diffusers/docs/source/_toctree.yml

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- sections:
- local: index
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title: "🧨 Diffusers"
- local: quicktour
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title: "Quicktour"
- local: installation
title: "Installation"
title: "Get started"
- sections:
- sections:
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- local: using-diffusers/loading
title: "Loading Pipelines, Models, and Schedulers"
- local: using-diffusers/schedulers
title: "Using different Schedulers"
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- local: using-diffusers/configuration
title: "Configuring Pipelines, Models, and Schedulers"
- local: using-diffusers/custom_pipeline_overview
title: "Loading and Adding Custom Pipelines"
title: "Loading & Hub"
- sections:
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- local: using-diffusers/unconditional_image_generation
title: "Unconditional Image Generation"
- local: using-diffusers/conditional_image_generation
title: "Text-to-Image Generation"
- local: using-diffusers/img2img
title: "Text-Guided Image-to-Image"
- local: using-diffusers/inpaint
title: "Text-Guided Image-Inpainting"
- local: using-diffusers/custom_pipeline_examples
title: "Community Pipelines"
- local: using-diffusers/contribute_pipeline
title: "How to contribute a Pipeline"
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title: "Pipelines for Inference"
- sections:
- local: using-diffusers/rl
title: "Reinforcement Learning"
- local: using-diffusers/audio
title: "Audio"
- local: using-diffusers/other-modalities
title: "Other Modalities"
title: "Taking Diffusers Beyond Images"
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title: "Using Diffusers"
- sections:
- local: optimization/fp16
title: "Memory and Speed"
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- local: optimization/onnx
title: "ONNX"
- local: optimization/open_vino
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title: "OpenVINO"
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- local: optimization/mps
title: "MPS"
- local: optimization/habana
title: "Habana Gaudi"
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title: "Optimization/Special Hardware"
- sections:
- local: training/overview
title: "Overview"
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- local: training/unconditional_training
title: "Unconditional Image Generation"
- local: training/text_inversion
title: "Textual Inversion"
- local: training/dreambooth
title: "Dreambooth"
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- local: training/text2image
title: "Text-to-image fine-tuning"
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title: "Training"
- sections:
- local: conceptual/stable_diffusion
title: "Stable Diffusion"
- local: conceptual/philosophy
title: "Philosophy"
- local: conceptual/contribution
title: "How to contribute?"
title: "Conceptual Guides"
- sections:
- sections:
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- local: api/models
title: "Models"
- local: api/schedulers
title: "Schedulers"
- local: api/diffusion_pipeline
title: "Diffusion Pipeline"
- local: api/logging
title: "Logging"
- local: api/configuration
title: "Configuration"
- local: api/outputs
title: "Outputs"
title: "Main Classes"
- sections:
- local: api/pipelines/overview
title: "Overview"
- local: api/pipelines/alt_diffusion
title: "AltDiffusion"
Add CycleDiffusion pipeline using Stable Diffusion (#888) * Add CycleDiffusion pipeline for Stable Diffusion * Add the option of passing noise to DDIMScheduler Add the option of providing the noise itself to DDIMScheduler, instead of the random seed generator. * Update README.md * Update README.md * Update pipeline_stable_diffusion_cycle_diffusion.py * Update pipeline_stable_diffusion_cycle_diffusion.py * Update pipeline_stable_diffusion_cycle_diffusion.py * Update pipeline_stable_diffusion_cycle_diffusion.py * Update scheduling_ddim.py * Update import format * Update pipeline_stable_diffusion_cycle_diffusion.py * Update scheduling_ddim.py * Update src/diffusers/schedulers/scheduling_ddim.py Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com> * Update src/diffusers/schedulers/scheduling_ddim.py Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com> * Update src/diffusers/schedulers/scheduling_ddim.py Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com> * Update src/diffusers/schedulers/scheduling_ddim.py Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com> * Update src/diffusers/schedulers/scheduling_ddim.py Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com> * Update scheduling_ddim.py * Update scheduling_ddim.py * Update scheduling_ddim.py * add two tests * Update pipeline_stable_diffusion_cycle_diffusion.py * Update pipeline_stable_diffusion_cycle_diffusion.py * Update README.md * Rename pipeline name as suggested in the latest reviewer comment * Update test_pipelines.py * Update test_pipelines.py * Update test_pipelines.py * Update pipeline_stable_diffusion_cycle_diffusion.py * Remove the generator This generator does not control all randomness during sampling, which can be misleading. * Update optimal hyperparameters * Update src/diffusers/pipelines/stable_diffusion/README.md Co-authored-by: Suraj Patil <surajp815@gmail.com> * Update src/diffusers/pipelines/stable_diffusion/README.md Co-authored-by: Suraj Patil <surajp815@gmail.com> * Update src/diffusers/pipelines/stable_diffusion/README.md Co-authored-by: Suraj Patil <surajp815@gmail.com> * Apply suggestions from code review * uP * Update src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_cycle_diffusion.py Co-authored-by: Suraj Patil <surajp815@gmail.com> * up * up * Replace assert with ValueError * finish docs Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com> Co-authored-by: Suraj Patil <surajp815@gmail.com>
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- local: api/pipelines/cycle_diffusion
title: "Cycle Diffusion"
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- local: api/pipelines/ddim
title: "DDIM"
- local: api/pipelines/ddpm
title: "DDPM"
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- local: api/pipelines/latent_diffusion
title: "Latent Diffusion"
- local: api/pipelines/latent_diffusion_uncond
title: "Unconditional Latent Diffusion"
- local: api/pipelines/paint_by_example
title: "PaintByExample"
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- local: api/pipelines/pndm
title: "PNDM"
- local: api/pipelines/score_sde_ve
title: "Score SDE VE"
- local: api/pipelines/stable_diffusion
title: "Stable Diffusion"
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- local: api/pipelines/stable_diffusion_2
title: "Stable Diffusion 2"
- local: api/pipelines/stable_diffusion_safe
title: "Safe Stable Diffusion"
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- local: api/pipelines/stochastic_karras_ve
title: "Stochastic Karras VE"
- local: api/pipelines/dance_diffusion
title: "Dance Diffusion"
- local: api/pipelines/versatile_diffusion
title: "Versatile Diffusion"
VQ-diffusion (#658) * 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: Pedro Cuenca <pedro@huggingface.co> * finish * finish * up Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com> Co-authored-by: Anton Lozhkov <aglozhkov@gmail.com> Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
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- local: api/pipelines/vq_diffusion
title: "VQ Diffusion"
- local: api/pipelines/repaint
title: "RePaint"
add AudioDiffusionPipeline and LatentAudioDiffusionPipeline #1334 (#1426) * 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 <anton@huggingface.co> Fix the order of casts for onnx inpainting (#1338) Legacy Inpainting Pipeline for Onnx Models (#1237) * Add legacy inpainting pipeline compatibility for onnx * remove commented out line * Add onnx legacy inpainting test * Fix slow decorators * pep8 styling * isort styling * dummy object * ordering consistency * style * docstring styles * Refactor common prompt encoding pattern * Update tests to permanent repository home * support all available schedulers until ONNX IO binding is available Co-authored-by: Anton Lozhkov <aglozhkov@gmail.com> * updated styling from PR suggested feedback Co-authored-by: Anton Lozhkov <aglozhkov@gmail.com> Jax infer support negative prompt (#1337) * support negative prompts in sd jax pipeline * pass batched neg_prompt * only encode when negative prompt is None 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: Patrick von Platen <patrick.v.platen@gmail.com> * move Mel to module in pipeline construction, make librosa optional * fix imports * fix copy & paste error in comment * fix style * add missing register_to_config * fix class docstrings * fix class docstrings * tweak docstrings * tweak docstrings * update slow test * put trailing commas back * respect alphabetical order * remove LatentAudioDiffusion, make vqvae optional * move Mel from models back to pipelines :-) * allow loading of pretrained audiodiffusion models * fix tests * fix dummies * remove reference to latent_audio_diffusion in docs * unused import * inherit from SchedulerMixin to make loadable * Apply suggestions from code review * Apply suggestions from code review Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
2022-12-05 10:06:30 -07:00
- local: api/pipelines/audio_diffusion
title: "Audio Diffusion"
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title: "Pipelines"
- sections:
- local: api/experimental/rl
title: "RL Planning"
title: "Experimental Features"
title: "API"