Bump timm from 0.4.12 to 0.9.2

[dependabot]

Bumps timm from 0.4.12 to 0.9.2.

Release notes

Sourced from timm's releases.

Release v0.9.2

• Fix _hub deprecation pass through import

Release v0.9.1

The first non pre-release since Oct 2022 with a long list of changes from 0.6.x releases...

May 12, 2023

• Fix Python 3.7 import error re Final[] typing annotation

May 11, 2023

• timm 0.9 released, transition from 0.8.xdev releases

May 10, 2023

• Hugging Face Hub downloading is now default, 1132 models on https://huggingface.co/timm, 1163 weights in timm
• DINOv2 vit feature backbone weights added thanks to Leng Yue
• FB MAE vit feature backbone weights added
• OpenCLIP DataComp-XL L/14 feat backbone weights added
• MetaFormer (poolformer-v2, caformer, convformer, updated poolformer (v1)) w/ weights added by Fredo Guan
• Experimental get_intermediate_layers function on vit/deit models for grabbing hidden states (inspired by DINO impl). This is WIP and may change significantly... feedback welcome.
• Model creation throws error if pretrained=True and no weights exist (instead of continuing with random initialization)
• Fix regression with inception / nasnet TF sourced weights with 1001 classes in original classifiers
• bitsandbytes (https://github.com/TimDettmers/bitsandbytes) optimizers added to factory, use bnb prefix, ie bnbadam8bit
• Misc cleanup and fixes
• Final testing before switching to a 0.9 and bringing timm out of pre-release state

April 27, 2023

• 97% of timm models uploaded to HF Hub and almost all updated to support multi-weight pretrained configs
• Minor cleanup and refactoring of another batch of models as multi-weight added. More fused_attn (F.sdpa) and features_only support, and torchscript fixes.

April 21, 2023

• Gradient accumulation support added to train script and tested (--grad-accum-steps), thanks Taeksang Kim
• More weights on HF Hub (cspnet, cait, volo, xcit, tresnet, hardcorenas, densenet, dpn, vovnet, xception_aligned)
• Added --head-init-scale and --head-init-bias to train.py to scale classiifer head and set fixed bias for fine-tune
• Remove all InplaceABN (inplace_abn) use, replaced use in tresnet with standard BatchNorm (modified weights accordingly).

April 12, 2023

• Add ONNX export script, validate script, helpers that I've had kicking around for along time. Tweak 'same' padding for better export w/ recent ONNX + pytorch.
• Refactor dropout args for vit and vit-like models, separate drop_rate into drop_rate (classifier dropout), proj_drop_rate (block mlp / out projections), pos_drop_rate (position embedding drop), attn_drop_rate (attention dropout). Also add patch dropout (FLIP) to vit and eva models.
• fused F.scaled_dot_product_attention support to more vit models, add env var (TIMM_FUSED_ATTN) to control, and config interface to enable/disable
• Add EVA-CLIP backbones w/ image tower weights, all the way up to 4B param 'enormous' model, and 336x336 OpenAI ViT mode that was missed.

April 5, 2023

• ALL ResNet models pushed to Hugging Face Hub with multi-weight support
  • All past timm trained weights added with recipe based tags to differentiate
  • All ResNet strikes back A1/A2/A3 (seed 0) and R50 example B/C1/C2/D weights available
  • Add torchvision v2 recipe weights to existing torchvision originals
  • See comparison table in https://huggingface.co/timm/seresnextaa101d_32x8d.sw_in12k_ft_in1k_288#model-comparison
• New ImageNet-12k + ImageNet-1k fine-tunes available for a few anti-aliased ResNet models
  • resnetaa50d.sw_in12k_ft_in1k - 81.7 @ 224, 82.6 @ 288
  • resnetaa101d.sw_in12k_ft_in1k - 83.5 @ 224, 84.1 @ 288

... (truncated)

Commits

• 3d05c0e Version 0.9.2
• ccb9dc4 Merge pull request #1804 from philipsgithub/patch-1
• fc77e9e Update hub.py
• cc77096 Version 0.9.1
• f744bda use torch.jit.Final instead of Final for beit, eva
• 35b9fc7 Update README.md
• 1751080 Update README.md
• 2e99bca Update README, prep for version 0.9.0 release
• 3eaf729 F.sdpa for visformer fails w/o contiguous on qkv, make experimental
• cf1884b Add 21k maxvit tf weights
• Additional commits viewable in compare view

Dependabot will resolve any conflicts with this PR as long as you don't alter it yourself. You can also trigger a rebase manually by commenting @dependabot rebase.

---

Dependabot commands and options

You can trigger Dependabot actions by commenting on this PR:

• @dependabot rebase will rebase this PR
• @dependabot recreate will recreate this PR, overwriting any edits that have been made to it
• @dependabot merge will merge this PR after your CI passes on it
• @dependabot squash and merge will squash and merge this PR after your CI passes on it
• @dependabot cancel merge will cancel a previously requested merge and block automerging
• @dependabot reopen will reopen this PR if it is closed
• @dependabot close will close this PR and stop Dependabot recreating it. You can achieve the same result by closing it manually
• @dependabot ignore this major version will close this PR and stop Dependabot creating any more for this major version (unless you reopen the PR or upgrade to it yourself)
• @dependabot ignore this minor version will close this PR and stop Dependabot creating any more for this minor version (unless you reopen the PR or upgrade to it yourself)
• @dependabot ignore this dependency will close this PR and stop Dependabot creating any more for this dependency (unless you reopen the PR or upgrade to it yourself)