"gallery/transforms/plot_transforms_e2e.py" did not exist on "90e0b79229ae68ad869515cfb1e556ae018233c3"
- 10 Apr, 2024 1 commit
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IDKiro authored
Co-authored-by:
Sayak Paul <spsayakpaul@gmail.com> Co-authored-by:
YiYi Xu <yixu310@gmail.com>
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- 08 Feb, 2024 1 commit
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Sayak Paul authored
change to 2024
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- 23 Jan, 2024 1 commit
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Sayak Paul authored
* move unets to module
🦋 * parameterize unet-level import. * fix flax unet2dcondition model import * models __init__ * mildly depcrecating models.unet_2d_blocks in favor of models.unets.unet_2d_blocks. * noqa * correct depcrecation behaviour * inherit from the actual classes. * Empty-Commit * backwards compatibility for unet_2d.py * backward compatibility for unet_2d_condition * bc for unet_1d * bc for unet_1d_blocks
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- 21 Dec, 2023 1 commit
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Will Berman authored
amused rename Update docs/source/en/api/pipelines/amused.md Co-authored-by:
Patrick von Platen <patrick.v.platen@gmail.com> AdaLayerNormContinuous default values custom micro conditioning micro conditioning docs put lookup from codebook in constructor fix conversion script remove manual fused flash attn kernel add training script temp remove training script add dummy gradient checkpointing func clarify temperatures is an instance variable by setting it remove additional SkipFF block args hardcode norm args rename tests folder fix paths and samples fix tests add training script training readme lora saving and loading non-lora saving/loading some readme fixes guards Update docs/source/en/api/pipelines/amused.md Co-authored-by:
Suraj Patil <surajp815@gmail.com> Update examples/amused/README.md Co-authored-by:
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- 18 Dec, 2023 1 commit
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Sayak Paul authored
* feat: introduce autoencoders module * more changes for styling and copy fixing * path changes in the docs. * fix: import structure in init. * fix controlnetxs import
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- 29 Nov, 2023 1 commit
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Suraj Patil authored
* begin model * finish blocks * add_embedding * addition_time_embed_dim * use TimestepEmbedding * fix temporal res block * fix time_pos_embed * fix add_embedding * add conversion script * fix model * up * add new resnet blocks * make forward work * return sample in original shape * fix temb shape in TemporalResnetBlock * add spatio temporal transformers * add vae blocks * fix blocks * update * update * fix shapes in Alphablender and add time activation in res blcok * use new blocks * style * fix temb shape * fix SpatioTemporalResBlock * reuse TemporalBasicTransformerBlock * fix TemporalBasicTransformerBlock * use TransformerSpatioTemporalModel * fix TransformerSpatioTemporalModel * fix time_context dim * clean up * make temb optional * add blocks * rename model * update conversion script * remove UNetMidBlockSpatioTemporal * add in init * remove unused arg * remove unused arg * remove more unsed args * up * up * check for None * update vae * update up/mid blocks for decoder * begin pipeline * adapt scheduler * add guidance scalings * fix norm eps in temporal transformers * add temporal autoencoder * make pipeline run * fix frame decodig * decode in float32 * decode n frames at a time * pass decoding_t to decode_latents * fix decode_latents * vae encode/decode in fp32 * fix dtype in TransformerSpatioTemporalModel * type image_latents same as image_embeddings * allow using differnt eps in temporal block for video decoder * fix default values in vae * pass num frames in decode * switch spatial to temporal for mixing in VAE * fix num frames during split decoding * cast alpha to sample dtype * fix attention in MidBlockTemporalDecoder * fix typo * fix guidance_scales dtype * fix missing activation in TemporalDecoder * skip_post_quant_conv * add vae conversion * style * take guidance scale as input * up * allow passing PIL to export_video * accept fps as arg * add pipeline and vae in init * remove hack * use AutoencoderKLTemporalDecoder * don't scale image latents * add unet tests * clean up unet * clean TransformerSpatioTemporalModel * add slow svd test * clean up * make temb optional in Decoder mid block * fix norm eps in TransformerSpatioTemporalModel * clean up temp decoder * clean