372ad5fa0d
Significant model refactor and additions:
...
* All models updated with revised foward_features / forward_head interface
* Vision transformer and MLP based models consistently output sequence from forward_features (pooling or token selection considered part of 'head')
* WIP param grouping interface to allow consistent grouping of parameters for layer-wise decay across all model types
* Add gradient checkpointing support to a significant % of models, especially popular architectures
* Formatting and interface consistency improvements across models
* layer-wise LR decay impl part of optimizer factory w/ scale support in scheduler
* Poolformer and Volo architectures added
2 years ago
1420c118df
Missed comitting outstanding changes to default_cfg keys and test exclusions for swin v2
2 years ago
c6e4b7895a
Swin V2 CR impl refactor.
...
* reformat and change some naming so closer to existing timm vision transformers
* remove typing that wasn't adding clarity (or causing torchscript issues)
* support non-square windows
* auto window size adjust from image size
* post-norm + main-branch no
2 years ago
67d140446b
Fix bug in classification head
2 years ago
29add820ac
Refactor (back to relative imports)
2 years ago
74a04e0016
Add parameter to change normalization type
2 years ago
2a4f6c13dd
Create model functions
2 years ago
87b4d7a29a
Add get and reset classifier method
2 years ago
ff5f6bcd6c
Check input resolution
2 years ago
81bf0b4033
Change parameter names to match Swin V1
2 years ago
f227b88831
Add initials (CR) to model and file
2 years ago
90dc74c450
Add code from https://github.com/ChristophReich1996/Swin-Transformer-V2 and change docstring style to match timm
2 years ago
2c3870e107
semobilevit_s for good measure
2 years ago
58ba49c8ef
Add MobileViT models (w/ ByobNet base). Close #1038 .
2 years ago
5f81d4de23
Move DeiT to own file, vit getting crowded. Working towards fixing #1029 , make pooling interface for transformers and mlp closer to convnets. Still working through some details...
2 years ago
95cfc9b3e8
Merge remote-tracking branch 'origin/master' into norm_norm_norm
2 years ago
abc9ba2544
Transitioning default_cfg -> pretrained_cfg. Improving handling of pretrained_cfg source (HF-Hub, files, timm config, etc). Checkpoint handling tweaks.
2 years ago
07379c6d5d
Add vit_base2_patch32_256 for a model between base_patch16 and patch32 with a slightly larger img size and width
2 years ago
83b40c5a58
Last batch of small model weights (for now). mobilenetv3_small 050/075/100 and updated mnasnet_small with lambc/lamb optimizer.
2 years ago
1aa617cb3b
Add AvgPool2d anti-aliasing support to ResNet arch (as per OpenAI CLIP models), add a few blur aa models as well
2 years ago
010b486590
Add Dino pretrained weights (no head) for vit models. Add support to tests and helpers for models w/ no classifier (num_classes=0 in pretrained cfg)
2 years ago
738a9cd635
unbiased=False for torch.var_mean path of ConvNeXt LN. Fix #1090
2 years ago
e0c4eec4b6
Default conv_mlp to False across the board for ConvNeXt, causing issues on more setups than it's improving right now...
2 years ago
b669f4a588
Add ConvNeXt 22k->1k fine-tuned and 384 22k-1k fine-tuned weights after testing
2 years ago
e967c72875
Update REAMDE.md. Sneak in g/G (giant / gigantic?) ViT defs from scaling paper
2 years ago
9ca3437178
Add some more small model weights lcnet, mnas, mnv2
2 years ago
fa81164378
Fix stem width for really small mobilenetv3 arch defs
2 years ago
edd3d73695
Add missing dropout for head reset in ConvNeXt default head
2 years ago
b093dcb46d
Some convnext cleanup, remove in place mul_ for gamma, breaking symbolic trace, cleanup head a bit...
2 years ago
18934debc5
Add initial ConvNeXt impl (mods of official code)
2 years ago
656757d26b
Fix MobileNetV2 head conv size for multiplier < 1.0. Add some missing modification copyrights, fix starting date of some old ones.
