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
...
More models, GPU-Efficient Nets, RepVGG, classic VGG, and flexible Byob backbone.
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
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
...
Add symbolic for SwishJitAutoFn to support onnx
4 years ago
7a4be5c035
add operator HardSwishJitAutoFn export to onnx
4 years ago
f0e65e37b7
Fix NF-ResNet101 model defs
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
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
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
...
* 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
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
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
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
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
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
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
43f2500c26
Add symbolic for SwishJitAutoFn to support onnx
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
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
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
f31933cb37
Initial Vision Transformer impl w/ patch and hybrid variants. Refactor tuple helpers.
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
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
470220b1f4
Fix MobileNetV3 crash with global_pool='', output consistent with other models but not equivalent due to efficient head.
4 years ago
fc8b8afb6f
Fix a silly bug in Sample version of EvoNorm missing x* part of swish, update EvoNormBatch to accumulated unbiased variance.
4 years ago
0f5d9d8166
Add CSPResNet50 weights, 79.6 top-1 at 256x256
4 years ago
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.
4 years ago
512b2dd645
Add new EfficientNet-B3 and RegNetY-3.2GF weights, both just over 82 top-1
4 years ago
6890300877
Add DropPath (stochastic depth) to RegNet
4 years ago
f6b56602f9
fix test_model_default_cfgs
4 years ago
d5145fa4d5
Change default_cfg names for senet to include the legacy and match model names
4 years ago
b1f1a54de9
More uniform treatment of classifiers across all models, reduce code duplication.
4 years ago
d72ddafe56
Fix some checkpoint / model str regressions
4 years ago
ac18adb9c3
Remove debug print from RexNet
4 years ago
ec4976fdba
Add EfficientNet-Lite0 weights trained with this code by @hal-314, 75.484 top-1
4 years ago
9ecd16bd7b
Add new seresnet50 (non-legacy) model weights, 80.274 top-1
4 years ago
7995295968
Merge branch 'logger' into features. Change 'logger' to '_logger'.
4 years ago
1998bd3180
Merge branch 'feature/AB/logger' of https://github.com/antoinebrl/pytorch-image-models into logger
4 years ago
6c17d57a2c
Fix some attributions, add copyrights to some file docstrings
4 years ago
a69c0e04f0
Fix pool size in cspnet
4 years ago
14ef7a0dd6
Rename csp.py -> cspnet.py
4 years ago
ec37008432
Add pretrained weight links to CSPNet for cspdarknet53, cspresnext50
4 years ago
08016e839d
Cleanup FeatureInfo getters, add TF models sourced Xception41/65/71 weights
4 years ago
7ba5a384d3
Add ReXNet w/ remapped weights, feature support
4 years ago
c9d54bc1c3
Add HRNet feature extraction, fix senet type, lower feature testing res to 96x96
4 years ago
2ac663f340
Add feature support to legacy senets, add 32x32 resnext models to exclude list for feature testing.
4 years ago
c146b54abc
Cleanup EfficientNet/MobileNetV3 feature extraction a bit, only two tap locations now, small mobilenetv3 models work
4 years ago
68fd8a267b
Merge branch 'master' into features
4 years ago
4e61c6a12d
Cleanup, refactoring of Feature extraction code, add tests, fix tests, non hook feature extraction working with torchscript
4 years ago
6eec3fb4a4
Move FeatureHooks into features.py, switch EfficientNet, MobileNetV3 to use build model helper
4 years ago
9eba134d79
More models supporting feature extraction, xception, gluon_xception, inception_v3, inception_v4, pnasnet, nasnet, dla. Fix DLA unused projection params.
4 years ago
298fba09ac
Back out some activation hacks trialing upcoming pytorch changes
4 years ago
3b9004bef9
Lots of changes to model creation helpers, close to finalizing feature extraction / interfaces
4 years ago
e2cc481310
Update CSP ResNets for cross expansion without activation. Fix VovNet IABN compatibility with fixed activation arg.
5 years ago
3b6cce4c95
Add initial impl of CrossStagePartial networks, yet to be trained, not quite the same as darknet cfgs.
5 years ago
3aebc2f06c
Switch DPN to use BnAct layer, train a new DPN 68b model with RA to 79.21
5 years ago
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
5 years ago
a66df5fb91
More model feature extraction support, start to deprecate senet.py, dilations added to regnet, add proper aligned xception
5 years ago
7729f40dca
Fix another bug, update all gluon resnet models to use new creation method (feature support)
5 years ago
d72ac0db25
Fix #173 , lr cycle default 0 vs 1. Fix #177 , mirror resnest weights for future stability.