up * clean up * use c_noise values for timesteps * use math for log * update * fix copies * doc * upcast vae * update forward pass for gradient checkpointing * make added_time_ids is tensor * up * fix upcasting * remove post quant conv * add _resize_with_antialiasing * fix _compute_padding * cleanup model * more cleanup * more cleanup * more cleanup * remove freeu * remove attn slice * small clean * up * up * remove extra step kwargs * remove eta * remove dropout * remove callback * remove merge factor args * clean * clean up * move to dedicated folder * remove attention_head_dim * docstr and small fix * update unet doc strings * rename decoding_t * correct linting * store c_skip and c_out * cleanup * clean TemporalResnetBlock * more cleanup * clean up vae * clean up * begin doc * more cleanup * up * up * doc * Improve * better naming * better naming * better naming * better naming * better naming * better naming * better naming * better naming * Apply suggestions from code review * Default chunk size to None * add example * Better * Apply suggestions from code review * update doc * Update src/diffusers/pipelines/stable_diffusion_video/pipeline_stable_diffusion_video.py Co-authored-by:
Dhruv Nair <dhruv.nair@gmail.com> Co-authored-by:
apolinário <joaopaulo.passos@gmail.com>
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- 01 Nov, 2023 1 commit
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Chi authored
* I added a new doc string to the class. This is more flexible to understanding other developers what are doing and where it's using. * Update src/diffusers/models/unet_2d_blocks.py This changes suggest by maintener. Co-authored-by:
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- 25 Oct, 2023 1 commit
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Aryan V S authored
* improvement: add typehints and docs to src/diffusers/models/attention_processor.py * improvement: add typehints and docs to src/diffusers/models/vae.py * improvement: add missing docs in src/diffusers/models/vq_model.py * improvement: add typehints and docs to src/diffusers/models/transformer_temporal.py * improvement: add typehints and docs to src/diffusers/models/t5_film_transformer.py * improvement: add type hints to src/diffusers/models/unet_1d_blocks.py * improvement: add missing type hints to src/diffusers/models/unet_2d_blocks.py * fix: CI error (make fix-copies required) * fix: CI error (make fix-copies required again) --------- Co-authored-by:
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- 11 Sep, 2023 1 commit
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Dhruv Nair authored
* initial commit * move modules to import struct * add dummy objects and _LazyModule * add lazy import to schedulers * clean up unused imports * lazy import on models module * lazy import for schedulers module * add lazy import to pipelines module * lazy import altdiffusion * lazy import audio diffusion * lazy import audioldm * lazy import consistency model * lazy import controlnet * lazy import dance diffusion ddim ddpm * lazy import deepfloyd * lazy import kandinksy * lazy imports * lazy import semantic diffusion * lazy imports * lazy import stable diffusion * move sd output to its own module * clean up * lazy import t2iadapter * lazy import unclip * lazy import versatile and vq diffsuion * lazy import vq diffusion * helper to fetch objects from modules * lazy import sdxl * lazy import txt2vid * lazy import stochastic karras * fix model imports * fix bug * lazy import * clean up * clean up * fixes for tests * fixes for tests * clean up * remove import of torch_utils from utils module * clean up * clean up * fix mistake import statement * dedicated modules for exporting and loading * remove testing utils from utils module * fixes from merge conflicts * Update src/diffusers/pipelines/kandinsky2_2/__init__.py * fix docs * fix alt diffusion copied from * fix check dummies * fix more docs * remove accelerate import from utils module * add type checking * make style * fix check dummies * remove torch import from xformers check * clean up error message * fixes after upstream merges * dummy objects fix * fix tests * remove unused module import --------- Co-authored-by:
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- 06 Sep, 2023 1 commit
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Kashif Rasul authored
