7c846d9970
Better vmap compat across recent torch versions
2 years ago
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
2 years ago
8ece53e194
Switch BEiT to HF hub weights
2 years ago
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.
2 years ago
e2fc43bc63
Version 0.8.2dev0
2 years ago
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
2 years ago
656e1776de
Convert mobilenetv3 to multi-weight, tweak PretrainedCfg metadata
2 years ago
6a01101905
Update efficientnet.py and convnext.py to multi-weight, add ImageNet-12k pretrained EfficientNet-B5 and ConvNeXt-Nano.
2 years ago
74d6afb4cd
Add Adan to __init__.py
2 years ago
e7da205345
Fix aa min_max level clamp
2 years ago
e3b2f5be0a
Add 3-Augment support to auto_augment.py, clean up weighted choice handling, and allow adjust per op prob via arg string
2 years ago
d5e7d6b27e
Merge remote-tracking branch 'origin/main' into refactor-imports
2 years ago
cda39b35bd
Add a deprecation phase to module re-org
2 years ago
7c4ed4d5a4
Add EVA-large models
2 years ago
98047ef5e3
Add EVA FT results, hopefully fix BEiT test failures
2 years ago
3cc4d7a894
Fix missing register for 224 eva model
2 years ago
eba07b0de7
Add eva models to beit.py
2 years ago
927f031293
Major module / path restructure, timm.models.layers -> timm.layers, add _ prefix to all non model modules in timm.models
2 years ago
3785c234d7
Remove clip vit models that won't be ft and comment two that aren't uploaded yet
2 years ago
f82239b30e
multi-weight branch version -> 0.8.0dev
2 years ago
755570e2d6
Rename _pretrained.py -> pretrained.py, not feasible to change the other files to same scheme without breaking uses
2 years ago
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.
2 years ago
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
2 years ago
3db4e346e0
Switch TFDS dataset to use INTEGER_ACCURATE jpeg decode by default
2 years ago
9da7e3a799
Add crop_mode for pretraind config / image transforms. Add support for dynamo compilation to benchmark/train/validate
2 years ago
b2b6285af7
Add two more FT clip weights
2 years ago
5895056dc4
Add openai b32 ft
2 years ago
9dea5143d5
Adding more clip ft variants
2 years ago
444dcba4ad
CLIP B16 12k weights added
2 years ago
dff4717cbf
Add clip b16 384x384 finetunes
2 years ago
883fa2eeaa
Add fine-tuned B/16 224x224 in1k clip models
2 years ago
9a3d2ac2d5
Add latest CLIP ViT fine-tune pretrained configs / model entrypt updates
2 years ago
42bbbddee9
Add missing model config
2 years ago
def68befa7
Updating vit model defs for mult-weight support trial (vit first). Prepping for CLIP (laion2b and openai) fine-tuned weights.
2 years ago
0dadb4a6e9
Initial multi-weight support, handled so old pretraing config handling co-exists with new tags.
2 years ago
653bdc7105
Fix comment: https://github.com/rwightman/pytorch-image-models/pull/1564#issuecomment-1326743424
2 years ago
bdc9fad638
Fix compatible BUG: QMNIST and ImageNet datasets do not exist in torchvision 0.10.1.
2 years ago
9b114754db
refactor push_to_hub helper
2 years ago
ae0a0db7de
Create repo before cloning with Repository.clone_from
2 years ago
803254bb40
Fix spacing misalignment for fast norm path in LayerNorm modules
2 years ago
475ecdfa3d
cast env var args for dataset readers to int
2 years ago
39190f5f44
Remove inplace operators when calculating the loss
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Remove inplace operators to overcome the following error when using `asymmetric_loss`
```
RuntimeError: one of the variables needed for gradient computation has been modified by an inplace operation
```
2 years ago
6635bc3f7d
Merge pull request #1479 from rwightman/script_cleanup
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Train / val script enhancements, non-GPU (ie CPU) device support, HF datasets support, TFDS/WDS dataloading improvements
2 years ago
0e6023f032
Merge pull request #1381 from ChristophReich1996/master
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Fix typo in PositionalEncodingFourier
2 years ago
66f4af7090
Merge remote-tracking branch 'origin/master' into script_cleanup
2 years ago
d3961536c9
comment some debug logs for WDS dataset
2 years ago
e9dccc918c
Rename dataset/parsers -> dataset/readers, create_parser to create_reader, etc
2 years ago
8c28363dc9
Version 0.7.dev0 for master
2 years ago
30bafd7347
🔖 add dev suffix to version tag
2 years ago
f67a7ee8bd
Set num_workers in Iterable WDS/TFDS datasets early so sample estimate is correct
2 years ago
Ross Wightman