chore(deps): update dependency timm to v1.0.14

[renovate]

This PR contains the following updates:

Package	Change	Age	Adoption	Passing	Confidence
timm	==1.0.11 -> ==1.0.14

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Release Notes

huggingface/pytorch-image-models (timm)

v1.0.14

Compare Source

Jan 19, 2025

• Fix loading of LeViT safetensor weights, remove conversion code which should have been deactivated
• Add 'SO150M' ViT weights trained with SBB recipes, decent results, but not optimal shape for ImageNet-12k/1k pretrain/ft
  • vit_so150m_patch16_reg4_gap_256.sbb_e250_in12k_ft_in1k - 86.7% top-1
  • vit_so150m_patch16_reg4_gap_384.sbb_e250_in12k_ft_in1k - 87.4% top-1
  • vit_so150m_patch16_reg4_gap_256.sbb_e250_in12k
• Misc typing, typo, etc. cleanup
• 1.0.14 release to get above LeViT fix out

What's Changed

• Fix nn.Module type hints by @​adamjstewart in https://github.com/huggingface/pytorch-image-models/pull/2400
• Add missing paper title by @​JosuaRieder in https://github.com/huggingface/pytorch-image-models/pull/2405
• fix 'timm recipe scripts' link by @​JosuaRieder in https://github.com/huggingface/pytorch-image-models/pull/2404
• fix typo in EfficientNet docs by @​JosuaRieder in https://github.com/huggingface/pytorch-image-models/pull/2403
• disable abbreviating csv inference output with ellipses by @​JosuaRieder in https://github.com/huggingface/pytorch-image-models/pull/2402
• fix incorrect LaTeX formulas by @​JosuaRieder in https://github.com/huggingface/pytorch-image-models/pull/2406
• VGG ConvMlp: fix layer defaults/types by @​adamjstewart in https://github.com/huggingface/pytorch-image-models/pull/2409
• Implement --no-console-results in inference.py by @​JosuaRieder in https://github.com/huggingface/pytorch-image-models/pull/2408
• LeViT safetensors load is broken by conversion code that wasn't deactivated by @​rwightman in https://github.com/huggingface/pytorch-image-models/pull/2412
• A few more weights by @​rwightman in https://github.com/huggingface/pytorch-image-models/pull/2413
• Fix typos by @​JosuaRieder in https://github.com/huggingface/pytorch-image-models/pull/2415

New Contributors

• @​adamjstewart made their first contribution in https://github.com/huggingface/pytorch-image-models/pull/2400

Full Changelog: huggingface/pytorch-image-models@v1.0.13...v1.0.14

v1.0.13

Compare Source

Jan 9, 2025

• Add support to train and validate in pure bfloat16 or float16
• wandb project name arg added by https://github.com/caojiaolong, use arg.experiment for name
• Fix old issue w/ checkpoint saving not working on filesystem w/o hard-link support (e.g. FUSE fs mounts)
• 1.0.13 release

Jan 6, 2025

• Add torch.utils.checkpoint.checkpoint() wrapper in timm.models that defaults use_reentrant=False, unless TIMM_REENTRANT_CKPT=1 is set in env.

Dec 31, 2024

• convnext_nano 384x384 ImageNet-12k pretrain & fine-tune. https://huggingface.co/models?search=convnext_nano%20r384
• Add AIM-v2 encoders from https://github.com/apple/ml-aim, see on Hub: https://huggingface.co/models?search=timm%20aimv2
• Add PaliGemma2 encoders from https://github.com/google-research/big_vision to existing PaliGemma, see on Hub: https://huggingface.co/models?search=timm%20pali2
• Add missing L/14 DFN2B 39B CLIP ViT, vit_large_patch14_clip_224.dfn2b_s39b
• Fix existing RmsNorm layer & fn to match standard formulation, use PT 2.5 impl when possible. Move old impl to SimpleNorm layer, it's LN w/o centering or bias. There were only two timm models using it, and they have been updated.
• Allow override of cache_dir arg for model creation
• Pass through trust_remote_code for HF datasets wrapper
• inception_next_atto model added by creator
• Adan optimizer caution, and Lamb decoupled weighgt decay options
• Some feature_info metadata fixed by https://github.com/brianhou0208
• All OpenCLIP and JAX (CLIP, SigLIP, Pali, etc) model weights that used load time remapping were given their own HF Hub instances so that they work with hf-hub: based loading, and thus will work with new Transformers TimmWrapperModel