* initial * initial * added initial convert script for paella vqmodel * initial wuerstchen pipeline * add LayerNorm2d * added modules * fix typo * use model_v2 * embed clip caption amd negative_caption * fixed name of var * initial modules in one place * WuerstchenPriorPipeline * inital shape * initial denoising prior loop * fix output * add WuerstchenPriorPipeline to __init__.py * use the noise ratio in the Prior * try to save pipeline * save_pretrained working * Few additions * add _execution_device * shape is int * fix batch size * fix shape of ratio * fix shape of ratio * fix output dataclass * tests folder * fix formatting * fix float16 + started with generator * Update pipeline_wuerstchen.py * removed vqgan code * add WuerstchenGeneratorPipeline * fix WuerstchenGeneratorPipeline * fix docstrings * fix imports * convert generator pipeline * fix convert * Work on Generator Pipeline. WIP * Pipeline works with our diffuzz code * apply scale factor * removed vqgan.py * use cosine schedule * redo the denoising loop * Update src/diffusers/models/resnet.py Co-authored-by:
Dominic Rampas <d6582533@gmail.com> Co-authored-by:
Dominic Rampas <61938694+dome272@users.noreply.github.com>
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- 23 Aug, 2023 1 commit
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Ollin Boer Bohan authored
* Fix AutoencoderTiny encoder scaling convention * Add [-1, 1] -> [0, 1] rescaling to EncoderTiny * Move [0, 1] -> [-1, 1] rescaling from AutoencoderTiny.decode to DecoderTiny (i.e. immediately after the final conv, as early as possible) * Fix missing [0, 255] -> [0, 1] rescaling in AutoencoderTiny.forward * Update AutoencoderTinyIntegrationTests to protect against scaling issues. The new test constructs a simple image, round-trips it through AutoencoderTiny, and confirms the decoded result is approximately equal to the source image. This test checks behavior with and without tiling enabled. This test will fail if new AutoencoderTiny scaling issues are introduced. * Context: Raw TAESD weights expect images in [0, 1], but diffusers' convention represents images with zero-centered values in [-1, 1], so AutoencoderTiny needs to scale / unscale images at the start of encoding and at the end of decoding in order to work with diffusers. * Re-add existing AutoencoderTiny test, update golden values * Add comments to AutoencoderTiny.forward
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- 02 Aug, 2023 1 commit
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Sayak Paul authored
* add: model implementation of tiny autoencoder. * add: inits. * push the latest devs. * add: conversion script and finish. * add: scaling factor args. * debugging * fix denormalization. * fix: positional argument. * handle use_torch_2_0_or_xformers. * handle post_quant_conv * handle dtype * fix: sdxl image processor for tiny ae. * fix: sdxl image processor for tiny ae. * unify upcasting logic. * copied from madness. * remove trailing whitespace. * set is_tiny_vae = False * address PR comments. * change to AutoencoderTiny * make act_fn an str throughout * fix: apply_forward_hook decorator call * get rid of the special is_tiny_vae flag. * directly scale the output. * fix dummies? * fix: act_fn. * get rid of the Clamp() layer. * bring back copied from. * movement of the blocks to appropriate modules. * add: docstrings to AutoencoderTiny * add: documentation. * changes to the conversion script. * add doc entry. * settle tests. * style * add one slow test. * fix * fix 2 * fix 2 * fix: 4 * fix: 5 * finish integration tests * Apply suggestions from code review Co-authored-by:
Steven Liu <59462357+stevhliu@users.noreply.github.com> * style --------- 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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- 30 Jun, 2023 1 commit
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Steven Liu authored
* add modelmixin and unets * remove old model page * minor fixes * fix unet2dcondition * add vqmodel and autoencoderkl * add rest of models * fix autoencoderkl path * fix toctree * fix toctree again * apply feedback * apply feedback * fix copies * fix controlnet copy * fix copies
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- 22 Jun, 2023 1 commit
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Patrick von Platen authored
* relax tolerance slightly * correct incorrect naming * correct namingc * correct more * Apply suggestions from code review * Fix more * Correct more * correct incorrect naming * Update src/diffusers/models/controlnet.py * Correct flax * Correct renaming * Correct blocks * Fix more * Correct more * mkae style * mkae style * mkae style * mkae style * mkae style * Fix flax * mkae style * rename * rename * rename attn head dim to attention_head_dim * correct flax * make style * improve * Correct more * make style * fix more * mkae style * Update src/diffusers/models/controlnet_flax.py * Apply suggestions from code review Co-authored-by:
