8556462a18
fix doc typo in resnetv2
2023-10-20 11:56:50 -07:00
462fb3ec9f
Push new repvit weights to hub, tweak tag names
2023-10-20 11:49:29 -07:00
5309424d5e
Merge branch 'main' of https://github.com/jameslahm/pytorch-image-models into jameslahm-main
2023-10-20 11:08:12 -07:00
d3ebdcfd93
Disable strict load when siglip vit pooling removed
2023-10-19 12:03:40 -07:00
e728f3efdb
Cleanup ijepa models, they're just gap (global-avg-pool) models w/o heads. fc-norm conversion was wrong, gigantic should have been giant
2023-10-17 15:44:46 -07:00
49a459e8f1
Merge remote-tracking branch 'upstream/main' into vit_siglip_and_reg
2023-10-17 09:36:48 -07:00
59b622233b
Change ijepa names, add pretrain cfg for reg experimentts
2023-10-17 07:16:17 -07:00
71365165a2
Add SigLIP weights
2023-10-16 23:26:08 -07:00
42daa3b497
Add full set of SigLIP models
2023-10-10 22:15:45 -07:00
4aa166de9c
Add hgnet ssld weights
2023-10-09 19:14:10 +08:00
159e91605c
Add PP-HGNet and PP-HGNetv2 models
2023-10-09 19:04:58 +08:00
884ef88818
fix all SDPA dropouts
2023-10-05 08:58:41 -07:00
b500cae4c5
fastvit: don't dropout in eval
2023-10-05 08:58:41 -07:00
b9dde58076
Fixup attention pooling in siglip vit support
2023-10-02 11:44:12 -07:00
f061b539d7
Update RepViT models
2023-10-01 14:00:53 +08:00
99cfd6702f
Use global pool arg to select attention pooling in head
2023-09-30 16:16:21 -07:00
82cc53237e
Working on support for siglip (w/ attn pool) vit backbone, and adding registers (reg tokens)
2023-09-30 16:03:01 -07:00
6bae514656
Add pretrained patch embed resizing to swin
2023-09-27 10:27:28 -07:00
5c504b4ded
flip these two
2023-09-27 10:24:12 -07:00
8ba2038e6b
fast_vit: propagate act_layer argument
2023-09-27 10:24:12 -07:00
95ba90157f
Update tiny_vit.py to fix bug
2023-09-23 10:05:52 -07:00
245ad4f41a
Added missing RuntimeError to builder functions of models that do not currently support feature extraction
2023-09-19 08:19:14 -07:00
d4c21b95f4
Update repghost.py
2023-09-15 11:41:56 -07:00
7eb7d13845
Fix in_features for linear layer in reset_classifier.
2023-09-13 09:29:38 -07:00
0d124ffd4f
Update README. Fine-grained layer-wise lr decay working for tiny_vit and both efficientvits. Minor fixes.
2023-09-01 15:05:29 -07:00
2f0fbb59b3
TinyViT weights on HF hub
2023-09-01 11:05:56 -07:00
507cb08acf
TinyVitBlock needs adding as leaf for FX now, tweak a few dim names
2023-09-01 11:05:56 -07:00
9caf32b93f
Move levit style pos bias resize with other rel pos bias utils
2023-09-01 11:05:56 -07:00
63417b438f
TinyViT adjustments
...
