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
4e4b863b15
Missed norm.py
4 years ago
ce62f96d4d
ByoaNet with bottleneck transformer, lambda resnet, and halo net experiments
4 years ago
a5310a3451
Merge remote-tracking branch 'origin/benchmark-fixes-vit_hybrids' into pit_and_vit_update
4 years ago
cf5fec5047
Cleanup experimental vit weight init a bit
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
f57db99101
Update README, fix iabn pip version print.
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
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
94ca140b67
update collections.abc import
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
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
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
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
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
e90edce438
Support native silu activation (aka swish). An optimized ver is available in PyTorch 1.7.
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
e8ca45854c
More models in sotabench, more control over sotabench run, dataset filename extraction consistency
4 years ago
80c9d9cc72
Add 'fast' global pool option, remove redundant SEModule from tresnet, normal one is now 'fast'
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
fc8b8afb6f
Fix a silly bug in Sample version of EvoNorm missing x* part of swish, update EvoNormBatch to accumulated unbiased variance.
4 years ago
b1f1a54de9
More uniform treatment of classifiers across all models, reduce code duplication.
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
7ba5a384d3
Add ReXNet w/ remapped weights, feature support
4 years ago
298fba09ac
Back out some activation hacks trialing upcoming pytorch changes
5 years ago
3b9004bef9
Lots of changes to model creation helpers, close to finalizing feature extraction / interfaces
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:
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* 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
d0113f9cdb
Fix a few issues that came up in tests
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
78fa0772cc
Leverage python hierachical logger
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with this update one can tune the kind of logs generated by timm but
training and inference traces are unchanged
5 years ago
4ddde1d3a4
Fix two regressions
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
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* 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
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
208e7912f7
Missed one of the abalation model entrypoints, update README
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
8d8677e03b
Fix #139 . Broken SKResNets after BlurPool addition, as a plus, SKResNets support AA now too.
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
e3a98171b2
Remove some CRLF that made it into TResNet merge
5 years ago
0004f37d25
Some TResNet cleanup.
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* 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
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
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'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
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clean up code for PR
5 years ago
3a287a6e76
Create blurpool.py
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Initial implementation of blur layer.
currently tests as correct against Downsample of original github
5 years ago
c60069c1eb
Annotate types on drop fns to avoid torchscript error
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
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
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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
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
4defbbbaa8
Fix module name mistake, start layers sub-package
5 years ago
Ross Wightman