fix(deps): update dependency timm to >=1.0.27

[renovate]

This PR contains the following updates:

Package	Change	Age	Confidence
timm	>=1.0.26 → >=1.0.27

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Release Notes

huggingface/pytorch-image-models (timm)

v1.0.27

Compare Source

April 23, 2026

• Add Gemma4 ViT encoders w/ NaFlex pipeline support (variable aspect/size per image). Thanks Yonghye Kwon
• Support DINOv3 weights in NaFlexVit. Thanks Yonghye Kwon
• Some improvements to Muon fallback (AdamW/NadamW) lr behavior

What's Changed

• 🔒 Pin GitHub Actions to commit SHAs by @​paulinebm in #​2689
• Improve fallback (adamw/nadamw) LR handling for Muon optimizer by @​rwightman in #​2688
• Fix NaFlexVit DINOv3 support: propagate rope_type and rotate_half by @​developer0hye in #​2692
• chore: bump doc-builder SHA for PR upload workflow by @​rtrompier in #​2694
• Gemma4 by @​rwightman in #​2697
• Add encoder_pool option to gemma4 classification model to toggle soft… by @​rwightman in #​2698
• Fix some performance regressions with torch.compile + Tasks. Fix #​2693 by @​rwightman in #​2699

New Contributors

• @​paulinebm made their first contribution in #​2689

Full Changelog: huggingface/pytorch-image-models@v1.0.26...v1.0.27

v1.0.26

Compare Source

March 23, 2026

• Improve pickle checkpoint handling security. Default all loading to weights_only=True, add safe_global for ArgParse.
• Improve attention mask handling for core ViT/EVA models & layers. Resolve bool masks, pass is_causal through for SSL tasks.
• Fix class & register token uses with ViT and no pos embed enabled.
• Add Patch Representation Refinement (PRR) as a pooling option in ViT. Thanks Sina (https://github.com/sinahmr).
• Improve consistency of output projection / MLP dimensions for attention pooling layers.
• Hiera model F.SDPA optimization to allow Flash Attention kernel use.
• Caution added to SGDP optimizer.
• Release 1.0.26. First maintenance release since my departure from Hugging Face.

What's Changed

• fix: replace 5 bare except clauses with except Exception by @​haosenwang1018 in #​2672
• Add timmx model export tool to README by @​Boulaouaney in #​2673
• Enhance SGDP optimizer with caution parameter by @​Yuan-Jinghui in #​2675
• Fix CLS and Reg tokens usage when pos_embed is disabled by @​sinahmr in #​2676
• default weights_only=True for load fns by @​rwightman in #​2679
• Fix Hiera global attention to use 4D tensors for efficient SDPA dispatch by @​Raiden129 in #​2680
• Improve 2d and latent attention pool dimension handling. Fix #​2682 by @​rwightman in #​2684
• Improve attention mask handling for vision_transformer and eva and related blocks by @​rwightman in #​2686
• Implement PRR as a pooling module. Alternative to #​2678 by @​rwightman in #​2685

New Contributors

• @​haosenwang1018 made their first contribution in #​2672
• @​Raiden129 made their first contribution in #​2680

Full Changelog: huggingface/pytorch-image-models@v1.0.25...v1.0.26

v1.0.25

Compare Source

Feb 23, 2026

• Add token distillation training support to distillation task wrappers
• Remove some torch.jit usage in prep for official deprecation
• Caution added to AdamP optimizer
• Call reset_parameters() even if meta-device init so that buffers get init w/ hacks like init_empty_weights
• Tweak Muon optimizer to work with DTensor/FSDP2 (clamp_ instead of clamp_min_, alternate NS branch for DTensor)
• Release 1.0.25

Jan 21, 2026

• Compat Break: Fix oversight w/ QKV vs MLP bias in ParallelScalingBlock (& DiffParallelScalingBlock)
  • Does not impact any trained timm models but could impact downstream use.

What's Changed

• Token distill task & distill task refactoring by @​rwightman in #​2647
• Fix distilled head dropout using wrong token in PiT forward_head by @​hassonofer in #​2649
• Fix #​2653, no models with weights impacted so just a clean fix by @​rwightman in #​2654
• Add the cautious optimizer to AdamP. by @​Yuan-Jinghui in #​2657
• Enhance the numerical stability of the Cautious Optimizer by @​Yuan-Jinghui in #​2658
• Some misc fixes for torch.jit deprecation and meta device init by @​rwightman in #​2664
• fix(optim): replace bare except with Exception in Lion optimizer by @​llukito in #​2666
• Change clamp_min_ to clamp_(min=) as former doesn't work with DTensor / FSDP2 by @​rwightman in #​2668
• Add DTensor compatible NS impl for Muon by @​rwightman in #​2669

New Contributors

• @​Yuan-Jinghui made their first contribution in #​2657
• @​llukito made their first contribution in #​2666

Full Changelog: huggingface/pytorch-image-models@v1.0.24...v1.0.25

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[renovate]

⚠️ Artifact update problem

Renovate failed to update an artifact related to this branch. You probably do not want to merge this PR as-is.

♻ Renovate will retry this branch, including artifacts, only when one of the following happens:

• any of the package files in this branch needs updating, or
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The artifact failure details are included below:

File name: MAGE/uv.lock

Command failed: uv lock --upgrade-package timm
Using CPython 3.14.4 interpreter at: /opt/containerbase/tools/python/3.14.4/bin/python3
  × No solution found when resolving dependencies for split (markers:
  │ sys_platform == 'darwin'):
  ╰─▶ Because litellm==1.83.3 depends on python-dotenv==1.0.1 and
      openrag==0.4.1 depends on litellm==1.83.3, we can conclude that
      openrag==0.4.1 depends on python-dotenv==1.0.1.
      And because only the following versions of openrag are available:
          openrag<=0.4.1
          openrag>0.5.0
      and aimer depends on openrag>=0.4.1, we can conclude that aimer depends
      on python-dotenv==1.0.1.
      And because aimer depends on python-dotenv==1.2.2 and your workspace
      requires aimer, we can conclude that your workspace's requirements are
      unsatisfiable.

      hint: The resolution failed for an environment that is not the current
      one, consider limiting the environments with `tool.uv.environments`.

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