Add --reparam arg to benchmark.py, onnx_export.py, and validate.py to trigger layer reparameterization / fusion for models with any one of reparameterize(), switch_to_deploy() or fuse()
Including FastViT, MobileOne, RepGhostNet, EfficientViT (MSRA), RepViT, RepVGG, and LeViT
Preparing 0.9.6 'back to school' release
Aug 11, 2023
Swin, MaxViT, CoAtNet, and BEiT models support resizing of image/window size on creation with adaptation of pretrained weights
Example validation cmd to test w/ non-square resize python validate.py /imagenet --model swin_base_patch4_window7_224.ms_in22k_ft_in1k --amp --amp-dtype bfloat16 --input-size 3 256 320 --model-kwargs window_size=8,10 img_size=256,320
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Bumps timm from 0.9.5 to 0.9.6.
Release notes
Sourced from timm's releases.
Commits
f544d49
Version 0.9.6 for releasee2a34d9
Update readme with resizing additionc8b2f28
Fix a few typos, fix fastvit proj_drop, add code linkfc5d705
dynamic_size -> dynamic_img_size, add dynamic_img_pad for padding option1f4512f
Support dynamic_resize in eva.py modelsea3519a
Fix dynamic_resize for deit models (distilled or no_embed_cls) and vit w/o cl...4d8ecde
Fix torchscript for vit-hybrid dynamic_resizefdd8c7c
Initial impl of dynamic resize for existing vit models (incl vit-resnet hybrids)38c474e
Update README, add --reparm to onnx_export5d599a6
RepViT weights on HF hubDependabot 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
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