Files
hao-ai-lab-FastVideo/docs
82e532727f feat(api): typed per-component CompileConfig + FastVideoArgs carriers
Extend the typed inference API so callers can drive torch.compile per
component without falling back to the legacy flat-kwargs pathway.

* ``CompileConfig`` now exposes ``vae_enabled``, ``audio_vae_enabled``,
  ``dit_kwargs``, ``text_encoder_kwargs``, ``vae_kwargs``,
  ``audio_vae_kwargs`` alongside the existing ``enabled`` /
  ``text_encoder_enabled`` switches. The master ``backend``/
  ``fullgraph``/``mode``/``dynamic``/``extras`` continue to apply to
  every compiled submodule unless a per-component kwargs dict is
  non-empty (in which case it overrides entirely — matches the
  FastVideo-internal precedent).
* Add the matching runtime carrier fields on ``FastVideoArgs``:
  ``enable_torch_compile_text_encoder/vae/audio_vae`` plus
  ``torch_compile_kwargs_dit/text_encoder/vae/audio_vae``. These let
  the legacy flat-kwargs path round-trip through the typed config.
* ``api/compat.legacy_from_pretrained_to_config`` now lifts the new
  flat kwargs into ``CompileConfig``, and
  ``generator_config_to_fastvideo_args`` writes them back out so
  ``VideoGenerator.from_pretrained(model_path, ...)`` callers keep
  working unchanged.

No behavior change yet — these surfaces are ports of carriers only.
The composed pipeline base will start consuming them in the next
commit.

Co-authored-by: Junda (David) Su <90978028+Davids048@users.noreply.github.com>
Co-authored-by: Matthew Noto <99706358+RandNMR73@users.noreply.github.com>
Co-authored-by: XOR-op <17672363+XOR-op@users.noreply.github.com>
Co-authored-by: Zhang Peiyuan <42993249+jzhang38@users.noreply.github.com>
2026-05-07 13:37:25 -07:00
..
2026-02-23 15:14:42 -08:00
2026-02-19 14:23:32 -08:00
2026-03-09 18:58:56 -07:00
2026-02-23 15:14:42 -08:00
2026-02-23 15:14:42 -08:00

FastVideo Documentation

This directory contains the FastVideo documentation built with MkDocs.

Build the docs locally

# Install dependencies
uv pip install -r requirements-mkdocs.txt

# Serve docs with live reload (recommended for development)
mkdocs serve

# Or build static site
mkdocs build

View the docs

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mkdocs serve

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mkdocs build
python -m http.server -d site/

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