0721559511
Improved (hopefully) init for SA/SA-like layers used in ByoaNets
3 years ago
d5473c17f7
Fix incorrect name of shortcut/identity paths in many residual nets. Inherited from naming in old old torchvision, long fixed there.
3 years ago
0d87650fea
Remove filter hack from BlurPool w/ non-persistent buffer. Use BlurPool2d instead of AntiAliasing.. for TResNet. Breaks PyTorch < 1.6.
3 years ago
ddc743fdf8
Update ResNet-RS models to EMA weights
3 years ago
08d60f4a9a
resnetrs50 pool sizing wrong
3 years ago
1daa15ecc3
Initial Cait commit. Still some cleanup to do.
3 years ago
67d0665b46
Post ResNet-RS merge cleanup. Add weight urls, adjust train/test/crop pct.
3 years ago
560eae38f5
[WIP] Add ResNet-RS models ( #554 )
...
* Add ResNet-RS models
* Only include resnet-rs changes
* remove whitespace diff
* EOF newline
* Update time
* increase time
* Add first conv
* Try running only resnetv2_101x1_bitm on Linux runner
* Add to exclude filter
* Run test_model_forward_features for all
* Add to exclude ftrs
* back to defaults
* only run test_forward_features
* run all tests
* Run all tests
* Add bigger resnetrs to model filters to fix Github CLI
* Remove resnetv2_101x1_bitm from exclude feat features
* Remove hardcoded values
* Make sure reduction ratio in resnetrs is 0.25
* There is no bias in replaced maxpool so remove it
3 years ago
9cc7dda6e5
Fixup byoanet configs to pass unit tests. Add swin_attn and swinnet26t model for testing.
3 years ago
e15c3886ba
Defaul lambda r=7. Define '26t' stage 4/5 256x256 variants for all of bot/halo/lambda nets for experiment. Add resnet50t for exp. Fix a few comments.
3 years ago
e5e15754c9
Fix coat first conv ident
3 years ago
76739a7589
CoaT merge. Bit of formatting, fix torchscript (for non features), remove einops/einsum dep, add pretrained weight hub (url) support.
3 years ago
026430c083
Merge branch 'master' of https://github.com/morizin/pytorch-image-models-1 into morizin-master
3 years ago
a0492e3b48
A few miil weights naming tweaks to improve compat with model registry and filtering wildcards.
3 years ago
8c1f03e56c
comment
3 years ago
19e1b67a84
old spaces
3 years ago
a443865876
update naming and scores
3 years ago
cf0e371594
84_0
3 years ago
0968bdeca3
vit, tresnet and mobilenetV3 ImageNet-21K-P weights
3 years ago
1e3b6d4dfc
Update __init__.py
3 years ago
fd022fd6a2
Update __init__.py
3 years ago
c2d5087eae
Add files via upload
3 years ago
c1cf9712fc
Add updated EfficientNet-V2S weights, 83.8 @ 384x384 test. Add PyTorch trained EfficientNet-B4 weights, 83.4 @ 384x384 test. Tweak non TF EfficientNet B1-B4 train/test res scaling.
3 years ago
e8a64fb881
Test input size for efficientnet_v2s was wrong in last results run
3 years ago
2df77ee5cb
Fix torchscript compat and features_only behaviour in GhostNet PR. A few minor formatting changes. Reuse existing layers.
3 years ago
d793deb51a
Merge branch 'master' of https://github.com/iamhankai/pytorch-image-models into iamhankai-master
3 years ago
f606c45c38
Add Swin Transformer models from https://github.com/microsoft/Swin-Transformer
3 years ago
de445e7827
Add GhostNet
3 years ago
b3d7580df1
Update ByoaNet comments. Fix first Steam feat chs for ByobNet.
3 years ago
16f7aa9f54
Add default_cfg options for min_input_size / fixed_input_size, queries in model registry, and use for testing self-attn models
3 years ago
4e4b863b15
Missed norm.py
3 years ago
7c97e66f7c
Remove commented code, add more consistent seed fn
3 years ago
ce62f96d4d
ByoaNet with bottleneck transformer, lambda resnet, and halo net experiments
3 years ago
21812d33aa
Add prelim efficientnet_v2s weights from 224x224 train, eval 83.3 @ 288. Add eca_nfnet_l1 weights, train at 256, eval 84 @ 320.
