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
4 years ago
f8039c7492
Fix gc effv2 model cfg name
4 years ago
3a55a30ed1
add notes from author
4 years ago
899cf84ccc
bug fix - missing _dist postfix for many of the 224_dist models
4 years ago
623e8b8eb8
wip xcit
4 years ago
392368e210
Add efficientnetv2_rw_t defs w/ weights, and gc variant, as well as gcresnet26ts for experiments. Version 0.4.13
4 years ago
daab57a6d9
1. Added a simple multi step LR scheduler
4 years ago
6d8272e92c
Add SAM pretrained model defs/weights for ViT B16 and B32 models.
4 years ago
ee4d8fc69a
Remove unecessary line from nest post refactor
4 years ago
8165cacd82
Realized LayerNorm2d won't work in all cases as is, fixed.
4 years ago
81cd6863c8
Move aggregation (convpool) for nest into NestLevel, cleanup and enable features_only use. Finalize weight url.
4 years ago
6ae0ac6420
Merge branch 'nested_transformer' of https://github.com/alexander-soare/pytorch-image-models into alexander-soare-nested_transformer
4 years ago
7b8a0017f1
wip to review
4 years ago
b11d949a06
wip checkpoint with some feature extraction work
4 years ago
23bb72ce5e
nested_transformer wip
4 years ago
766b4d3262
Fix features for resnetv2_50t
4 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.
4 years ago
20a2be14c3
Add gMLP-S weights, 79.6 top-1
4 years ago
85f894e03d
Fix ViT in21k representation (pre_logits) layer handling across old and new npz checkpoints
4 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
4 years ago
9c9755a808
AugReg release
4 years ago
381b279785
Add hybrid model fwds back
4 years ago
26f04a8e3e
Fix a weight link
4 years ago
8f4a0222ed
Add GMixer-24 MLP model weights, trained w/ TPU + PyTorch XLA
4 years ago
4c09a2f169
Bump version 0.4.12
4 years ago
b319eb5b5d
Update ViT weights, more details to be added before merge.
4 years ago
8257b86550
Fix up resnetv2 bit/bitm model default res
4 years ago
1228f5a3d8
Add BiT distilled 50x1 and teacher 152x2 models from 'A good teacher is patient and consistent' paper.
4 years ago
511a8e8c96
Add official ResMLP weights.
4 years ago
b9cfb64412
Support npz custom load for vision transformer hybrid models. Add posembed rescale for npz load.
4 years ago
8319e0c373
Add file docstring to std_conv.py
4 years ago
4d96165989
Merge branch 'master' into cleanup_xla_model_fixes
4 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
4 years ago
ba2ca4b464
One codepath for stdconv, switch layernorm to batchnorm so gain included. Tweak epsilon values for nfnet, resnetv2, vit hybrid.
4 years ago
b7a568f065
Fix torchscript issue in bat
4 years ago
d17b374f0f
Minimum input_size needed to be higher
4 years ago
b3b90d944d
Add min_input_size to bat_resnext to prevent test breakage.
4 years ago
d413eef1bf
Add ResMLP-24 model weights that I trained in PyTorch XLA on TPU-VM. 79.2 top-1.
4 years ago
10d8fa4620
Add gc and bat attention resnext26ts variants to byob for test.
4 years ago
2f5ed2dec1
Update `init_values` const for 24 and 36 layer ResMLP models
4 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.
4 years ago
2a63d0246b
Post merge cleanup
4 years ago
45dec179e5
Merge pull request #681 from lmk123568/master
...
Update convit.py
4 years ago
ded1671483
Fix stochastic depth working only with a shortcut
4 years ago
b87d98b238
Update convit.py
...
Cut out the duplicates
4 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
94d4b53352
Add temporary default_cfgs to visformer models so they pass tests
4 years ago
3bffc701f1
Merge branch 'master' into levit_visformer_rednet
4 years ago
ecc7552c5c
Add levit, levit_c, and visformer model defs. Largely untested and not finished cleanup.
