5f47518f27
Fix pit implementation to be clsoer to deit/levit re distillation head handling
3 years ago
0862e6ebae
Fix correctness of some group matching regex (no impact on result), some formatting, missed forward_head for resnet
3 years ago
94bcdebd73
Add latest weights trained on TPU-v3 VM instances
3 years ago
0557c8257d
Fix bug introduced in non layer_decay weight_decay application. Remove debug print, fix arg desc.
3 years ago
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
3 years ago
1420c118df
Missed comitting outstanding changes to default_cfg keys and test exclusions for swin v2
3 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
3 years ago
67d140446b
Fix bug in classification head
3 years ago
29add820ac
Refactor (back to relative imports)
3 years ago
74a04e0016
Add parameter to change normalization type
3 years ago
2a4f6c13dd
Create model functions
3 years ago
87b4d7a29a
Add get and reset classifier method
3 years ago
ff5f6bcd6c
Check input resolution
3 years ago
81bf0b4033
Change parameter names to match Swin V1
3 years ago
f227b88831
Add initials (CR) to model and file
3 years ago
90dc74c450
Add code from https://github.com/ChristophReich1996/Swin-Transformer-V2 and change docstring style to match timm
3 years ago
2c3870e107
semobilevit_s for good measure
3 years ago
bcaeb91b03
Version to 0.6.0, possible interface incompatibilities vs 0.5.x
3 years ago
58ba49c8ef
Add MobileViT models (w/ ByobNet base). Close #1038 .
3 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...
3 years ago
cf57695938
sched noise dup code remove
3 years ago
95cfc9b3e8
Merge remote-tracking branch 'origin/master' into norm_norm_norm
3 years ago
abc9ba2544
Transitioning default_cfg -> pretrained_cfg. Improving handling of pretrained_cfg source (HF-Hub, files, timm config, etc). Checkpoint handling tweaks.
3 years ago
07379c6d5d
Add vit_base2_patch32_256 for a model between base_patch16 and patch32 with a slightly larger img size and width
3 years ago
447677616f
version 0.5.5
3 years ago
83b40c5a58
Last batch of small model weights (for now). mobilenetv3_small 050/075/100 and updated mnasnet_small with lambc/lamb optimizer.
3 years ago
cdcd0a92ca
fix lars
3 years ago
1aa617cb3b
Add AvgPool2d anti-aliasing support to ResNet arch (as per OpenAI CLIP models), add a few blur aa models as well
3 years ago
f0f9eccda8
Add --fuser arg to train/validate/benchmark scripts to select jit fuser type
3 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)
3 years ago
738a9cd635
unbiased=False for torch.var_mean path of ConvNeXt LN. Fix #1090
3 years ago
e0c4eec4b6
Default conv_mlp to False across the board for ConvNeXt, causing issues on more setups than it's improving right now...
3 years ago
b669f4a588
Add ConvNeXt 22k->1k fine-tuned and 384 22k-1k fine-tuned weights after testing
3 years ago
e967c72875
Update REAMDE.md. Sneak in g/G (giant / gigantic?) ViT defs from scaling paper
3 years ago
9ca3437178
Add some more small model weights lcnet, mnas, mnv2
3 years ago
fa6463c936
Version 0.5.4
3 years ago
fa81164378
Fix stem width for really small mobilenetv3 arch defs
3 years ago
edd3d73695
Add missing dropout for head reset in ConvNeXt default head
3 years ago
b093dcb46d
Some convnext cleanup, remove in place mul_ for gamma, breaking symbolic trace, cleanup head a bit...
3 years ago
18934debc5
Add initial ConvNeXt impl (mods of official code)
3 years ago
656757d26b
Fix MobileNetV2 head conv size for multiplier < 1.0. Add some missing modification copyrights, fix starting date of some old ones.
3 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
02ae11e526
Leaving repeat aug sampler indices as tensor thrashes worker shared process memory
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
a0b2657497
Use `torch.repeat_interleave()` to generate repeated indices faster ( #1058 )
...
* update: use numpy to generate repeated indices faster
* update: use torch.repeat_interleave() instead of np.repeat()
* refactor: remove unused import, numpy
* refactor: torch.range to torch.arange
* update: tensor to list before appending the extra samples
* update: concatenate the paddings with torch.cat
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
55adfbeb8d
Add commented code to increase open file limit via Python (for TFDS dataset building)
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
f0507f6da6
Fix k_decay default arg != 1.0 in poly scheduler
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
78b36bf46c
Places365 doesn't exist in some still used torchvision version
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
9b5d6dc7e2
Merge branch 'add-vit-b8' of https://github.com/martinsbruveris/pytorch-image-models into martinsbruveris-add-vit-b8
3 years ago
cfa414cad2
Matching two bits_and_tpu changes for TFDs wrapper
...
