8ece53e194
Switch BEiT to HF hub weights
2022-12-22 21:43:04 -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
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
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
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
9b114754db
refactor push_to_hub helper
2022-11-16 12:03:34 +01:00
ae0a0db7de
Create repo before cloning with Repository.clone_from
2022-11-15 15:17:20 +01:00
803254bb40
Fix spacing misalignment for fast norm path in LayerNorm modules
2022-10-24 21:43:49 -07:00
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
2022-10-15 09:29:39 -07:00
0e6023f032
Merge pull request #1381 from ChristophReich1996/master
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Fix typo in PositionalEncodingFourier
2022-10-14 18:34:33 -07:00
66f4af7090
Merge remote-tracking branch 'origin/master' into script_cleanup
2022-10-14 15:54:00 -07:00
9914f744dc
Add more maxxvit weights includ ConvNeXt conv block based experiments.
2022-10-10 21:49:18 -07:00
8fda68aff6
Fix repo id bug
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This to fix this issue #1482
2022-10-05 16:26:06 +02:00
1199c5a1a4
clip_laion2b models need 1e-5 eps for LayerNorm
2022-09-25 10:36:54 -07:00
e858912e0c
Add brute-force checkpoint remapping option
2022-09-23 16:07:03 -07:00
b293dfa595
Add CL SE module
2022-09-23 16:06:09 -07:00
a383ef99f5
Make huggingface_hub necessary if it's the only source for a pretrained weight
2022-09-23 13:54:21 -07:00
e069249a2d
Add hf hub entries for laion2b clip models, add huggingface_hub dependency, update some setup/reqs, torch >= 1.7
2022-09-16 21:39:05 -07:00
9d65557be3
Fix errant import
2022-09-15 17:47:23 -07:00
9709dbaaa9
Adding support for fine-tune CLIP LAION-2B image tower weights for B/32, L/14, H/14 and g/14. Still WIP
2022-09-15 17:25:59 -07:00
a520da9b49
Update tresnet features_info for v2
2022-09-13 20:54:54 -07:00
c8ab747bf4
BEiT-V2 checkpoints didn't remove 'module' from weights, adapt checkpoint filter
2022-09-13 17:56:49 -07:00
73049dc2aa
Fix type in dla weight update
2022-09-13 17:52:45 -07:00
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
fa8c84eede
Update maxvit_tiny_256 weight to better iter, add coatnet / maxvit / maxxvit model defs for future runs
2022-09-07 12:37:37 -07:00
c1b3cea19d
Add maxvit_rmlp_tiny_rw_256 model def and weights w/ 84.2 top-1 @ 256, 84.8 @ 320
2022-09-07 10:27:11 -07:00
914544fc81
Add beitv2 224x224 checkpoints from https://github.com/microsoft/unilm/tree/master/beit2
2022-09-06 20:25:18 -07:00
dc90816f26
Add `maxvit_tiny_rw_224` weights 83.5 @ 224 and `maxvit_rmlp_pico_rw_256` relpos weights, 80.5 @ 256, 81.3 @ 320
2022-09-06 16:14:41 -07:00
f489f02ad1
Make gcvit window size ratio based to improve resolution changing support #1449 . Change default init to original.
2022-09-06 16:14:00 -07:00
7f1b223c02
Add maxvit_rmlp_nano_rw_256 model def & weights, make window/grid size dynamic wrt img_size by default
2022-08-29 15:49:32 -07:00
e6a4361306
pretrained_cfg entry for mvitv2_small_cls
2022-08-28 15:27:01 -07:00
f66e5f0e35
Fix class token support in MViT-V2, add small_class variant to ensure it's tested. Fix #1443
2022-08-28 15:24:04 -07:00
f1d2160d85
Update a few maxxvit comments, rename PartitionAttention -> PartitionAttenionCl for consistency with other blocks
2022-08-26 12:53:49 -07:00
eca6f0a25c
Fix syntax error (extra dataclass comma) in maxxvit.py
2022-08-26 11:29:09 -07:00
ff6a919cf5
Add --fast-norm arg to benchmark.py, train.py, validate.py
2022-08-25 17:20:46 -07:00
769ab4b98a
Clean up no_grad for trunc normal weight inits
2022-08-25 16:29:52 -07:00
48e1df8b37
Add norm/norm_act header comments
2022-08-25 16:29:34 -07:00
7c2660576d
Tweak init for convnext block using maxxvit/coatnext.
2022-08-25 15:30:59 -07:00
1d8d6f6072
Fix two default args in DenseNet blocks... fix #1427
2022-08-25 15:00:35 -07:00
527f9a4cb2
Updated to correct maxvit_nano weights...
2022-08-24 12:42:11 -07:00
b2e8426fca
Make k=stride=2 ('avg2') pooling default for coatnet/maxvit. Add weight links. Rename 'combined' partition to 'parallel'.
2022-08-24 11:01:20 -07:00
837c68263b
For ConvNeXt, use timm internal LayerNorm for fast_norm in non conv_mlp mode
2022-08-23 15:17:12 -07:00
cac0a4570a
More test fixes, pool size for 256x256 maxvit models
2022-08-23 13:38:26 -07:00
e939ed19b9
Rename internal creation fn for maxvit, has not been just coatnet for a while...
2022-08-22 17:44:51 -07:00
ffaf97f813
MaxxVit! A very configurable MaxVit and CoAtNet impl with lots of goodies..
