de6046e213
Initial commit for dataset / parser reorg to support additional datasets / types
2020-12-28 16:59:15 -08:00
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.
2020-12-18 21:28:47 -08:00
b1f1228a41
Add ResNet101D, 152D, and 200D weights, remove meh 66d model
2020-12-18 17:13:37 -08:00
7c56c718f3
Configure create_optimizer with args.opt_args
...
Closes #301
2020-12-08 00:03:09 -06:00
9a25fdf3ad
Merge pull request #297 from rwightman/ema_simplify
...
Simplified JIT compatible Ema module. Fixes for SiLU export and torchscript training w/ Linear layer.
2020-12-05 11:42:45 -08:00
de15b43865
Fix a bug with accuracy retrieving from RealLabels
2020-12-04 16:12:50 +01:00
cd72e66eff
Bug in last mod for features_only default_cfg
2020-12-03 12:33:01 -08:00
867a0e5a04
Add default_cfg back to models wrapped in feature extraction module as per discussion in #294 .
2020-12-03 10:24:35 -08:00
4ca52d73d8
Add separate set and update method to ModelEmaV2
2020-12-03 10:05:09 -08:00
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.
2020-11-30 16:19:52 -08:00
6504a42832
Version 0.3.2
2020-11-30 13:39:08 -08:00
460eba7f24
Work around casting issue with combination of native torch AMP and torchscript for Linear layers
2020-11-30 13:30:51 -08:00
5f4b6076d8
Fix inplace arg compat for GELU and PreLU via activation factory
2020-11-30 13:27:40 -08:00
fd962c4b4a
Native SiLU (Swish) op doesn't export to ONNX
2020-11-29 21:56:55 -08:00
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.
2020-11-29 16:22:19 -08:00
43f2500c26
Add symbolic for SwishJitAutoFn to support onnx
2020-11-18 14:36:12 +08:00
9214ca0716
Simplifying EMA...
2020-11-16 12:51:52 -08:00
53aeed3499
ver 0.3.1
2020-10-31 18:14:58 -07:00
30ab4a1494
Fix issue in optim factory with sgd / eps flag. Bump version to 0.3.1
2020-10-31 18:05:30 -07:00
741572dc9d
Bump version to 0.3.0 for pending PyPi push
2020-10-29 17:31:39 -07:00
b401952caf
Add newly added vision transformer large/base 224x224 weights ported from JAX official repo
2020-10-29 17:31:01 -07:00
61200db0ab
in_chans=1 working w/ pretrained weights for vision_transformer
2020-10-29 15:49:36 -07:00
e90edce438
Support native silu activation (aka swish). An optimized ver is available in PyTorch 1.7.
2020-10-29 15:45:17 -07:00
da6cd2cc1f
Fix regression for pretrained classifier loading when using entrypt functions directly
2020-10-29 15:43:39 -07:00
f591e90b0d
Make sure num_features attr is present in vit models as with others
2020-10-29 15:33:47 -07:00
4a3df7842a
Fix topn metric view regression on PyTorch 1.7
2020-10-29 14:04:15 -07:00
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.
2020-10-29 13:58:28 -07:00
736f209e7d
Update vision transformers to be compatible with official code. Port official ViT weights from jax impl.
2020-10-26 18:42:11 -07:00
477a78ed81
Fix optimizer factory regressin for optimizers like sgd/momentum that don't have an eps arg
2020-10-22 15:59:47 -07:00
27a93e9de7
Improve test crop for ViT models. Small now 77.85, added base weights at 79.35 top-1.
2020-10-21 23:35:25 -07:00
d4db9e7977
Add small vision transformer weights. 77.42 top-1.
2020-10-21 12:14:12 -07:00
27fadaa922
asymmetric_loss
2020-10-16 17:12:28 +03:00
f31933cb37
Initial Vision Transformer impl w/ patch and hybrid variants. Refactor tuple helpers.
2020-10-13 13:33:44 -07:00
a4d8fea61e
Add model based wd skip support. Improve cross version compat of optimizer factory. Fix #247
2020-10-13 12:49:47 -07:00
80078c47bb
Add Adafactor and Adahessian optimizers, cleanup optimizer arg passing, add gradient clipping support.