* change 'samples' -> 'examples' for tfds wrapper to match tfds naming
* add class_to_idx for image classification datasets in tfds wrapper
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
9ec3210c2d
More TFDS parser cleanup, support improved TFDS even_split impl (on tfds-nightly only currently).
3 years ago
ba65dfe2c6
Dataset work
...
* support some torchvision datasets
* improvements to TFDS wrapper for subsplit handling (fix #942 ), shuffle seed
* add class-map support to train (fix #957 )
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
a41de1f666
Add interpolation mode handling to transforms. Removes InterpolationMode warning. Works for torchvision versions w/ and w/o InterpolationMode enum. Fix #738 .
3 years ago
ed41d32637
Add repr to auto_augment and random_erasing impl
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
57992509f9
Fix some formatting in utils/model.py
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
047a5ec05f
Fix bugs that Mixup does not work device=cpu
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
e5da481073
Small post-merge tweak for freeze/unfreeze, add to __init__ for utils
3 years ago
5ca72dcc75
Merge branch 'freeze-functionality' of https://github.com/alexander-soare/pytorch-image-models into alexander-soare-freeze-functionality
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
431e60c83f
Add acknowledgements for freeze_batch_norm inspiration
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
93901e992f
Version bump to 0.5.0 for pending release post RSB and ATTN updates
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
65c3d78b96
Freeze unfreeze functionality finalized. Tests added
3 years ago
0cb8ea432c
wip
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
51eaf9360d
Remove a duplicate layer creation in byobnet.py
...
`self.conv2_kxk` is repeated in `byobnet.py`. Remove the duplicate code.
3 years ago
b81e79aae9
Fix bottleneck attn transpose typo, hopefully these train better now..
3 years ago
80075b0b8a
Add worker_seeding arg to allow selecting old vs updated data loader worker seed for (old) experiment repeatability
3 years ago
6478bcd02c
Fix regnetz_d conv layer name, use inception mean/std
3 years ago
0387e6057e
Update binary cross ent impl to use thresholding as an option (convert soft targets from mixup/cutmix to 0, 1)
3 years ago
f8a63a3b71
Add worker_init_fn to loader for numpy seed per worker
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
fb94350896
Update training script and loader factory to allow use of scheduler updates, repeat augment, and bce loss
3 years ago
f262137ff2
Add RepeatAugSampler as per DeiT RASampler impl, showing promise for current (distributed) training experiments.
3 years ago
ba9c1108a1
Add a BCE loss impl that converts dense targets to sparse /w smoothing as an alternate to CE w/ smoothing. For training experiments.
3 years ago
29a37e23ee
LR scheduler update:
...
* add polynomial decay 'poly'
* cleanup cycle specific args for cosine, poly, and tanh sched, t_mul -> cycle_mul, decay -> cycle_decay, default cycle_limit to 1 in each opt
* add k-decay for cosine and poly sched as per https://arxiv.org/abs/2004.05909
* change default tanh ub/lb to push inflection to later epochs
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
d667351eac
Tweak accuracy topk safety. Fix #807
3 years ago
35c9740826
Fix accuracy when topk > num_classes
3 years ago
a16a753852
Add lamb/lars to optim init imports, remove stray comment
3 years ago
c207e02782
MOAR optimizer changes. Woo!
3 years ago
a426511c95
More optimizer cleanup. Change all to no longer use .data. Improve (b)float16 use with adabelief. Add XLA compatible Lars.
3 years ago
9541f4963b
One more scalar -> tensor fix for lamb optimizer
3 years ago
8f68193c91
Update lamp.py comment
3 years ago
4d284017b8
Merge pull request #813 from rwightman/opt_cleanup
...
Optimizer cleanup and additions
3 years ago
a6af48be64
add madgradw optimizer
3 years ago
55fb5eedf6
Remove experiment from lamb impl
3 years ago
8a9eca5157
A few optimizer comments, dead import, missing import
3 years ago
ac469b50da
Optimizer improvements, additions, cleanup
...
* Add MADGRAD code
* Fix Lamb (non-fused variant) to work w/ PyTorch XLA
* Tweak optimizer factory args (lr/learning_rate and opt/optimizer_name), may break compat
* Use newer fn signatures for all add,addcdiv, addcmul in optimizers
* Use upcoming PyTorch native Nadam if it's available
* Cleanup lookahead opt
* Add optimizer tests
* Remove novograd.py impl as it was messy, keep nvnovograd
* Make AdamP/SGDP work in channels_last layout
* Add rectified adablief mode (radabelief)
* Support a few more PyTorch optim, adamax, adagrad
3 years ago
abf3e044bb
Update scheduler_factory.py
...
remove duplicate code from create_scheduler()
3 years ago
3cdaf5ed56
Add `mmax` config key to auto_augment for increasing upper bound of RandAugment magnitude beyond 10. Make AugMix uniform sampling default not override config setting.