2022-08-22 17:42:10 -07:00
8c9696c9df
More model and test fixes
2022-08-22 17:40:31 -07:00
ca52108c2b
Fix some model support functions
2022-08-19 10:20:51 -07:00
f332fc2db7
Fix some test failures, torchscript issues
2022-08-18 16:19:46 -07:00
6e559e9b5f
Add MViT (Multi-Scale) V2
2022-08-17 15:12:31 -07:00
43aa84e861
Add 'fast' layer norm that doesn't cast to float32, support APEX LN impl for slight speed gain, update norm and act factories, tweak SE for ability to disable bias (needed by GCVit)
2022-08-17 14:32:58 -07:00
c486aa71f8
Add GCViT
2022-08-17 14:29:18 -07:00
fba6ecd39b
Add EfficientFormer
2022-08-17 14:08:53 -07:00
ff4a38e2c3
Add PyramidVisionTransformerV2
2022-08-17 12:06:05 -07:00
1d8ada359a
Add timm ConvNeXt 'atto' weights, change test resolution for FB ConvNeXt 224x224 weights, add support for different dw kernel_size
2022-08-15 17:56:08 -07:00
2544d3b80f
ConvNeXt pico, femto, and nano, pico, femto ols (overlapping stem) weights and model defs
2022-08-05 17:05:50 -07:00
13565aad50
Add edgenext_base model def & weight link, update to improve ONNX export #1385
2022-08-05 16:58:34 -07:00
8ad4bdfa06
Allow ntuple to be used with string values
2022-07-28 16:18:18 -07:00
faae93e62d
Fix typo in PositionalEncodingFourier
2022-07-28 19:08:08 -04:00
ec6a28830f
Add DeiT-III 'medium' model defs and weights
2022-07-28 15:03:20 -07:00
6f103a442b
Add convnext_nano weights, 80.8 @ 224, 81.5 @ 288
2022-07-26 16:40:27 -07:00
4042a94f8f
Add weights for two 'Edge' block (3x3->1x1) variants of CS3 networks.
2022-07-26 16:40:27 -07:00
c8f69e04a9
Merge pull request #1365 from veritable-tech/fix-resize-pos-embed
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Take `no_emb_class` into account when calling `resize_pos_embed`
2022-07-24 21:03:01 -07:00
0b64117592
Take `no_emb_class` into account when calling `resize_pos_embed`
2022-07-24 19:11:45 +08:00
56c3a84db3
Update type hint for `register_notrace_module`
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register_notrace_module is used to decorate types (i.e. subclasses of nn.Module).
It is not called on module instances.
2022-07-22 16:59:55 -05:00
1b278136c3
Change models with mean 0,0,0 std 1,1,1 from int to float for consistency as mentioned in #1355
2022-07-21 17:36:15 -07:00
909705e7ff
Remove some redundant requires_grad=True from nn.Parameter in third party code
2022-07-20 12:37:41 -07:00
c5e0d1c700
Add dilation support to convnext, allows output_stride=8 and 16 use. Fix #1341
2022-07-19 17:52:10 -07:00
dc376e3676
Ensure all model entrypoint fn default to `pretrained=False` (a few didn't)
2022-07-19 13:58:41 -07:00
23b102064a
Add cs3sedarknet_x weights w/ 82.65 @ 288 top1. Add 2 cs3 edgenet models (w/ 3x3-1x1 block), remove aa from cspnet blocks (not needed)
2022-07-19 13:56:44 -07:00
05313940e2
Add cs3darknet_x, cs3sedarknet_l, and darknetaa53 weights from TPU sessions. Move SE btwn conv1 & conv2 in DarkBlock. Improve SE/attn handling in Csp/DarkNet. Fix leaky_relu bug on older csp models.
2022-07-15 16:55:16 -07:00
51cca82aa1
👽 use hf_hub_download instead of cached_download
2022-07-14 16:41:45 -04:00
a45b4bce9a
x and xx small edgenext models do benefit from larger test input size
2022-07-08 10:53:27 -07:00
a8e34051c1
Unbreak gamma remap impacting beit checkpoint load, version bump to 0.6.4
2022-07-07 23:07:43 -07:00
a1cb25066e
Add edgnext_small_rw weights trained with swin like recipe. Better than original 'small' but not the recent 'USI' distilled weights.
2022-07-07 22:02:57 -07:00
7c7ecd2492
Add --use-train-size flag to force use of train input_size (over test input size) for validation. Default test-time pooling to use train input size (fixes issues).
2022-07-07 22:01:24 -07:00
ce65a7b29f
Update vit_relpos w/ some additional weights, some cleanup to match recent vit updates, more MLP log coord experiments.
2022-07-07 21:33:25 -07:00
58621723bd
Add CrossStage3 DarkNet (cs3) weights
2022-07-07 17:43:38 -07:00
db0cee9910
Refactor cspnet configuration using dataclasses, update feature extraction for new cs3 variants.
2022-07-07 14:43:27 -07:00
eca09b8642
Add MobileVitV2 support. Fix #1332 . Move GroupNorm1 to common layers (used in poolformer + mobilevitv2). Keep ol custom ConvNeXt LayerNorm2d impl as LayerNormExp2d for reference.
2022-07-07 14:41:01 -07:00
Ross Wightman
Wauplin
Ross Wightman
Mohamed Rashad
Christoph Reich
Ceshine Lee
Jasha10
nateraw