5 years ago
d0113f9cdb
Fix a few issues that came up in tests
5 years ago
d23a2697d0
Working on feature extraction, interfaces refined, a number of models working, some in progress.
5 years ago
328339a086
Add ESE-VoVNet-19-DW weights
5 years ago
2d83752bc2
Fix default interpolation/crop of largest 2 ResNeSt models
5 years ago
39f27c1add
Almost ready to merge, vovnet typo, version bump, readme addition
5 years ago
151679c2f1
Add custom grad tests, fix cut & paste error with hard_mish ME, add a few more pytorch act fns to factory
5 years ago
6c7932fe75
Update sotabench.py, tweak VovNet cfg
5 years ago
0aca08384f
Update regnet cfg keys to match model names so registry works properly
5 years ago
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
5 years ago
13c0a6290e
Add ESE-VovNet39 weights, 79.32 top-1
5 years ago
4ddde1d3a4
Fix two regressions
5 years ago
a7e8cadd15
Remove pointless densenet configs, add an iabn version of 264 as it makes more sense to try someday...
5 years ago
e78daf586a
better densenet121 and densenetblur121d weights
5 years ago
7be299504f
Add missing feature_info() on MobileNetV3, make hook feature output order/type consistent with bottleneck (list, decreasing fmap size)
5 years ago
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.
5 years ago
f28170df3f
Fix an an untested change, remove a debug print
5 years ago
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
5 years ago
0ea53cecc3
Merge branch 'master' into densenet_update_and_more
5 years ago
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.
5 years ago
afb6bd0669
Add backward and default_cfg tests and fix a few issues found. Fix #153
5 years ago
50658b9a67
Add RegNet models and weights
5 years ago
7df83258c9
Merge branch 'master' into densenet_update_and_more
5 years ago
1904ed8fec
Improve dropblock impl, add fast variant, and better AMP speed, inplace, batchwise... few ResNeSt cleanups
5 years ago
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.
5 years ago
c4ca016656
Merge pull request #145 from rwightman/resnest
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ResNeSt
5 years ago
208e7912f7
Missed one of the abalation model entrypoints, update README
5 years ago
9cc289f18c
Exclude EfficientNet-L2 models from test
5 years ago
2f884a0ce5
Add resnest14, resnest26, and two of the abalation grouped resnest50 models
5 years ago
f4cdc2ac31
Add ResNeSt models
5 years ago
780860d140
Add norm_act factory method, move JIT of norm layers to factory
5 years ago
14edacdf9a
DenseNet converted to support ABN (norm + act) modules. Experimenting with EvoNorm, IABN
5 years ago
022ed001f3
Update DenseNet to latest in Torchvision (torchscript compat, checkpointing, proper init). Start adding ehanced configurability, stem options...
5 years ago
a7ebe09029
Replace all None by nn.Identity() in all models reset_classifier when False-values num_classes is given.
...
Make small code refactoring
5 years ago
f0eb021620
Replace all None by nn.Identity() in HRNet modules
5 years ago
8d8677e03b
Fix #139 . Broken SKResNets after BlurPool addition, as a plus, SKResNets support AA now too.
5 years ago
9c15d57505
added efficientnet pruned weights
5 years ago
ea300709f0
Fix model create fn not passing num_classes through. Fix #135
5 years ago
2c438c4e0d
Merge branch 'master' of github.com:rwightman/pytorch-models
5 years ago
2681a8d618
Final blurpool2d cleanup and add resnetblur50 weights, match tresnet Downsample arg order to BlurPool2d for interop
5 years ago
9590f301a9
Merge branch 'blur' of https://github.com/VRandme/pytorch-image-models into VRandme-blur
5 years ago
a5220ad3aa
Merge pull request #125 from Separius/patch-1
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fix typo in eca
5 years ago
0834fbc01c
Move pruned model adapt strings to separate txt files. A few minor formatting alignment tweaks.
