a6b2f6eca5
Update README, bump version
5 years ago
2a1d09b4c0
Add result csv with summary of all pretrained models
5 years ago
edb425ea48
Add crop_pct arg to validate, extra fields to csv output, 'all' filters pretrained
5 years ago
949b7a81c4
Fix typo in Densenet default resolutions
5 years ago
da52fcf78a
Add NASNet-Large model
5 years ago
f632190fd9
Add .gitattributes
5 years ago
5bc0ed3d7c
Grammar
5 years ago
c89acdfc02
Update EffResNetComparison.ipynb
5 years ago
73642f7462
Adjust notebook path
5 years ago
c30f625215
Update EffResNetComparison
5 years ago
c4916897f8
EfficientNet vs ResNet comparison in Colaboratory
5 years ago
6057496409
Register dpn107
5 years ago
3d1a66b6fc
Version 0.1.6
5 years ago
a6878b5218
Fix DPN config keys that I broke
5 years ago
8a05b8d555
Merge pull request #16 from rwightman/misc-epoch
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Weights, arguments, epoch counting, and more
5 years ago
9b0070edc9
Add two comments back, fix typo
5 years ago
188aeae8f4
Bump version 0.1.4
5 years ago
c3287aafb3
Slight improvement in EfficientNet-B2 native PyTorch weights
5 years ago
b8762cc67d
Model updates. Add my best ResNet50 weights top-1=78.47. Add some other torchvision weights.
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* Remove some models that don't exist as pretrained an likely never will (se)resnext152
* Add some torchvision weights as tv_ for models that I have added better weights for
* Add wide resnet recently added to torchvision along with resnext101-32x8d
* Add functionality to model registry to allow filtering on pretrained weight presence
5 years ago
65a634626f
Switch random erasing to doing normal_() on CPU to avoid instability, remove a debug print
5 years ago
c6b32cbe73
A number of tweaks to arguments, epoch handling, config
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* reorganize train args
* allow resolve_data_config to be used with dict args, not just arparse
* stop incrementing epoch before save, more consistent naming vs csv, etc
* update resume and start epoch handling to match above
* stop auto-incrementing epoch in scheduler
5 years ago
9d653b68a2
Make drop_connect rate scaling match official impl. Fixes #14
5 years ago
13c19e213d
Add native PyTorch EfficientNet B1 and B2 weights. Not quite where I want them, but hitting the brick wall and moving on to other projects...
5 years ago
a0275cfa2f
Fix arg positions in two entrypoint aliases
5 years ago
fe59249701
Bump version to 0.1.2
5 years ago
171c0b88b6
Add model registry and model listing fns, refactor model_factory/create_model fn
5 years ago
8512436436
Add instagram pretrained ResNeXt models from https://pytorch.org/hub/facebookresearch_WSL-Images_resnext/ , update README
5 years ago
1202d053bc
markdown in setup.py
5 years ago
87b92c528e
Some pretrianed URL changes
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* host some of Cadene's weights on github instead of .fr for speed
* add my old port of ensemble adversarial inception resnet v2
* switch to my TF port of normal inception res v2 and change FC layer back to 'classif' for compat with ens_adv
5 years ago
827a3d6010
Add current checkpoints output back to CheckpointSaver (via logger)
5 years ago
63961b36a2
Missed pnasnet entrypoint
5 years ago
6cc214bd7a
Consistency in model entrypoints
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* move pretrained entrypoint arg to first pos to be closer to torchvision/hub
* change DPN weight URLS to my github location
5 years ago
b20bb58284
Distributed tweaks
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* Support PyTorch native DDP as fallback if APEX not present
* Support SyncBN for both APEX and Torch native (if torch >= 1.1)
* EMA model does not appear to need DDP wrapper, no gradients, updated from wrapped model
5 years ago
6fc886acaf
Remove all prints, change most to logging calls, tweak alignment of batch logs, improve setup.py
5 years ago
1d7f2d93a6
Python >= 3.6 requirement
5 years ago
aa4354f466
Big re-org, working towards making pip/module as 'timm'
5 years ago
871f4c1b0c
Change some absolute imports to relative
5 years ago
b9f8d40b10
Fix pretrained override logic for validate, checkpoint always trump pretrained flag during model create
5 years ago
0e1fd11ad8
Merge pull request #12 from rwightman/ema-cleanup
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Model weights Exponential Moving Average
5 years ago
1019414fd2
Add ported Tensorflow EfficientNet B4/B5 weights
5 years ago
c9a61b7d98
Add gitignore
5 years ago
c6b8259ad6
Update README.md
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Add blurb about python environment
5 years ago
f3134973b5
Add the MnasNet-B1 variant weights, add A1/B1 model names as in the stand-alone repo, remove a bit of unused code
5 years ago
c1a84ecb22
dataset not passed through PrefetchLoader for inference script. Fix #10
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* also, make top5 configurable for lower class count cases
6 years ago
2060e433c0
Add native PyTorch weights for SE-MnasNet aka MnasNet-A1
6 years ago
7dab6d1ec7
Default to img_size in model default_cfg, defer output folder creation until later in the init sequence
6 years ago
7d17394bdc
Add native PyTorch weights for EfficientNet-B0 w/ top-1 > 76.9
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* also add pooling details to default cfg for efficiennets so testtimepool wrapper works
6 years ago
9bcd65181b
Add exponential moving average for model weights + few other additions and cleanup
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* ModelEma class added to track an EMA set of weights for the model being trained
* EMA handling added to train, validation and clean_checkpoint scripts
* Add multi checkpoint or multi-model validation support to validate.py
* Add syncbn option (APEX) to train script for experimentation
* Cleanup interface of CheckpointSaver while adding ema functionality
6 years ago
105d5702d7
Update README.md
6 years ago
6688d0669f
PyTorch trained MobileNetV3 weights that match/best paper. Update fbnetc weights to improved copy.
6 years ago
Ross Wightman