3 years ago
fb896c0b26
Update some comments re preliminary EfficientNet-V2 assumptions
3 years ago
2b49ab7a36
Fix ResNetV2 pretrained classifier issue. Fixes #540
3 years ago
de9dff933a
EfficientNet-V2S preliminary model def (for experimentation)
3 years ago
2bb65bd875
Wrong default_cfg pool_size for L1
3 years ago
bf2ca6bdf4
Merge jax and original weight init
3 years ago
acbd698c83
Update README.md with updates. Small tweak to head_dist handling.
3 years ago
9071568f0e
Add weights for SE NFNet-L0 model, rename nfnet_l0b -> nfnet_l0. 82.75 top-1 @ 288. Add nfnet_l1 model def for training.
3 years ago
c468c47a9c
Add regnety_160 weights from DeiT teacher model, update that and my regnety_032 weights to use higher test size.
3 years ago
288682796f
Update benchmark script to add precision arg. Fix some downstream (DeiT) compat issues with latest changes. Bump version to 0.4.7
3 years ago
ea9c9550b2
Fully move ViT hybrids to their own file, including embedding module. Remove some extra DeiT models that were for benchmarking only.
3 years ago
a5310a3451
Merge remote-tracking branch 'origin/benchmark-fixes-vit_hybrids' into pit_and_vit_update
3 years ago
7953e5d11a
Fix pos_embed scaling for ViT and num_classes != 1000 for pretrained distilled deit and pit models. Fix #426 and fix #433
3 years ago
a760a4c3f4
Some ViT cleanup, merge distilled model with main, fixup torchscript support for distilled models
3 years ago
0dfc5a66bb
Add PiT model from https://github.com/naver-ai/pit
3 years ago
51febd869b
Small tweak to tests for tnt model, reorder model imports.
3 years ago
de86314655
Update TNT
3 years ago
cfc15283a4
Update TNT url
3 years ago
4a09bc851e
Add TNT model
3 years ago
cf5fec5047
Cleanup experimental vit weight init a bit
3 years ago
cbcb76d72c
Should have included Conv2d layers in original weight init. Lets see what the impact is...
3 years ago
4de57ccf01
Add weight init scheme that's closer to JAX impl
3 years ago
14ac4abf74
Change huggingface hub revision delimiter to '@', add hf_hub reference for eca_nfnet_l0 model as an example.
3 years ago
740f32c96a
Add ECA-NFNet-L0 weights and update model name. Update README and bump version to 0.4.6
3 years ago
5e2e4e7fb6
Merge pull request #502 from khatami-mehrdad/efficientnet_dg
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adding efficientnet_el, efficientnet_es_pruned and efficientnet_el_pruned pre-trained models
3 years ago
45c048ba13
A few minor fixes and bit more cleanup on the huggingface hub integration.
3 years ago
97f49d163c
adding efficientnet_el, efficientnet_es_prunedefficientnet_es_pruned and efficientnet_el_pruned pretrained models to timm/models
3 years ago
ead80d33c5
Fix typo, naming consistency
3 years ago
d584e7f617
Support for huggingface hub via create_model and default_cfgs.
...
* improve consistency of model creation helper fns
* add comments to some of the model helpers
* support passing external default_cfgs so they can be sourced from hub
3 years ago
1f799afcb3
Remove capital letters in model names
3 years ago
82c1fe958a
added hardcorenas model
...
refactoring to support feature extraction
3 years ago
f57db99101
Update README, fix iabn pip version print.
3 years ago
7ef7788ee9
Fix CUDA crash w/ channels-last + CSP models. Remove use of chunk()
3 years ago
317ea3e599
Tweak NFNet, ResNetV2, RexNet feature extraction, use pre-act features for simplicty. Update tests for pytorch 1.8. 0.4.5 version bump.
