b5315e66b5
Streamline SelecSLS model without breaking checkpoint compat. Move cfg handling out of model class. Update feature/pooling behaviour to match current.
5 years ago
d59a756c16
Run PyCharm autoformat on selecsls and change mix cap variables and model names to all lower
5 years ago
fb3a0f4bb8
Merge pull request #65 from mehtadushy/selecsls
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Incorporate SelecSLS Models
5 years ago
0554b7942c
Update README.md
5 years ago
a4497afa21
Update sotabench.py
5 years ago
53f578e16f
Update README with B3 training details
5 years ago
19fc205a4d
Update comments on the new SE-ResNeXt26 models
5 years ago
8894a6bc08
Update sotabench.py with latest seresnext26 and efficientnet_b3 models
5 years ago
acc3ed2b8c
Add EfficientNet-B3 weights, trained from scratch with RA.
5 years ago
2404361f62
correct asset paths
5 years ago
31939311f6
Added SelecSLS models
5 years ago
1f4498f217
Add ResNet deep tiered stem and model weights for seresnext26t_32x4d and seresnext26d_32x4d
5 years ago
32012a44fd
Added SelecSLS model
5 years ago
73b78459dc
Add update RandAugment MixNet-XL weights
5 years ago
3afc2a4dc0
Some cleanup/improvements to AugMix impl:
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* make 'increasing' levels for Contrast, Color, Brightness, Saturation ops
* remove recursion from faster blending mix
* add config striing parsing for AugMix
5 years ago
232ab7fb12
Working on an implementation of AugMix with JensenShannonDivergence loss that's compatible with my AutoAugment and RandAugment impl
5 years ago
ff8688ca3d
Merge pull request #62 from rwightman/reduce-bn
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Distribute BatchNorm stats
5 years ago
5719b493ad
Missed update dist-bn logic for EMA model
5 years ago
a435ea1327
Change reduce_bn to distribute_bn, add ability to choose between broadcast and reduce (mean). Add crop_pct arg to allow selecting validation crop while training.
5 years ago
3bff2b21dc
Add support for keeping running bn stats the same across distributed training nodes before eval/save
5 years ago
0161de0127
Switch RandoErasing back to on GPU normal sampling
5 years ago
5d7af97981
Update README.md
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Update latest training hparam/command line with correct RandAugment config string (`noise` -> `mstd`)
5 years ago
3129bdb2c1
Update README.md
5 years ago
ff421e5e09
New PyTorch trained EfficientNet-B2 weights with my RandAugment impl
5 years ago
00b93407c7
Update results-all.csv with latest models/weights
5 years ago
5259dbcbb4
Update README.md with latest changes
5 years ago
3bef524f9c
Finish with HRNet, weights and models updated. Improve consistency in model classifier/global pool treatment.
5 years ago
3ceeedc441
Merge pull request #53 from rwightman/condconvs_and_features
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Major model merge (EfficientNet-CondConv, EfficientNet-AdvProp, TF MobileNetV3, HRNet, more)
5 years ago
7b3c235ccc
Update sotabench with new models
5 years ago
6ca0828166
Update EfficientNet comments, MobileNetV3 non-TF create fns, fix factory arg checks, bump PyTorch version req to 1.2
5 years ago
eccbadca74
Update EfficientNet comments
5 years ago
902d32fb16
Renamed gen_efficientnet.py -> efficientnet.py
5 years ago
5a0a8de7e3
ResNet updates:
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* remove redundant GluonResNet model/blocks and use the code in ResNet for Gluon weights
* change SEModules back to using AdaptiveAvgPool instead of mean, PyTorch issue long fixed
5 years ago
3b8f63084d
Clean checkpoint renames pth w/ SHA hash in a torch hub compatible way
5 years ago
a39cc43374
Bring EfficientNet and MobileNetV3 up to date with my gen-efficientnet repo
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* Split MobileNetV3 and EfficientNet model files and put builder and blocks in own files (getting too large)
* Finalize CondConv EfficientNet variant
* Add the AdvProp weights files and B8 EfficientNet model
* Refine the feature extraction module for EfficientNet and MobileNetV3
5 years ago
ad93347548
Initial HRNet classification model commit
5 years ago
2393708650
Missed stashing of out_indices in model
5 years ago
35e8f0c5e7
Fixup a few comments, add PyTorch version aware Flatten and finish as_sequential for GenEfficientNet
5 years ago
7ac6db4543
Missed activations.py
5 years ago
506df0e3d0
Add CondConv support for EfficientNet into WIP for GenEfficientNet Feature extraction setup
5 years ago
db04677c94
Merge pull request #52 from rwightman/randaugment
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RandAugment and more
5 years ago
576d360f20
Bring in JIT version of optimized swish activation from gen_efficientnet as default (while working on feature extraction functionality here).
5 years ago
1f39d15f15
Allow float decay epochs arg for training, works out with step lr math
5 years ago
7b83e67f77
Pass drop connect arg through to EfficientNet models
5 years ago
31453b039e
Update Auto/RandAugment comments, README, more.
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* Add a weighted choice option for RandAugment
* Adjust magnitude noise/std naming, config
5 years ago
4243f076f1
Adding RandAugment to AutoAugment impl, some tweaks to AA included
5 years ago
4748c6dff2
Fix non-prefetch variant of Mixup. Fixes #50
5 years ago
0d58c50fb1
Add TF RandAug weights for B5/B7 EfficientNet models.
5 years ago
62105ed4a0
Better differentiate sotabench WSL, SSL, and SWSL models via model_desc
5 years ago
c099374771
Map pretrained checkpoint to cpu to avoid issue with some pretrained checkpoints still having CUDA tensors. Fixes #42
5 years ago
Ross Wightman
Ross Wightman
Dushyant Mehta