5 years ago
ba793f5c1c
Merge branch 'adding_ECA_resnet' of https://github.com/yoniaflalo/pytorch-image-models into yoniaflalo-adding_ECA_resnet
5 years ago
07f19dd699
added eca resnet
5 years ago
be7c784d21
Small TResNet simplification, just use SelectAdaptivePool, don't notice any perf difference
5 years ago
e3a98171b2
Remove some CRLF that made it into TResNet merge
5 years ago
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
5 years ago
20290b5b56
fix typo in eca
5 years ago
ebf82b84ac
Merge pull request #122 from mrT23/master
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TResNet models
5 years ago
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.
5 years ago
8a63c1add8
finalizing
5 years ago
6209146738
TResNet models
5 years ago
1a8f5900ab
Update EfficientNet feature extraction for EfficientDet. Add needed MaxPoolSame as well.
5 years ago
06a50a94a8
Fix minor typos in create_attn.py and resnet.py
...
'eca'->'ceca'
and
doest not-> does not
5 years ago
1a9ab07307
One too many changes at a time, fix missing C
5 years ago
f17b42bc33
Blur filter no longer a buffer
5 years ago
6cdeca24a3
Some cleanup and fixes for initial BlurPool impl. Still some testing and tweaks to go...
5 years ago
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
5 years ago
ce3d82b58b
Update blurpool.py
...
clean up code for PR
5 years ago
3a287a6e76
Create blurpool.py
...
Initial implementation of blur layer.
currently tests as correct against Downsample of original github
5 years ago
c99a5abed4
Merge pull request #115 from rwightman/mobilenetv2-experiment
...
MobileNet-V2 experiments
5 years ago
e34074b4da
Add final weights for MobileNet-V2 experiments
5 years ago
a6a5565de7
Fiddling...
5 years ago
5a16c533ff
Add better resnext50_32x4d weights trained by andravin
5 years ago
bc998cad91
Experimenting with some MobileNetV2 variations to compare against EfficientNet-Lite
5 years ago
3406e582cf
Add EfficientNet-Lite results, update README
5 years ago
bd05258f7b
EfficientNet-Lite model added w/ converted checkpoints, validation in progress...
5 years ago
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
5 years ago
c16f25ced2
Add MobileNetV3 Large weights, results, update README and sotabench for merge
5 years ago
c60069c1eb
Annotate types on drop fns to avoid torchscript error
5 years ago
9fee316752
Enable fixed fanout calc in EfficientNet/MobileNetV3 weight init by default. Fix #84
5 years ago
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.
5 years ago
f1d5f8a6c4
Update comments for Selective Kernel and DropBlock/Path impl, add skresnet34 weights
5 years ago
569419b38d
Tweak some comments, add SKNet models with weights to sotabench, remove an unused branch
5 years ago
53c47479c4
Batch validation batch size adjustment, tweak L2 crop pct
5 years ago
08553e16b3
Merge branch 'master' into attention
5 years ago
fa38f24967
Update SK network configs, add weights for skresnet8 and skresnext50
5 years ago
ba15ca47e8
Add ported EfficientNet-L2, B0-B7 NoisyStudent weights from TF TPU
5 years ago
5e6dbbaf30
Add CBAM for experimentation
5 years ago
d725991870
Remove debug print from ECA module
5 years ago
2a7d256fd5
Re-enable mem-efficient/jit activations after torchscript tests
5 years ago
f902bcd54c
Layer refactoring continues, ResNet downsample rewrite for proper dilation in 3x3 and avg_pool cases
...
* 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
5 years ago
a99ec4e7d1
A bunch more layer reorg, splitting many layers into own files. Improve torchscript compatibility.
5 years ago
13746a33fc
Big move, layer modules and fn to timm/models/layers
5 years ago
f54612f648
Merge branch 'select_kernel' into attention
5 years ago
4defbbbaa8
Fix module name mistake, start layers sub-package
5 years ago
7011cd0902
A little bit of ECA cleanup
5 years ago
46471df7b2
Merge pull request #82 from VRandme/eca
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ECA-Net Efficient Channel Attention
5 years ago
d0eb59ef46
Remove unused default_init for EfficientNets, experimenting with fanout calc for #84
5 years ago
e6a762346a
Implement Adaptive Kernel selection
...
When channel size is given,
calculate adaptive kernel size according to original paper.
Otherwise use the given kernel size(k_size), which defaults to 3
5 years ago
13e8da2b46
SelectKernel split_input works best when input channels split like grouped conv, but output is full width. Disable zero_init for SK nets, seems a bad combo.