3 years ago
17cdee7354
Fix C&P patch_size error, and order of op patch_size arg resolution bug. Remove a test vit model.
3 years ago
0706d05d52
Benchmark models listed in txt file. Add more hybrid vit variants for testing
3 years ago
de97be9146
Spell out diff between my small and deit small vit models.
3 years ago
f0ffdf89b3
Add numerous experimental ViT Hybrid models w/ ResNetV2 base. Update the ViT naming for hybrids. Fix #426 for pretrained vit resizing.
3 years ago
4bc103f504
Fix CUDA crash w/ channels-last + CSP models. Remove use of chunk()
3 years ago
8563609b28
Update notes in ScaledStdConv impl
3 years ago
678ba4e0a2
Add NFNet-F model weights ported from DeepMind Haiku impl and new set of models w/ compatible config.
3 years ago
4f49b94311
Initial AGC impl. Still testing.
3 years ago
5f9aff395c
Fix stem width in NFNet-F models, add some more comments, add some 'light' NFNet models for testing.
3 years ago
d86dbe45c2
Update README.md and few more comments
3 years ago
0d253e2c5e
Fix issue with nfnet tests, bit more cleanup.
3 years ago
cb06c7a910
Add NFNet-F models and tweak existing NF models.
3 years ago
e4de077021
Add first 'Normalizer Free' models. nf_regnet_b1 79.3 @ 288x288 test, and nf_resnet50 80.3 @ 256x256 test (80.68 @ 288x288).
3 years ago
d8e69206be
Merge pull request #419 from rwightman/byob_vgg_models
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More models, GPU-Efficient Nets, RepVGG, classic VGG, and flexible Byob backbone.
3 years ago
6853b07bbd
Improve RegVGG block identity/vs non for clariy and fix attn usage. Add comments.
3 years ago
0356e773f5
Default to native PyTorch AMP instead of APEX amp. Too many APEX issues cropping up lately.
3 years ago
94ca140b67
update collections.abc import
3 years ago
b4e216e377
Fix a few small things.
3 years ago
dc85e5a237
Add ByobNet w/ GPU-EfficientNets and RepVGG. Also add classic vgg models.
3 years ago
1bcc69e0ad
Use in_channels for depthwise groups, allows using `out_channels=N * in_channels` (does not impact existing models). Fix #354 .
3 years ago
9811e229f7
Fix regression in models with 1001 class pretrained weights. Improve batchnorm arg and BatchNormAct layer handling in several models.
3 years ago
a39c3ee216
Merge branch 'master' into eca-weights
3 years ago
666de85cf1
Move stride in EdgeResidual block to 3x3 expansion conv. Fix #414
3 years ago
3b57490a63
Fix some half removed resnet model defs, pooling for ecaresnet269d
3 years ago
68a4144882
Add new weights for ecaresnet26t/50t/269d models. Remove distinction between 't' and 'tn' (tiered models), tn is now t. Add test time img size spec to default cfg.
3 years ago
b9843f954b
Merge pull request #282 from tigert1998/patch-1
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Add symbolic for SwishJitAutoFn to support onnx
3 years ago
7a4be5c035
add operator HardSwishJitAutoFn export to onnx
3 years ago
f0e65e37b7
Fix NF-ResNet101 model defs
3 years ago
2de54d174a
Fix pool size defs for NFNet models, add a comment.
3 years ago
90980de4a9
Fix up a few details in NFResNet models, managed stable training. Add support for gamma gain to be applied in activation or ScaleStdConv. Some tweaks to ScaledStdConv.
3 years ago
5a8e1e643e
Initial Normalizer-Free Reg/ResNet impl. A bit of related layer refactoring.
3 years ago
38d8f67570
Fix potential issue with change to num_classes arg in train/validate.py defaulting to None (rely on model def / default_cfg)
3 years ago
bb50ac4708
Add DeiT distilled weights and distilled model def. Remove some redudant ViT model args.
3 years ago
Ross Wightman
Aman Arora
talrid
morizin
iamhankai
contrastive
Ross Wightman
Mehrdad
AFLALO, Jonathan Isaac
Reuben
hwangdeyu