4 years ago
165fb354b2
Add initial RedNet model / Involution layer impl for testing
4 years ago
328249f11a
Update README, tweak fine-tune effv2 model names.
4 years ago
c4f482a08b
EfficientNetV2 official impl w/ weights ported from TF. Cleanup/refactor of related EfficientNet classes and models.
4 years ago
4fbc32d3d0
Fix crop_pct for cait models.
4 years ago
715519a5ef
Rethink name of patch embed grid info
4 years ago
b2c305c2aa
Move Mlp and PatchEmbed modules into layers. Being used in lots of models now...
4 years ago
3ba6b55cb2
More adjustments to ByoaNet models for further experiments.
4 years ago
5fcddb96a8
Merge branch 'master' into cait
4 years ago
3db12b4b6a
Finish CaiT cleanup
4 years ago
2d8b09fe8b
Add official pretrained weights to MLP-Mixer, complete model cfgs.
4 years ago
12efffa6b1
Initial MLP-Mixer attempt...
4 years ago
0721559511
Improved (hopefully) init for SA/SA-like layers used in ByoaNets
4 years ago
d5473c17f7
Fix incorrect name of shortcut/identity paths in many residual nets. Inherited from naming in old old torchvision, long fixed there.
4 years ago
0d87650fea
Remove filter hack from BlurPool w/ non-persistent buffer. Use BlurPool2d instead of AntiAliasing.. for TResNet. Breaks PyTorch < 1.6.
4 years ago
ddc743fdf8
Update ResNet-RS models to EMA weights
4 years ago
08d60f4a9a
resnetrs50 pool sizing wrong
4 years ago
1daa15ecc3
Initial Cait commit. Still some cleanup to do.
4 years ago
67d0665b46
Post ResNet-RS merge cleanup. Add weight urls, adjust train/test/crop pct.
4 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
4 years ago
9cc7dda6e5
Fixup byoanet configs to pass unit tests. Add swin_attn and swinnet26t model for testing.
4 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.
4 years ago
e5e15754c9
Fix coat first conv ident
4 years ago
76739a7589
CoaT merge. Bit of formatting, fix torchscript (for non features), remove einops/einsum dep, add pretrained weight hub (url) support.
4 years ago
026430c083
Merge branch 'master' of https://github.com/morizin/pytorch-image-models-1 into morizin-master
4 years ago
a0492e3b48
A few miil weights naming tweaks to improve compat with model registry and filtering wildcards.
4 years ago
8c1f03e56c
comment
4 years ago
19e1b67a84
old spaces
4 years ago
a443865876
update naming and scores
4 years ago
cf0e371594
84_0
4 years ago
0968bdeca3
vit, tresnet and mobilenetV3 ImageNet-21K-P weights
4 years ago
1e3b6d4dfc
Update __init__.py
4 years ago
fd022fd6a2
Update __init__.py
4 years ago
c2d5087eae
Add files via upload
4 years ago
79640fcc1f
Enable uniform augmentation magnitude sampling and set AugMix default
4 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.
4 years ago
e8a64fb881
Test input size for efficientnet_v2s was wrong in last results run
4 years ago
2df77ee5cb
Fix torchscript compat and features_only behaviour in GhostNet PR. A few minor formatting changes. Reuse existing layers.
4 years ago
d793deb51a
Merge branch 'master' of https://github.com/iamhankai/pytorch-image-models into iamhankai-master
4 years ago
e685618f45
Merge pull request #550 from amaarora/wandb
...
Wandb Support
4 years ago
f606c45c38
Add Swin Transformer models from https://github.com/microsoft/Swin-Transformer
4 years ago
de445e7827
Add GhostNet
4 years ago
5a196dddf6
Update README.md with latest, bump version to 0.4.8
4 years ago
b3d7580df1
Update ByoaNet comments. Fix first Steam feat chs for ByobNet.