What's Changed

• Punch cache_dir through model factory / builder / pretrain helpers by @​rwightman in https://github.com/huggingface/pytorch-image-models/pull/2356
• Yuweihao inception next atto merge by @​rwightman in https://github.com/huggingface/pytorch-image-models/pull/2360
• Dataset trust remote tweaks by @​rwightman in https://github.com/huggingface/pytorch-image-models/pull/2361
• Add --dataset-trust-remote-code to the train.py and validate.py scripts by @​grodino in https://github.com/huggingface/pytorch-image-models/pull/2328
• Fix feature_info.reduction by @​brianhou0208 in https://github.com/huggingface/pytorch-image-models/pull/2369
• Add caution to Adan. Add decouple decay option to LAMB. by @​rwightman in https://github.com/huggingface/pytorch-image-models/pull/2357
• Switching to timm specific weight instances for open_clip image encoders by @​rwightman in https://github.com/huggingface/pytorch-image-models/pull/2376
• Fix broken image link in Quickstart doc by @​ariG23498 in https://github.com/huggingface/pytorch-image-models/pull/2381
• Supporting aimv2 encoders by @​rwightman in https://github.com/huggingface/pytorch-image-models/pull/2379
• fix: minor typos in markdowns by @​ruidazeng in https://github.com/huggingface/pytorch-image-models/pull/2382
• Add 384x384 in12k pretrain and finetune for convnext_nano by @​rwightman in https://github.com/huggingface/pytorch-image-models/pull/2384
• Fixed unfused attn2d scale by @​laclouis5 in https://github.com/huggingface/pytorch-image-models/pull/2387
• Fix MQA V2 by @​laclouis5 in https://github.com/huggingface/pytorch-image-models/pull/2388
• Wrap torch checkpoint() fn to default use_reentrant flag to False and allow env var override by @​rwightman in https://github.com/huggingface/pytorch-image-models/pull/2394
• Add half-precision (bfloat16, float16) support to train & validate scripts by @​rwightman in https://github.com/huggingface/pytorch-image-models/pull/2397
• Merging wandb project name chages w/ addition by @​rwightman in https://github.com/huggingface/pytorch-image-models/pull/2398

New Contributors

• @​brianhou0208 made their first contribution in https://github.com/huggingface/pytorch-image-models/pull/2369
• @​ariG23498 made their first contribution in https://github.com/huggingface/pytorch-image-models/pull/2381
• @​ruidazeng made their first contribution in https://github.com/huggingface/pytorch-image-models/pull/2382
• @​laclouis5 made their first contribution in https://github.com/huggingface/pytorch-image-models/pull/2387

Full Changelog: huggingface/pytorch-image-models@v1.0.12...v1.0.13

v1.0.12

Compare Source

Nov 28, 2024

• More optimizers
  • Add MARS optimizer (https://arxiv.org/abs/2411.10438, https://github.com/AGI-Arena/MARS)
  • Add LaProp optimizer (https://arxiv.org/abs/2002.04839, https://github.com/Z-T-WANG/LaProp-Optimizer)
  • Add masking from 'Cautious Optimizers' (https://arxiv.org/abs/2411.16085, https://github.com/kyleliang919/C-Optim) to Adafactor, Adafactor Big Vision, AdamW (legacy), Adopt, Lamb, LaProp, Lion, NadamW, RMSPropTF, SGDW
  • Cleanup some docstrings and type annotations re optimizers and factory
• Add MobileNet-V4 Conv Medium models pretrained on in12k and fine-tuned in1k @​ 384x384
  • https://huggingface.co/timm/mobilenetv4\_conv_medium.e250\_r384\_in12k_ft_in1k
  • https://huggingface.co/timm/mobilenetv4\_conv_medium.e250\_r384\_in12k
  • https://huggingface.co/timm/mobilenetv4\_conv_medium.e180\_ad_r384\_in12k
  • https://huggingface.co/timm/mobilenetv4\_conv_medium.e180\_r384\_in12k
• Add small cs3darknet, quite good for the speed
  • https://huggingface.co/timm/cs3darknet_focus_s.ra4\_e3600\_r256\_in1k

Nov 12, 2024

• Optimizer factory refactor
  • New factory works by registering optimizers using an OptimInfo dataclass w/ some key traits
  • Add list_optimizers, get_optimizer_class, get_optimizer_info to reworked create_optimizer_v2 fn to explore optimizers, get info or class
  • deprecate optim.optim_factory, move fns to optim/_optim_factory.py and optim/_param_groups.py and encourage import via timm.optim
• Add Adopt (https://github.com/iShohei220/adopt) optimizer
• Add 'Big Vision' variant of Adafactor (https://github.com/google-research/big_vision/blob/main/big_vision/optax.py) optimizer
• Fix original Adafactor to pick better factorization dims for convolutions
• Tweak LAMB optimizer with some improvements in torch.where functionality since original, refactor clipping a bit
• dynamic img size support in vit, deit, eva improved to support resize from non-square patch grids, thanks https://github.com/wojtke

Oct 31, 2024

Add a set of new very well trained ResNet & ResNet-V2 18/34 (basic block) weights. See https://huggingface.co/blog/rwightman/resnet-trick-or-treat

Oct 19, 2024

• Cleanup torch amp usage to avoid cuda specific calls, merge support for Ascend (NPU) devices from MengqingCao that should work now in PyTorch 2.5 w/ new device extension autoloading feature. Tested Intel Arc (XPU) in Pytorch 2.5 too and it (mostly) worked.