2 years ago
ccfeb06936
Fix out_indices handling breakage, should have left as per vgg approach.
3 years ago
a9f91483a6
Fix #1078 , DarkNet has 6 feature maps. Make vgg and darknet out_indices handling/comments equivalent
3 years ago
c21b21660d
visformer supports spatial feat map, update pool_size in pretrained cfg to match
3 years ago
9c11dfd9cb
Fix fbnetv3 pretrained cfg changes
3 years ago
1406cddc2e
FBNetV3 timm trained weights added for b/d/g variants. Update version to 0.5.2 for pypi release.
3 years ago
4df51f3932
Add lcnet_100 and mnasnet_small weights
3 years ago
5ccf682a8f
Remove deprecated bn-tf train arg and create_model handler. Add evos/evob models back into fx test filter until norm_norm_norm branch merged.
3 years ago
b9a715c86a
Add more small model defs for MobileNetV3/V2/LCNet
3 years ago
b27c21b09a
Update drop_path and drop_block (fast impl) to be symbolically traceable, slightly faster
3 years ago
214c84a235
Disable use of timm nn.Linear wrapper since AMP autocast + torchscript use appears fixed
3 years ago
72b57163d1
Merge branch 'master' of https://github.com/mrT23/pytorch-image-models into mrT23-master
3 years ago
de5fa791c6
Merge branch 'master' into norm_norm_norm
3 years ago
26ff57f953
Add more small model defs for MobileNetV3/V2/LCNet
3 years ago
450ac6a0f5
Post merge tinynet fixes for pool_size, feature extraction
3 years ago
a04164cd75
Merge branch 'tinynet' of https://github.com/rsomani95/pytorch-image-models into rsomani95-tinynet
3 years ago
8a93ce6ee3
Fix regnetv/w tests, refactor regnet generator code a bit
3 years ago
4dec8c8087
Fix skip path regression for updated EfficientNet and RegNet def. Add Pre-Act RegNet support (experimental). Remove BN-TF flag. Add efficientnet_b0_g8_gn model.
3 years ago
a52a614475
Remove layer experiment which should not have been added
3 years ago
ab49d275de
Significant norm update
...
* ConvBnAct layer renamed -> ConvNormAct and ConvNormActAa for anti-aliased
* Significant update to EfficientNet and MobileNetV3 arch to support NormAct layers and grouped conv (as alternative to depthwise)
* Update RegNet to add Z variant
* Add Pre variant of XceptionAligned that works with NormAct layers
* EvoNorm matches bits_and_tpu branch for merge
3 years ago
31bcd36e46
add tinynet models
3 years ago
b4b8d1ec18
fix hard-coded strides
3 years ago
d04f2f1377
Update drop_path and drop_block (fast impl) to be symbolically traceable, slightly faster
3 years ago
834a9ec721
Disable use of timm nn.Linear wrapper since AMP autocast + torchscript use appears fixed
3 years ago
78912b6375
Updated EvoNorm implementations with some experimentation. Add FilterResponseNorm. Updated RegnetZ and ResNetV2 model defs for trials.
3 years ago
c11f4c3218
support CNNs
3 years ago
d6701d8a81
Merge branch 'rwightman:master' into master
3 years ago
ccb3815360
update arxiv link
3 years ago
3dc71695bf
Merge pull request #989 from martinsbruveris/feat/resmlp-dino
...
Added DINO pretrained ResMLP models.
3 years ago
480c676ffa
Fix FX breaking assert in evonorm
3 years ago
85c5ff26d7
Added DINO pretrained ResMLP models.
3 years ago
d633a014e6
Post merge cleanup. Fix potential security issue passing kwargs directly through to serialized web data.
3 years ago
b18c9e323b
Update helpers.py
3 years ago
308d0b9554
Merge branch 'master' into hf-save-and-push
3 years ago
41559247e9
use_ml_decoder_head
3 years ago
1f53db2ece
Updated lamhalobotnet weights, 81.5 top-1
3 years ago
15ef108eb4
Add better halo2botnet50ts weights, 82 top-1 @ 256
3 years ago
734b2244fe
Add RegNetZ-D8 (83.5 @ 256, 84 @ 320) and RegNetZ-E8 (84.5 @ 256, 85 @ 320) weights. Update names of existing RegZ models to include group size.
