Upgrade to cu130#4753
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Pull request overview
Updates the CUDA 13 (cu130) container stack and runtime dependency caps to support newer PyTorch / Triton versions, while improving Docker build determinism by installing torch/torchvision from the correct PyTorch CUDA index before resolving the rest of the requirements.
Changes:
- Bump CUDA runtime dependency upper bounds (torch/torchvision/triton) and update Triton environment checker max version.
- Refresh Docker images/stages to CUDA 13.0.3 / CUDA 12.8.1 on Ubuntu 24.04 and introduce
PYTORCH_CUDA_VERSIONto decouple “base CUDA” from “PyTorch wheel CUDA channel”. - Harden Docker install/build scripts: safer apt mirror rewrites, conditional Python PPA use, explicit torch install from the matching PyTorch index, and wheel presence/import checks.
Reviewed changes
Copilot reviewed 8 out of 8 changed files in this pull request and generated 1 comment.
Show a summary per file
| File | Description |
|---|---|
| requirements/runtime_cuda.txt | Updates torch/torchvision/triton version constraints for CUDA runtime installs. |
| lmdeploy/pytorch/check_env/triton.py | Raises the maximum Triton version considered “tested”. |
| docker/prepare_3rdparty_wheel.sh | Adjusts CUDA 13 detection and changes flash-attn-3 wheel acquisition strategy. |
| docker/install.sh | Makes Docker installs more deterministic (torch from correct index), adds validation and missing-wheel checks. |
| docker/Dockerfile_dev | Moves to Ubuntu 24.04 and installs torch/torchvision from PYTORCH_CUDA_VERSION index first. |
| docker/Dockerfile | Updates CUDA stages/images, adds PYTORCH_CUDA_VERSION, and improves wheel mounting/install flow. |
| docker/build.sh | Generalizes CUDA 13 detection for NCCL wheel selection. |
| builder/manywheel/README.md | Updates builder image examples to include CUDA 13.0. |
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| torch<=2.12.1,>=2.0.0 | ||
| torchvision<=0.27.1,>=0.15.0 |
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