4 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
4 years ago
4e4b863b15
Missed norm.py
4 years ago
7c97e66f7c
Remove commented code, add more consistent seed fn
4 years ago
364dd6a58e
Merge branch 'master' into byoanet-self_attn
4 years ago
ce62f96d4d
ByoaNet with bottleneck transformer, lambda resnet, and halo net experiments
4 years ago
cd3dc4979f
Fix adabelief imports, remove prints, preserve memory format is the default arg for zeros_like
4 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.
4 years ago
5772c55c57
Make wandb optional
4 years ago
f54897cc0b
make wandb not required but rather optional as huggingface_hub
4 years ago
3f028ebc0f
import wandb in summary.py
4 years ago
624c9b6949
log to wandb only if using using wandb
4 years ago
addfc7c1ac
adabelief
4 years ago
fb896c0b26
Update some comments re preliminary EfficientNet-V2 assumptions
4 years ago
2b49ab7a36
Fix ResNetV2 pretrained classifier issue. Fixes #540
4 years ago
de9dff933a
EfficientNet-V2S preliminary model def (for experimentation)
4 years ago
37c71a5609
Some further create_optimizer_v2 tweaks, remove some redudnant code, add back safe model str. Benchmark step times per batch.
4 years ago
2bb65bd875
Wrong default_cfg pool_size for L1
4 years ago
bf2ca6bdf4
Merge jax and original weight init
4 years ago
acbd698c83
Update README.md with updates. Small tweak to head_dist handling.
4 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.
4 years ago
c468c47a9c
Add regnety_160 weights from DeiT teacher model, update that and my regnety_032 weights to use higher test size.
4 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
4 years ago
ea9c9550b2
Fully move ViT hybrids to their own file, including embedding module. Remove some extra DeiT models that were for benchmarking only.
4 years ago
a5310a3451
Merge remote-tracking branch 'origin/benchmark-fixes-vit_hybrids' into pit_and_vit_update
4 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
4 years ago
a760a4c3f4
Some ViT cleanup, merge distilled model with main, fixup torchscript support for distilled models
4 years ago
0dfc5a66bb
Add PiT model from https://github.com/naver-ai/pit
4 years ago
51febd869b
Small tweak to tests for tnt model, reorder model imports.
4 years ago
b27a4e0d88
Merge branch 'master' of https://github.com/contrastive/pytorch-image-models into contrastive-master
4 years ago
6b18061773
Add GIST to docstring for quick access
4 years ago
de86314655
Update TNT
4 years ago
92b1db9a79
update docstrings and add check on and
4 years ago
b85be24054
update to work with fnmatch
4 years ago
cfc15283a4
Update TNT url
4 years ago
4a09bc851e
Add TNT model
4 years ago
20626e8387
Add to extract stats for SPP
4 years ago
cf5fec5047
Cleanup experimental vit weight init a bit
4 years ago
f42f1df26c
Improve evenness of per-worker split for validation set with TFDS
4 years ago
cbcb76d72c
Should have included Conv2d layers in original weight init. Lets see what the impact is...
4 years ago
4de57ccf01
Add weight init scheme that's closer to JAX impl
4 years ago
14ac4abf74
Change huggingface hub revision delimiter to '@', add hf_hub reference for eca_nfnet_l0 model as an example.
4 years ago
740f32c96a
Add ECA-NFNet-L0 weights and update model name. Update README and bump version to 0.4.6
4 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
4 years ago
45c048ba13
A few minor fixes and bit more cleanup on the huggingface hub integration.
4 years ago
97f49d163c
adding efficientnet_el, efficientnet_es_prunedefficientnet_es_pruned and efficientnet_el_pruned pretrained models to timm/models
4 years ago
ead80d33c5
Fix typo, naming consistency
4 years ago
d584e7f617
Support for huggingface hub via create_model and default_cfgs.
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* 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
4 years ago
1f799afcb3
Remove capital letters in model names
4 years ago
82c1fe958a
added hardcorenas model
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refactoring to support feature extraction
4 years ago
f57db99101
Update README, fix iabn pip version print.
4 years ago
7ef7788ee9
Fix CUDA crash w/ channels-last + CSP models. Remove use of chunk()
4 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.