3 years ago
93cc08fdc5
Make evonorm variables 1d to match other PyTorch norm layers, will break weight compat for any existing use (likely minimal, easy to fix).
3 years ago
af607b75cc
Prep a set of ResNetV2 models with GroupNorm, EvoNormB0, EvoNormS0 for BN free model experiments on TPU and IPU
3 years ago
c976a410d9
Add ResNet-50 w/ GN (resnet50_gn) and SEBotNet-33-TS (sebotnet33ts_256) model defs and weights. Update halonet50ts weights w/ slightly better variant in1k val, more robust to test sets.
3 years ago
f2006b2437
Cleanup qkv_bias cat in beit model so it can be traced
3 years ago
1076a65df1
Minor post FX merge cleanup
3 years ago
32c9937dec
Merge branch 'fx-feature-extract-new' of https://github.com/alexander-soare/pytorch-image-models into alexander-soare-fx-feature-extract-new
3 years ago
65d827c7a6
rename notrace registration and standardize trace_utils imports
3 years ago
9b2daf2a35
Add ResNeXt-50 weights 81.1 top-1 @ 224, 82 @ 288 with A1 'high aug' recipe
3 years ago
5220711d87
Added B/8 models to ViT.
3 years ago
0262a0e8e1
fx ready for review
3 years ago
d2994016e9
Add try/except guards
3 years ago
b25ff96768
wip - pre-rebase
3 years ago
e051dce354
Make all models FX traceable
3 years ago
cf4561ca72
Add FX based FeatureGraphNet capability
3 years ago
0149ec30d7
wip - attempting to rebase
3 years ago
02c3a75a45
wip - make it possible to use fx graph in train and eval mode
3 years ago
bc3d4eb403
wip -rebase
3 years ago
ab3ac3f25b
Add FX based FeatureGraphNet capability
3 years ago
ddc29da974
Add ResNet101 and ResNet152 weights from higher aug RSB recipes. 81.93 and 82.82 top-1 at 224x224.
3 years ago
b328e56f49
Update eca_halonext26ts weights to a better set
3 years ago
2ddef942b9
Better fix for #954 that doesn't break torchscript, pull torch._assert into timm namespace when it exists
3 years ago
4f0f9cb348
Fix #954 by bringing traceable _assert into timm to allow compat w/ PyTorch < 1.8
3 years ago
ae72d009fa
Add weights for lambda_resnet50ts, halo2botnet50ts, lamhalobotnet50ts, updated halonet50ts
3 years ago
b745d30a3e
Fix formatting of last commit
3 years ago
3478f1d7f1
Traceability fix for vit models for some experiments
3 years ago
f658a72e72
Cleanup re-use of Dropout modules in Mlp modules after some twitter feedback :p
3 years ago
f805ba86d9
use .unbind instead of explicitly listing the indices
3 years ago
0fe4fd3f1f
add d8 and e8 regnetz models with group size 8
3 years ago
25e7c8c5e5
Update broken resnetv2_50 weight url, add resnetv1_101 a1h recipe weights for 224x224 train
3 years ago
b6caa356d2
Fixed eca_botnext26ts_256 weights added, 79.27
3 years ago
c02334d9fa
Add weights for regnetz_d and haloregnetz_c, update regnetz_c weights. Add commented PyTorch XLA code for halo attention
3 years ago
02daf2ab94
Add option to include relative pos embedding in the attention scaling as per references. See discussion #912
3 years ago
cd34913278
Remove some outdated comments, botnet networks working great now.
3 years ago
6ed4cdccca
Update lambda_resnet26t weights with better set
3 years ago
44d6d51668
Add ConvMixer
3 years ago
a85df34993
Update lambda_resnet26rpt weights to 78.9, add better halonet26t weights at 79.1 with tweak to attention dim
3 years ago
b544ad4d3f
regnetz model default cfg tweaks
3 years ago
e2b8d44ff0
Halo, bottleneck attn, lambda layer additions and cleanup along w/ experimental model defs
...
