build(deps-dev): bump torch from 2.11.0 to 2.13.0

[dependabot]

Bumps torch from 2.11.0 to 2.13.0.

Release notes

Sourced from torch's releases.

PyTorch 2.13.0 Release Notes

• Highlights
• Backwards Incompatible Changes
• Deprecations
• New Features
• Improvements
• Bug fixes
• Performance
• Documentation
• Developers

Highlights

For more details about these highlighted features, you can look at the release blogpost. Below are the full release notes for this release.

Tracked Regressions

ROCm wheels break torch.compile on CPU in environments without a GPU

Running a torch==2.13.0+rocm7.2 wheel in an environment where no GPU is available (torch.cuda.is_available() is False) breaks torch.compile on the CPU path: the first compile raises RuntimeError: Can't detect vectorized ISA for CPU (#189194). This is a regression from torch==2.12.1+rocm7.2, which compiles CPU code fine (detecting e.g. VecAVX2) in the same setup. The 2.13 ROCm wheel appears to rely on something present in the ROCm builder image to detect the CPU vectorized ISA, so it works when run on a ROCm image but fails on a plain CPU-only image.

Workaround: run the +rocm wheel on a ROCm image, or install a standard CPU/CUDA build for GPU-less environments.

Backwards Incompatible Changes

• Stop building CPython 3.13t (free-threaded) binaries (#182951)

  Upstream pypa/manylinux removed CPython 3.13t (free-threaded) on 2026-05-07, because 3.13t was experimental and has been superseded by the now-non-experimental CPython 3.14t. As a result, PyTorch 2.13 no longer ships cp313t wheels (Linux, Triton, and related artifacts). Users on the free-threaded interpreter should move to Python 3.14t.

  PyTorch 2.12:

  # cp313t (free-threaded 3.13) wheels were available
  python3.13t -m pip install torch

  PyTorch 2.13:

... (truncated)

Commits

• cf30153 [release/2.13] Strip +PTX from CUDA arch list on release/RC builds (#188914) ...
• 3e3e24b [release/2.13] Restrict cuda-bindings to Python < 3.15 for CUDA 12.9 builds (...
• 7986b06 [release/2.13] Bump binary build timeout 280 -> 400 minutes (#188551)
• 0bdbc26 [release/2.13] Add CUDA 12.9 to TORCH_CUDA_ARCH_LIST tables (#188443)
• 9cabb45 [release/2.13] Update manywheel docker image pin to 78e737ad (#188409)
• 78e737a [release/2.13] Revert "Tighten generalized scatter graph target (#184075)" (#...
• 0bb9b5b [release/2.13] Revert "dynamo: round-trip torch.cuda.stream ctx mgr across gr...
• aaac2bf [release/2.13] Revert "[Reland] Port D104346887/PR 182675 for index_add fast ...
• 9330813 Fix build_with_debinfo.py broken by CONFIGURE_DEPENDS globbing (#188192)
• 4e077a7 Remove setuptools upper bound (#188190)
• Additional commits viewable in compare view

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Note

Medium Risk
Major PyTorch/CUDA stack bump affects GPU examples and CI installs; 2.13 drops cp313t wheels and may introduce runtime or compile behavior changes on Linux CUDA paths.

Overview
Updates uv.lock only (Dependabot): torch 2.11.0 → 2.13.0, with aligned torchvision 0.26.0 → 0.28.0 and triton 3.6.0 → 3.7.1.

The lock refresh also pulls newer CUDA 13 meta-packages and NVIDIA wheels (cuda-toolkit, nvidia-cublas, nvidia-cudnn-cu13, nvidia-nccl-cu13, etc.), including tighter platform_machine markers on several cuda-toolkit extras. exclude-newer is set to the epoch timestamp with a comment for compatibility with relative exclude-newer settings.

Wheel sets change with the PyTorch release (e.g. macOS 14 arm64 torch/torchvision artifacts; no cp313t torch/triton wheels in the new resolution). No application or pyproject source edits in this diff.

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Note

Bump dev dependency torch from 2.11.0 to 2.13.0

Updates the torch dev dependency in uv.lock to the latest version.

^{Macroscope summarized 38c070e.}

[macroscopeapp]

Approvability

Verdict: Approved

Standard dependabot dependency update bumping torch from 2.11.0 to 2.13.0 in the lock file. No application code changes - only pinned dependency versions are updated.

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