5 years ago
6db087a1ff
Merge remote-tracking branch 'upstream/master' into eca
5 years ago
904c618040
Update EcaModule.py
...
Make pylint happy
(commas, unused imports, missed imports)
5 years ago
db91ba053b
EcaModule(CamelCase)
...
CamelCased EcaModule.
Renamed all instances of ecalayer to EcaModule.
eca_module.py->EcaModule.py
5 years ago
5c4991a088
Add PyTorch trained EfficientNet-ES weights from Andrew Lavin
5 years ago
d63ae121d5
Clean up eca_module code
...
functionally similar
adjusted rwightman's version of reshaping and viewing.
Use F.pad for circular eca version for cleaner code
5 years ago
f87fcd7e88
Implement Eca modules
...
implement ECA module by
1. adopting original eca_module.py into models folder
2. adding use_eca layer besides every instance of SE layer
5 years ago
7d07ebb660
Adding some configs to sknet, incl ResNet50 variants from 'Compounding ... Assembled Techniques' paper and original SKNet50
5 years ago
a9d2424fd1
Add separate zero_init_last_bn function to support more block variety without a mess
5 years ago
355aa152d5
Just leave it float for now, will look at fp16 later. Remove unused reference code.
5 years ago
ef457555d3
BlockDrop working on GPU
5 years ago
3ff19079f9
Missed nn_ops.py from last commit
5 years ago
9f11b4e8a2
Add ConvBnAct layer to parallel integrated SelectKernelConv, add support for DropPath and DropBlock to ResNet base and SK blocks
5 years ago
cefc9b7761
Move SelectKernelConv to conv2d_layers and more
...
* always apply attention in SelectKernelConv, leave MixedConv for no attention alternative
* make MixedConv torchscript compatible
* refactor first/previous dilation name to make more sense in ResNet* networks
5 years ago
9abe610931
Used wrong channel var for split
5 years ago
58e28dc7e7
Move Selective Kernel blocks/convs to their own sknet.py file
5 years ago
a93bae6dc5
A SelectiveKernelBasicBlock for more experiments
5 years ago
ad087b4b17
Missed bias=False in selection conv
5 years ago
c8b3d6b81a
Initial impl of Selective Kernel Networks. Very much a WIP.
5 years ago
91534522f9
Add newly added TF ported EfficientNet-B8 weights (RandAugment)
5 years ago
12dbc74742
New ResNet50 JSD + RandAugment weights
5 years ago
2f41905ba5
Update ResNet50 weights to AuxMix trained 78.994 top-1. A few commentes re 'tiered_narrow' tn variant.
5 years ago
d9a6a9d0af
Merge pull request #74 from rwightman/augmix-jsd
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AugMix, JSD loss, SplitBatchNorm (Auxiliary BN), and more
5 years ago
3eb4a96eda
Update AugMix, JSD, etc comments and references
5 years ago
a28117ea46
Add tiered narrow ResNet (tn) and weights for seresnext26tn_32x4d
5 years ago
833066b540
A few minor things in SplitBN
5 years ago
7547119891
Add SplitBatchNorm. AugMix, Rand/AutoAugment, Split (Aux) BatchNorm, Jensen-Shannon Divergence, RandomErasing all working together
5 years ago
ec0dd4053a
Add updated RandAugment trained EfficientNet-B0 trained weights from @michaelklachko
5 years ago
40fea63ebe
Add checkpoint averaging script. Add headers, shebangs, exec perms to all scripts
5 years ago
53001dd292
ResNet / Res2Net additions:
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* ResNet torchscript compat
* output_stride arg supported to limit network stride via dilations (support for dilation added to Res2Net)
* allow activation layer to be changed via act_layer arg
5 years ago
f96b3e5e92
InceptionResNetV2 torchscript compatible
5 years ago
19d93fe454
Add selecsls60 weights
5 years ago
0062c15fb0
Update checkpoint url with modelzoo compatible ones.
5 years ago
b5315e66b5
Streamline SelecSLS model without breaking checkpoint compat. Move cfg handling out of model class. Update feature/pooling behaviour to match current.
5 years ago
d59a756c16
Run PyCharm autoformat on selecsls and change mix cap variables and model names to all lower
5 years ago
fb3a0f4bb8
Merge pull request #65 from mehtadushy/selecsls
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Incorporate SelecSLS Models
5 years ago
19fc205a4d
Update comments on the new SE-ResNeXt26 models
5 years ago
acc3ed2b8c
Add EfficientNet-B3 weights, trained from scratch with RA.