* keep most of net in BCHW layout, performance appears same, can remove static resolution attribs and features easier to use
* add F.sdpa, decent gains in pt 2.1
* tweak crop pct based on eval
2023-09-01 11:05:56 -07:00
39aa44b192
Fixing tinyvit trace issue
2023-09-01 11:05:56 -07:00
aea3b9c854
Fixing tinyvit input_size issue
2023-09-01 11:05:56 -07:00
fabc4e5bcd
Fixing tinyvit torchscript issue
2023-09-01 11:05:56 -07:00
bae949f830
fix attention_bias_cache in tinyvit
2023-09-01 11:05:56 -07:00
170a5b6e27
add tinyvit
2023-09-01 11:05:56 -07:00
983310d6a2
Fix #1935 , torch.amp.autocast -> torch.autocast (namespace issue for 1.10 pt compat)
2023-08-30 15:03:28 -07:00
c8b2f28096
Fix a few typos, fix fastvit proj_drop, add code link
2023-08-28 21:26:29 -07:00
fc5d705b83
dynamic_size -> dynamic_img_size, add dynamic_img_pad for padding option
2023-08-27 15:58:35 -07:00
1f4512fca3
Support dynamic_resize in eva.py models
2023-08-27 15:58:35 -07:00
ea3519a5f0
Fix dynamic_resize for deit models (distilled or no_embed_cls) and vit w/o class tokens
2023-08-27 15:58:35 -07:00
4d8ecde6cc
Fix torchscript for vit-hybrid dynamic_resize
2023-08-27 15:58:35 -07:00
fdd8c7c2da
Initial impl of dynamic resize for existing vit models (incl vit-resnet hybrids)
2023-08-27 15:58:35 -07:00
5d599a6a10
RepViT weights on HF hub
2023-08-25 10:39:02 -07:00
56c285445c
Wrong pool size for 384x384 inception_next_base
2023-08-24 18:31:44 -07:00
af9f56f3bf
inception_next dilation support, weights on hf hub, classifier reset / global pool / no head fixes
2023-08-24 18:31:44 -07:00
2d33b9df6c
Add features_only support to inception_next
2023-08-24 18:31:44 -07:00
3d8d7450ad
InceptionNeXt using timm builder, more cleanup
2023-08-24 18:31:44 -07:00
f4cf9775c3
Adding InceptionNeXt
2023-08-24 18:31:44 -07:00
d6c348765a
Fix first_conv for mobileone and fastvit
2023-08-23 22:50:37 -07:00
16334e4bec
Fix two fastvit issues
2023-08-23 22:50:37 -07:00
5242ba6edc
MobileOne and FastViT weights on HF hub, more code cleanup and tweaks, features_only working. Add reparam flag to validate and benchmark, support reparm of all models with fuse(), reparameterize() or switch_to_deploy() methods on modules
2023-08-23 22:50:37 -07:00
40dbaafef5
Stagify FastViT /w downsample to top of stage
2023-08-23 22:50:37 -07:00
8470eb1cb5
More fastvit & mobileone updates, ready for weight upload
2023-08-23 22:50:37 -07:00
8474508d07
More work on FastViT, use own impl of MobileOne, validation working with remapped weight, more refactor TODO
2023-08-23 22:50:37 -07:00
c7a20cec13
Begin adding FastViT
2023-08-23 22:50:37 -07:00
7fd3674d0d
Add mobileone and update repvgg
2023-08-23 22:50:37 -07:00
3055411c1b
Fix samvit bug, add F.sdpa support and ROPE option ( #1920 )
...
* Fix a bug I introduced in samvit, add F.sdpa support and ROPE option to samvit, neck is LayerNorm if not used and standard classifier used
* Add attn dropout to F.sdpa
* Fix fx trace for sam vit
* Fixing torchscript issues in samvit
* Another torchscript fix
* samvit head fc name fix
2023-08-20 21:22:59 -07:00
300f54a96f
Another effcientvit (mit) tweak, fix torchscript/fx conflict with autocast disable
2023-08-20 15:07:25 -07:00
dc18cda2e7
efficientvit (mit) msa attention q/k/v ops need to be in float32 to train w/o NaN
2023-08-20 11:49:36 -07:00
be4e0d8f76
Update attrib comment to include v2
2023-08-19 23:39:09 -07:00
126a58e563
Combine ghostnetv2 with ghostnet, reduec redundancy, add weights to hf hub.
2023-08-19 23:33:43 -07:00
3f320a9e57
Merge branch 'Add-GhostNetV2' of github.com:yehuitang/pytorch-image-models into yehuitang-Add-GhostNetV2
2023-08-19 22:07:54 -07:00
7c2728c6fe
Merge pull request #1919 from ChengpengChen/main
...