* align interfaces of halo, bottleneck attn and lambda layer
* add qk_ratio to all of above, control q/k dim relative to output dim
* add experimental haloregnetz, and trionet (lambda + halo + bottle) models
3 years ago
fbf59c04ee
Change crop ratio on correct resnet50 variant.
3 years ago
ae1ff5792f
Clean a1/a2/3 rsb _0 checkpoints properly, fix v2 loading.
3 years ago
da0d39bedd
Update default crop_pct for byoanet
3 years ago
cc9bedf373
Add initial ResNet Strikes Back weights for ResNet50 and ResNetV2-50 models
3 years ago
64495505b7
Add updated lambda resnet26 and botnet26 checkpoints with fixes applied
3 years ago
b2094f4ee8
support bits checkpoints in avg/load
3 years ago
007bc39323
Some halo and bottleneck attn code cleanup, add halonet50ts weights, use optimal crop ratios
3 years ago
b1c2e3eb92
Match rel_pos_indices attr rename in conv branch
3 years ago
b49630a138
Add relative pos embed option to LambdaLayer, fix last transpose/reshape.
3 years ago
d657e2cc0b
Remove dead code line from efficientnet
3 years ago
0ca687f224
Make 'regnetz' model experiments closer to actual RegNetZ, bottleneck expansion, expand from in_chs, no shortcut on stride 2, tweak model sizes
3 years ago
b81e79aae9
Fix bottleneck attn transpose typo, hopefully these train better now..
3 years ago
6478bcd02c
Fix regnetz_d conv layer name, use inception mean/std
3 years ago
515121cca1
Use reshape instead of view in std_conv, causing issues in recent PyTorch in channels_last
3 years ago
da06cc61d4
ResNetV2 seems to work best without zero_init residual
3 years ago
8e11da0ce3
Add experimental RegNetZ(ish) models for training / perf trials.
3 years ago
6bbc50beb4
make it possible to provide norm_layer via create_model
3 years ago
adcb74f87f
🎨 Import load_state_dict_from_url directly
3 years ago
e65a2cba3d
🎨 cleanup and add a couple comments
3 years ago
2b6ade24b3
🎨 write model card to enable inference
3 years ago
cf5ac2800c
BotNet models were still off, remove weights for bad configs. Add good SE-HaloNet33-TS weights.
3 years ago
24720abe3b
Merge branch 'master' into attn_update
3 years ago
1c9284c640
Add BeiT 'finetuned' 1k weights and pretrained 22k weights, pretraining specific (masked) model excluded for now
3 years ago
f8a215cfe6
A few more crossvit tweaks, fix training w/ no_weight_decay names, add crop option for scaling, adjust default crop_pct for large img size to 1.0 for better results
3 years ago
7ab2491ab7
Better handling of crossvit for tests / forward_features, fix torchscript regression in my changes
3 years ago
f1808e0970
Post crossvit merge cleanup, change model names to reflect input size, cleanup img size vs scale handling, fix tests
3 years ago
4027412757
Add resnet33ts weights, update resnext26ts baseline weights
3 years ago
9fe5798bee
fix bug for reset classifier and fix for validating the dimension
3 years ago
3718c5a5bd
fix loading pretrained model
3 years ago
bb50b69a57
fix for torch script
3 years ago
abf9d51bc3
🚧 wip
3 years ago
5bd04714e4
Cleanup weight init for byob/byoanet and related
3 years ago
8642401e88
Swap botnet 26/50 weights/models after realizing a mistake in arch def, now figuring out why they were so low...
3 years ago
5f12de4875
Add initial AttentionPool2d that's being trialed. Fix comment and still trying to improve reliability of sgd test.
3 years ago
76881d207b
Add baseline resnet26t @ 256x256 weights. Add 33ts variant of halonet with at least one halo in stage 2,3,4
3 years ago
484e61648d
Adding the attn series weights, tweaking model names, comments...
