857f33015a
Add native PyTorch weights for MixNet-Medium with no SAME padding necessary. Remove unused block of code.
2019-07-29 11:59:15 -07:00
e7c8a37334
Make min-lr and cooldown-epochs cmdline args, change dash in color_jitter arg for consistency
2019-07-26 09:35:31 -07:00
d4debe6597
Update version, results csv files, and move remaining dropbox weights to github
2019-07-25 16:54:44 -07:00
dfa9298b4e
Add MixNet ( https://arxiv.org/abs/1907.09595 ) with pretrained weights converted from Tensorflow impl
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* refactor 'same' convolution and add helper to use MixedConv2d when needed
* improve performance of 'same' padding for cases that can be handled statically
* add support for extra exp, pw, and dw kernel specs with grouping support to decoder/string defs for MixNet
* shuffle some args for a bit more consistency, a little less clutter overall in gen_efficientnet.py
2019-07-25 11:42:01 -07:00
7a92caa560
Add basic image folder style dataset to read directly out of tar files, example in validate.py
2019-07-25 10:51:03 -07:00
d6ac5bbc48
EfficientNet and related cleanup
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* remove folded_bn support and corresponding untrainable tflite ported weights
* combine bn args into dict
* add inplace support to activations and use where possible for reduced mem on large models
2019-07-22 09:29:58 -07:00
c11973602d
Merge pull request #19 from rwightman/resnet-refactor
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Resnet refactoring
2019-07-20 08:47:21 -07:00
d97510fd4a
Add new results csv and update README with 3 new ResNet weight results
2019-07-20 08:45:05 -07:00
3d9be78fc6
A bit more ResNet cleanup.
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* add inplace=True back
* minor comment improvements
* few clarity changes
2019-07-19 16:44:35 -07:00
33436fafad
Add weights for ResNeXt50d model
2019-07-19 14:09:10 -07:00
e78cd79073
Move ResNet additions for Gluon into main ResNet impl. Add ResNet-26 and ResNet-26d models with weights.
2019-07-14 18:17:35 -07:00
c37cb0f2b7
ImageNet-1k vs ImageNet-v2 comparison
2019-07-06 17:19:56 -07:00
6cdf35e670
Add explicit half/fp16 support to loader and validation script
2019-07-05 13:52:25 -07:00
5684c6af32
Update README.md
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Add blurb about results csv
2019-07-04 10:52:03 -07:00
a6b2f6eca5
Update README, bump version
2019-07-03 22:48:33 -07:00
2a1d09b4c0
Add result csv with summary of all pretrained models
2019-07-03 22:34:36 -07:00
edb425ea48
Add crop_pct arg to validate, extra fields to csv output, 'all' filters pretrained
2019-07-03 22:28:07 -07:00
949b7a81c4
Fix typo in Densenet default resolutions
2019-07-03 22:11:26 -07:00
da52fcf78a
Add NASNet-Large model
2019-07-03 22:10:50 -07:00
f632190fd9
Add .gitattributes
2019-07-01 21:44:50 -07:00
5bc0ed3d7c
Grammar
2019-07-01 15:15:21 -07:00
c89acdfc02
Update EffResNetComparison.ipynb
2019-07-01 14:57:11 -07:00
73642f7462
Adjust notebook path
2019-07-01 14:16:18 -07:00
c30f625215
Update EffResNetComparison
2019-07-01 14:07:47 -07:00
c4916897f8
EfficientNet vs ResNet comparison in Colaboratory
2019-07-01 13:55:47 -07:00
6057496409
Register dpn107
2019-06-30 09:57:06 -07:00
3d1a66b6fc
Version 0.1.6
2019-06-30 09:55:23 -07:00
a6878b5218
Fix DPN config keys that I broke
2019-06-30 09:54:52 -07:00
8a05b8d555
Merge pull request #16 from rwightman/misc-epoch
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Weights, arguments, epoch counting, and more
2019-06-29 16:59:11 -07:00
9b0070edc9
Add two comments back, fix typo
2019-06-29 16:44:25 -07:00
188aeae8f4
Bump version 0.1.4
2019-06-29 16:17:54 -07:00
c3287aafb3
Slight improvement in EfficientNet-B2 native PyTorch weights
2019-06-29 16:17:29 -07:00
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
2019-06-29 15:50:33 -07:00
65a634626f
Switch random erasing to doing normal_() on CPU to avoid instability, remove a debug print
2019-06-29 10:03:13 -07:00
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
2019-06-28 13:49:20 -07:00
9d653b68a2
Make drop_connect rate scaling match official impl. Fixes #14
2019-06-25 09:30:36 -07:00
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...
2019-06-24 13:12:04 -07:00
a0275cfa2f
Fix arg positions in two entrypoint aliases
2019-06-24 08:25:14 -07:00
fe59249701
Bump version to 0.1.2
2019-06-23 18:27:30 -07:00
171c0b88b6
Add model registry and model listing fns, refactor model_factory/create_model fn
2019-06-23 18:22:16 -07:00
8512436436
Add instagram pretrained ResNeXt models from https://pytorch.org/hub/facebookresearch_WSL-Images_resnext/ , update README
2019-06-23 12:29:02 -07:00
1202d053bc
markdown in setup.py
2019-06-21 14:08:43 -07:00
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
2019-06-21 13:57:08 -07:00
827a3d6010
Add current checkpoints output back to CheckpointSaver (via logger)
2019-06-21 11:57:43 -07:00
63961b36a2
Missed pnasnet entrypoint
2019-06-20 23:34:20 -07:00
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
2019-06-20 23:29:44 -07:00
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
2019-06-20 22:30:23 -07:00
6fc886acaf
Remove all prints, change most to logging calls, tweak alignment of batch logs, improve setup.py
2019-06-20 17:29:25 -07:00
1d7f2d93a6
Python >= 3.6 requirement
2019-06-19 17:28:08 -07:00
aa4354f466
Big re-org, working towards making pip/module as 'timm'
2019-06-19 17:20:51 -07:00
Ross Wightman
Ross Wightman