2020-10-09 17:24:43 -07:00
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.
2020-10-02 16:19:39 -07:00
e8e2d9cabf
Add DropPath (stochastic depth) to ReXNet and VoVNet. RegNet DropPath impl tweak and dedupe se args.
2020-09-24 18:20:36 -07:00
e8ca45854c
More models in sotabench, more control over sotabench run, dataset filename extraction consistency
2020-09-24 15:56:57 -07:00
9c406532bd
Add EfficientNet-EdgeTPU-M (efficientnet_em) model trained natively in PyTorch. More sotabench fiddling.
2020-09-23 17:12:07 -07:00
c40384f5bd
Add ResNet weights. 80.5 (top-1) ResNet-50-D, 77.1 ResNet-34-D, 72.7 ResNet-18-D.
2020-09-18 12:05:37 -07:00
47a7b3b5b1
More flexible mixup mode, add 'half' mode.
2020-09-07 20:03:06 -07:00
532e3b417d
Reorg of utils into separate modules
2020-09-07 13:58:09 -07:00
33f8a1bf36
Updated README, add wide_resnet50_2 and seresnext50_32x4d weights
2020-09-03 10:45:17 -07:00
751b0bba98
Add global_pool (--gp) arg changes to allow passing 'fast' easily for train/validate to avoid channels_last issue with AdaptiveAvgPool
2020-09-02 16:13:47 -07:00
9c297ec67d
Cleanup Apex vs native AMP scaler state save/load. Cleanup CheckpointSaver a bit.
2020-09-02 15:12:59 -07:00
80c9d9cc72
Add 'fast' global pool option, remove redundant SEModule from tresnet, normal one is now 'fast'
2020-09-02 09:11:48 -07:00
90a01f47d1
hrnet features_only pretrained weight loading issue. Fix #232 .
2020-09-01 17:37:55 -07:00
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
2020-09-01 16:05:32 -07:00
c2cd1a332e
Improve torch amp support and add channels_last support for train/validate scripts
2020-08-31 17:58:16 -07:00
470220b1f4
Fix MobileNetV3 crash with global_pool='', output consistent with other models but not equivalent due to efficient head.
2020-08-18 14:11:30 -07:00
fc8b8afb6f
Fix a silly bug in Sample version of EvoNorm missing x* part of swish, update EvoNormBatch to accumulated unbiased variance.
2020-08-13 18:25:01 -07:00
f614df7921
Bump version to 0.2.1 and update README
2020-08-12 18:05:07 -07:00
b423bc8362
Merge pull request #218 from rwightman/cutmix
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CutMix + MixUp overhaul
2020-08-12 17:17:41 -07:00
8c9814e3f5
Final cleanup of mixup/cutmix. Element/batch modes working with both collate (prefetcher active) and without prefetcher.
2020-08-12 17:01:32 -07:00
0f5d9d8166
Add CSPResNet50 weights, 79.6 top-1 at 256x256
2020-08-12 11:20:11 -07:00
b1b6e7c361
Fix a few more issues related to #216 w/ TResNet (space2depth) and FP16 weights in wide resnets. Also don't completely dump pretrained weights in in_chans != 1 or 3 cases.
2020-08-11 18:57:47 -07:00
512b2dd645
Add new EfficientNet-B3 and RegNetY-3.2GF weights, both just over 82 top-1
2020-08-11 14:18:51 -07:00
6890300877
Add DropPath (stochastic depth) to RegNet
2020-08-11 14:08:53 -07:00
cd23f55397
Fix mixed prec issues with new mixup code
2020-08-11 12:17:43 -07:00
f6b56602f9
fix test_model_default_cfgs
2020-08-11 23:23:57 +09:00
f471c17c9d
More cutmix/mixup overhaul, ready to kick-off some trials.
2020-08-11 00:10:33 -07:00
d5145fa4d5
Change default_cfg names for senet to include the legacy and match model names
2020-08-08 11:12:58 -07:00
92f2d0d65d
Merge branch 'master' into cutmix. Fixup a few issues.