Add RepGhost models and weights
2023-08-19 16:26:45 -07:00
69e0ca2e36
Weights on hf hub, bicubic yields slightly better eval
2023-08-19 16:25:45 -07:00
b8011565bd
Merge pull request #1894 from seefun/master
...
add two different EfficientViT models
2023-08-19 09:24:14 -07:00
7d7589e8da
Fixing efficient_vit torchscript, fx, default_cfg issues
2023-08-18 23:23:11 -07:00
58ea1c02c4
Add fixed_input_size flag to msra efficient_vit
2023-08-18 16:48:17 -07:00
c28324a150
Update efficient_vit (msra), hf hub weights
2023-08-18 16:45:37 -07:00
e700a32626
Cleanup of efficient_vit (mit), tweak eps for better AMP behaviour, formatting/cleanup, weights on hf hub
2023-08-18 16:06:07 -07:00
00f670fa69
fix bug in ci for efficientvits
2023-08-17 14:40:17 +08:00
e7f97cb5ce
Fix typos RepGhost models
2023-08-16 14:27:45 +08:00
d1d0193615
Add RepGhost models and weights
2023-08-16 11:54:53 +08:00
7938f28542
Fix typo in efficientformer_v2
2023-08-16 03:29:01 +09:00
b407794e3a
Add GhostNetV2
2023-08-13 18:20:27 +08:00
fc865282e5
Add ghostnetv2.py
2023-08-13 18:16:26 +08:00
da75cdd212
Merge pull request #1900 from huggingface/swin_maxvit_resize
...
Add support for resizing swin transformer, maxvit, coatnet at creation time
2023-08-11 15:05:28 -07:00
78a04a0e7d
Merge pull request #1911 from dsuess/1910-fixes-batchnormact-fx
...
Register norm_act layers as leaf modules
2023-08-11 14:34:16 -07:00
2048f6f20f
set self.num_features to neck_chans if neck_chans > 0
2023-08-11 13:45:06 +09:00
3a44e6c602
Fix #1912 CoaT model not loading w/ return_interm_layers
2023-08-10 11:15:58 -07:00
986de90360
Register orm_act layers as leaf modules
2023-08-10 15:37:26 +10:00
c692715388
Some RepVit tweaks
...
* add head dropout to RepVit as all models have that arg
* default train to non-distilled head output via distilled_training flag (set_distilled_training) so fine-tune works by default w/o distillation script
* camel case naming tweaks to match other models
2023-08-09 12:41:12 -07:00
c153cd4a3e
Add more advanced interpolation method from BEiT and support non-square window & image size adaptation for
...
* beit/beit-v2
* maxxvit/coatnet
* swin transformer
And non-square windows for swin-v2
2023-08-08 16:41:16 -07:00
bb2b6b5f09
fix num_classes not found
2023-08-07 15:16:03 +08:00
1dab536cb1
Fix torch.fx for swin padding change
2023-08-05 13:09:55 -07:00
7c0f492dbb
Fix type annotation for torchscript
2023-08-04 23:03:52 -07:00
7790ea709b
Add support for resizing swin transformer img_size and window_size on init and load from pretrained weights. Add support for non-square window_size to both swin v1/v2
2023-08-04 22:10:46 -07:00
81089b10a2
Remove unecessary LongTensor in EfficientFormer. Possibly maybe fix #1878
2023-08-03 16:38:53 -07:00
d138a9bf88
Add gluon hrnet small weights, fix #1895
2023-08-03 12:15:04 -07:00
150356c493
Fix unfortunate selecsls case bug caused by aggressive IDE rename
2023-08-03 10:37:06 -07:00
6e8c53d0d3
Comment out beit url, no longer valid as now require long query string, leave for reference, must use HF hub now.
