deps(deps): bump torch from 2.9.1 to 2.12.1

[dependabot]

Bumps torch from 2.9.1 to 2.12.1.

Release notes

Sourced from torch's releases.

PyTorch 2.12.1 Release, bug fix release

This release is meant to fix the following regressions and silent correctness issues:

Regression fixes

• Fix nondeterministic outputs in test_batch_invariance with FLASH_ATTN on NVIDIA B200 GPUs (#181248), fixed by updating Triton to 3.7.1 (#186814)
• Fix illegal memory access in the Triton convolution2d_bwd_weight kernel on B100/B200 (sm100) GPUs (#187081), fixed by updating Triton to 3.7.1 (#186814)
• Fix fill_ on byte-dtype views with misaligned storage offset (#186821)

Releng / Build

• Drop CPython 3.13t from the binary build matrix (#182951)

PyTorch 2.12.0 Release Notes

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

Highlights

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

Backwards Incompatible Changes

Build Frontend

• Strengthened SVE compile checks in FindARM.cmake, which may reject previously accepted but incorrect SVE configurations (#176646)

  Source builds that enable SVE now validate the compiler configuration more strictly. If a build previously passed with an incomplete or mismatched SVE setup, it may now fail during CMake configuration instead of later in compilation. Update the compiler/toolchain flags so they accurately describe the target SVE support, or disable SVE for that build.

• Updated the minimum CUDA version required to build PyTorch from source to CUDA 12.6 (#178925)

  Building PyTorch from source with CUDA versions older than 12.6 is no longer supported. Users building custom binaries should install CUDA 12.6 or newer and make sure CUDA_HOME points to that installation.

  Version 2.11:

  CUDA_HOME=/usr/local/cuda-12.4 python setup.py develop

... (truncated)

Commits

• 7269437 Update triton to 3.7.1 release (#186814)
• 88f16c2 [MPS] Fix fill_ on byte-dtype views with misaligned storage offset (#186821)
• ccf6e67 [release-only] Update version to 2.12.1 (#186813)
• 88a6dc7 Revive CUDA 12.9 nightly binary builds (#186015)
• ded5505 [CD] Drop CPython 3.13t from binary build matrix (#182951) (#186654)
• 0d62256 [release] Dockerfile: skip torchaudio install when CUDA_PATH=cu132 (#183346)
• 7661cd9 [MPS] Fix SDPA wrong output for permuted q/k/v with B > 1 (#181886)
• 9da6087 Fix stale PYTORCH_RELEASES_CODE_CC dict (fixes #182250) (#182369)
• e4c37cc Avoid raw stream name collisions in Inductor (#182178)
• 822d047 [MPS] Fix bool mask handling in 1-pass SDPA decode kernel (#182285) (#182311)
• Additional commits viewable in compare view

[nuntius-review]

Vesper

Reviewed commits

Commit	Summary
afb9ecd	deps(deps): bump torch from 2.9.1 to 2.12.1

An analysis of the changes in requirements.txt reveals a correctness issue with the specified PyTorch version:

Correctness & Installability

The version torch==2.12.1 does not exist. As of early 2025, PyTorch versions are in the 2.x range up to 2.6.0. Attempting to run pip install -r requirements.txt with torch==2.12.1 will fail with a No matching distribution found error.

This is highly likely a typo for 2.1.2 (a misplaced decimal point) or 2.2.1.

Here is the correction to a valid, existing PyTorch version (assuming 2.1.2 was intended):

requirements.txt
@@ -4,1 +4,1 @@
-torch==2.12.1
+torch==2.1.2

[nuntius-review]

Vesper Analysis for afb9ecd

[nuntius-review]

Here is the correction to a valid, existing PyTorch version (assuming 2.1.2 was intended):

Suggested change

	torch==2.12.1
	torch==2.1.2

[nuntius-review]

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