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
f6b56602f9
fix test_model_default_cfgs
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
9ecd16bd7b
Add new seresnet50 (non-legacy) model weights, 80.274 top-1
4 years ago
6c17d57a2c
Fix some attributions, add copyrights to some file docstrings
4 years ago
3b9004bef9
Lots of changes to model creation helpers, close to finalizing feature extraction / interfaces
4 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
4 years ago
a66df5fb91
More model feature extraction support, start to deprecate senet.py, dilations added to regnet, add proper aligned xception
4 years ago
7729f40dca
Fix another bug, update all gluon resnet models to use new creation method (feature support)
4 years ago
d0113f9cdb
Fix a few issues that came up in tests
4 years ago
d23a2697d0
Working on feature extraction, interfaces refined, a number of models working, some in progress.
4 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
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
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
0834fbc01c
Move pruned model adapt strings to separate txt files. A few minor formatting alignment tweaks.
5 years ago
07f19dd699
added eca resnet
5 years ago
06a50a94a8
Fix minor typos in create_attn.py and resnet.py
...
'eca'->'ceca'
and
doest not-> does not
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
...
1. add ResNet argument blur=''
2. implement blur for maxpool and strided convs in downsampling blocks
5 years ago
5a16c533ff
Add better resnext50_32x4d weights trained by andravin
5 years ago
f1d5f8a6c4
Update comments for Selective Kernel and DropBlock/Path impl, add skresnet34 weights
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
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
db91ba053b
EcaModule(CamelCase)
...
CamelCased EcaModule.
Renamed all instances of ecalayer to EcaModule.
eca_module.py->EcaModule.py
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
a9d2424fd1
Add separate zero_init_last_bn function to support more block variety without a mess
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
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
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
a28117ea46
Add tiered narrow ResNet (tn) and weights for seresnext26tn_32x4d
5 years ago
53001dd292
ResNet / Res2Net additions:
...
* 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
19fc205a4d
Update comments on the new SE-ResNeXt26 models
5 years ago
1f4498f217
Add ResNet deep tiered stem and model weights for seresnext26t_32x4d and seresnext26d_32x4d
5 years ago
3bef524f9c
Finish with HRNet, weights and models updated. Improve consistency in model classifier/global pool treatment.
5 years ago
5a0a8de7e3
ResNet updates:
...
* 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
b93fcf0708
Add Facebook Research Semi-Supervised and Semi-Weakly Supervised ResNet model weights.
5 years ago
adbf770f16
Add Res2Net and DLA models w/ pretrained weights. Update sotabench.
5 years ago
fac58f609a
Add RAdam, NovoGrad, Lookahead, and AdamW optimizers, a few ResNet tweaks and scheduler factory tweak.
...
* 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
3d9be78fc6
A bit more ResNet cleanup.
...
* add inplace=True back
* minor comment improvements
* few clarity changes
5 years ago
33436fafad
Add weights for ResNeXt50d model
5 years ago
Ross Wightman