Pedro Cuenca <pedro@huggingface.co> --------- Co-authored-by:
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- 25 May, 2023 1 commit
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YiYi Xu authored
add kandinsky2.1 --------- Co-authored-by:
yiyixuxu <yixu310@gmail,com> Co-authored-by:
Ayush Mangal <43698245+ayushtues@users.noreply.github.com> Co-authored-by:
ayushmangal <ayushmangal@microsoft.com> Co-authored-by:
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- 17 May, 2023 1 commit
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7eu7d7 authored
* gradient checkpointing bug fix * bug fix; changes for reviews * reformat * reformat --------- Co-authored-by:
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- 26 Apr, 2023 1 commit
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Patrick von Platen authored
* Add all files * update * Make sure vae is memory efficient for PT 1 * make style
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- 17 Mar, 2023 1 commit
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Andy authored
* updated black format * update black format * make style format * updated line endings * update code formatting * Update examples/research_projects/onnxruntime/text_to_image/train_text_to_image.py Co-authored-by:
Will Berman <wlbberman@gmail.com>
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- 01 Mar, 2023 1 commit
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Patrick von Platen authored
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- 04 Jan, 2023 1 commit
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Patrick von Platen authored
* [Repro] Correct reproducability * up * up * uP * up * need better image * allow conversion from no state dict checkpoints * up * up * up * up * check tensors * check tensors * check tensors * check tensors * next try * up * up * better name * up * up * Apply suggestions from code review * correct more * up * replace all torch randn * fix * correct * correct * finish * fix more * up
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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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- 05 Dec, 2022 1 commit
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Benjamin Lefaudeux authored
small but mighty
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- 29 Nov, 2022 1 commit
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Ilmari Heikkinen authored
* StableDiffusion: Decode latents separately to run larger batches * Move VAE sliced decode under enable_vae_sliced_decode and vae.enable_sliced_decode * Rename sliced_decode to slicing * fix whitespace * fix quality check and repository consistency * VAE slicing tests and documentation * API doc hooks for VAE slicing * reformat vae slicing tests * Skip VAE slicing for one-image batches * Documentation tweaks for VAE slicing Co-authored-by:Ilmari Heikkinen <ilmari@fhtr.org>
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- 03 Nov, 2022 1 commit
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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:
Anton Lozhkov <aglozhkov@gmail.com> * Apply suggestions from code review 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:
Anton Lozhkov <anton@huggingface.co> * remove hardcoded 16 * Remove bogus * fix some stuff * finish * improve logging * docs * upload Co-authored-by:
Nathan Lambert <nol@berkeley.edu> Co-authored-by:
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- 12 Oct, 2022 1 commit
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Nathan Lambert authored
* add or fix license formatting * fix quality
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- 07 Oct, 2022 1 commit
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Suraj Patil authored
* handle dtype in vae and image2image pipeline * fix inpaint in fp16 * dtype should be handled in add_noise * style * address review comments * add simple fast tests to check fp16 * fix test name * put mask in fp16
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- 15 Sep, 2022 1 commit
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Suraj Patil authored
* pass norm_num_groups to unet blocs and attention * fix UNet2DConditionModel * add norm_num_groups arg in vae * add tests * remove comment * Apply suggestions from code review
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- 12 Sep, 2022 1 commit
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Kashif Rasul authored
