanup * manually invert attention * nn.linear need bias=False * added T5LayerFFCond * remove to fix conflict * make style and dummy * remove unsed variables * remove predict_epsilon * Move accelerate to a soft-dependency (#1134) * finish * finish * Update src/diffusers/modeling_utils.py * Update src/diffusers/pipeline_utils.py Co-authored-by:
Anton Lozhkov <anton@huggingface.co> * more fixes * fix Co-authored-by:
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- 22 Mar, 2023 1 commit
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Patrick von Platen authored
* [MS Text To Video} Add first text to video * upload * make first model example * match unet3d params * make sure weights are correcctly converted * improve * forward pass works, but diff result * make forward work * fix more * finish * refactor video output class. * feat: add support for a video export utility. * fix: opencv availability check. * run make fix-copies. * add: docs for the model components. * add: standalone pipeline doc. * edit docstring of the pipeline. * add: right path to TransformerTempModel * add: first set of tests. * complete fast tests for text to video. * fix bug * up * three fast tests failing. * add: note on slow tests * make work with all schedulers * apply styling. * add slow tests * change file name * update * more correction * more fixes * finish * up * Apply suggestions from code review * up * finish * make copies * fix pipeline tests * fix more tests * Apply suggestions from code review Co-authored-by:
Pedro Cuenca <pedro@huggingface.co> * apply suggestions * up * revert --------- Co-authored-by:
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- 02 Mar, 2023 1 commit
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Takuma Mori authored
* add scaffold - copied convert_controlnet_to_diffusers.py from convert_original_stable_diffusion_to_diffusers.py * Add support to load ControlNet (WIP) - this makes Missking Key error on ControlNetModel * Update to convert ControlNet without error msg - init impl for StableDiffusionControlNetPipeline - init impl for ControlNetModel * cleanup of commented out * split create_controlnet_diffusers_config() from create_unet_diffusers_config() - add config: hint_channels * Add input_hint_block, input_zero_conv and middle_block_out - this makes missing key error on loading model * add unet_2d_blocks_controlnet.py - copied from unet_2d_blocks.py as impl CrossAttnDownBlock2D,DownBlock2D - this makes missing key error on loading model * Add loading for input_hint_block, zero_convs and middle_block_out - this makes no error message on model loading * Copy from UNet2DConditionalModel except __init__ * Add ultra primitive test for ControlNetModel inference * Support ControlNetModel inference - without exceptions * copy forward() from UNet2DConditionModel * Impl ControlledUNet2DConditionModel inference - test_controlled_unet_inference passed * Frozen weight & biases for training * Minimized version of ControlNet/ControlledUnet - test_modules_controllnet.py passed * make style * Add support model loading for minimized ver * Remove all previous version files * from_pretrained and inference test passed * copied from pipeline_stable_diffusion.py except `__init__()` * Impl pipeline, pixel match test (almost) passed. * make style * make fix-copies * Fix to add import ControlNet blocks for `make fix-copies` * Remove einops dependency * Support np.ndarray, PIL.Image for controlnet_hint * set default config file as lllyasviel's * Add support grayscale (hw) numpy array * Add and update docstrings * add control_net.mdx * add control_net.mdx to toctree * Update copyright year * Fix to add PIL.Image RGB->BGR conversion - thanks @Mystfit * make fix-copies * add basic fast test for controlnet * add slow test for controlnet/unet * Ignore down/up_block len check on ControlNet * add a copy from test_stable_diffusion.py * Accept controlnet_hint is None * merge pipeline_stable_diffusion.py diff * Update class name to SDControlNetPipeline * make style * Baseline fast test almost passed (w long desc) * still needs investigate. Following didn't passed descriped in TODO comment: - test_stable_diffusion_long_prompt - test_stable_diffusion_no_safety_checker Following didn't passed same as stable_diffusion_pipeline: - test_attention_slicing_forward_pass - test_inference_batch_single_identical - test_xformers_attention_forwardGenerator_pass these seems come from calc accuracy. * Add note comment related vae_scale_factor * add