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90be7233a3f55c29692a72da6ee4dcb5aab267d4
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177 Commits

Author SHA1 Message Date
lucidrains
90be7233a3 rotary needs to be done with full precision to be safe 2024-05-11 08:04:32 -07:00
Phil Wang
bca88e9039 address https://github.com/lucidrains/vit-pytorch/issues/300 2024-05-02 08:46:39 -07:00
Phil Wang
96f66d2754 address https://github.com/lucidrains/vit-pytorch/issues/306 2024-04-18 09:44:29 -07:00
Phil Wang
12249dcc5f address https://github.com/lucidrains/vit-pytorch/issues/304 2024-04-17 09:40:03 -07:00
SOUMYADIP MAL
8b8da8dede Update setup.py (#303) 2024-04-17 08:21:30 -07:00
lucidrains
5578ac472f address https://github.com/lucidrains/vit-pytorch/issues/292 2023-12-23 08:11:39 -08:00
lucidrains
d446a41243 share an idea that should be tried if it has not been 2023-11-14 16:55:36 -08:00
lucidrains
0ad09c4cbc allow channels to be customizable for cvt 2023-10-25 14:47:58 -07:00
Phil Wang
92b69321f4 1.6.2 2023-10-24 12:47:38 -07:00
lucidrains
53fe345e85 no longer needed with einops 0.7 2023-10-19 18:16:46 -07:00
Phil Wang
1616288e30 add xcit (#284) 
* add xcit

* use Rearrange layers

* give cross correlation transformer a final norm at end

* document
 2023-10-13 09:15:13 -07:00
lucidrains
bbb24e34d4 give a learned bias to and from registers for maxvit + register token variant 2023-10-06 10:40:26 -07:00
lucidrains
df8733d86e improvise a max vit with register tokens 2023-10-06 10:27:36 -07:00
lucidrains
3fdb8dd352 fix pypi 2023-10-01 08:14:20 -07:00
lucidrains
a36546df23 add simple vit with register tokens example, cite 2023-10-01 08:11:40 -07:00
lucidrains
d830b05f06 address https://github.com/lucidrains/vit-pytorch/issues/279 2023-09-10 09:32:57 -07:00
Phil Wang
8208c859a5 just remove PreNorm wrapper from all ViTs, as it is unlikely to change at this point 2023-08-14 09:48:55 -07:00
Phil Wang
4264efd906 1.4.2 2023-08-14 07:59:35 -07:00
lucidrains
950c901b80 fix linear head in simple vit, thanks to @atkos 2023-08-10 14:36:21 -07:00
Phil Wang
3e5d1be6f0 address https://github.com/lucidrains/vit-pytorch/pull/274 2023-08-09 07:53:38 -07:00
Phil Wang
6e2393de95 wrap up NaViT 2023-07-25 10:38:55 -07:00
Phil Wang
32974c33df one can pass a callback to token_dropout_prob for NaViT that takes in height and width and calculate appropriate dropout rate 2023-07-24 14:52:40 -07:00
Phil Wang
17675e0de4 add constant token dropout for NaViT 2023-07-24 14:14:36 -07:00
Phil Wang
598cffab53 release NaViT 2023-07-24 13:55:54 -07:00
Phil Wang
e9ca1f4d57 1.2.5 2023-07-24 06:43:24 -07:00
Phil Wang
9e3fec2398 fix mpp 2023-06-28 08:02:43 -07:00
Phil Wang
ce4bcd08fb address https://github.com/lucidrains/vit-pytorch/issues/266 2023-05-20 08:24:49 -07:00
Phil Wang
ad4ca19775 enforce latest einops 2023-05-08 09:34:14 -07:00
Phil Wang
c59843d7b8 add a version of simple vit using flash attention 2023-03-18 09:41:39 -07:00
lucidrains
9a8e509b27 separate a simple vit from mp3, so that simple vit can be used after being pretrained 2023-03-07 19:31:10 -08:00
Phil Wang
258dd8c7c6 release mp3, contributed by @Vishu26 2023-03-07 14:29:45 -08:00
Phil Wang
5699ed7d13 double down on dual patch norm, fix MAE and Simmim to be compatible with dual patchnorm 2023-02-10 10:39:50 -08:00
Phil Wang
46dcaf23d8 seeing a signal with dual patchnorm in another repository, fully incorporate 2023-02-06 09:45:12 -08:00
Phil Wang
bdaf2d1491 adopt dual patchnorm paper for as many vit as applicable, release 1.0.0 2023-02-03 08:11:29 -08:00
Phil Wang
500e23105a need simple vit with patch dropout for another project 2022-12-05 10:47:36 -08:00
Phil Wang
89e1996c8b add vit with patch dropout, fully embrace structured dropout as multiple papers are now corroborating each other 2022-12-02 11:28:11 -08:00
Phil Wang
2f87c0cf8f offer 1d versions, in light of https://arxiv.org/abs/2211.14730 2022-12-01 10:31:05 -08:00
Phil Wang
59c8948c6a try to fix tests 2022-10-29 11:44:17 -07:00
Phil Wang
cb6d749821 add a 3d version of cct, addressing https://github.com/lucidrains/vit-pytorch/issues/238 0.38.1 2022-10-29 11:35:06 -07:00
Phil Wang
6ec8fdaa6d make sure global average pool can be used for vivit in place of cls token 2022-10-24 19:59:48 -07:00
Phil Wang
13fabf901e add vivit 2022-10-24 09:34:04 -07:00
Phil Wang
5f1a6a05e9 release updated mae where one can more easily visualize reconstructions, thanks to @Vishu26 2022-10-17 10:41:46 -07:00
Phil Wang
b4853d39c2 add the 3d simple vit 2022-10-16 20:45:30 -07:00
Phil Wang
29fbf0aff4 begin extending some of the architectures over to 3d, starting with basic ViT 2022-10-16 15:31:59 -07:00
Phil Wang
f86e052c05 offer way for extractor to return latents without detaching them 2022-07-16 16:22:40 -07:00
Phil Wang
2fa2b62def slightly more clear of einops rearrange for cls token, for https://github.com/lucidrains/vit-pytorch/issues/224 2022-06-30 08:11:17 -07:00
Phil Wang
9f87d1c43b follow @arquolo feedback and advice for MaxViT 2022-06-29 08:53:09 -07:00
Phil Wang
2c6dd7010a fix hidden dimension in MaxViT thanks to @arquolo 2022-06-24 23:28:35 -07:00
Phil Wang
6460119f65 be able to accept a reference to a layer within the model for forward hooking and extracting the embedding output, for regionvit to work with extractor 2022-06-19 08:22:18 -07:00
Phil Wang
4e62e5f05e make extractor flexible for layers that output multiple tensors, show CrossViT example 2022-06-19 08:11:41 -07:00