01aea8c1bf
Version 0.8.6dev0
2023-01-09 13:38:31 -08:00
2e83bba142
Revert head norm changes to ConvNeXt as it broke some downstream use, alternate workaround for fcmae weights
2023-01-09 13:37:40 -08:00
1825b5e314
maxxvit type
2023-01-09 08:57:31 -08:00
5078b28f8a
More kwarg handling tweaks, maxvit_base_rw def added
2023-01-09 08:57:31 -08:00
c0d7388a1b
Improving kwarg merging in more models
2023-01-09 08:57:31 -08:00
ae9153052f
Update version.py
2023-01-06 17:17:35 -08:00
60ebb6cefa
Re-order vit pretrained entries for more sensible default weights (no .tag specified)
2023-01-06 16:12:33 -08:00
e861b74cf8
Pass through --model-kwargs (and --opt-kwargs for train) from command line through to model __init__. Update some models to improve arg overlay. Cleanup along the way.
2023-01-06 16:12:33 -08:00
add3fb864e
Working on improved model card template for push_to_hf_hub
2023-01-06 16:12:33 -08:00
dd0bb327e9
Update version.py
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Ver 0.8.4dev0
2023-01-05 07:55:18 -08:00
6e5553da5f
Add ConvNeXt-V2 support (model additions and weights) ( #1614 )
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* Add ConvNeXt-V2 support (model additions and weights)
* ConvNeXt-V2 weights on HF Hub, tweaking some tests
* Update README, fixing convnextv2 tests
2023-01-05 07:53:32 -08:00
6902c48a5f
Fix ResNet based models to work w/ norm layers w/o affine params. Reformat long arg lists into vertical form.
2022-12-29 16:32:26 -08:00
d5aa17e415
Remove print from auto_augment
2022-12-28 17:11:35 -08:00
7c846d9970
Better vmap compat across recent torch versions
2022-12-24 14:37:04 -08:00
4e24f75289
Merge pull request #1593 from rwightman/multi-weight_effnet_convnext
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Update efficientnet.py and convnext.py to multi-weight, add new 12k pretrained weights
2022-12-23 10:09:08 -08:00
8ece53e194
Switch BEiT to HF hub weights
2022-12-22 21:43:04 -08:00
d1bfa9a000
Support HF datasets and TFSD w/ a sub-path by fixing split, fix #1598 ... add class mapping support to HF datasets in case class label isn't in info.
2022-12-22 21:34:13 -08:00
e2fc43bc63
Version 0.8.2dev0
2022-12-22 17:34:09 -08:00
9a51e4ea2e
Add FlexiViT models and weights, refactoring, push more weights
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* push all vision_transformer*.py weights to HF hub
* finalize more pretrained tags for pushed weights
* refactor pos_embed files and module locations, move some pos embed modules to layers
* tweak hf hub helpers to aid bulk uploading and updating
2022-12-22 17:23:09 -08:00
656e1776de
Convert mobilenetv3 to multi-weight, tweak PretrainedCfg metadata
2022-12-16 09:29:13 -08:00
6a01101905
Update efficientnet.py and convnext.py to multi-weight, add ImageNet-12k pretrained EfficientNet-B5 and ConvNeXt-Nano.
2022-12-14 20:33:23 -08:00
74d6afb4cd
Add Adan to __init__.py
2022-12-15 11:37:29 +08:00
e7da205345
Fix aa min_max level clamp
2022-12-10 16:43:28 -08:00
e3b2f5be0a
Add 3-Augment support to auto_augment.py, clean up weighted choice handling, and allow adjust per op prob via arg string
2022-12-10 16:25:50 -08:00
d5e7d6b27e
Merge remote-tracking branch 'origin/main' into refactor-imports
2022-12-09 14:49:44 -08:00
cda39b35bd
Add a deprecation phase to module re-org
2022-12-09 14:39:45 -08:00
7c4ed4d5a4
Add EVA-large models
2022-12-08 16:21:30 -08:00
98047ef5e3
Add EVA FT results, hopefully fix BEiT test failures
2022-12-07 08:54:06 -08:00
3cc4d7a894
Fix missing register for 224 eva model
2022-12-07 08:54:06 -08:00
eba07b0de7
Add eva models to beit.py
2022-12-07 08:54:06 -08:00
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
3785c234d7
Remove clip vit models that won't be ft and comment two that aren't uploaded yet
2022-12-05 10:21:34 -08:00
f82239b30e
multi-weight branch version -> 0.8.0dev
2022-12-05 10:21:34 -08:00
755570e2d6
Rename _pretrained.py -> pretrained.py, not feasible to change the other files to same scheme without breaking uses
2022-12-05 10:21:34 -08:00
72cfa57761
Add ported Tensorflow MaxVit weights. Add a few more CLIP ViT fine-tunes. Tweak some model tag names. Improve model tag name sorting. Update HF hub push config layout.
2022-12-05 10:21:34 -08:00
4d5c395160
MaxVit, ViT, ConvNeXt, and EfficientNet-v2 updates
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* Add support for TF weights and modelling specifics to MaxVit (testing ported weights)
* More fine-tuned CLIP ViT configs
* ConvNeXt and MaxVit updated to new pretrained cfgs use
* EfficientNetV2, MaxVit and ConvNeXt high res models use squash crop/resize
2022-12-05 10:21:34 -08:00
3db4e346e0
Switch TFDS dataset to use INTEGER_ACCURATE jpeg decode by default
2022-12-05 10:21:34 -08:00
9da7e3a799
Add crop_mode for pretraind config / image transforms. Add support for dynamo compilation to benchmark/train/validate
2022-12-05 10:21:34 -08:00
b2b6285af7
Add two more FT clip weights
2022-12-05 10:21:34 -08:00
5895056dc4
Add openai b32 ft
2022-12-05 10:21:34 -08:00
9dea5143d5
Adding more clip ft variants
2022-12-05 10:21:34 -08:00
444dcba4ad
CLIP B16 12k weights added
2022-12-05 10:21:34 -08:00
dff4717cbf
Add clip b16 384x384 finetunes
2022-12-05 10:21:34 -08:00
883fa2eeaa
Add fine-tuned B/16 224x224 in1k clip models
2022-12-05 10:21:34 -08:00
9a3d2ac2d5
Add latest CLIP ViT fine-tune pretrained configs / model entrypt updates
2022-12-05 10:21:34 -08:00
42bbbddee9
Add missing model config
2022-12-05 10:21:34 -08:00
def68befa7
Updating vit model defs for mult-weight support trial (vit first). Prepping for CLIP (laion2b and openai) fine-tuned weights.
2022-12-05 10:21:34 -08:00
0dadb4a6e9
Initial multi-weight support, handled so old pretraing config handling co-exists with new tags.
2022-12-05 10:21:34 -08:00
653bdc7105
Fix comment: https://github.com/rwightman/pytorch-image-models/pull/1564#issuecomment-1326743424
2022-11-25 09:52:52 +08:00
bdc9fad638
Fix compatible BUG: QMNIST and ImageNet datasets do not exist in torchvision 0.10.1.
2022-11-24 14:37:44 +08:00
Ross Wightman
Ross Wightman
alec.tu
hongxin xiang