3 years ago
28d2841acf
💄 apply isort
3 years ago
492c0a4e20
Update HaloAttn comment
3 years ago
e72c989973
✨ add ability to push to hf hub
3 years ago
7ab9d4555c
add crossvit
3 years ago
3b9032ea48
Use Tensor.unfold().unfold() for HaloAttn, fast like as_strided but more clarity
3 years ago
78933122c9
Fix silly typo
3 years ago
2568ffc5ef
Merge branch 'master' into attn_update
3 years ago
708d87a813
Fix ViT SAM weight compat as weights at URL changed to not use repr layer. Fix #825 . Tweak optim test.
3 years ago
8449ba210c
Improve performance of HaloAttn, change default dim calc. Some cleanup / fixes for byoanet. Rename resnet26ts to tfs to distinguish (extra fc).
3 years ago
a8b65695f1
Add resnet26ts and resnext26ts models for non-attn baselines
3 years ago
a5a542f17d
Fix typo
3 years ago
925e102982
Update attention / self-attn based models from a series of experiments:
...
* remove dud attention, involution + my swin attention adaptation don't seem worth keeping
* add or update several new 26/50 layer ResNe(X)t variants that were used in experiments
* remove models associated with dead-end or uninteresting experiment results
* weights coming soon...
3 years ago
01cb46a9a5
Add gc_efficientnetv2_rw_t weights (global context instead of SE attn). Add TF XL weights even though the fine-tuned ones don't validate that well. Change default arg for GlobalContext to use scal (mul) mode.
3 years ago
d3f7440650
Add EfficientNetV2 XL model defs
3 years ago
72b227dcf5
Merge pull request #750 from drjinying/master
...
Specify "interpolation" mode in vision_transformer's resize_pos_embed
3 years ago
748ab852ca
Allow act_layer switch for xcit, fix in_chans for some variants
3 years ago
20b2d4b69d
Use bicubic interpolation in resize_pos_embed()
3 years ago
d3255adf8e
Merge branch 'xcit' of https://github.com/alexander-soare/pytorch-image-models into alexander-soare-xcit
3 years ago
f8039c7492
Fix gc effv2 model cfg name
3 years ago
3a55a30ed1
add notes from author
3 years ago
899cf84ccc
bug fix - missing _dist postfix for many of the 224_dist models
3 years ago
623e8b8eb8
wip xcit
3 years ago
392368e210
Add efficientnetv2_rw_t defs w/ weights, and gc variant, as well as gcresnet26ts for experiments. Version 0.4.13
3 years ago
6d8272e92c
Add SAM pretrained model defs/weights for ViT B16 and B32 models.
3 years ago
ee4d8fc69a
Remove unecessary line from nest post refactor
3 years ago
8165cacd82
Realized LayerNorm2d won't work in all cases as is, fixed.
3 years ago
81cd6863c8
Move aggregation (convpool) for nest into NestLevel, cleanup and enable features_only use. Finalize weight url.
3 years ago
6ae0ac6420
Merge branch 'nested_transformer' of https://github.com/alexander-soare/pytorch-image-models into alexander-soare-nested_transformer
3 years ago
7b8a0017f1
wip to review
3 years ago
b11d949a06
wip checkpoint with some feature extraction work
3 years ago
23bb72ce5e
nested_transformer wip
3 years ago
766b4d3262
Fix features for resnetv2_50t
3 years ago
e8045e712f
Fix BatchNorm for ResNetV2 non GN models, add more ResNetV2 model defs for future experimentation, fix zero_init of last residual for pre-act.
3 years ago
20a2be14c3
Add gMLP-S weights, 79.6 top-1
3 years ago
85f894e03d
Fix ViT in21k representation (pre_logits) layer handling across old and new npz checkpoints
3 years ago
b41cffaa93
Fix a few issues loading pretrained vit/bit npz weights w/ num_classes=0 __init__ arg. Missed a few other small classifier handling detail on Mlp, GhostNet, Levit. Should fix #713
3 years ago
9c9755a808
AugReg release
3 years ago
381b279785
Add hybrid model fwds back
3 years ago
26f04a8e3e
Fix a weight link
3 years ago
8f4a0222ed
Add GMixer-24 MLP model weights, trained w/ TPU + PyTorch XLA
3 years ago
b319eb5b5d
Update ViT weights, more details to be added before merge.
