93a79a3dd9
Fix num_features in Sequencer
3 years ago
578d52e752
Add Sequencer
3 years ago
09e9f3defb
migrate azure blob for beit checkpoints
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## Motivation
We are going to use a new blob account to store the checkpoints.
## Modification
Modify the azure blob storage URLs for BEiT checkpoints.
3 years ago
52ac881402
Missed first_conv in latest seresnext 'D' default_cfgs
3 years ago
7629d8264d
Add two new SE-ResNeXt101-D 32x8d weights, one anti-aliased and one not. Reshuffle default_cfgs vs model entrypoints for resnet.py so they are better aligned.
3 years ago
8f0bc0591e
fix convnext args
3 years ago
c5a8e929fb
Add initial swinv2 tiny / small weights
3 years ago
f670d98cb8
Make a few more layers symbolically traceable (remove from FX leaf modules)
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* remove dtype kwarg from .to() calls in EvoNorm as it messed up script + trace combo
* BatchNormAct2d always uses custom forward (cut & paste from original) instead of super().forward. Fixes #1176
* BlurPool groups==channels, no need to use input.dim[1]
3 years ago
ec4e9aa5a0
Add ConvNeXt tiny and small pretrain in22k
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Add ConvNeXt tiny and small pretrain in22k from ConvNeXt repo:
06f7b05f92
3 years ago
575924ed60
Update test crop for new RegNet-V weights to match Y
3 years ago
1618527098
Add layer scale and parallel blocks to vision_transformer
3 years ago
c42be74621
Add attrib / comments about Swin-S3 (AutoFormerV2) weights
3 years ago
474ac906a2
Add 'head norm first' convnext_tiny_hnf weights
3 years ago
dc51334cdc
Fix pruned adapt for EfficientNet models that are now using BatchNormAct layers
3 years ago
024fc4d9ab
version 0.6.1 for master
3 years ago
e1e037ba52
Fix bad tuple typing fix that was on XLA branch bust missed on master merge
3 years ago
fe457c1996
Update SwinTransformerV2Cr post-merge, update with grad checkpointing / grad matcher
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* weight compat break, activate norm3 for final block of final stage (equivalent to pre-head norm, but while still in BLC shape)
* remove fold/unfold for TPU compat, add commented out roll code for TPU
* add option for end of stage norm in all stages
* allow weight_init to be selected between pytorch default inits and xavier / moco style vit variant
3 years ago
b049a5c5c6
Merge remote-tracking branch 'origin/master' into norm_norm_norm
3 years ago
9440a50c95
Merge branch 'mrT23-master'
3 years ago
d98aa47d12
Revert ml-decoder changes to model factory and train script
3 years ago
b20665d379
Merge pull request #1007 from qwertyforce/patch-1
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update arxiv link
3 years ago
61d3493f87
Fix hf-hub handling when hf-hub is config source
3 years ago
5f47518f27
Fix pit implementation to be clsoer to deit/levit re distillation head handling
3 years ago
0862e6ebae
Fix correctness of some group matching regex (no impact on result), some formatting, missed forward_head for resnet
3 years ago
94bcdebd73
Add latest weights trained on TPU-v3 VM instances
3 years ago
0557c8257d
Fix bug introduced in non layer_decay weight_decay application. Remove debug print, fix arg desc.
3 years ago
372ad5fa0d
Significant model refactor and additions:
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* All models updated with revised foward_features / forward_head interface
* Vision transformer and MLP based models consistently output sequence from forward_features (pooling or token selection considered part of 'head')
* WIP param grouping interface to allow consistent grouping of parameters for layer-wise decay across all model types
* Add gradient checkpointing support to a significant % of models, especially popular architectures
* Formatting and interface consistency improvements across models
* layer-wise LR decay impl part of optimizer factory w/ scale support in scheduler
* Poolformer and Volo architectures added
3 years ago
1420c118df
Missed comitting outstanding changes to default_cfg keys and test exclusions for swin v2
3 years ago
c6e4b7895a
Swin V2 CR impl refactor.
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* reformat and change some naming so closer to existing timm vision transformers
* remove typing that wasn't adding clarity (or causing torchscript issues)
* support non-square windows
* auto window size adjust from image size
* post-norm + main-branch no
3 years ago
67d140446b
Fix bug in classification head
3 years ago
29add820ac
Refactor (back to relative imports)
3 years ago
74a04e0016
Add parameter to change normalization type
3 years ago
2a4f6c13dd
Create model functions
3 years ago
87b4d7a29a
Add get and reset classifier method
3 years ago
ff5f6bcd6c
Check input resolution
3 years ago
81bf0b4033
Change parameter names to match Swin V1
3 years ago
f227b88831
Add initials (CR) to model and file
3 years ago
90dc74c450
Add code from https://github.com/ChristophReich1996/Swin-Transformer-V2 and change docstring style to match timm
3 years ago
2c3870e107
semobilevit_s for good measure
3 years ago
58ba49c8ef
Add MobileViT models (w/ ByobNet base). Close #1038 .
3 years ago
5f81d4de23
Move DeiT to own file, vit getting crowded. Working towards fixing #1029 , make pooling interface for transformers and mlp closer to convnets. Still working through some details...
3 years ago
95cfc9b3e8
Merge remote-tracking branch 'origin/master' into norm_norm_norm
3 years ago
abc9ba2544
Transitioning default_cfg -> pretrained_cfg. Improving handling of pretrained_cfg source (HF-Hub, files, timm config, etc). Checkpoint handling tweaks.
3 years ago
07379c6d5d
Add vit_base2_patch32_256 for a model between base_patch16 and patch32 with a slightly larger img size and width
3 years ago
83b40c5a58
Last batch of small model weights (for now). mobilenetv3_small 050/075/100 and updated mnasnet_small with lambc/lamb optimizer.
3 years ago
1aa617cb3b
Add AvgPool2d anti-aliasing support to ResNet arch (as per OpenAI CLIP models), add a few blur aa models as well
3 years ago
010b486590
Add Dino pretrained weights (no head) for vit models. Add support to tests and helpers for models w/ no classifier (num_classes=0 in pretrained cfg)
3 years ago
738a9cd635
unbiased=False for torch.var_mean path of ConvNeXt LN. Fix #1090
3 years ago
e0c4eec4b6
Default conv_mlp to False across the board for ConvNeXt, causing issues on more setups than it's improving right now...
3 years ago
b669f4a588
Add ConvNeXt 22k->1k fine-tuned and 384 22k-1k fine-tuned weights after testing
3 years ago
okojoalg
Li Dong
Ross Wightman
SeeFun
Ross Wightman
Christoph Reich