Ross Wightman
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231d04e91a
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ResNetV2 pre-act and non-preact model, w/ BiT pretrained weights and support for ViT R50 model. Tweaks for in21k num_classes passing. More to do... tests failing.
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4 years ago |
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Ross Wightman
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de6046e213
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Initial commit for dataset / parser reorg to support additional datasets / types
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4 years ago |
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Ross Wightman
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392595c7eb
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Add pool_size to default cfgs for new models to prevent tests from failing. Add explicit 200D_320 model entrypoint for next benchmark run.
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4 years ago |
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Ross Wightman
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b1f1228a41
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Add ResNet101D, 152D, and 200D weights, remove meh 66d model
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4 years ago |
Jasha
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7c56c718f3
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Configure create_optimizer with args.opt_args
Closes #301
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4 years ago |
Ross Wightman
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9a25fdf3ad
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Merge pull request #297 from rwightman/ema_simplify
Simplified JIT compatible Ema module. Fixes for SiLU export and torchscript training w/ Linear layer.
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4 years ago |
Tymoteusz Wiśniewski
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de15b43865
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Fix a bug with accuracy retrieving from RealLabels
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4 years ago |
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Ross Wightman
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cd72e66eff
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Bug in last mod for features_only default_cfg
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4 years ago |
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Ross Wightman
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867a0e5a04
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Add default_cfg back to models wrapped in feature extraction module as per discussion in #294.
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4 years ago |
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Ross Wightman
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4ca52d73d8
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Add separate set and update method to ModelEmaV2
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4 years ago |
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Ross Wightman
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2ed8f24715
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A few more changes for 0.3.2 maint release. Linear layer change for mobilenetv3 and inception_v3, support no bias for linear wrapper.
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4 years ago |
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Ross Wightman
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6504a42832
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Version 0.3.2
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4 years ago |
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Ross Wightman
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460eba7f24
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Work around casting issue with combination of native torch AMP and torchscript for Linear layers
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4 years ago |
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Ross Wightman
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5f4b6076d8
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Fix inplace arg compat for GELU and PreLU via activation factory
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4 years ago |
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Ross Wightman
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fd962c4b4a
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Native SiLU (Swish) op doesn't export to ONNX
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4 years ago |
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Ross Wightman
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27bbc70d71
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Add back old ModelEma and rename new one to ModelEmaV2 to avoid compat breaks in dependant code. Shuffle train script, add a few comments, remove DataParallel support, support experimental torchscript training.
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4 years ago |
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Ross Wightman
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9214ca0716
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Simplifying EMA...
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4 years ago |
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Ross Wightman
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53aeed3499
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ver 0.3.1
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4 years ago |
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Ross Wightman
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30ab4a1494
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Fix issue in optim factory with sgd / eps flag. Bump version to 0.3.1
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4 years ago |
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Ross Wightman
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741572dc9d
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Bump version to 0.3.0 for pending PyPi push
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4 years ago |
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Ross Wightman
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b401952caf
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Add newly added vision transformer large/base 224x224 weights ported from JAX official repo
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4 years ago |
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Ross Wightman
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61200db0ab
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in_chans=1 working w/ pretrained weights for vision_transformer
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4 years ago |
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Ross Wightman
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e90edce438
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Support native silu activation (aka swish). An optimized ver is available in PyTorch 1.7.
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4 years ago |
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Ross Wightman
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da6cd2cc1f
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Fix regression for pretrained classifier loading when using entrypt functions directly
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4 years ago |
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Ross Wightman
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f591e90b0d
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Make sure num_features attr is present in vit models as with others
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4 years ago |
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Ross Wightman
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4a3df7842a
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Fix topn metric view regression on PyTorch 1.7
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4 years ago |
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Ross Wightman
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f944242cb0
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Fix #262, num_classes arg mixup. Make vision_transformers a bit closer to other models wrt get/reset classfier/forward_features. Fix torchscript for ViT.
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4 years ago |
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Ross Wightman
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736f209e7d
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Update vision transformers to be compatible with official code. Port official ViT weights from jax impl.
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4 years ago |
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Ross Wightman
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477a78ed81
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Fix optimizer factory regressin for optimizers like sgd/momentum that don't have an eps arg
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4 years ago |
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Ross Wightman
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27a93e9de7
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Improve test crop for ViT models. Small now 77.85, added base weights at 79.35 top-1.
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4 years ago |
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Ross Wightman
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d4db9e7977
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Add small vision transformer weights. 77.42 top-1.
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4 years ago |
talrid
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27fadaa922
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asymmetric_loss
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4 years ago |
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Ross Wightman
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f31933cb37
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Initial Vision Transformer impl w/ patch and hybrid variants. Refactor tuple helpers.
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4 years ago |
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Ross Wightman
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a4d8fea61e
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Add model based wd skip support. Improve cross version compat of optimizer factory. Fix #247
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4 years ago |
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Ross Wightman
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80078c47bb
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Add Adafactor and Adahessian optimizers, cleanup optimizer arg passing, add gradient clipping support.
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4 years ago |
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Ross Wightman
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fcb6258877
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Add missing leaky_relu layer factory defn, update Apex/Native loss scaler interfaces to support unscaled grad clipping. Bump ver to 0.2.2 for pending release.
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4 years ago |
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Ross Wightman
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e8e2d9cabf
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Add DropPath (stochastic depth) to ReXNet and VoVNet. RegNet DropPath impl tweak and dedupe se args.
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4 years ago |
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Ross Wightman
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e8ca45854c
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More models in sotabench, more control over sotabench run, dataset filename extraction consistency
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4 years ago |
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Ross Wightman
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9c406532bd
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Add EfficientNet-EdgeTPU-M (efficientnet_em) model trained natively in PyTorch. More sotabench fiddling.
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4 years ago |
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Ross Wightman
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c40384f5bd
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Add ResNet weights. 80.5 (top-1) ResNet-50-D, 77.1 ResNet-34-D, 72.7 ResNet-18-D.
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4 years ago |
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Ross Wightman
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47a7b3b5b1
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More flexible mixup mode, add 'half' mode.
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4 years ago |
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Ross Wightman
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532e3b417d
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Reorg of utils into separate modules
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4 years ago |
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Ross Wightman
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33f8a1bf36
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Updated README, add wide_resnet50_2 and seresnext50_32x4d weights
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4 years ago |
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Ross Wightman
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751b0bba98
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Add global_pool (--gp) arg changes to allow passing 'fast' easily for train/validate to avoid channels_last issue with AdaptiveAvgPool
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4 years ago |
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Ross Wightman
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9c297ec67d
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Cleanup Apex vs native AMP scaler state save/load. Cleanup CheckpointSaver a bit.
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4 years ago |
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Ross Wightman
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80c9d9cc72
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Add 'fast' global pool option, remove redundant SEModule from tresnet, normal one is now 'fast'
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4 years ago |
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Ross Wightman
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90a01f47d1
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hrnet features_only pretrained weight loading issue. Fix #232.
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4 years ago |
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Ross Wightman
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110a7c4982
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AdaptiveAvgPool2d -> mean((2,3)) for all SE/attn layers to avoid NaN with AMP + channels_last layout. See https://github.com/pytorch/pytorch/issues/43992
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4 years ago |
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Ross Wightman
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c2cd1a332e
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Improve torch amp support and add channels_last support for train/validate scripts
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4 years ago |
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Ross Wightman
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470220b1f4
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Fix MobileNetV3 crash with global_pool='', output consistent with other models but not equivalent due to efficient head.
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4 years ago |