3 years ago
8257b86550
Fix up resnetv2 bit/bitm model default res
3 years ago
1228f5a3d8
Add BiT distilled 50x1 and teacher 152x2 models from 'A good teacher is patient and consistent' paper.
3 years ago
511a8e8c96
Add official ResMLP weights.
3 years ago
b9cfb64412
Support npz custom load for vision transformer hybrid models. Add posembed rescale for npz load.
3 years ago
8319e0c373
Add file docstring to std_conv.py
3 years ago
4d96165989
Merge branch 'master' into cleanup_xla_model_fixes
3 years ago
8880f696b6
Refactoring, cleanup, improved test coverage.
...
* Add eca_nfnet_l2 weights, 84.7 @ 384x384
* All 'non-std' (ie transformer / mlp) models have classifier / default_cfg test added
* Fix #694 reset_classifer / num_features / forward_features / num_classes=0 consistency for transformer / mlp models
* Add direct loading of npz to vision transformer (pure transformer so far, hybrid to come)
* Rename vit_deit* to deit_*
* Remove some deprecated vit hybrid model defs
* Clean up classifier flatten for conv classifiers and unusual cases (mobilenetv3/ghostnet)
* Remove explicit model fns for levit conv, just pass in arg
3 years ago
ba2ca4b464
One codepath for stdconv, switch layernorm to batchnorm so gain included. Tweak epsilon values for nfnet, resnetv2, vit hybrid.
3 years ago
b7a568f065
Fix torchscript issue in bat
3 years ago
d17b374f0f
Minimum input_size needed to be higher
3 years ago
b3b90d944d
Add min_input_size to bat_resnext to prevent test breakage.
3 years ago
d413eef1bf
Add ResMLP-24 model weights that I trained in PyTorch XLA on TPU-VM. 79.2 top-1.
3 years ago
10d8fa4620
Add gc and bat attention resnext26ts variants to byob for test.
3 years ago
2f5ed2dec1
Update `init_values` const for 24 and 36 layer ResMLP models
3 years ago
8e4ac3549f
All ScaledStdConv and StdConv uses default to using F.layernorm so that they work with PyTorch XLA. eps value tweaking is a WIP.
3 years ago
2a63d0246b
Post merge cleanup
3 years ago
45dec179e5
Merge pull request #681 from lmk123568/master
...
Update convit.py
3 years ago
ded1671483
Fix stochastic depth working only with a shortcut
3 years ago
b87d98b238
Update convit.py
...
Cut out the duplicates
3 years ago
bda8ab015a
Remove min channels for SelectiveKernel, divisor should cover cases well enough.
3 years ago
a27f4aec4a
Missed args for skresnext w/ refactoring.
3 years ago
307a935b79
Add non-local and BAT attention. Merge attn and self-attn factories into one. Add attention references to README. Add mlp 'mode' to ECA.
3 years ago
8bf63b6c6c
Able to use other attn layer in EfficientNet now. Create test ECA + GC B0 configs. Make ECA more configurable.
3 years ago
bcec14d3b5
Bring EfficientNet SE layer in line with others, pull se_ratio outside of blocks. Allows swapping w/ other attn layers.
3 years ago
9611458e19
Throw in some FBNetV3 code I had lying around, some refactoring of SE reduction channel calcs for all EffNet archs.
3 years ago
01b9108619
Merge branch 'master' into more_attn
3 years ago
d7bab8a6c5
Fix strict flag change for checkpoint load.
3 years ago
02f9d4bc34
Add weights for resnet51q model, add 61q def.
3 years ago
f615474be3
Fix broken test, repvgg block doesn't have attn_last attr.
3 years ago
742c2d5247
Add Gather-Excite and Global Context attn modules. Refactor existing SE-like attn for consistency and refactor byob/byoanet for less redundancy.