2023-08-03 10:00:46 -07:00
a56e2bbf19
fix efficientvit_msra pretrained load
2023-08-03 18:44:38 +08:00
e94c60b546
efficientvit_msra refactor
2023-08-03 17:45:50 +08:00
047bab6ab2
efficientvit_mit stage refactor
2023-08-03 14:59:35 +08:00
e8fb866ccf
fix efficientvit_msra pool
2023-08-02 14:40:01 +08:00
43443f64eb
fix efficientvits
2023-08-02 14:12:37 +08:00
82d1e99e1a
add efficientvit(msra)
2023-08-01 18:51:08 +08:00
b91a77fab7
add EfficientVit (MIT)
2023-08-01 12:42:21 +08:00
a9d0615f42
Fix ijepa vit issue with 448 model, minor formatting fixes
2023-07-26 20:46:27 -07:00
5874d1bfc7
Merge pull request #1876 from jameslahm/main
...
Add RepViT models
2023-07-26 14:38:41 -07:00
b10310cc27
Add proper pool size for new resnexts
2023-07-26 14:36:03 -07:00
b71d60cdb7
Two small fixes, num_classes in base class, add model tag
2023-07-26 13:18:49 -07:00
3561f8e885
Add seresnextaa201d_32x8d 12k and 1k weights
2023-07-26 13:17:05 -07:00
3318e7614d
Add RepViT models
2023-07-21 14:56:53 +08:00
158bf129c4
Replace deprecated NumPy aliases of builtin types
2023-07-03 22:24:25 +03:00
c241081251
Merge pull request #1850 from huggingface/effnet_improve_features_only
...
Support other features only modes for EfficientNet. Fix #1848 fix #1849
2023-06-23 22:56:08 -07:00
47517dbefd
Clean more feature extract issues
...
* EfficientNet/MobileNetV3/HRNetFeatures cls and FX mode support -ve index
* MobileNetV3 allows feature_cfg mode to bypass MobileNetV3Features
2023-06-14 14:46:22 -07:00
a09c88ed0f
Support other features only modes for EfficientNet
2023-06-14 12:57:39 -07:00
c3f24a5ae5
‘add ViT weight from I-JEPA pretrain’
2023-06-14 22:30:31 +08:00
c308dbc6f2
update dinov2 layerscale init values
2023-05-24 12:20:17 -04:00
e9373b1b92
Cleanup before samvit merge. Resize abs posembed on the fly, undo some line-wraps, remove redundant unbind, fix HF hub weight load
2023-05-18 16:43:48 -07:00
c1c6eeb909
fix loading pretrained weight for samvit
2023-05-18 08:49:29 +08:00
15de561f2c
fix unit test for samvit
2023-05-17 12:51:12 +08:00
ea1f52df3e
add ViT for Segment-Anything Model
2023-05-17 11:39:29 +08:00
c5d3ee47f3
Add B/16 datacompxl CLIP weights
2023-05-16 11:27:20 -07:00
fc77e9ecc5
Update hub.py
...
fixed import of _hub modules
2023-05-12 21:48:46 +02:00
f744bda994
use torch.jit.Final instead of Final for beit, eva
2023-05-12 09:12:14 -07:00
2e99bcaedd
Update README, prep for version 0.9.0 release
2023-05-11 15:22:50 -07:00
3eaf729f3f
F.sdpa for visformer fails w/o contiguous on qkv, make experimental
2023-05-11 11:37:37 -07:00
cf1884bfeb
Add 21k maxvit tf weights
2023-05-10 18:23:32 -07:00
6c2edf4d74
Missed hub_id entries for byoanet models
2023-05-10 15:58:55 -07:00
850ab4931f
Missed a few pretrained tags...
2023-05-10 12:16:30 -07:00
ff2464e2a0
Throw when pretrained weights not available and pretrained=True (principle of least surprise).
2023-05-10 10:44:34 -07:00
e0ec0f7252
Merge pull request #1643 from nateraw/docstrings-update
...
