[dependabot]

Updates the requirements on torch and transformers to permit the latest version.
Updates torch to 2.14.1

Release notes

Sourced from torch's releases.

PyTorch 2.14.1 Release

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

Silent correctness fixes

• Fix incorrect torch.linalg.lstsq solutions on MPS for complex batched underdetermined systems (#196113), fixed by #196128
• Fix non-orthogonal U and inaccurate small singular values from torch.linalg.svd on MPS for rank-deficient and ill-conditioned inputs (#196112), fixed by #196139 and #199063
• Update the CUDA 13.2 Linux binaries to CUDA 13.2.2 (#196351). This NVIDIA update resolves two critical issues that could produce incorrect results (CUDA 13.2.2 release notes):
  • cuBLAS: cublasLtMatmul() could ignore tensor-wide scaling for NVFP4 matrix multiplications (introduced in CUDA 13.2 Update 1)
  • Compiler: failed thread reconvergence could leave stale or corrupted register values in kernels with nested thread divergence (present since CUDA 12.8)

Regression fixes

• Fix torch.linalg.svd, torch.linalg.svdvals and torch.linalg.lstsq failing on MPS with a Metal pipeline-state error for inputs above 8192 elements (#195937), fixed by #195949 and #195950
• Fix internal assert in torch.svd(out=) on MPS for complex inputs (#195822), fixed by #195872

Changelog

Sourced from torch's changelog.

Releasing PyTorch

• Release Compatibility Matrix
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• Cutting a release branch preparations
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  • Making release branch specific changes for PyTorch
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• Running Launch Execution team Core XFN sync
• Drafting RCs (https://github.com/pytorch/pytorch/blob/main/Release Candidates) for PyTorch and domain libraries
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  • Python
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  • Updating submodules for a release
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Release Compatibility Matrix

Following is the Release Compatibility Matrix for PyTorch releases:

... (truncated)

Commits

• 5c48869 [MPS] Fix Jacobi SVD convergence for small columns (#199086)
• 35223a2 [release/2.14] Run the release runner-group reconcile in pytorch/pytorch (#19...
• 41ffbc4 [release-only] Update version to 2.14.1 (#198661)
• e8f0c01 [release/2.14] [CD] Update to CUDA 13.2.2 for Linux binaries (#198644)
• 911665d [MPS] Cherry-pick native SVD fixes into release/2.14 (#198394)
• 2b3ec34 [release/2.14] Import SDPAParams in test_transformers to fix lint (#194970)
• 08187d9 [cuDNN] Add guards for cuDNN SDPA decode (#194963)
• 8ceea97 Pin cython < 3.3.0 for the Windows Triton wheel build (#194931)
• 99ecebc [Cherry-pick][release/2.14] [inductor] Fix loop-local load CSE lifetime (#194...
• ec283a7 Bump the Python 3.15 numpy pin to 2.5.2 (#194821)
• Additional commits viewable in compare view

Updates transformers to 5.20.2

Release notes

Sourced from transformers's releases.

Patch release v5.20.2

Patch release: v5.20.2

This patch notably solves an issue where some inputs could loose their original type inside prepare_inputs_for_generation in generate, leading to problems with multimodal models. It also fixes some other issues listed on the below commits.

It contains the following commits:

• Fix inputs dict casting in generate (#49731) by @​Cyrilvallez
• Fix zero expert gradients in bfloat16 with expert parallelism and ep_size < fsdp_size (#49688) by @​qgallouedec
• Declare the input modalities of the VLMs that report text only (#49677) by @​qgallouedec
• Avoid a host-to-device copy in eager_mask (#49684) by @​hmellor

Commits

• 18329f1 Release: v5.20.2
• 2ce3082 Avoid a host-to-device copy in eager_mask (#49684)
• 62bc6fd Declare the input modalities of the VLMs that report text only (#49677)
• 30f4e38 Fix zero expert gradients in bfloat16 with expert parallelism and ep_size < f...
• ce8231f Fix inputs dict casting in generate (#49731)
• 0ea8779 v5.20.1
• de4f35f Fix small bug in auto mappings (#49664)
• 759c538 Make DtensorShardOperation work on torch 2.6 and 2.7 (#49657)
• c180e2d Fix from_pretrained on torch 2.7: require torch>=2.8 for distributed checkpoi...
• 10d36aa Fix DeepGEMM Mega MoE under expert parallelism (#49428)
• Additional commits viewable in compare view

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