5cce2185e1
Update version.py
2024-06-07 13:13:23 -07:00
7ccb10ebff
Disable efficient_builder debug flag
2024-06-06 21:50:27 -07:00
ad026e6e33
Fix in_chans switching on create
2024-06-06 17:56:14 -07:00
fc1b66a51d
Fix first conv name for mci vit-b
2024-06-06 13:42:26 -07:00
88a1006e02
checkpoint filter fns with consistent name, add mobileclip-b pretrained cfgs
2024-06-06 12:38:52 -07:00
7d4ada6d16
Update ViTamin model defs
2024-06-06 09:16:43 -07:00
cc8a03daac
Add ConvStem and MobileCLIP hybrid model for B variant. Add full norm disable support to ConvNormAct layers
2024-06-06 09:15:27 -07:00
3c9d8e5b33
Merge remote-tracking branch 'origin/efficientnet_x' into fastvit_mobileclip
2024-06-05 17:35:15 -07:00
5756a81c55
Merge remote-tracking branch 'origin/Beckschen-vitamin' into fastvit_mobileclip
2024-06-05 15:20:54 -07:00
58591a97f7
Enable features_only properly
2024-06-04 16:57:16 -07:00
1b66ec7cf3
Fixup ViTamin, add hub weight reference
2024-06-03 17:14:03 -07:00
b2c0aeb0ec
Merge branch 'main' of https://github.com/Beckschen/pytorch-image-models into Beckschen-vitamin
2024-06-02 14:16:30 -07:00
7f96538052
Add missing lkc act for mobileclip fastvits
2024-05-31 11:59:51 -07:00
a503639bcc
Add mobileclip fastvit model defs, support extra SE. Add forward_intermediates API to fastvit
2024-05-30 10:17:38 -07:00
5fa6efa158
Add anti-aliasing support to mobilenetv3 and efficientnet family models. Update MobileNetV4 model defs, resolutions. Fix #599
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* create_aa helper function centralized for all timm uses (resnet, convbnact helper)
* allow BlurPool w/ pre-defined channels (expand)
* mobilenetv4 UIB block using ConvNormAct layers for improved clarity, esp with AA added
* improve more mobilenetv3 and efficientnet related type annotations
2024-05-27 22:06:22 -07:00
5dce710101
Add vit_little in12k + in12k-ft-in1k weights
2024-05-27 14:56:03 -07:00
3c0283f9ef
Fix reparameterize for NextViT. Fix #2187
2024-05-27 14:48:58 -07:00
4ff7c25766
Pass layer_scale_init_value to Mnv3Features module
2024-05-24 16:44:50 -07:00
a12b72b5c4
Fix missing head_norm arg pop for feature model
2024-05-24 15:50:34 -07:00
7fe96e7a92
More MobileNet-v4 fixes
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* missed final norm after post pooling 1x1 PW head conv
* improve repr of model by flipping a few modules to None when not used, nn.Sequential for MultiQueryAttention query/key/value/output
* allow layer scaling to be enabled/disabled at model variant level, conv variants don't use it
2024-05-24 15:09:29 -07:00
28d76a97db
Mixed up kernel size for last blocks in mnv4-conv-small
2024-05-24 11:50:42 -07:00
0c6a69e7ef
Add comments to MNV4 model defs with block variants
2024-05-23 15:54:05 -07:00
cb33956b20
Fix some mistakes in mnv4 model defs
2024-05-23 14:24:32 -07:00
70176a2dae
torchscript typing fixes
2024-05-23 11:43:05 -07:00
2a1a6b1236
Adding missing attention2d.py
2024-05-23 11:06:32 -07:00
cee79dada0
Merge remote-tracking branch 'origin/main' into efficientnet_x
2024-05-23 11:01:39 -07:00
6a8bb03330
Initial MobileNetV4 pass
2024-05-23 10:49:18 -07:00
e748805be3
Add regex matching support to AttentionExtract. Add return_dict support to graph extractors and use returned output in AttentionExtractor
2024-05-22 14:33:39 -07:00
44f72c04b3
Change node/module name matching for AttentionExtract so it keeps outputs in order. #1232
2024-05-22 13:45:25 -07:00
84cb225ecb
Add in12k + 12k_ft_in1k vit_medium weights
2024-05-20 15:52:46 -07:00
4634c3e134
Version 1.0.4.dev0
2024-05-20 15:52:27 -07:00
7a2ad6bce1
Add link to model weights on Hugging Face
2024-05-17 06:51:35 -04:00
530fb49e7e
Add link to model weights on Hugging Face
2024-05-17 06:48:59 -04:00
9b11801cb4
Credit earlier work with the same idea.
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Hi, this earlier work has the same name and idea behind this layer. It could be useful for readers to keep both links here if they want to see the effects of introducing this layer on a very different domain. 😄
2024-05-16 22:50:34 +02:00
cb0e4391be
Release 1.0.3
2024-05-15 11:06:22 -07:00
27fd2f35d3
Merge pull request #2181 from huggingface/Delaunay-dist-backend
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Delaunay dist backend flag
2024-05-15 10:00:59 -07:00
e57625e814
Tweak dist_backend to use device_type (before possible :)
2024-05-15 08:49:25 -07:00
6ca92570f7
Merge branch 'patch-1' of https://github.com/Delaunay/pytorch-image-models into Delaunay-dist-backend
2024-05-15 08:40:58 -07:00
cd0e7b11ff
Merge pull request #2180 from yvonwin/main
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Remove a duplicate function in mobilenetv3.py
2024-05-15 07:54:17 -07:00
83aee5c28c
Add explicit GAP (avg pool) variants of other SigLIP models.
2024-05-15 07:53:19 -07:00
58f2f79b04
Remove a duplicate function in mobilenetv3.py: `_gen_lcnet` is repeated in mobilenetv3.py.Remove the duplicate code.
2024-05-15 17:59:34 +08:00
7b3b11b63f
Support loading of paligemma weights into GAP variants of SigLIP ViT. Minor tweak to npz loading for packed transformer weights.
2024-05-14 15:44:37 -07:00
df304ffbf2
the dataclass init needs to use the default factory pattern, according to Ross
2024-05-14 15:10:05 -04:00
cc5f2f6f70
version 1.0.2dev0
2024-05-13 15:25:15 -07:00
3bfd036b58
Add normalize flag to transforms factory, allow return of non-normalized native dtype torch.Tensors
2024-05-13 15:23:25 -07:00
a69863ad61
Merge pull request #2156 from huggingface/hiera
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WIP Hiera implementation.
2024-05-13 14:58:12 -07:00
8848dad362
Update distributed.py
2024-05-13 16:55:42 -04:00
f7aa0a1a71
Add missing vit_wee weight
2024-05-13 12:05:47 -07:00
7a4e987b9f
Hiera weights on hub
2024-05-13 11:43:22 -07:00
23f09af08e
Merge branch 'main' into efficientnet_x
2024-05-12 21:31:08 -07:00
Ross Wightman
Ross Wightman
Beckschen
Fernando Cossio
yvonwin
Setepenre