3 years ago
1042b8a146
Add non fused LAMB optimizer option
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
2907c1f967
Merge pull request #746 from samarth4149/master
...
Adding a Multi Step LR Scheduler
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
daab57a6d9
1. Added a simple multi step LR scheduler
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
4c09a2f169
Bump version 0.4.12
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
02320c3e3d
Bump version to 0.4.11
4 years ago
bda8ab015a
Remove min channels for SelectiveKernel, divisor should cover cases well enough.
4 years ago
a27f4aec4a
Missed args for skresnext w/ refactoring.
4 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.
4 years ago
8bf63b6c6c
Able to use other attn layer in EfficientNet now. Create test ECA + GC B0 configs. Make ECA more configurable.
4 years ago
bcec14d3b5
Bring EfficientNet SE layer in line with others, pull se_ratio outside of blocks. Allows swapping w/ other attn layers.
4 years ago
9611458e19
Throw in some FBNetV3 code I had lying around, some refactoring of SE reduction channel calcs for all EffNet archs.
4 years ago
01b9108619
Merge branch 'master' into more_attn
4 years ago
d7bab8a6c5
Fix strict flag change for checkpoint load.
4 years ago
02f9d4bc34
Add weights for resnet51q model, add 61q def.
4 years ago
f615474be3
Fix broken test, repvgg block doesn't have attn_last attr.
4 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.
4 years ago
9c78de8c02
Fix #661 , move hardswish out of default args for LeViT. Enable native torch support for hardswish, hardsigmoid, mish if present.
4 years ago
5db7452173
Fix visformer in_chans stem handling
4 years ago
318360c3f9
Update README.md before merge. Bump version to 0.4.10
4 years ago
11ae795e99
Redo LeViT attention bias caching in a way that works with both torchscript and DataParallel
4 years ago
d400f1dbdd
Filter test models before creation for backward/torchscript tests
4 years ago
c4572cc5aa
Add Visformer-small weighs, tweak torchscript jit test img size.
4 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.
4 years ago
18bf520ad1
Add eca_nfnet_l2/l3 defs for future training
4 years ago
f45de37690
Merge branch 'master' into levit_visformer_rednet
4 years ago
23c18a33e4
Add efficientnetv2_rw_m weights trained in PyTorch. 84.8 top-1 @ 416 test. 53M params.
4 years ago
c2ba229d99
Prep for effcientnetv2_rw_m model weights that started training before official release..
4 years ago
30b9880d06
Minor adjustment, mutable default arg, extra check of valid len...
4 years ago
be0abfbcce
Merge branch 'master' of https://github.com/alexander-soare/pytorch-image-models into alexander-soare-master
4 years ago
b7de82e835
ConViT cleanup, fix torchscript, bit of reformatting, reuse existing layers.
4 years ago
306c86b668
Merge branch 'convit' of https://github.com/amaarora/pytorch-image-models into amaarora-convit
4 years ago
a569635045
Update twin weights to a copy in GitHub releases for faster dl. Tweak model class comment.
4 years ago
be99eef9c1
Remove redundant code, cleanup, fix torchscript.
4 years ago
5ab372a3ec
Merge branch 'master' of https://github.com/abcdvzz/pytorch-image-models into abcdvzz-master
4 years ago
5db1eb6ba5
Add defaults
4 years ago
8b1f2e8e1f
remote unused matplotlib import
4 years ago
40c506ba1e
Add ConViT
4 years ago
7976019864
extend positional embedding resizing functionality to tnt
4 years ago
8086943b6f
allow resize positional embeddings to non-square grid
4 years ago
dc1a4efd28
mixer_b16_224_miil, mixer_b16_224_miil_in21k models
4 years ago
7b799c4e79
add latest code
4 years ago
d5af752117
Add preliminary gMLP and ResMLP impl to Mlp-Mixer
4 years ago
00548b8427
Add Twins
4 years ago
e7f0db8664
Fix drop/drop_path arg on MLP-Mixer model. Fix #641
4 years ago
9a3ae97311
Another set of byoanet models w/ ECA channel + SA + groups
4 years ago
d53e91218e
Fix tf.data options setting for newer TF versions
4 years ago
7077f16c6a
Change 21k model naming from _21k to _in21k for consistency with existing 21k models.
4 years ago
Ross Wightman