Update Docstring for create_model
2023-05-09 21:33:20 -07:00
627b6315ba
Add typing to dinov2 entrypt fns, use hf hub for mae & dinov2 weights
2023-05-09 20:42:11 -07:00
960a882510
Remove label offsets and remove old weight url for 1001 class (background + in1k) TF origin weights
2023-05-09 18:00:41 -07:00
a01d8f86f4
Tweak DinoV2 add, add MAE ViT weights, add initial intermediate layer getter experiment
2023-05-09 17:59:22 -07:00
59bea4c306
Merge branch 'main' into dot_nine_cleanup
2023-05-09 12:27:32 -07:00
5cc87e6485
Add dinov2 pretrained models ( #1797 )
...
* add dinov2 small, base, and large
* fix input size
* fix swiglu & dinov2 vit giant
* use SwiGLUPacked to replace GluMlp
* clean up & add ffn_layer placeholder for ParallelScalingBlock
2023-05-09 12:24:47 -07:00
21e57c0b9e
Add missing beitv2 in1k -> in1k models
2023-05-08 17:03:51 -07:00
8c6fccb879
Allow passing state_dict directly via pretrained cfg mechanism as an override
2023-05-08 15:15:44 -07:00
e4e43190ce
Add typing to all model entrypoint fns, add old cache check env var to builder
2023-05-08 08:52:38 -07:00
cb3f9c23bb
Metaformer baselines for vision (final PR with cleanup) ( #1793 )
...
* update
* Update metaformers.py
* Update metaformers.py
* Update metaformers.py
* Update metaformers.py
* Update metaformers.py
* Update metaformers.py
* Update metaformers.py
* Update metaformers.py
* Update metaformers.py
* Update metaformers.py
* Update metaformers.py
* Update metaformers.py
* Update metaformers.py
* Update metaformers.py
* Update metaformers.py
* Update metaformers.py
* Update metaformers.py
* Update metaformers.py
* Update metaformers.py
* Update metaformers.py
* Update metaformers.py
* Update metaformers.py
* Update metaformers.py
* Update metaformers.py
* Update metaformers.py
* Update metaformers.py
* Update metaformers.py
* Update metaformers.py
* Update metaformers.py
* Update metaformers.py
* Update metaformers.py
* Update metaformers.py
* Update metaformers.py
* Update metaformers.py
* Update metaformers.py
* Update metaformers.py
* Update metaformers.py
* Update metaformers.py
* Update metaformers.py
* Update metaformers.py
* Update metaformers.py
* Update metaformers.py
* Update metaformers.py
* Update metaformers.py
* merge with poolformer, initial version
* Update metaformers.py
* Update metaformers.py
* Update metaformers.py
* Update metaformers.py
* Update metaformers.py
* Update metaformers.py
* Update metaformers.py
* Update metaformers.py
* Update metaformers.py
* Update metaformers.py
* Update metaformers.py
* Update metaformers.py
* Update metaformers.py
* Update metaformers.py
* Update metaformers.py
* Update metaformers.py
* Update metaformers.py
* Update metaformers.py
* Revert "Update metaformers.py"
This reverts commit 2916f37f8d1d882eb4942209d0830e32bede4e274ed934e0003f0b0753672fef9006d7b7696a30a741fe5c3626a3aee37c35f938beb81b10bde717e539274bd45ea2329ab8ec53b8ce5b8aab6225b94102fcc30eaa366aae930426a8e481a5a913f5d438https://github.com/fffffgggg54/pytorch-image-models into metaformer_workspace
commit d577129aaa23fb348a8bb93bcd17cf1d5a4e8ff8
Author: Fredo Guan <fredo.guan@hotmail.com>
Date: Mon Mar 6 01:57:20 2023 -0800
Update metaformers.py
commit f7367304e8f3b7a9a7f16e0a032bb72546afcc2a
Author: Fredo Guan <fredo.guan@hotmail.com>
Date: Mon Mar 6 01:56:11 2023 -0800
Metaformer baselines for vision (#12 )
* formatting, cleanup, fix dropout
* fix regression, pass kwargs
* fix poolformerv1 weights, formatting
* Update metaformers.py
* Update metaformers.py
* Update metaformers.py
* Update metaformers.py
* Update metaformers.py
* Update metaformers.py
* Update metaformers.py
* Update metaformers.py
* Update metaformers.py
* Update metaformers.py
* Update metaformers.py
* Update metaformers.py
* Update metaformers.py
* some cleanup
* SDPA from ViT, fix imports
* Update metaformers.py
* fix head reset
* fast norm bias patch for metaformers
* Metaformer refactor, remove rand/ident models, fix issues, remove old poolformer
* Switch to hub weights
---------
Co-authored-by: Fredo Guan <fredo.guan@hotmail.com>
2023-05-05 11:18:26 -07:00
320bf9c469
Remove redundant types, kwargs back in own section (lesser of many evils?)