5 years ago
2404361f62
correct asset paths
5 years ago
31939311f6
Added SelecSLS models
5 years ago
1f4498f217
Add ResNet deep tiered stem and model weights for seresnext26t_32x4d and seresnext26d_32x4d
5 years ago
32012a44fd
Added SelecSLS model
5 years ago
73b78459dc
Add update RandAugment MixNet-XL weights
5 years ago
ff421e5e09
New PyTorch trained EfficientNet-B2 weights with my RandAugment impl
5 years ago
3bef524f9c
Finish with HRNet, weights and models updated. Improve consistency in model classifier/global pool treatment.
5 years ago
6ca0828166
Update EfficientNet comments, MobileNetV3 non-TF create fns, fix factory arg checks, bump PyTorch version req to 1.2
5 years ago
eccbadca74
Update EfficientNet comments
5 years ago
902d32fb16
Renamed gen_efficientnet.py -> efficientnet.py
5 years ago
5a0a8de7e3
ResNet updates:
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* remove redundant GluonResNet model/blocks and use the code in ResNet for Gluon weights
* change SEModules back to using AdaptiveAvgPool instead of mean, PyTorch issue long fixed
5 years ago
a39cc43374
Bring EfficientNet and MobileNetV3 up to date with my gen-efficientnet repo
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* Split MobileNetV3 and EfficientNet model files and put builder and blocks in own files (getting too large)
* Finalize CondConv EfficientNet variant
* Add the AdvProp weights files and B8 EfficientNet model
* Refine the feature extraction module for EfficientNet and MobileNetV3
5 years ago
ad93347548
Initial HRNet classification model commit
5 years ago
2393708650
Missed stashing of out_indices in model
5 years ago
35e8f0c5e7
Fixup a few comments, add PyTorch version aware Flatten and finish as_sequential for GenEfficientNet
5 years ago
7ac6db4543
Missed activations.py
5 years ago
506df0e3d0
Add CondConv support for EfficientNet into WIP for GenEfficientNet Feature extraction setup
5 years ago
576d360f20
Bring in JIT version of optimized swish activation from gen_efficientnet as default (while working on feature extraction functionality here).
5 years ago
7b83e67f77
Pass drop connect arg through to EfficientNet models
5 years ago
0d58c50fb1
Add TF RandAug weights for B5/B7 EfficientNet models.
5 years ago
c099374771
Map pretrained checkpoint to cpu to avoid issue with some pretrained checkpoints still having CUDA tensors. Fixes #42
5 years ago
b93fcf0708
Add Facebook Research Semi-Supervised and Semi-Weakly Supervised ResNet model weights.
5 years ago
a9eb484835
Add memory efficient Swish impl
5 years ago
d3ba34ee7e
Fix Mobilenet V3 model name for sotabench. Minor res2net cleanup.
5 years ago
2680ad14bb
Add Res2Net and DLA to README
5 years ago
adbf770f16
Add Res2Net and DLA models w/ pretrained weights. Update sotabench.
5 years ago
aff194f42c
Merge pull request #32 from rwightman/opt
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More optimizer work
5 years ago
3d9c8a6489
Add support for new AMP checkpointing support w/ amp.state_dict
5 years ago
e9d2ec4d8e
Merge pull request #31 from rwightman/opt
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Optimizers and more
5 years ago
fac58f609a
Add RAdam, NovoGrad, Lookahead, and AdamW optimizers, a few ResNet tweaks and scheduler factory tweak.
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* Add some of the trendy new optimizers. Decent results but not clearly better than the standards.
* Can create a None scheduler for constant LR
* ResNet defaults to zero_init of last BN in residual
* add resnet50d config
5 years ago
81875d52a6
Update sotabench model list, add Mean-Max pooling DPN variants, disable download progress
5 years ago
73fbd97ed4
Add weights for my MixNet-XL creation, include README updates for EdgeTPU models
5 years ago
51a2375b0c
Experimenting with a custom MixNet-XL and MixNet-XXL definition
5 years ago
9ec6824bab
Finally got around to adding EdgeTPU EfficientNet variant
5 years ago
aeaaad7304
Merge pull request #24 from rwightman/gluon_xception
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Port Gluon Aligned Xception models
5 years ago
3b4868f6dc
A few more additions to Gluon Xception models to match interface of others.
