build(deps): update torch requirement from ==2.13.0.* to ==2.14.0.* in /skills/remove-ai-marks/scripts

[dependabot]

Updates the requirements on torch to permit the latest version.

Release notes

Sourced from torch's releases.

PyTorch 2.14.0 Release Notes

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

Backwards Incompatible Changes

torch.nn

• torch.nn.LinearCrossEntropyOptions no longer accepts acc_policy="balanced"; use "compact" instead (#188283)

  The "balanced" policy was removed because "compact" provides the same weight-gradient accumulation precision with lower memory use on CUDA, already uses the equivalent scratch layout for mixed-precision inputs on other devices, and was never selected by "auto". Constructing the options with acc_policy="balanced" now raises ValueError: invalid acc_policy: 'balanced'; expected one of 'auto', 'accurate', 'compact'.

  Before:

  options = torch.nn.LinearCrossEntropyOptions(acc_policy="balanced")
  loss = torch.nn.functional.linear_cross_entropy(
      input, linear_weight, target, options=options
  )

  After:

  options = torch.nn.LinearCrossEntropyOptions(acc_policy="compact")
  loss = torch.nn.functional.linear_cross_entropy(

... (truncated)

Changelog

Sourced from torch's changelog.

Releasing PyTorch

• Release Compatibility Matrix
  • PyTorch CUDA Support Matrix
• Release Cadence
• General Overview
  • Frequently Asked Questions
• Cutting a release branch preparations
• Cutting release branches
  • pytorch/pytorch
  • PyTorch ecosystem libraries
  • Making release branch specific changes for PyTorch
  • Making release branch specific changes for ecosystem libraries
• Running Launch Execution team Core XFN sync
• Drafting RCs (https://github.com/pytorch/pytorch/blob/main/Release Candidates) for PyTorch and domain libraries
  • Release Candidate Storage
  • Release Candidate health validation
  • Cherry Picking Fixes
    • How to do Cherry Picking
  • Cherry Picking Reverts
• Preparing and Creating Final Release Candidate
• Promoting RCs to Stable
• Additional Steps to prepare for release day
  • Modify release matrix
  • Open Google Colab issue
• Patch Releases
  • Patch Release Criteria
  • Patch Release Process
    • Patch Release Process Description
    • Triage
    • Issue Tracker for Patch releases
    • Building a release schedule / cherry picking
    • Building Binaries / Promotion to Stable
• Hardware / Software Support in Binary Build Matrix
  • Python
  • Accelerator Software
    • Special support cases
  • Operating Systems
• Submitting Tutorials
• Special Topics
  • Updating submodules for a release
  • Triton dependency for the release

Release Compatibility Matrix

Following is the Release Compatibility Matrix for PyTorch releases:

... (truncated)

Commits

• 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)
• 65890f3 Fix docker-release validate job to use the channel matching the pushed image ...
• 1682388 Fix macOS py3.15 wheel builds: pin Cython < 3.3.0 and bump the cp315 numpy pi...
• 9724418 Fix Windows py3.15 builds: constrain Cython < 3.3.0 and bump the cp315 numpy ...
• f1b7554 [MPS] Fix pin_memory() recycling buffers still in use by the GPU (#194662)
• 9f205f7 [MPS] fail loudly on large reductions (#194661)
• Additional commits viewable in compare view

[elkaix]

@dependabot rebase

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