2023-05-01 14:21:48 -07:00
8fa86a28a8
Add datacomp L/14 (79.2 zs) image tower weights
2023-05-01 10:24:08 -07:00
5e64777804
0.8.21dev0
2023-04-28 13:46:59 -07:00
493c730ffc
Fix pit regression
2023-04-26 23:16:06 -07:00
437d344e03
Always some torchscript issues
2023-04-26 20:42:34 -07:00
528faa0e04
Some fixes
2023-04-26 17:46:20 -07:00
3386af8c86
Final push to get remaining models using multi-weight pretrained configs, almost all weights on HF hub
2023-04-26 15:52:13 -07:00
7ad7ddb7ad
DenseNet, DPN, VoVNet, Aligned Xception weights on HF hub. DenseNet grad_checkpointing using timm API
2023-04-21 16:56:44 -07:00
864bfd43d0
hardcore nas weights on hf hub
2023-04-21 14:35:10 -07:00
6e4529ae35
TResNet weights now on HF hub, modified to remove InplaceABN dependency
2023-04-21 14:20:48 -07:00
04dcbc02ec
Fix weight remap for tresnet_v2_l
2023-04-21 09:05:04 -07:00
a08e5aed1d
More models w/ multi-weight support, moving to HF hub. Removing inplace_abn from all models including TResNet
2023-04-20 22:44:49 -07:00
34df125be6
cait, volo, xvit hub weights
2023-04-14 10:13:13 -07:00
f6d5767551
cspnet models on HF hub w/ multi-weight support
2023-04-12 14:02:38 -07:00
80b247d843
Update swin_v2 attn_mask buffer change in #1790 to apply to updated checkpoints in hub
2023-04-11 14:40:32 -07:00
1a1aca0cee
Merge pull request #1761 from huggingface/patch_drop_refactor
...
Implement patch dropout for eva / vision_transformer, refactor dropout args
2023-04-11 14:37:36 -07:00
c0670822d2
Small factory handling fix for pretrained tag vs cfg
2023-04-11 07:42:13 -07:00
2f25f73b90
Missed a fused_attn update in relpos vit
2023-04-10 23:30:50 -07:00
0b65b5c0ac
Add finalized eva CLIP weights pointing to remapped timm hub models
2023-04-10 23:13:12 -07:00
965d0a2d36
fast_attn -> fused_attn, implement global config for enable/disable fused_attn, add to more models. vit clip openai 336 weights.
2023-04-10 12:04:33 -07:00
4d135421a3
Implement patch dropout for eva / vision_transformer, refactor / improve consistency of dropout args across all vit based models
2023-04-07 20:27:23 -07:00
c76818a592
skip attention mask buffers
...
Allows more flexibility in the resolutions accepted by SwinV2.
