Ross Wightman
abff3f12ec
Wrong pool_size for 288 ft
2023-04-05 16:07:51 -07:00
Ross Wightman
356309959c
ResNet models on HF hub, multi-weight support, add torchvision v2 weights, new 12k pretrained and fine-tuned timm anti-aliased weights
2023-04-05 14:19:42 -07:00
Fredo Guan
81ca323751
Davit update formatting and fix grad checkpointing ( #7 )
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fixed head to gap->norm->fc as per convnext, along with option for norm->gap->fc
failed tests due to clip convnext models, davit tests passed
2023-01-15 14:34:56 -08:00
Ross Wightman
927f031293
Major module / path restructure, timm.models.layers -> timm.layers, add _ prefix to all non model modules in timm.models
2022-12-06 15:00:06 -08:00
Ross Wightman
e11efa872d
Update a bunch of weights with external links to timm release assets. Fixes issue with *aliyuncs.com returning forbidden. Did pickle scan / verify and re-hash. Add TresNet-V2-L weights.
2022-09-13 16:35:26 -07:00
Ross Wightman
dc376e3676
Ensure all model entrypoint fn default to `pretrained=False` (a few didn't)
2022-07-19 13:58:41 -07:00
Ross Wightman
d765305821
Remove first_conv for resnetaa50 def
2022-07-02 15:56:17 -07:00
Ross Wightman
c170ba3173
Add weights for resnet10t, resnet14t, and resnetaa50 models. Fix #1314
2022-07-02 15:18:06 -07:00
Ross Wightman
a050fde5cd
Add resnet10t (basic block) and resnet14t (bottleneck) with 1,1,1,1 repeats
2022-07-01 15:03:28 -07:00
Ross Wightman
52ac881402
Missed first_conv in latest seresnext 'D' default_cfgs
2022-04-22 20:55:52 -07:00
Ross Wightman
7629d8264d
Add two new SE-ResNeXt101-D 32x8d weights, one anti-aliased and one not. Reshuffle default_cfgs vs model entrypoints for resnet.py so they are better aligned.
2022-04-22 16:54:53 -07:00
Ross Wightman
0862e6ebae
Fix correctness of some group matching regex (no impact on result), some formatting, missed forward_head for resnet
2022-03-19 14:58:54 -07:00
Ross Wightman
94bcdebd73
Add latest weights trained on TPU-v3 VM instances
2022-03-18 21:35:41 -07:00
Ross Wightman
372ad5fa0d
Significant model refactor and additions:
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* All models updated with revised foward_features / forward_head interface
* Vision transformer and MLP based models consistently output sequence from forward_features (pooling or token selection considered part of 'head')
* WIP param grouping interface to allow consistent grouping of parameters for layer-wise decay across all model types
* Add gradient checkpointing support to a significant % of models, especially popular architectures
* Formatting and interface consistency improvements across models
* layer-wise LR decay impl part of optimizer factory w/ scale support in scheduler
* Poolformer and Volo architectures added
2022-02-28 13:56:23 -08:00
Ross Wightman
95cfc9b3e8
Merge remote-tracking branch 'origin/master' into norm_norm_norm
2022-01-25 22:20:45 -08:00
Ross Wightman
abc9ba2544
Transitioning default_cfg -> pretrained_cfg. Improving handling of pretrained_cfg source (HF-Hub, files, timm config, etc). Checkpoint handling tweaks.
2022-01-25 21:54:13 -08:00
Ross Wightman
1aa617cb3b
Add AvgPool2d anti-aliasing support to ResNet arch (as per OpenAI CLIP models), add a few blur aa models as well
2022-01-18 21:57:24 -08:00
Ross Wightman
656757d26b
Fix MobileNetV2 head conv size for multiplier < 1.0. Add some missing modification copyrights, fix starting date of some old ones.
2022-01-14 16:28:27 -08:00
Ross Wightman
ab49d275de
Significant norm update
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* ConvBnAct layer renamed -> ConvNormAct and ConvNormActAa for anti-aliased
* Significant update to EfficientNet and MobileNetV3 arch to support NormAct layers and grouped conv (as alternative to depthwise)
* Update RegNet to add Z variant
* Add Pre variant of XceptionAligned that works with NormAct layers
* EvoNorm matches bits_and_tpu branch for merge
2021-12-14 13:48:30 -08:00
Ross Wightman
c976a410d9
Add ResNet-50 w/ GN (resnet50_gn) and SEBotNet-33-TS (sebotnet33ts_256) model defs and weights. Update halonet50ts weights w/ slightly better variant in1k val, more robust to test sets.
2021-11-19 14:24:43 -08:00
Ross Wightman
9b2daf2a35
Add ResNeXt-50 weights 81.1 top-1 @ 224, 82 @ 288 with A1 'high aug' recipe
2021-11-14 13:17:27 -08:00
Ross Wightman
ddc29da974
Add ResNet101 and ResNet152 weights from higher aug RSB recipes. 81.93 and 82.82 top-1 at 224x224.
2021-11-02 17:59:16 -07:00
Ross Wightman
6ed4cdccca
Update lambda_resnet26t weights with better set
2021-10-10 16:32:54 -07:00
Ross Wightman
fbf59c04ee
Change crop ratio on correct resnet50 variant.
2021-10-04 22:31:08 -07:00
Ross Wightman
ae1ff5792f
Clean a1/a2/3 rsb _0 checkpoints properly, fix v2 loading.