test_stable_diffusion_controlnet_ddim * add assertion for vae_scale_factor != 8 * slow test of pipeline almost passed Failed: test_stable_diffusion_pipeline_with_model_offloading - ImportError: `enable_model_offload` requires `accelerate v0.17.0` or higher but currently latest version == 0.16.0 * test_stable_diffusion_long_prompt passed * test_stable_diffusion_no_safety_checker passed - due to its model size, move to slow test * remove PoC test files * fix num_of_image, prompt length issue add add test * add support List[PIL.Image] for controlnet_hint * wip * all slow test passed * make style * update for slow test * RGB(PIL)->BGR(ctrlnet) conversion * fixes * remove manual num_images_per_prompt test * add document * add `image` argument docstring * make style * Add line to correct conversion * add controlnet_conditioning_scale (aka control_scales strength) * rgb channel ordering by default * image batching logic * Add control image descriptions for each checkpoint * Only save controlnet model in conversion script * Update src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_controlnet.py typo Co-authored-by:
dqueue <dbyqin@gmail.com> * remove controlnet constructor arguments re: @patrickvonplaten * [integration tests] test canny * test_canny fixes * [integration tests] test_depth * [integration tests] test_hed * [integration tests] test_mlsd * add channel order config to controlnet * [integration tests] test normal * [integration tests] test_openpose test_scribble * change height and width to default to conditioning image * [integration tests] test seg * style * test_depth fix * [integration tests] size fixes * [integration tests] cpu offloading * style * generalize controlnet embedding * fix conversion script * Update docs/source/en/api/pipelines/stable_diffusion/controlnet.mdx Co-authored-by:
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- 17 Feb, 2023 1 commit
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Patrick von Platen authored
* add * finish * add tests * add tests * up * up * pull from main * uP * Apply suggestions from code review * finish * Update docs/source/en/_toctree.yml Co-authored-by:
Suraj Patil <surajp815@gmail.com> * finish * clean docs * next * next * Apply suggestions from code review Co-authored-by:
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- 16 Feb, 2023 1 commit
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Wenliang Zhao authored
* add UniPC scheduler * add the return type to the functions * code quality check * add tests * finish docs --------- Co-authored-by:
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- 07 Feb, 2023 1 commit
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Patrick von Platen authored
* before running make style * remove left overs from flake8 * finish * make fix-copies * final fix * more fixes
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- 17 Jan, 2023 1 commit
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Kashif Rasul authored
* 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:
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- 04 Jan, 2023 1 commit
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qsh-zh authored
* feat : add log-rho deis multistep deis * docs :fix typo * docs : add docs for impl algo * docs : remove duplicate ref * finish deis * add docs * fix Co-authored-by:
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- 30 Dec, 2022 1 commit
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Patrick von Platen authored
* move files a bit * more refactors * fix more * more fixes * fix more onnx * make style * upload * fix * up * fix more * up again * up * small fix * Update src/diffusers/__init__.py Co-authored-by:
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- 18 Dec, 2022 1 commit
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Will Berman authored
* [wip] attention block updates * [wip] unCLIP unet decoder and super res * [wip] unCLIP prior transformer * [wip] scheduler changes * [wip] text proj utility class * [wip] UnCLIPPipeline * [wip] kakaobrain unCLIP convert script * [unCLIP pipeline] fixes re: @patrickvonplaten remove callbacks move denoising loops into call function * UNCLIPScheduler re: @patrickvonplaten Revert changes to DDPMScheduler. Make UNCLIPScheduler, a modified DDPM scheduler with changes to support karlo * mask -> attention_mask re: @patrickvonplaten * [DDPMScheduler] remove leftover change * [docs] PriorTransformer * [docs] UNet2DConditionModel and UNet2DModel * [nit] UNCLIPScheduler -> UnCLIPScheduler matches existing unclip naming better * [docs] SchedulingUnCLIP * [docs] UnCLIPTextProjModel * refactor * finish licenses * rename all to attention_mask and prep in models * more renaming * don't expose unused configs * final renaming fixes * remove x attn mask when not necessary * configure kakao script to use new class embedding config * fix copies * [tests] UnCLIPScheduler * finish x attn * finish * remove more * rename condition blocks * clean more * Apply suggestions from code review * up * fix * [tests] UnCLIPPipelineFastTests * remove unused imports * [tests] UnCLIPPipelineIntegrationTests * correct * make style Co-authored-by:
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- 08 Dec, 2022 1 commit
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Anton Lozhkov authored
* Fix PyCharm/VSCode static type checking for dummy objects * Re-add dummies * Fix AudioDiffusion imports * fix import * fix import * Update utils/check_dummies.py Co-authored-by:
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- 07 Dec, 2022 1 commit
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Cheng Lu authored
* add singlestep dpmsolver * fix a style typo * fix a style typo * add docs * finish Co-authored-by:
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- 05 Dec, 2022 1 commit
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Robert Dargavel Smith authored
* add AudioDiffusionPipeline and LatentAudioDiffusionPipeline * add docs to toc * fix tests * fix tests * fix tests * fix tests * fix tests * Update pr_tests.yml Fix tests * parent 499ff34b3edc3e0c506313ab48f21514d8f58b09 author teticio <teticio@gmail.com> 1668765652 +0000 committer teticio <teticio@gmail.com> 1669041721 +0000 parent 499ff34b3edc3e0c506313ab48f21514d8f58b09 author teticio <teticio@gmail.com> 1668765652 +0000 committer teticio <teticio@gmail.com> 1669041704 +0000 add colab notebook [Flax] Fix loading scheduler from subfolder (#1319) [FLAX] Fix loading scheduler from subfolder Fix/Enable all schedulers for in-painting (#1331) * inpaint fix k lms * onnox as well * up Correct path to schedlure (#1322) * [Examples] Correct path * uP Avoid nested fix-copies (#1332) * Avoid nested `# Copied from` statements during `make fix-copies` * style Fix img2img speed with LMS-Discrete Scheduler (#896) Casting `self.sigmas` into a different dtype (the one of original_samples) is not advisable. In my img2img pipeline this leads to a long running time in the `integrate.quad` call later on- by long I mean more than 10x slower. Co-authored-by:
Anton Lozhkov <aglozhkov@gmail.com> * updated styling from PR suggested feedback Co-authored-by:
Juan Acevedo <jfacevedo@google.com> Update README.md: Minor change to Imagic code snippet, missing dir error (#1347) Minor change to Imagic Readme Missing dir causes an error when running the example code. make style change the sample model (#1352) * Update alt_diffusion.mdx * Update alt_diffusion.mdx Add bit diffusion [WIP] (#971) * Create bit_diffusion.py Bit diffusion based on the paper, arXiv:2208.04202, Chen2022AnalogBG * adding bit diffusion to new branch ran tests * tests * tests * tests * tests * removed test folders + added to README * Update README.md Co-authored-by:
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- 02 Dec, 2022 1 commit
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Patrick von Platen authored
* up * up * finish * finish * up * up * finish
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- 28 Nov, 2022 1 commit
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Patrick von Platen authored
* Add heun * Finish first version of heun * remove bogus * finish * finish * improve * up * up * fix more * change progress bar * Update src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion.py * finish * up * up * up
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- 09 Nov, 2022 1 commit
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Duong A. Nguyen authored
* Add ldm super resolution pipeline * style * fix copies * style * fix doc * Update src/diffusers/pipelines/latent_diffusion/pipeline_latent_diffusion_superresolution.py Co-authored-by:
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- 06 Nov, 2022 1 commit
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Cheng Lu authored