2023-04-07 18:50:02 +02:00
1bb3989b61
Improve kwarg passthrough for swin, vit, deit, beit, eva
2023-04-05 21:37:16 -07:00
35c94b836c
Update warning message for deprecated model names
2023-04-05 17:24:17 -07:00
9eaab795c2
Add some vit model deprecations
2023-04-05 17:21:03 -07:00
abff3f12ec
Wrong pool_size for 288 ft
2023-04-05 16:07:51 -07:00
356309959c
ResNet models on HF hub, multi-weight support, add torchvision v2 weights, new 12k pretrained and fine-tuned timm anti-aliased weights
2023-04-05 14:19:42 -07:00
beef7f0a22
Add ImageNet-12k intermediate fine-tunes of convnext base & large CLIP models, add first 1k fine-tune of xxlarge
2023-03-31 16:45:01 -07:00
9aa1133bd2
Fix #1750 , uncomment weight that exists on HF hub, add FIXME to 3 others that are still on local storage
2023-03-31 14:49:30 -07:00
7326470514
Merge pull request #1746 from huggingface/eva02
...
Adding EVA02 weights and model defs
2023-03-31 12:17:00 -07:00
adeb9de7c6
Mismatch in eva pretrained_cfg vs model for one of the clip variants
2023-03-31 10:30:30 -07:00
0737bd3ec8
eva02 non-CLIP weights on HF hub, add initial eva02 clip model configs w/ postnorm variant & attn LN
2023-03-30 23:43:59 -07:00
ac67098147
Add final attr for fast_attn on beit / eva
2023-03-28 08:40:40 -07:00
1885bdc431
Merge pull request #1745 from huggingface/mw-mlp_mixer
...
MLP-Mixer multi-weight support, HF hub push
2023-03-28 07:55:17 -07:00
e9f427b953
Add hf hub entries for mlp_mixer
2023-03-27 22:50:43 -07:00
cff81deb78
multi-weight and hf hub for deit / deit3
2023-03-27 22:47:16 -07:00
3863d63516
Adding EVA02 weights and model defs, move beit based eva_giant to same eva.py file. Cleanup rotary pos, add lang oriented freq bands to be compat with eva design choice. Fix #1738
2023-03-27 17:16:07 -07:00
b12060996c
MLP-Mixer multi-weight support, hf hub push
2023-03-27 16:42:13 -07:00
d196fa536d
Fix last min torchscript regression in nfnet changes
2023-03-24 00:10:17 -07:00
33ada0cbca
Add group_matcher to focalnet for proper layer-wise LR decay
2023-03-23 23:21:49 -07:00
b271dc0e16
NFNet multi-weight support + HF hub push
2023-03-23 23:20:38 -07:00
dbd33e4b62
Update crop settings for new rexnet weights
2023-03-22 15:39:49 -07:00
da6bdd4560
Update resnetv2.py for multi-weight and HF hub weights
2023-03-22 15:38:04 -07:00
b3e816d6d7
Improve filtering behaviour for tag + non-tagged model wildcard consistency.
2023-03-22 10:21:22 -07:00
7aba64ebdb
Add update byobnet.py w/ models pushed to HF hub
2023-03-22 10:00:00 -07:00
e7ef8335bf
regnet.py multi-weight conversion, new ImageNet-12k pretrain/ft from timm for y_120 and y_160, also new tv v2, swag, & seer weights for push to Hf hub.
2023-03-21 15:51:49 -07:00
c78319adce
Add ImageNet-12k ReXNet-R 200 & 300 weights, and push existing ReXNet models to HF hub. Dilation support added to rexnet
2023-03-20 13:48:17 -07:00
041de79f9e
Fix numel use in helpers for checkpoint remap
2023-03-20 09:36:48 -07:00
49b9c3be80
Include pretrained tag in deprecated mapping warning
2023-03-19 21:21:19 -07:00
572f05096a
Swin and FocalNet weights on HF hub. Add model deprecation functionality w/ some registry tweaks.
2023-03-18 14:55:09 -07:00
5aebad3fbc
return_map back to out_map for _feature helpers
2023-03-16 14:50:55 -07:00
acfd85ad68
All swin models support spatial output, add output_fmt to v1/v2 and use ClassifierHead.
...