2021-10-04 16:46:00 -07:00
Ross Wightman
cc9bedf373
Add initial ResNet Strikes Back weights for ResNet50 and ResNetV2-50 models
2021-10-03 17:32:02 -07:00
Ross Wightman
76881d207b
Add baseline resnet26t @ 256x256 weights. Add 33ts variant of halonet with at least one halo in stage 2,3,4
2021-09-04 14:52:54 -07:00
Ross Wightman
8880f696b6
Refactoring, cleanup, improved test coverage.
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* Add eca_nfnet_l2 weights, 84.7 @ 384x384
* All 'non-std' (ie transformer / mlp) models have classifier / default_cfg test added
* Fix #694 reset_classifer / num_features / forward_features / num_classes=0 consistency for transformer / mlp models
* Add direct loading of npz to vision transformer (pure transformer so far, hybrid to come)
* Rename vit_deit* to deit_*
* Remove some deprecated vit hybrid model defs
* Clean up classifier flatten for conv classifiers and unusual cases (mobilenetv3/ghostnet)
* Remove explicit model fns for levit conv, just pass in arg
2021-06-12 16:40:02 -07:00
Ross Wightman
742c2d5247
Add Gather-Excite and Global Context attn modules. Refactor existing SE-like attn for consistency and refactor byob/byoanet for less redundancy.
2021-05-27 18:03:29 -07:00
Ross Wightman
b2c305c2aa
Move Mlp and PatchEmbed modules into layers. Being used in lots of models now...
2021-05-06 14:03:23 -07:00
Ross Wightman
d5473c17f7
Fix incorrect name of shortcut/identity paths in many residual nets. Inherited from naming in old old torchvision, long fixed there.
2021-05-04 21:27:15 -07:00
Ross Wightman
ddc743fdf8
Update ResNet-RS models to EMA weights
2021-05-04 16:16:55 -07:00
Ross Wightman
08d60f4a9a
resnetrs50 pool sizing wrong
2021-05-04 12:41:09 -07:00
Ross Wightman
67d0665b46
Post ResNet-RS merge cleanup. Add weight urls, adjust train/test/crop pct.
2021-05-04 11:04:23 -07:00
Aman Arora
560eae38f5
[WIP] Add ResNet-RS models ( #554 )
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* Add ResNet-RS models
* Only include resnet-rs changes
* remove whitespace diff
* EOF newline
* Update time
* increase time
* Add first conv
* Try running only resnetv2_101x1_bitm on Linux runner
* Add to exclude filter
* Run test_model_forward_features for all
* Add to exclude ftrs
* back to defaults
* only run test_forward_features
* run all tests
* Run all tests
* Add bigger resnetrs to model filters to fix Github CLI
* Remove resnetv2_101x1_bitm from exclude feat features
* Remove hardcoded values
* Make sure reduction ratio in resnetrs is 0.25
* There is no bias in replaced maxpool so remove it
2021-05-04 10:59:44 -07:00
Ross Wightman
e15c3886ba
Defaul lambda r=7. Define '26t' stage 4/5 256x256 variants for all of bot/halo/lambda nets for experiment. Add resnet50t for exp. Fix a few comments.
2021-04-29 10:58:49 -07:00
Ross Wightman
d584e7f617
Support for huggingface hub via create_model and default_cfgs.
...
* improve consistency of model creation helper fns
* add comments to some of the model helpers
* support passing external default_cfgs so they can be sourced from hub
2021-03-16 22:48:26 -07:00
Ross Wightman
3b57490a63
Fix some half removed resnet model defs, pooling for ecaresnet269d
2021-02-07 22:09:25 -08:00
Ross Wightman
68a4144882
Add new weights for ecaresnet26t/50t/269d models. Remove distinction between 't' and 'tn' (tiered models), tn is now t. Add test time img size spec to default cfg.
2021-02-06 16:30:02 -08:00
Ross Wightman
22748f1a2d
Convert samples/targets in ParserImageInTar to numpy arrays, slightly less mem usage for massive datasets. Add a few more se/eca model defs to resnet.py
2021-01-22 16:54:33 -08:00
Ross Wightman
4e2533db77
Add 320x320 model default cfgs for 101D and 152D ResNets. Add SEResNet-152D weights and 320x320 cfg.
2021-01-03 12:10:25 -08:00
Ross Wightman
392595c7eb
Add pool_size to default cfgs for new models to prevent tests from failing. Add explicit 200D_320 model entrypoint for next benchmark run.
2020-12-18 21:28:47 -08:00
Ross Wightman
b1f1228a41
Add ResNet101D, 152D, and 200D weights, remove meh 66d model
2020-12-18 17:13:37 -08:00
Ross Wightman
c40384f5bd
Add ResNet weights. 80.5 (top-1) ResNet-50-D, 77.1 ResNet-34-D, 72.7 ResNet-18-D.
2020-09-18 12:05:37 -07:00
Ross Wightman
33f8a1bf36
Updated README, add wide_resnet50_2 and seresnext50_32x4d weights
2020-09-03 10:45:17 -07:00
Yusuke Uchida
f6b56602f9
fix test_model_default_cfgs
2020-08-11 23:23:57 +09:00
Ross Wightman
b1f1a54de9
More uniform treatment of classifiers across all models, reduce code duplication.
2020-08-03 22:18:24 -07:00
Ross Wightman
d72ddafe56
Fix some checkpoint / model str regressions
2020-07-29 19:43:01 -07:00
Ross Wightman
9ecd16bd7b
Add new seresnet50 (non-legacy) model weights, 80.274 top-1
2020-07-29 00:17:42 -07:00
Ross Wightman
6c17d57a2c
Fix some attributions, add copyrights to some file docstrings
2020-07-27 13:44:56 -07:00