2020-08-07 15:59:52 -07:00
1696499ce5
Bump version to 0.2.0, ready to roll (I think)
2020-08-05 16:55:18 -07:00
e62758cf4f
More documentation updates, fix a typo
2020-08-05 15:59:31 -07:00
dfe80414a6
Add bool arg helper
2020-08-05 13:17:23 -07:00
fa28067704
Add more augmentation arguments, including a no_aug disable flag. Fix #209
2020-08-05 13:16:44 -07:00
b1f1a54de9
More uniform treatment of classifiers across all models, reduce code duplication.
2020-08-03 22:18:24 -07:00
d72ddafe56
Fix some checkpoint / model str regressions
2020-07-29 19:43:01 -07:00
ac18adb9c3
Remove debug print from RexNet
2020-07-29 11:15:19 -07:00
c53ec33ae0
Add synset/label indices for results generation. Add 'valid labels' to validation script to support imagenet-a/r label subsets properly.
2020-07-29 00:58:57 -07:00
ec4976fdba
Add EfficientNet-Lite0 weights trained with this code by @hal-314, 75.484 top-1
2020-07-29 00:32:08 -07:00
9ecd16bd7b
Add new seresnet50 (non-legacy) model weights, 80.274 top-1
2020-07-29 00:17:42 -07:00
7995295968
Merge branch 'logger' into features. Change 'logger' to '_logger'.
2020-07-27 18:00:46 -07:00
1998bd3180
Merge branch 'feature/AB/logger' of https://github.com/antoinebrl/pytorch-image-models into logger
2020-07-27 16:06:01 -07:00
6c17d57a2c
Fix some attributions, add copyrights to some file docstrings
2020-07-27 13:44:56 -07:00
a69c0e04f0
Fix pool size in cspnet
2020-07-27 13:44:02 -07:00
14ef7a0dd6
Rename csp.py -> cspnet.py
2020-07-27 11:15:07 -07:00
ec37008432
Add pretrained weight links to CSPNet for cspdarknet53, cspresnext50
2020-07-27 11:13:21 -07:00
e93e571f7a
Add `adamp` and 'sgdp' optimizers.
...
Update requirements.txt
Update optim_factory.py
Add `adamp` optimizer
Update __init__.py
copy files of adamp & sgdp
Create adamp.py
Update __init__.py
Create sgdp.py
Update optim_factory.py
Update optim_factory.py
Update requirements.txt
Update adamp.py
Update sgdp.py
Update sgdp.py
Update adamp.py
2020-07-25 15:33:20 -07:00
08016e839d
Cleanup FeatureInfo getters, add TF models sourced Xception41/65/71 weights
2020-07-24 17:59:21 -07:00
7ba5a384d3
Add ReXNet w/ remapped weights, feature support
2020-07-23 10:28:57 -07:00
c9d54bc1c3
Add HRNet feature extraction, fix senet type, lower feature testing res to 96x96
2020-07-21 17:39:29 -07:00
2ac663f340
Add feature support to legacy senets, add 32x32 resnext models to exclude list for feature testing.
2020-07-21 11:15:30 -07:00
c146b54abc
Cleanup EfficientNet/MobileNetV3 feature extraction a bit, only two tap locations now, small mobilenetv3 models work
2020-07-21 01:21:38 -07:00
68fd8a267b
Merge branch 'master' into features
2020-07-20 16:11:38 -07:00
4e61c6a12d
Cleanup, refactoring of Feature extraction code, add tests, fix tests, non hook feature extraction working with torchscript
2020-07-20 16:10:31 -07:00
6eec3fb4a4
Move FeatureHooks into features.py, switch EfficientNet, MobileNetV3 to use build model helper
2020-07-19 15:00:43 -07:00
9eba134d79
More models supporting feature extraction, xception, gluon_xception, inception_v3, inception_v4, pnasnet, nasnet, dla. Fix DLA unused projection params.
2020-07-19 14:02:02 -07:00
298fba09ac
Back out some activation hacks trialing upcoming pytorch changes
2020-07-17 18:41:37 -07:00
3b9004bef9
Lots of changes to model creation helpers, close to finalizing feature extraction / interfaces
2020-07-17 17:54:26 -07:00
e2cc481310
Update CSP ResNets for cross expansion without activation. Fix VovNet IABN compatibility with fixed activation arg.