* update ClassifierHead to allow different input format
* add output format support to patch embed
* fix some flatten issues for a few conv head models
* add Format enum and helpers for tensor format (layout) choices
2023-03-15 23:21:51 -07:00
c30a160d3e
Merge remote-tracking branch 'origin/main' into focalnet_and_swin_refactor
2023-03-15 15:58:39 -07:00
ad94d737b7
Add support to ConvNextBlock for downsample and channel expansion to improve stand alone use. Fix #1699
2023-03-13 14:06:24 -07:00
992bf7c3d4
chore: Modify the MobileVitV2Block to be coreml exportable
...
based on is_exportable() set variable controlling behaviour of the block
CoreMLTools support im2col from 6.2 version, unfortunately col2im
is still not supported.
Tested with exporting to ONNX, Torchscript, CoreML, and TVM.
2023-03-03 09:38:24 +01:00
4b8cfa6c0a
Add convnext_xxlarge CLIP image tower weights, version 0.8.15dev0
2023-02-26 21:51:48 -08:00
1c13ef7b46
Add default norm_eps=1e-5 for convnext_xxlarge, improve kwarg merging for all convnext models
2023-02-26 12:11:49 -08:00
a5b01ec04e
Add type annotations to _registry.py
...
Description
Add type annotations to _registry.py so that they will pass mypy
--strict.
Comment
I was reading the code and felt that this module would be easier to
understand with type annotations. Therefore, I went ahead and added the
annotations.
The idea with this PR is to start small to see if we can align on _how_
to annotate types. I've seen people in the past disagree on how strictly
to annotate the code base, so before spending too much time on this, I
wanted to check if you agree, Ross.
Most of the added types should be straightforward. Some notes on the
non-trivial changes:
- I made no assumption about the fn passed to register_model, but maybe
the type could be stricter. Are all models nn.Modules?
- If I'm not mistaken, the type hint for get_arch_name was incorrect
- I had to add a # type: ignore to model.__all__ = ...
- I made some minor code changes to list_models to facilitate the
typing. I think the changes should not affect the logic of the function.
- I removed list from list(sorted(...)) because sorted returns always a
list.
2023-02-22 09:19:30 -08:00
4d9c3ae2fb
Add laion2b 320x320 ConvNeXt-Large CLIP weights
2023-02-18 16:34:03 -08:00
d0b45c9b4d
Make safetensor import option for now. Improve avg/clean checkpoints ext handling a bit (more consistent).
2023-02-18 16:06:42 -08:00
947c1d757a
Merge branch 'main' into focalnet_and_swin_refactor
2023-02-17 16:28:52 -08:00
cf324ea38f
Fix grad checkpointing in focalnet
2023-02-17 16:26:26 -08:00
848d200767
Overhaul FocalNet implementation
2023-02-17 16:24:59 -08:00
7266c5c716
Merge branch 'main' into focalnet_and_swin_refactor
2023-02-17 09:20:14 -08:00
7d9e321b76
Improve tracing of window attn models with simpler reshape logic
2023-02-17 07:59:06 -08:00
2e38d53dca
Remove dead line
2023-02-16 16:57:42 -08:00
f77c04ff36
Torchscript fixes/hacks for rms_norm, refactor ParallelScalingBlock with manual combination of input projections, closer paper match
2023-02-16 16:57:42 -08:00
122621daef
Add Final annotation to attn_fas to avoid symbol lookup of new scaled_dot_product_attn fn on old PyTorch in jit
2023-02-16 16:57:42 -08:00
621e1b2182
Add ideas from 'Scaling ViT to 22-B Params', testing PyTorch 2.0 fused F.scaled_dot_product_attention impl in vit, vit_relpos, maxxvit / coatnet.
2023-02-16 16:57:42 -08:00
pUmpKin-Co
Ross Wightman
方曦
Yassine
jameslahm
Nguyen Nhat Hoang
belfner
Thorsten Hempel
Ross Wightman
Chengpeng Chen
Minseo Kang
yehuitang
Yonghye Kwon
Daniel Suess
alec.tu
Ruslan Baikulov
SeeFun
Lengyue
Philip Keller
Marco Forte
Piotr Sebastian Kluska
Benjamin Bossan