* update expected results of slow tests * relax sum and mean tests * Print shapes when reporting exception * formatting * fix sentence * relax test_stable_diffusion_fast_ddim for gpu fp16 * relax flakey tests on GPU * added comment on large tolerences * black * format * set scheduler seed * added generator * use np.isclose * set num_inference_steps to 50 * fix dep. warning * update expected_slice * preprocess if image * updated expected results * updated expected from CI * pass generator to VAE * undo change back to orig * use orignal * revert back the expected on cpu * revert back values for CPU * more undo * update result after using gen * update mean * set generator for mps * update expected on CI server * undo * use new seed every time * cpu manual seed * reduce num_inference_steps * style * use generator for randn Co-authored-by:
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- 08 Sep, 2022 2 commits
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Kashif Rasul authored
* docs for attention * types for embeddings * unet2d docstrings * UNet2DConditionModel docstrings * fix typos * style and vq-vae docstrings * docstrings for VAE * Update src/diffusers/models/unet_2d.py Co-authored-by:
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Pedro Cuenca authored
* Initial support for mps in Stable Diffusion pipeline. * Initial "warmup" implementation when using mps. * Make some deterministic tests pass with mps. * Disable training tests when using mps. * SD: generate latents in CPU then move to device. This is especially important when using the mps device, because generators are not supported there. See for example https://github.com/pytorch/pytorch/issues/84288. In addition, the other pipelines seem to use the same approach: generate the random samples then move to the appropriate device. After this change, generating an image in MPS produces the same result as when using the CPU, if the same seed is used. * Remove prints. * Pass AutoencoderKL test_output_pretrained with mps. Sampling from `posterior` must be done in CPU. * Style * Do not use torch.long for log op in mps device. * Perform incompatible padding ops in CPU. UNet tests now pass. See https://github.com/pytorch/pytorch/issues/84535 * Style: fix import order. * Remove unused symbols. * Remove MPSWarmupMixin, do not apply automatically. We do apply warmup in the tests, but not during normal use. This adopts some PR suggestions by @patrickvonplaten. * Add comment for mps fallback to CPU step. * Add README_mps.md for mps installation and use. * Apply `black` to modified files. * Restrict README_mps to SD, show measures in table. * Make PNDM indexing compatible with mps. Addresses #239. * Do not use float64 when using LDMScheduler. Fixes #358. * Fix typo identified by @patil-suraj Co-authored-by:
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- 05 Sep, 2022 3 commits
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Partho authored
* [Type Hint] VAE models * Update src/diffusers/models/vae.py * apply suggestions from code review Co-authored-by: -
Samuel Ajisegiri authored
* type hints: models/vae.py * modify typings in vae.py Co-authored-by:
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Patrick von Platen authored
* add outputs for models * add for pipelines * finish schedulers * better naming * adapt tests as well * replace dict access with . access * make schedulers works * finish * correct readme * make bcp compatible * up * small fix * finish * more fixes * more fixes * Apply suggestions from code review Co-authored-by:
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- 04 Sep, 2022 1 commit
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Partho authored
* [Type Hints] VAE models * apply suggestions from code review apply suggestions to also return the return type
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- 30 Aug, 2022 1 commit
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Patrick von Platen authored
* [Examples readme] * Improve * more * save * save * save more * up * up * Apply suggestions from code review Co-authored-by:
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- 06 Aug, 2022 1 commit
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Suraj Patil authored
* pass downsample_padding in encoder * update tests
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- 28 Jul, 2022 1 commit
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Patrick von Platen authored
* [Vae and AutoencoderKL clean] * save intermediate finished work * more progress * more progress * finish modeling code * save intermediate * finish * Correct tests
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- 20 Jul, 2022 1 commit
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Anton Lozhkov authored
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