* add dpmsolver discrete pytorch scheduler * fix some typos in dpm-solver pytorch * add dpm-solver pytorch in stable-diffusion pipeline * add jax/flax version dpm-solver * change code style * change code style * add docs * add `add_noise` method for dpmsolver * add pytorch unit test for dpmsolver * add dummy object for pytorch dpmsolver * Update src/diffusers/schedulers/scheduling_dpmsolver_discrete.py Co-authored-by:
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- 04 Nov, 2022 1 commit
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Patrick von Platen authored
* finish * finish * Update src/diffusers/modeling_utils.py * Update src/diffusers/pipeline_utils.py Co-authored-by:
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- 03 Nov, 2022 2 commits
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Will Berman authored
* Changes for VQ-diffusion VQVAE Add specify dimension of embeddings to VQModel: `VQModel` will by default set the dimension of embeddings to the number of latent channels. The VQ-diffusion VQVAE has a smaller embedding dimension, 128, than number of latent channels, 256. Add AttnDownEncoderBlock2D and AttnUpDecoderBlock2D to the up and down unet block helpers. VQ-diffusion's VQVAE uses those two block types. * Changes for VQ-diffusion transformer Modify attention.py so SpatialTransformer can be used for VQ-diffusion's transformer. SpatialTransformer: - Can now operate over discrete inputs (classes of vector embeddings) as well as continuous. - `in_channels` was made optional in the constructor so two locations where it was passed as a positional arg were moved to kwargs - modified forward pass to take optional timestep embeddings ImagePositionalEmbeddings: - added to provide positional embeddings to discrete inputs for latent pixels BasicTransformerBlock: - norm layers were made configurable so that the VQ-diffusion could use AdaLayerNorm with timestep embeddings - modified forward pass to take optional timestep embeddings CrossAttention: - now may optionally take a bias parameter for its query, key, and value linear layers FeedForward: - Internal layers are now configurable ApproximateGELU: - Activation function in VQ-diffusion's feedforward layer AdaLayerNorm: - Norm layer modified to incorporate timestep embeddings * Add VQ-diffusion scheduler * Add VQ-diffusion pipeline * Add VQ-diffusion convert script to diffusers * Add VQ-diffusion dummy objects * Add VQ-diffusion markdown docs * Add VQ-diffusion tests * some renaming * some fixes * more renaming * correct * fix typo * correct weights * finalize * fix tests * Apply suggestions from code review Co-authored-by:
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Revist authored
* feat: add repaint * fix: fix quality check with `make fix-copies` * fix: remove old unnecessary arg * chore: change default to DDPM (looks better in experiments) * ".to(device)" changed to "device=" Co-authored-by:
fja <fja@zurich.ibm.com> Co-authored-by:
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- 31 Oct, 2022 1 commit
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hlky authored
* k-diffusion-euler * make style make quality * make fix-copies * fix tests for euler a * Update src/diffusers/schedulers/scheduling_euler_ancestral_discrete.py Co-authored-by:
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- 25 Oct, 2022 1 commit
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Patrick von Platen authored
* start * add more logic * Update src/diffusers/models/unet_2d_condition_flax.py * match weights * up * make model work * making class more general, fixing missed file rename * small fix * make new conversion work * up * finalize conversion * up * first batch of variable renamings * remove c and c_prev var names * add mid and out block structure * add pipeline * up * finish conversion * finish * upload * more fixes * Apply suggestions from code review * add attr * up * uP * up * finish tests * finish * uP * finish * fix test * up * naming consistency in tests * Apply suggestions from code review Co-authored-by:
Nathan Lambert <nathan@huggingface.co> Co-authored-by:
Nathan Lambert <nol@berkeley.edu> Co-authored-by:
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- 12 Oct, 2022 1 commit
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Patrick von Platen authored
* [Dummy imports] Better error message * Test: load pipeline with LMS scheduler. Fails with a cryptic message if scipy is not installed. * Correct Co-authored-by:
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- 13 Sep, 2022 1 commit
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Patrick von Platen authored
* start * finish
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