4 years ago
17cdee7354
Fix C&P patch_size error, and order of op patch_size arg resolution bug. Remove a test vit model.
4 years ago
0706d05d52
Benchmark models listed in txt file. Add more hybrid vit variants for testing
4 years ago
2db2d87ff7
Add epoch-repeats arg to multiply the number of dataset passes per epoch. Currently for iterable datasets (read TFDS wrapper) only.
4 years ago
de97be9146
Spell out diff between my small and deit small vit models.
4 years ago
f0ffdf89b3
Add numerous experimental ViT Hybrid models w/ ResNetV2 base. Update the ViT naming for hybrids. Fix #426 for pretrained vit resizing.
4 years ago
0e16d4e9fb
Add benchmark.py script, and update optimizer factory to be more friendly to use outside of argparse interface.
4 years ago
4bc103f504
Fix CUDA crash w/ channels-last + CSP models. Remove use of chunk()
4 years ago
8563609b28
Update notes in ScaledStdConv impl
4 years ago
678ba4e0a2
Add NFNet-F model weights ported from DeepMind Haiku impl and new set of models w/ compatible config.
4 years ago
9de2ec5e44
Update README for AGC and bump version to 0.4.4
4 years ago
4f49b94311
Initial AGC impl. Still testing.
4 years ago
5f9aff395c
Fix stem width in NFNet-F models, add some more comments, add some 'light' NFNet models for testing.
4 years ago
d86dbe45c2
Update README.md and few more comments
4 years ago
0d253e2c5e
Fix issue with nfnet tests, bit more cleanup.
4 years ago
cb06c7a910
Add NFNet-F models and tweak existing NF models.
4 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).
4 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.
4 years ago
ca9b078ac7
Update README.md and docs. Version bumped to 0.4.3
4 years ago
6853b07bbd
Improve RegVGG block identity/vs non for clariy and fix attn usage. Add comments.
4 years ago
0356e773f5
Default to native PyTorch AMP instead of APEX amp. Too many APEX issues cropping up lately.
4 years ago
94ca140b67
update collections.abc import
4 years ago
b4e216e377
Fix a few small things.
4 years ago
dc85e5a237
Add ByobNet w/ GPU-EfficientNets and RepVGG. Also add classic vgg models.
4 years ago
1bcc69e0ad
Use in_channels for depthwise groups, allows using `out_channels=N * in_channels` (does not impact existing models). Fix #354 .
4 years ago
9811e229f7
Fix regression in models with 1001 class pretrained weights. Improve batchnorm arg and BatchNormAct layer handling in several models.
4 years ago
a39c3ee216
Merge branch 'master' into eca-weights
4 years ago
e9d6fe293c
Update README for new weights. Version 0.4.2
4 years ago
666de85cf1
Move stride in EdgeResidual block to 3x3 expansion conv. Fix #414
4 years ago
3b57490a63
Fix some half removed resnet model defs, pooling for ecaresnet269d
4 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.
4 years ago
b9843f954b
Merge pull request #282 from tigert1998/patch-1
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Add symbolic for SwishJitAutoFn to support onnx
4 years ago
7a4be5c035
add operator HardSwishJitAutoFn export to onnx
4 years ago
4203efa36d
Fix #387 so that checkpoint saver works with max history of 1. Add checkpoint-hist arg to train.py.
4 years ago
f0e65e37b7
Fix NF-ResNet101 model defs
4 years ago
2c988c3b6e
Update README.md for NF-nets, bump version to 0.4.1 for merge
4 years ago
2de54d174a
Fix pool size defs for NFNet models, add a comment.
4 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.
4 years ago
5a8e1e643e
Initial Normalizer-Free Reg/ResNet impl. A bit of related layer refactoring.
4 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)
4 years ago
587780e56b
Update README.md and bump version to 0.4.0
4 years ago
bb50ac4708
Add DeiT distilled weights and distilled model def. Remove some redudant ViT model args.