2020-07-13 16:24:55 -07:00
3b6cce4c95
Add initial impl of CrossStagePartial networks, yet to be trained, not quite the same as darknet cfgs.
2020-07-13 15:01:06 -07:00
3aebc2f06c
Switch DPN to use BnAct layer, train a new DPN 68b model with RA to 79.21
2020-07-12 11:13:06 -07:00
f122f0274b
Significant ResNet refactor:
...
* stage creation + make_layer moved to separate fn with more sensible dilation/output_stride calc
* drop path rate decay easy to impl with refactored block creation loops
* fix dilation + blur pool combo
2020-07-05 00:48:12 -07:00
a66df5fb91
More model feature extraction support, start to deprecate senet.py, dilations added to regnet, add proper aligned xception
2020-07-03 00:41:30 -07:00
7729f40dca
Fix another bug, update all gluon resnet models to use new creation method (feature support)
2020-06-30 16:44:15 -07:00
d72ac0db25
Fix #173 , lr cycle default 0 vs 1. Fix #177 , mirror resnest weights for future stability.
2020-06-29 21:31:48 -07:00
d0113f9cdb
Fix a few issues that came up in tests
2020-06-29 21:13:21 -07:00
d23a2697d0
Working on feature extraction, interfaces refined, a number of models working, some in progress.
2020-06-29 18:18:59 -07:00
24e7535278
Remove tests from distrib
2020-06-16 22:57:26 -07:00
328339a086
Add ESE-VoVNet-19-DW weights
2020-06-15 14:31:55 -07:00
2d83752bc2
Fix default interpolation/crop of largest 2 ResNeSt models
2020-06-12 16:42:47 -07:00
f225ae8e59
Update README with model results and attribution. Make scheduler factory bit more robust to arg differences, add noise to plateau lr and fix min/max.
2020-06-12 13:33:12 -07:00
39f27c1add
Almost ready to merge, vovnet typo, version bump, readme addition
2020-06-11 15:41:58 -07:00
151679c2f1
Add custom grad tests, fix cut & paste error with hard_mish ME, add a few more pytorch act fns to factory
2020-06-11 14:49:23 -07:00
6c7932fe75
Update sotabench.py, tweak VovNet cfg
2020-06-11 14:34:25 -07:00
0aca08384f
Update regnet cfg keys to match model names so registry works properly
2020-06-09 14:37:45 -07:00
78fa0772cc
Leverage python hierachical logger
...
with this update one can tune the kind of logs generated by timm but
training and inference traces are unchanged
2020-06-09 18:28:48 +01:00
13c0a6290e
Add ESE-VovNet39 weights, 79.32 top-1
2020-06-06 22:50:21 -07:00
4ddde1d3a4
Fix two regressions
2020-06-05 11:04:51 -07:00
a7e8cadd15
Remove pointless densenet configs, add an iabn version of 264 as it makes more sense to try someday...
2020-06-03 17:13:52 -07:00
e78daf586a
better densenet121 and densenetblur121d weights
2020-06-03 13:30:03 -07:00
7be299504f
Add missing feature_info() on MobileNetV3, make hook feature output order/type consistent with bottleneck (list, decreasing fmap size)
2020-06-03 00:00:37 -07:00
88129b2569
Add set_layer_config contextmgr to adjust all layer configs at once, use in create_module with new args. Remove a few old warning causing constant annotations for jit.
2020-06-02 21:06:10 -07:00
f28170df3f
Fix an an untested change, remove a debug print
2020-06-01 17:26:42 -07:00
eb7653614f
Monster commit, activation refactor, VoVNet, norm_act improvements, more
...
