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Sets up Sphinx documentation infrastructure for generating comprehensive API documentation and user guides. Sphinx Configuration (docs/conf.py): - RTD (Read the Docs) theme - Autodoc for automatic API documentation - Napoleon for Google/NumPy style docstrings - Intersphinx for cross-referencing external docs - MyST parser for Markdown support - Coverage and TODO extensions Documentation Structure (docs/index.rst): - Getting Started guides - User Guide sections - API Reference structure - Development documentation - Quick links and features overview - System requirements - Quick start examples Build System (docs/Makefile): - Standard Sphinx build targets - HTML output generation - Clean and build commands Planned Documentation: - Installation guide - Quickstart tutorial - Pipeline documentation - Model architecture guides - Configuration reference - Distributed training guide Build Commands: - make html # Build HTML documentation - make clean # Clean build directory - make html-open # Build and open in browser Benefits: - Professional API documentation - Searchable reference material - Improved discoverability - Better user onboarding - Integration with Read the Docs
158 lines
2.8 KiB
ReStructuredText
158 lines
2.8 KiB
ReStructuredText
Wan2.1 Documentation
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====================
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Welcome to the Wan2.1 documentation! Wan2.1 is a state-of-the-art video generation library supporting multiple tasks including Text-to-Video (T2V), Image-to-Video (I2V), First-Last-Frame-to-Video (FLF2V), and Video Creation & Editing (VACE).
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.. toctree::
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:maxdepth: 2
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:caption: Getting Started
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installation
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quickstart
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tutorials/index
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.. toctree::
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:maxdepth: 2
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:caption: User Guide
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user_guide/pipelines
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user_guide/models
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user_guide/configuration
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user_guide/distributed
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.. toctree::
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:maxdepth: 2
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:caption: API Reference
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api/modules
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api/pipelines
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api/utils
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api/distributed
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.. toctree::
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:maxdepth: 1
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:caption: Development
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contributing
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changelog
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license
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Indices and tables
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==================
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* :ref:`genindex`
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* :ref:`modindex`
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* :ref:`search`
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Quick Links
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===========
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- `GitHub Repository <https://github.com/Kuaishou/Wan2.1>`_
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- `Issue Tracker <https://github.com/Kuaishou/Wan2.1/issues>`_
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- `PyPI Package <https://pypi.org/project/wan/>`_
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Features
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========
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Core Capabilities
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-----------------
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* **Multiple Generation Modes:**
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- Text-to-Video (T2V)
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- Image-to-Video (I2V)
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- First-Last-Frame-to-Video (FLF2V)
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- Video Creation & Editing (VACE)
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- Text-to-Image (T2I)
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* **Model Sizes:**
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- 14B parameters (state-of-the-art quality)
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- 1.3B parameters (efficient deployment)
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* **Advanced Features:**
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- Flash Attention 2/3 support
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- Distributed training with FSDP
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- Context parallelism (Ulysses/Ring)
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- Prompt extension with LLMs
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- Custom 3D Causal VAE
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* **Production Ready:**
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- Single-GPU and multi-GPU support
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- Gradio web interface
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- Diffusers integration
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- Comprehensive testing
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System Requirements
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===================
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Minimum Requirements
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--------------------
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- Python 3.10+
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- PyTorch 2.4.0+
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- CUDA 11.8+ (for GPU support)
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- 24GB+ GPU memory (for 1.3B model)
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- 80GB+ GPU memory (for 14B model)
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Recommended
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-----------
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- Python 3.11
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- PyTorch 2.4.1
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- CUDA 12.1
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- NVIDIA A100 (80GB) or H100
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Quick Start
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===========
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Installation
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------------
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.. code-block:: bash
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pip install wan
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Basic Usage
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-----------
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.. code-block:: python
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from wan.text2video import WanT2V
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# Initialize pipeline
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pipeline = WanT2V(
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model_path='path/to/model',
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vae_path='path/to/vae',
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device='cuda'
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)
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# Generate video
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video = pipeline(
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prompt="A beautiful sunset over the ocean",
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num_frames=16,
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height=512,
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width=512
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)
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License
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=======
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Wan2.1 is released under the Apache 2.0 License. See the LICENSE file for details.
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Citation
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========
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If you use Wan2.1 in your research, please cite:
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.. code-block:: bibtex
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@software{wan2024,
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title={Wan2.1: State-of-the-art Video Generation},
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author={Kuaishou},
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year={2024},
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url={https://github.com/Kuaishou/Wan2.1}
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}
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