4 years ago
c16e965037
Add some ViT comments and fix a few minor issues.
4 years ago
22748f1a2d
Convert samples/targets in ParserImageInTar to numpy arrays, slightly less mem usage for massive datasets. Add a few more se/eca model defs to resnet.py
4 years ago
5d4c3d0af3
Add enhanced ParserImageInTar that can read images from tars within tars, folders with multiple tars, etc. Additional comment cleanup.
4 years ago
55f7dfa9ea
Refactor vision_transformer entrpy fns, add pos embedding resize support for fine tuning, add some deit models for testing
4 years ago
d55bcc0fee
Finishing adding stochastic depth support to BiT ResNetV2 models
4 years ago
855d6cc217
More dataset work including factories and a tensorflow datasets (TFDS) wrapper
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* Add parser/dataset factory methods for more flexible dataset & parser creation
* Add dataset parser that wraps TFDS image classification datasets
* Tweak num_classes handling bug for 21k models
* Add initial deit models so they can be benchmarked in next csv results runs
4 years ago
20516abc18
Fix some broken tests for ResNetV2 BiT models
4 years ago
59ec7e6a53
Merge branch 'master' into imagenet21k_datasets_more
4 years ago
e7a9ddf982
Merge pull request #334 from kecsap/links
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Follow symbolic links during dataset scanning
4 years ago
7cae7e7035
Follow links during dataset scanning
4 years ago
c96e9f99a0
Update version to 0.3.3
4 years ago
4e2533db77
Add 320x320 model default cfgs for 101D and 152D ResNets. Add SEResNet-152D weights and 320x320 cfg.
4 years ago
0167f749d3
Remove some old __future__ imports
4 years ago
e35e9760a6
More work on dataset / parser split and imagenet21k (tar) support
4 years ago
ce69de70d3
Add 21k weight urls to vision_transformer. Cleanup feature_info for preact ResNetV2 (BiT) models
4 years ago
231d04e91a
ResNetV2 pre-act and non-preact model, w/ BiT pretrained weights and support for ViT R50 model. Tweaks for in21k num_classes passing. More to do... tests failing.
4 years ago
de6046e213
Initial commit for dataset / parser reorg to support additional datasets / types
4 years ago
392595c7eb
Add pool_size to default cfgs for new models to prevent tests from failing. Add explicit 200D_320 model entrypoint for next benchmark run.
4 years ago
b1f1228a41
Add ResNet101D, 152D, and 200D weights, remove meh 66d model
4 years ago
7c56c718f3
Configure create_optimizer with args.opt_args
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Closes #301
4 years ago
9a25fdf3ad
Merge pull request #297 from rwightman/ema_simplify
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Simplified JIT compatible Ema module. Fixes for SiLU export and torchscript training w/ Linear layer.
4 years ago
de15b43865
Fix a bug with accuracy retrieving from RealLabels
4 years ago
cd72e66eff
Bug in last mod for features_only default_cfg
4 years ago
867a0e5a04
Add default_cfg back to models wrapped in feature extraction module as per discussion in #294 .
4 years ago
4ca52d73d8
Add separate set and update method to ModelEmaV2
4 years ago
2ed8f24715
A few more changes for 0.3.2 maint release. Linear layer change for mobilenetv3 and inception_v3, support no bias for linear wrapper.
4 years ago
6504a42832
Version 0.3.2
4 years ago
460eba7f24
Work around casting issue with combination of native torch AMP and torchscript for Linear layers
4 years ago
5f4b6076d8
Fix inplace arg compat for GELU and PreLU via activation factory
4 years ago
fd962c4b4a
Native SiLU (Swish) op doesn't export to ONNX
4 years ago
27bbc70d71
Add back old ModelEma and rename new one to ModelEmaV2 to avoid compat breaks in dependant code. Shuffle train script, add a few comments, remove DataParallel support, support experimental torchscript training.
4 years ago
43f2500c26
Add symbolic for SwishJitAutoFn to support onnx
4 years ago
9214ca0716
Simplifying EMA...