* refactor activations into basic PyTorch, jit scripted, and memory efficient custom auto
* implement hard-mish, better grad for hard-swish
* add initial VovNet V1/V2 impl, fix #151
* VovNet and DenseNet first models to use NormAct layers (support BatchNormAct2d, EvoNorm, InplaceIABN)
* Wrap IABN for any models that use it
* make more models torchscript compatible (DPN, PNasNet, Res2Net, SelecSLS) and add tests
2020-06-01 17:16:52 -07:00
0ea53cecc3
Merge branch 'master' into densenet_update_and_more
2020-05-22 16:18:10 -07:00
6441e9cc1b
Fix memory_efficient mode for DenseNets. Add AntiAliasing (Blur) support for DenseNets and create one test model. Add lr cycle/mul params to train args.
2020-05-22 16:16:45 -07:00
afb6bd0669
Add backward and default_cfg tests and fix a few issues found. Fix #153
2020-05-21 15:30:58 -07:00
50658b9a67
Add RegNet models and weights
2020-05-18 00:08:52 -07:00
7df83258c9
Merge branch 'master' into densenet_update_and_more
2020-05-13 23:34:44 -07:00
1904ed8fec
Improve dropblock impl, add fast variant, and better AMP speed, inplace, batchwise... few ResNeSt cleanups
2020-05-13 15:17:08 -07:00
17270c69b9
Remove annoying InceptionV3 dependency on scipy and insanely slow trunc_norm init. Bring InceptionV3 code into this codebase and use upcoming torch trunch_norm_ init.
2020-05-12 21:59:34 -07:00
c4ca016656
Merge pull request #145 from rwightman/resnest
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ResNeSt
2020-05-12 13:38:29 -07:00
208e7912f7
Missed one of the abalation model entrypoints, update README
2020-05-12 13:36:31 -07:00
9cc289f18c
Exclude EfficientNet-L2 models from test
2020-05-12 13:07:03 -07:00
2f884a0ce5
Add resnest14, resnest26, and two of the abalation grouped resnest50 models
2020-05-12 12:21:52 -07:00
f4cdc2ac31
Add ResNeSt models
2020-05-11 23:27:09 -07:00
780860d140
Add norm_act factory method, move JIT of norm layers to factory
2020-05-09 22:09:21 -07:00
14edacdf9a
DenseNet converted to support ABN (norm + act) modules. Experimenting with EvoNorm, IABN
2020-05-09 18:26:41 -07:00
022ed001f3
Update DenseNet to latest in Torchvision (torchscript compat, checkpointing, proper init). Start adding ehanced configurability, stem options...
2020-05-07 09:57:48 -07:00
a7ebe09029
Replace all None by nn.Identity() in all models reset_classifier when False-values num_classes is given.
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Make small code refactoring
2020-05-06 09:54:03 +03:00
f0eb021620
Replace all None by nn.Identity() in HRNet modules
2020-05-05 21:09:35 +03:00
a7f570c9b7
added MultiEpochsDataLoader
2020-05-05 14:47:02 +03:00
8d8677e03b
Fix #139 . Broken SKResNets after BlurPool addition, as a plus, SKResNets support AA now too.
2020-05-04 12:14:43 -07:00
c9b6f415ca
Bump version for Pypi release
2020-05-03 21:18:47 -07:00
9c15d57505
added efficientnet pruned weights
2020-05-03 09:29:45 +03:00
ea300709f0
Fix model create fn not passing num_classes through. Fix #135
2020-05-01 18:37:03 -07:00
2c438c4e0d
Merge branch 'master' of github.com:rwightman/pytorch-models
2020-05-01 17:03:17 -07:00
2681a8d618
Final blurpool2d cleanup and add resnetblur50 weights, match tresnet Downsample arg order to BlurPool2d for interop
2020-05-01 17:00:21 -07:00
9590f301a9
Merge branch 'blur' of https://github.com/VRandme/pytorch-image-models into VRandme-blur
2020-05-01 15:19:57 -07:00
a5220ad3aa
Merge pull request #125 from Separius/patch-1
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fix typo in eca
2020-05-01 15:11:56 -07:00
0834fbc01c
Move pruned model adapt strings to separate txt files. A few minor formatting alignment tweaks.