3 years ago
9c78de8c02
Fix #661 , move hardswish out of default args for LeViT. Enable native torch support for hardswish, hardsigmoid, mish if present.
3 years ago
5db7452173
Fix visformer in_chans stem handling
3 years ago
11ae795e99
Redo LeViT attention bias caching in a way that works with both torchscript and DataParallel
3 years ago
d400f1dbdd
Filter test models before creation for backward/torchscript tests
3 years ago
c4572cc5aa
Add Visformer-small weighs, tweak torchscript jit test img size.
3 years ago
bfc72f75d3
Expand scope of testing for non-std vision transformer / mlp models. Some related cleanup and create fn cleanup for all vision transformer and mlp models. More CoaT weights.
3 years ago
18bf520ad1
Add eca_nfnet_l2/l3 defs for future training
3 years ago
f45de37690
Merge branch 'master' into levit_visformer_rednet
3 years ago
23c18a33e4
Add efficientnetv2_rw_m weights trained in PyTorch. 84.8 top-1 @ 416 test. 53M params.
3 years ago
c2ba229d99
Prep for effcientnetv2_rw_m model weights that started training before official release..
3 years ago
30b9880d06
Minor adjustment, mutable default arg, extra check of valid len...
3 years ago
be0abfbcce
Merge branch 'master' of https://github.com/alexander-soare/pytorch-image-models into alexander-soare-master
3 years ago
b7de82e835
ConViT cleanup, fix torchscript, bit of reformatting, reuse existing layers.
3 years ago
306c86b668
Merge branch 'convit' of https://github.com/amaarora/pytorch-image-models into amaarora-convit
3 years ago
a569635045
Update twin weights to a copy in GitHub releases for faster dl. Tweak model class comment.
3 years ago
be99eef9c1
Remove redundant code, cleanup, fix torchscript.
3 years ago
5ab372a3ec
Merge branch 'master' of https://github.com/abcdvzz/pytorch-image-models into abcdvzz-master
3 years ago
5db1eb6ba5
Add defaults
3 years ago
8b1f2e8e1f
remote unused matplotlib import
3 years ago
40c506ba1e
Add ConViT
3 years ago
7976019864
extend positional embedding resizing functionality to tnt
3 years ago
8086943b6f
allow resize positional embeddings to non-square grid
3 years ago
dc1a4efd28
mixer_b16_224_miil, mixer_b16_224_miil_in21k models
3 years ago
7b799c4e79
add latest code
3 years ago
d5af752117
Add preliminary gMLP and ResMLP impl to Mlp-Mixer
3 years ago
00548b8427
Add Twins
3 years ago
e7f0db8664
Fix drop/drop_path arg on MLP-Mixer model. Fix #641
3 years ago
9a3ae97311
Another set of byoanet models w/ ECA channel + SA + groups
3 years ago
7077f16c6a
Change 21k model naming from _21k to _in21k for consistency with existing 21k models.
3 years ago
94d4b53352
Add temporary default_cfgs to visformer models so they pass tests
3 years ago
3bffc701f1
Merge branch 'master' into levit_visformer_rednet
3 years ago
ecc7552c5c
Add levit, levit_c, and visformer model defs. Largely untested and not finished cleanup.
3 years ago
165fb354b2
Add initial RedNet model / Involution layer impl for testing
3 years ago
328249f11a
Update README, tweak fine-tune effv2 model names.
3 years ago
c4f482a08b
EfficientNetV2 official impl w/ weights ported from TF. Cleanup/refactor of related EfficientNet classes and models.
3 years ago
4fbc32d3d0
Fix crop_pct for cait models.
3 years ago
715519a5ef
Rethink name of patch embed grid info
3 years ago
Ross Wightman
Christoph Reich
Rahul Somani
KAI ZHAO
talrid
mrT23
qwertyforce
Ross Wightman
Martins Bruveris
Nathan Raw
Alexander Soare
Thomas Viehmann
ICLR Author
Richard Chen
Ying Jin
Dongyoon Han
Mike
Aman Arora
李鑫杰