* Add optional FP32 sampling state for Cosmos3
* Add cache execution contexts to Cosmos3 pipelines
* Add SeaCache support for Cosmos3
* Cap consecutive SeaCache reuses
* Align SeaCache defaults with Cosmos3 inference
* Enable SeaCache by default for Cosmos3
* Document SeaCache for Cosmos3
* Use FP32 sampling state by default for Cosmos3
* Fix SeaCache reconfiguration, transfer state isolation, and FP32 sampling
* Remove SeaCache stats and ablation instrumentation
* Move SeaCache to transformer-level and disable by default
* Align SeaCache and tests with model-level cache patterns
* Make Cosmos3 sampling state always FP32
* Add pipe definition to the docs snippet
* Remove redundant hook registry cache resets
* Use raw vision latents for SeaCache indicators
* Make Cosmos3 SeaCache safe for regional compilation
* Fix SeaCache with Cosmos3 model parallelism
* Support single-stream models in SeaCache
* Add Wan T2V support to SeaCache
* pass denoising step info to cache hooks via cache_context
Replaces SeaCache's pipeline-state callbacks: the pipeline attaches the loop
coordinates (step_index, sigma, num_inference_steps) to the denoiser call with
`cache_context(name, ...)`, carried by a frozen CacheContext dataclass and stored
on each stateful hook's StateManager (the registry no longer holds context).
Co-Authored-By: Dhruv Nair <dhruv.nair@gmail.com>
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
* Fix Wan cache metadata and Cosmos modular cleanup
Pass denoising step metadata to Wan T2V conditional and unconditional cache contexts.
Restore stateful cache reset after Cosmos modular pipeline calls, restore the required Literal import, and update regression tests and documentation.
* Refactor Cosmos3 SeaCache decoder hook
* Apply CI formatting updates
* Fix distilled system prompt fallback
* Preserve Cosmos3 fp32 sampling state
---------
Co-authored-by: yiyixuxu <yixu310@gmail.com>
Co-authored-by: Dhruv Nair <dhruv.nair@gmail.com>
Co-authored-by: Claude Fable 5 <noreply@anthropic.com>
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
docs: fix typos in docs, comments and docstrings
Prose, comments and docstrings only. No executable line changed.
docs/:
- optimization/memory.md: maxmium -> maximum; heigh -> height (in the
channels_last layout tuple, which read "(batch size, heigh, width,
channels)")
- api/pipelines/bria_fibo.md: proffesional -> professional
- api/pipelines/wan.md: involed -> involved
src/ comments and docstrings:
- guiders/magnitude_aware_guidance.py: supression -> suppression
- models/attention.py: spliting -> splitting
- models/attention_dispatch.py: abritrary -> arbitrary (x2)
- models/transformers/transformer_ltx2.py: timstamps -> timestamps (x2)
- pipelines/ltx2/pipeline_ltx2{,_image2video}.py: corrct -> correct
- pipelines/deprecated/unidiffuser/modeling_uvit.py: tbe -> the
- pipelines/visualcloze/pipeline_visualcloze_{combined,generation}.py:
"whe they are lists" -> "when they are lists" in a user-facing
ValueError message
Deliberately not touched:
- pipeline_kandinsky*.py "promt"/"scren" live inside prompt_template,
which is fed to the text encoder verbatim. Changing them would change
generation output.
- ANE (Apple Neural Engine), MoT (Mixture-of-Transformers): initialisms.
- "racoon": appears in prompt examples whose reference images were
generated with that exact prompt.
- "Shuting Wang": a paper author's name.
* docs: introduce cache-dit to diffusers
* docs: introduce cache-dit to diffusers
* docs: introduce cache-dit to diffusers
* docs: introduce cache-dit to diffusers
* docs: introduce cache-dit to diffusers
* docs: introduce cache-dit to diffusers
* docs: introduce cache-dit to diffusers
* misc: update examples link
* misc: update examples link
* docs: introduce cache-dit to diffusers
* docs: introduce cache-dit to diffusers
* docs: introduce cache-dit to diffusers
* docs: introduce cache-dit to diffusers
* docs: introduce cache-dit to diffusers
* Refine documentation for CacheDiT features
Updated the wording for clarity and consistency in the documentation. Adjusted sections on cache acceleration, automatic block adapter, patch functor, and hybrid cache configuration.
* Add Pruna optimization framework documentation
- Introduced a new section for Pruna in the table of contents.
- Added comprehensive documentation for Pruna, detailing its optimization techniques, installation instructions, and examples for optimizing and evaluating models
* Enhance Pruna documentation with image alt text and code block formatting
- Added alt text to images for better accessibility and context.
- Changed code block syntax from diff to python for improved clarity.
* Add installation section to Pruna documentation
- Introduced a new installation section in the Pruna documentation to guide users on how to install the framework.
- Enhanced the overall clarity and usability of the documentation for new users.
* Update pruna.md
* Update pruna.md
* Update Pruna documentation for model optimization and evaluation
- Changed section titles for consistency and clarity, from "Optimizing models" to "Optimize models" and "Evaluating and benchmarking optimized models" to "Evaluate and benchmark models".
- Enhanced descriptions to clarify the use of `diffusers` models and the evaluation process.
- Added a new example for evaluating standalone `diffusers` models.
- Updated references and links for better navigation within the documentation.
* Refactor Pruna documentation for clarity and consistency
- Removed outdated references to FLUX-juiced and streamlined the explanation of benchmarking.
- Enhanced the description of evaluating standalone `diffusers` models.
- Cleaned up code examples by removing unnecessary imports and comments for better readability.
* Apply suggestions from code review
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Enhance Pruna documentation with new examples and clarifications
- Added an image to illustrate the optimization process.
- Updated the explanation for sharing and loading optimized models on the Hugging Face Hub.
- Clarified the evaluation process for optimized models using the EvaluationAgent.
- Improved descriptions for defining metrics and evaluating standalone diffusers models.
---------
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