What's Changed

• mambaout.py: fixed bug by @​NightMachinery in https://github.com/huggingface/pytorch-image-models/pull/2305
• Cleanup some amp related behaviour to better support different (non-cuda) devices by @​rwightman in https://github.com/huggingface/pytorch-image-models/pull/2308
• Add NPU backend support for val and inference by @​MengqingCao in https://github.com/huggingface/pytorch-image-models/pull/2109
• Update some clip pretrained weights to point to new hub locations by @​rwightman in https://github.com/huggingface/pytorch-image-models/pull/2311
• ResNet vs MNV4 v1/v2 18 & 34 weights by @​rwightman in https://github.com/huggingface/pytorch-image-models/pull/2316
• Replace deprecated positional argument with --data-dir by @​JosuaRieder in https://github.com/huggingface/pytorch-image-models/pull/2322
• Fix typo in train.py: bathes > batches by @​JosuaRieder in https://github.com/huggingface/pytorch-image-models/pull/2321
• Fix positional embedding resampling for non-square inputs in ViT by @​wojtke in https://github.com/huggingface/pytorch-image-models/pull/2317
• Add trust_remote_code argument to ReaderHfds by @​grodino in https://github.com/huggingface/pytorch-image-models/pull/2326
• Extend train epoch schedule by warmup_epochs if warmup_prefix enabled by @​rwightman in https://github.com/huggingface/pytorch-image-models/pull/2325
• Extend existing unit tests using Cover-Agent by @​mrT23 in https://github.com/huggingface/pytorch-image-models/pull/2331
• An impl of adafactor as per big vision (scaling vit) changes by @​rwightman in https://github.com/huggingface/pytorch-image-models/pull/2320
• Add py.typed file as recommended by PEP 561 by @​antoinebrl in https://github.com/huggingface/pytorch-image-models/pull/2252
• Add CODE_OF_CONDUCT.md and CITATION.cff files by @​AlinaImtiaz018 in https://github.com/huggingface/pytorch-image-models/pull/2333
• Add some 384x384 small model weights by @​rwightman in https://github.com/huggingface/pytorch-image-models/pull/2334
• In dist training, update loss running avg every step, sync on log by @​rwightman in https://github.com/huggingface/pytorch-image-models/pull/2340
• Improve WandB logging by @​sinahmr in https://github.com/huggingface/pytorch-image-models/pull/2341
• A few weights to merge Friday by @​rwightman in https://github.com/huggingface/pytorch-image-models/pull/2343
• Update timm torchvision resnet weight urls to the updated urls in torchvision by @​JohannesTheo in https://github.com/huggingface/pytorch-image-models/pull/2346
• More optimizer updates, add MARS, LaProp, add Adopt fix and more by @​rwightman in https://github.com/huggingface/pytorch-image-models/pull/2347
• Cautious optimizer impl plus some typing cleanup. by @​rwightman in https://github.com/huggingface/pytorch-image-models/pull/2349
• Add cautious mars, improve test reliability by skipping grad diff for… by @​rwightman in https://github.com/huggingface/pytorch-image-models/pull/2351
• See if we can avoid some model / layer pickle issues with the aa attr in ConvNormAct by @​rwightman in https://github.com/huggingface/pytorch-image-models/pull/2353

New Contributors

• @​MengqingCao made their first contribution in https://github.com/huggingface/pytorch-image-models/pull/2109
• @​JosuaRieder made their first contribution in https://github.com/huggingface/pytorch-image-models/pull/2322
• @​wojtke made their first contribution in https://github.com/huggingface/pytorch-image-models/pull/2317
• @​grodino made their first contribution in https://github.com/huggingface/pytorch-image-models/pull/2326
• @​AlinaImtiaz018 made their first contribution in https://github.com/huggingface/pytorch-image-models/pull/2333
• @​sinahmr made their first contribution in https://github.com/huggingface/pytorch-image-models/pull/2341
• @​JohannesTheo made their first contribution in https://github.com/huggingface/pytorch-image-models/pull/2346

Full Changelog: huggingface/pytorch-image-models@v1.0.11...v1.0.12

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