2020-05-01 15:09:20 -07:00
ba793f5c1c
Merge branch 'adding_ECA_resnet' of https://github.com/yoniaflalo/pytorch-image-models into yoniaflalo-adding_ECA_resnet
2020-04-29 16:43:02 -07:00
07f19dd699
added eca resnet
2020-04-29 19:09:55 +03:00
1d4ac1b165
Bump version for pypi release. Fix #130
2020-04-27 18:02:40 -07:00
be7c784d21
Small TResNet simplification, just use SelectAdaptivePool, don't notice any perf difference
2020-04-27 17:50:19 -07:00
e3a98171b2
Remove some CRLF that made it into TResNet merge
2020-04-27 13:23:41 -07:00
0004f37d25
Some TResNet cleanup.
...
* allow use of global pool arg, test-time-pooling
* clean checkpoints to just contain state dict, add 448 res checkpoints
* support DataParallel via lazy filter creation for JIT Downsample
* some minor formatting (mostly alignment) preferences
2020-04-27 13:21:05 -07:00
64fe37d008
Remove old mean/std helper, rely fully on cmd line or default_cfg now. Fixes #126
2020-04-27 12:32:55 -07:00
e6f24e5578
Add 'momentum' optimizer (SGD w/o nesterov) for stable EfficientDet training defaults
2020-04-25 19:42:13 -07:00
20290b5b56
fix typo in eca
2020-04-14 15:20:35 +04:30
ebf82b84ac
Merge pull request #122 from mrT23/master
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TResNet models
2020-04-12 18:23:46 -07:00
bdb165a8a4
Merge changes in feature extraction interface to MobileNetV3
...
Experimental feature extraction interface seems to be changed
a little bit with the most up to date version apparently found
in EfficientNet class. Here these changes are added to
MobileNetV3 class to make it support it and work again, too.
2020-04-13 02:02:14 +03:00
8a63c1add8
finalizing
2020-04-12 19:08:35 +03:00
6209146738
TResNet models
2020-04-12 18:44:12 +03:00
13cf68850b
Remove poorly named metrics from torch imagenet example origins. Use top1/top5 in csv output for consistency with existing validation results files, acc elsewhere. Fixes #111
2020-04-10 14:41:08 -07:00
56608c9070
Bump version for pypi
2020-04-09 01:46:05 -07:00
1a8f5900ab
Update EfficientNet feature extraction for EfficientDet. Add needed MaxPoolSame as well.
2020-04-09 01:41:54 -07:00
06a50a94a8
Fix minor typos in create_attn.py and resnet.py
...
'eca'->'ceca'
and
doest not-> does not
2020-04-07 21:15:57 +09:00
1a9ab07307
One too many changes at a time, fix missing C
2020-04-07 21:12:08 +09:00
f17b42bc33
Blur filter no longer a buffer
2020-04-07 21:12:08 +09:00
6cdeca24a3
Some cleanup and fixes for initial BlurPool impl. Still some testing and tweaks to go...
2020-04-07 21:12:08 +09:00
acd1b6cccd
Implement Functional Blur on resnet.py
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1. add ResNet argument blur=''
2. implement blur for maxpool and strided convs in downsampling blocks
2020-04-07 21:12:08 +09:00
ce3d82b58b
Update blurpool.py
...
clean up code for PR
2020-04-07 21:12:07 +09:00
3a287a6e76
Create blurpool.py
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Initial implementation of blur layer.
currently tests as correct against Downsample of original github
2020-04-07 21:12:07 +09:00
c99a5abed4
Merge pull request #115 from rwightman/mobilenetv2-experiment
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MobileNet-V2 experiments
2020-04-05 17:32:06 -07:00
e34074b4da
Add final weights for MobileNet-V2 experiments
2020-04-05 17:31:02 -07:00
a6a5565de7
Fiddling...
2020-03-19 10:20:20 -07:00
5a16c533ff
Add better resnext50_32x4d weights trained by andravin
2020-03-18 14:43:50 -07:00
bc998cad91
Experimenting with some MobileNetV2 variations to compare against EfficientNet-Lite
2020-03-18 13:54:06 -07:00
3406e582cf
Add EfficientNet-Lite results, update README
2020-03-18 13:12:30 -07:00
bd05258f7b
EfficientNet-Lite model added w/ converted checkpoints, validation in progress...
