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Ross Wightman 0bc50e84f8 Lots of refactoring and cleanup. 
* Move 'test time pool' to Module that can be used by any model, remove from DPN
* Remove ResNext model file and combine with ResNet
* Remove fbresnet200 as it was an old conversion and pretrained performance not worth param count
* Cleanup adaptive avgmax pooling and add back conctat variant
* Factor out checkpoint load fn
2019-04-10 14:53:34 -07:00
data
Lots of refactoring and cleanup.
2019-04-10 14:53:34 -07:00
loss
Add smooth loss
2019-04-05 20:50:26 -07:00
models
Lots of refactoring and cleanup.
2019-04-10 14:53:34 -07:00
optim
Add some Nvidia performance enhancements (prefetch loader, fast collate), and refactor some of training and model fact/transforms
2019-03-10 14:23:16 -07:00
scheduler
…
distributed_train.sh
Fix distributed train script
2019-04-05 20:49:58 -07:00
inference.py
Lots of refactoring and cleanup.
2019-04-10 14:53:34 -07:00
train.py
Distributed (multi-process) train, multi-gpu single process train, and NVIDIA AMP support
2019-04-05 10:53:04 -07:00
utils.py
…
validate.py
Lots of refactoring and cleanup.
2019-04-10 14:53:34 -07:00
Description
PyTorch image models, scripts, pretrained weights -- ResNet, ResNeXT, EfficientNet, EfficientNetV2, NFNet, Vision Transformer, MixNet, MobileNet-V3/V2, RegNet, DPN, CSPNet, and more
augmixcnn-classificationdistributed-trainingdual-path-networksefficientnetefficientnet-trainingimagenet-classifiermixnetmnasnetmobile-deep-learningmobilenet-v2mobilenetv3nfnetsnormalization-free-trainingpretrained-modelspretrained-weightspytorchrandaugmentresnetvision-transformer-models
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