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v2.0.0 - Python 3.14 Exclusive Runtime & Multi-Platform Compatibility

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@ussoewwin ussoewwin released this 29 Aug 22:51
· 46 commits to main since this release
v2.0.0
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Version 2.0.0 — Python 3.14 Exclusive Runtime & Multi-Platform Compatibility

This major release transitions the Forge runtime environment exclusively to Python 3.14 across Windows and Linux (CUDA 13.2 / PyTorch 2.13 stack), providing automated universal wheel installations, native Linux and Windows Nunchaku 1.3.0 wheels, SageAttention 3 (SA3 / Blackwell FP4) backend support, and runtime compatibility fixes.

1. Summary

Item Detail
Runtime Target Python 3.14 exclusively (CUDA 13.2 / PyTorch 2.13) on Windows & Linux
Universal Wheels Automated installation of distutils, pyaudioop, imghdr, facexlib, and gradio 4.40.0
Nunchaku 1.3.0 Prebuilt Python 3.14 wheels for both Windows (win_amd64) and Linux (linux_x86_64)
Attention Backends Native runtime switching between Default (SDPA), SA2 (SageAttention 2), SA3 (SageAttention 3 / Blackwell FP4), and FA2 (FlashAttention 2)
Audio Compatibility Built-in torchaudio_compat providing standard ModuleSpec stub for Python 3.14
Architecture Fixes Fixed StableDiffusionProcessing.sd_model synchronization and eliminated module variable shadowing in modules/shared.py
Memory Management Fixed config.json persistence for CUDA Stream (Async) and Pinned Memory (Shared)

2. Key Changes & Technical Details

2.1 Python 3.14 Universal Wheel Distribution

To support Python 3.14 without manual compilation or missing legacy standard library modules:

  • distutils: Bundled custom universal wheel (distutils-3.14.0-py3-none-any.whl).
  • pyaudioop & imghdr: Bundled pure Python standard library replacement wheels for removed 3.13/3.14 modules.
  • facexlib: Built pure Python universal wheel (facexlib-0.3.0-py3-none-any.whl) stripping numba and filterpy hard dependencies, with embedded version.py and pure Python fallback JIT decorators for @jit functions.
  • gradio 4.40.0: Bundled dependency-unpinned universal wheel with OpenAPI boolean schema conversion patches (modules_forge/transformers_cache_compat.py).

2.2 Nunchaku 1.3.0 Prebuilt Wheels (Windows & Linux)

Integrated prebuilt binary wheels for Python 3.14 on CUDA 13.2:

  • Windows: https://huggingface.co/ussoewwin/nunchaku-built-on-cu132/resolve/main/nunchaku-1.3.0.dev20260619%2Bcu13.2torch2.12-cp314-cp314-win_amd64.whl
  • Linux: https://huggingface.co/ussoewwin/nunchaku-built-on-cu132/resolve/main/nunchaku-1.3.0.dev20260829%2Bcu13.2torch2.13-cp314-cp314-linux_x86_64.whl

2.3 SageAttention 3 (SA3 / Blackwell FP4) & Attention Backends

  • Added sageattn3 wheel auto-installation (sageattn3-1.0.0+cu132torch2.13.0-cp314-cp314-win_amd64.whl).
  • Full runtime Attention switching across Default, SA2, SA3, and FA2 in quicksettings.

2.4 Torchaudio Compatibility & SD Model Property Synchronization

  • Added modules_forge/torchaudio_compat.py with valid importlib.machinery.ModuleSpec to satisfy transformers and diffusers import guards without requiring binary torchaudio.
  • Removed static sd_model = None in modules/shared.py to prevent shadowing dynamic descriptor properties on Shared module class.
  • Configured StableDiffusionProcessing.sd_model as init=False dataclass field to prevent accidental None resets during processing instance construction.

3. Install & Update Notes

  1. Pull the latest repository changes: 
    git pull
  2. Verify Python version is Python 3.14: 
    python --version
  3. Launch WebUI via webui-user.bat (Windows) or webui.sh (Linux). All necessary universal wheels and dependencies will be automatically verified and installed on first startup.

4. Related Links

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