2020-03-17 23:31:45 -07:00
d92cc4da54
Modified save_checkpoint to always save last checkpoint. Fixes #98 .
2020-03-09 22:41:33 -07:00
56e2ac3a6d
Merge pull request #94 from rwightman/lr_noise
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Learning rate noise, MobileNetV3 weights, and activate MobileNetV3/EfficientNet weight init change
2020-02-29 20:41:05 -08:00
c16f25ced2
Add MobileNetV3 Large weights, results, update README and sotabench for merge
2020-02-29 20:37:20 -08:00
c60069c1eb
Annotate types on drop fns to avoid torchscript error
2020-02-27 09:30:23 -08:00
9fee316752
Enable fixed fanout calc in EfficientNet/MobileNetV3 weight init by default. Fix #84
2020-02-24 15:11:26 -08:00
27b3680d49
Revamp LR noise, move logic to scheduler base. Fixup PlateauLRScheduler and add it as an option.
2020-02-22 16:23:15 -08:00
cc5a11abba
version bump for PyPi update
2020-02-22 10:26:19 -08:00
514b0938c4
Experimenting with per-epoch learning rate noise w/ step scheduler
2020-02-21 11:51:05 -08:00
43225d110c
Unify drop connect vs drop path under 'drop path' name, switch all EfficientNet/MobilenetV3 refs to 'drop_path'. Update factory to handle new drop args.
2020-02-18 14:00:26 -08:00
f1d5f8a6c4
Update comments for Selective Kernel and DropBlock/Path impl, add skresnet34 weights
2020-02-18 13:58:30 -08:00
670c61b28f
Some cutmix/mixup cleanup/fixes
2020-02-17 11:00:54 -08:00
b3cb5f3275
Working on CutMix impl as per #8 , integrating with Mixup, currently experimenting...
2020-02-16 20:09:11 -08:00
569419b38d
Tweak some comments, add SKNet models with weights to sotabench, remove an unused branch
2020-02-15 21:18:25 -08:00
53c47479c4
Batch validation batch size adjustment, tweak L2 crop pct
2020-02-15 20:37:04 -08:00
08553e16b3
Merge branch 'master' into attention
2020-02-14 18:24:21 -08:00
fa38f24967
Update SK network configs, add weights for skresnet8 and skresnext50
2020-02-14 15:37:00 -08:00
f098fda2ca
Add map_location='cpu' to ModelEma resume, should improve #72
2020-02-12 13:23:56 -08:00
ba15ca47e8
Add ported EfficientNet-L2, B0-B7 NoisyStudent weights from TF TPU
2020-02-12 11:26:38 -08:00
5e6dbbaf30
Add CBAM for experimentation
2020-02-10 16:23:09 -08:00
d725991870
Remove debug print from ECA module
2020-02-10 16:21:33 -08:00
2a7d256fd5
Re-enable mem-efficient/jit activations after torchscript tests
2020-02-10 11:59:36 -08:00
f902bcd54c
Layer refactoring continues, ResNet downsample rewrite for proper dilation in 3x3 and avg_pool cases
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* select_conv2d -> create_conv2d
* added create_attn to create attention module from string/bool/module
* factor padding helpers into own file, use in both conv2d_same and avg_pool2d_same
* add some more test eca resnet variants
* minor tweaks, naming, comments, consistency
2020-02-10 11:55:03 -08:00
a99ec4e7d1
A bunch more layer reorg, splitting many layers into own files. Improve torchscript compatibility.
2020-02-09 14:46:28 -08:00
13746a33fc
Big move, layer modules and fn to timm/models/layers
2020-02-09 13:13:08 -08:00
f54612f648
Merge branch 'select_kernel' into attention
2020-02-09 12:59:24 -08:00
4defbbbaa8
Fix module name mistake, start layers sub-package
2020-02-09 12:44:26 -08:00
Ross Wightman
Jasha
Ross Wightman
Tymoteusz Wiśniewski
tigertang
talrid
Yusuke Uchida
Sangdoo Yun
Antoine Broyelle
Vyacheslav Shults
AFLALO, Jonathan Isaac
Sepehr Sameni
Alexey Chernov
Chris Ha
Andrew Lavin