4 years ago
53aeed3499
ver 0.3.1
4 years ago
30ab4a1494
Fix issue in optim factory with sgd / eps flag. Bump version to 0.3.1
4 years ago
741572dc9d
Bump version to 0.3.0 for pending PyPi push
4 years ago
b401952caf
Add newly added vision transformer large/base 224x224 weights ported from JAX official repo
4 years ago
61200db0ab
in_chans=1 working w/ pretrained weights for vision_transformer
4 years ago
e90edce438
Support native silu activation (aka swish). An optimized ver is available in PyTorch 1.7.
4 years ago
da6cd2cc1f
Fix regression for pretrained classifier loading when using entrypt functions directly
4 years ago
f591e90b0d
Make sure num_features attr is present in vit models as with others
4 years ago
4a3df7842a
Fix topn metric view regression on PyTorch 1.7
4 years ago
f944242cb0
Fix #262 , num_classes arg mixup. Make vision_transformers a bit closer to other models wrt get/reset classfier/forward_features. Fix torchscript for ViT.
4 years ago
736f209e7d
Update vision transformers to be compatible with official code. Port official ViT weights from jax impl.
4 years ago
477a78ed81
Fix optimizer factory regressin for optimizers like sgd/momentum that don't have an eps arg
4 years ago
27a93e9de7
Improve test crop for ViT models. Small now 77.85, added base weights at 79.35 top-1.
4 years ago
d4db9e7977
Add small vision transformer weights. 77.42 top-1.
4 years ago
27fadaa922
asymmetric_loss
4 years ago
f31933cb37
Initial Vision Transformer impl w/ patch and hybrid variants. Refactor tuple helpers.
4 years ago
a4d8fea61e
Add model based wd skip support. Improve cross version compat of optimizer factory. Fix #247
4 years ago
80078c47bb
Add Adafactor and Adahessian optimizers, cleanup optimizer arg passing, add gradient clipping support.
4 years ago
fcb6258877
Add missing leaky_relu layer factory defn, update Apex/Native loss scaler interfaces to support unscaled grad clipping. Bump ver to 0.2.2 for pending release.
4 years ago
e8e2d9cabf
Add DropPath (stochastic depth) to ReXNet and VoVNet. RegNet DropPath impl tweak and dedupe se args.
4 years ago
e8ca45854c
More models in sotabench, more control over sotabench run, dataset filename extraction consistency
4 years ago
9c406532bd
Add EfficientNet-EdgeTPU-M (efficientnet_em) model trained natively in PyTorch. More sotabench fiddling.
4 years ago
c40384f5bd
Add ResNet weights. 80.5 (top-1) ResNet-50-D, 77.1 ResNet-34-D, 72.7 ResNet-18-D.
4 years ago
47a7b3b5b1
More flexible mixup mode, add 'half' mode.
4 years ago
532e3b417d
Reorg of utils into separate modules
4 years ago
33f8a1bf36
Updated README, add wide_resnet50_2 and seresnext50_32x4d weights
4 years ago
751b0bba98
Add global_pool (--gp) arg changes to allow passing 'fast' easily for train/validate to avoid channels_last issue with AdaptiveAvgPool
4 years ago
9c297ec67d
Cleanup Apex vs native AMP scaler state save/load. Cleanup CheckpointSaver a bit.
4 years ago
80c9d9cc72
Add 'fast' global pool option, remove redundant SEModule from tresnet, normal one is now 'fast'
4 years ago
90a01f47d1
hrnet features_only pretrained weight loading issue. Fix #232 .
4 years ago
110a7c4982
AdaptiveAvgPool2d -> mean((2,3)) for all SE/attn layers to avoid NaN with AMP + channels_last layout. See https://github.com/pytorch/pytorch/issues/43992
4 years ago
c2cd1a332e
Improve torch amp support and add channels_last support for train/validate scripts
4 years ago
470220b1f4
Fix MobileNetV3 crash with global_pool='', output consistent with other models but not equivalent due to efficient head.
4 years ago
Alexander Soare