ludwig

What's changed

Bug fixes

• Fixed LLM fine-tuning crash with torchao>=0.17 (#4170)
  torchao 0.17 requires torch>=2.11 (uses torch.utils._pytree.register_constant), but the previous Docker images shipped torch==2.6.0, causing an AttributeError on import. Ludwig itself now enforces torch>=2.11 so the combination can never resolve to an incompatible pair again.

• Fixed torchaudio / torchcodec audio loading — torchaudio>=2.11 delegates all audio I/O to torchcodec, which requires FFmpeg. The CI images and Docker images now install FFmpeg explicitly.

• Fixed CI dependency resolver poisoning — passing --extra-index-url https://download.pytorch.org/whl/cpu to the Ludwig [test] install step caused uv to resolve all packages (including datasets, ray, packaging) through the PyTorch wheel server, returning ancient versions. The install order is now: pin all torch-family packages from the CPU extra-index first, then install .[test] against plain PyPI.

Dependency changes

Updated lower bounds in pyproject.toml:

| Package | Old lower bound | New lower bound |
|---------|----------------|----------------|
| torch | >=1.13 | >=2.11 |
| torchaudio | >=0.13 | >=2.11 |
| torchvision | >=0.14 | >=0.26 |
| torchcodec | (new) | >=0.1 |
| transformers | >=4.36 | >=5.0 |
| torchao (llm extra) | >=0.8.0 | >=0.17.0 |

Docker images

All four images (ludwig, ludwig-ray, ludwig-gpu, ludwig-ray-gpu) are rebuilt with:

• torch==2.12.0
• torchvision==0.27.0
• torchaudio==2.11.0
• torchcodec (CPU/CUDA variant as appropriate)
• FFmpeg installed in the image

AutoML improvement

• Changed the default tabular combiner in AutoML from tabnet to ft_transformer, which generally performs better on tabular datasets.