5 years ago
4d505e0785
Add working Gluon Xception-65 model. Some cleanup still needed.
5 years ago
4e7a854dd0
Update helpers.py
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Fixing out of memory error by loading the checkpoint onto the CPU.
5 years ago
4fe2da558c
Add MixNet Small and Large PyTorch native weights (no same padding)
5 years ago
e879cf52fa
Update validation scores for new TF EfficientNet weights.
5 years ago
77e2e0c4e3
Add new auto-augmentation Tensorflow EfficientNet weights, incl B6 and B7 models. Validation scores still pending but looking good.
5 years ago
857f33015a
Add native PyTorch weights for MixNet-Medium with no SAME padding necessary. Remove unused block of code.
5 years ago
d4debe6597
Update version, results csv files, and move remaining dropbox weights to github
5 years ago
dfa9298b4e
Add MixNet ( https://arxiv.org/abs/1907.09595 ) with pretrained weights converted from Tensorflow impl
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* refactor 'same' convolution and add helper to use MixedConv2d when needed
* improve performance of 'same' padding for cases that can be handled statically
* add support for extra exp, pw, and dw kernel specs with grouping support to decoder/string defs for MixNet
* shuffle some args for a bit more consistency, a little less clutter overall in gen_efficientnet.py
5 years ago
d6ac5bbc48
EfficientNet and related cleanup
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* remove folded_bn support and corresponding untrainable tflite ported weights
* combine bn args into dict
* add inplace support to activations and use where possible for reduced mem on large models
6 years ago
3d9be78fc6
A bit more ResNet cleanup.
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* add inplace=True back
* minor comment improvements
* few clarity changes
6 years ago
33436fafad
Add weights for ResNeXt50d model
6 years ago
e78cd79073
Move ResNet additions for Gluon into main ResNet impl. Add ResNet-26 and ResNet-26d models with weights.
6 years ago
949b7a81c4
Fix typo in Densenet default resolutions
6 years ago
da52fcf78a
Add NASNet-Large model
6 years ago
6057496409
Register dpn107
6 years ago
a6878b5218
Fix DPN config keys that I broke
6 years ago
9b0070edc9
Add two comments back, fix typo
6 years ago
c3287aafb3
Slight improvement in EfficientNet-B2 native PyTorch weights
6 years ago
b8762cc67d
Model updates. Add my best ResNet50 weights top-1=78.47. Add some other torchvision weights.
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* Remove some models that don't exist as pretrained an likely never will (se)resnext152
* Add some torchvision weights as tv_ for models that I have added better weights for
* Add wide resnet recently added to torchvision along with resnext101-32x8d
* Add functionality to model registry to allow filtering on pretrained weight presence
6 years ago
c6b32cbe73
A number of tweaks to arguments, epoch handling, config
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* reorganize train args
* allow resolve_data_config to be used with dict args, not just arparse
* stop incrementing epoch before save, more consistent naming vs csv, etc
* update resume and start epoch handling to match above
* stop auto-incrementing epoch in scheduler
6 years ago
9d653b68a2
Make drop_connect rate scaling match official impl. Fixes #14
6 years ago
13c19e213d
Add native PyTorch EfficientNet B1 and B2 weights. Not quite where I want them, but hitting the brick wall and moving on to other projects...
6 years ago
a0275cfa2f
Fix arg positions in two entrypoint aliases
6 years ago
171c0b88b6
Add model registry and model listing fns, refactor model_factory/create_model fn
6 years ago
8512436436
Add instagram pretrained ResNeXt models from https://pytorch.org/hub/facebookresearch_WSL-Images_resnext/ , update README
6 years ago
87b92c528e
Some pretrianed URL changes
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* host some of Cadene's weights on github instead of .fr for speed
* add my old port of ensemble adversarial inception resnet v2
* switch to my TF port of normal inception res v2 and change FC layer back to 'classif' for compat with ens_adv
6 years ago
63961b36a2
Missed pnasnet entrypoint
6 years ago
6cc214bd7a
Consistency in model entrypoints
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* move pretrained entrypoint arg to first pos to be closer to torchvision/hub
* change DPN weight URLS to my github location
6 years ago
6fc886acaf
Remove all prints, change most to logging calls, tweak alignment of batch logs, improve setup.py
6 years ago
aa4354f466
Big re-org, working towards making pip/module as 'timm'
6 years ago
Ross Wightman