6f103a442b
Add convnext_nano weights, 80.8 @ 224, 81.5 @ 288
2 years ago
4042a94f8f
Add weights for two 'Edge' block (3x3->1x1) variants of CS3 networks.
2 years ago
c8f69e04a9
Merge pull request #1365 from veritable-tech/fix-resize-pos-embed
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Take `no_emb_class` into account when calling `resize_pos_embed`
2 years ago
0b64117592
Take `no_emb_class` into account when calling `resize_pos_embed`
2 years ago
56c3a84db3
Update type hint for `register_notrace_module`
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register_notrace_module is used to decorate types (i.e. subclasses of nn.Module).
It is not called on module instances.
2 years ago
1b278136c3
Change models with mean 0,0,0 std 1,1,1 from int to float for consistency as mentioned in #1355
2 years ago
909705e7ff
Remove some redundant requires_grad=True from nn.Parameter in third party code
2 years ago
c5e0d1c700
Add dilation support to convnext, allows output_stride=8 and 16 use. Fix #1341
2 years ago
dc376e3676
Ensure all model entrypoint fn default to `pretrained=False` (a few didn't)
2 years ago
23b102064a
Add cs3sedarknet_x weights w/ 82.65 @ 288 top1. Add 2 cs3 edgenet models (w/ 3x3-1x1 block), remove aa from cspnet blocks (not needed)
2 years ago
05313940e2
Add cs3darknet_x, cs3sedarknet_l, and darknetaa53 weights from TPU sessions. Move SE btwn conv1 & conv2 in DarkBlock. Improve SE/attn handling in Csp/DarkNet. Fix leaky_relu bug on older csp models.
2 years ago
51cca82aa1
👽 use hf_hub_download instead of cached_download
2 years ago
a45b4bce9a
x and xx small edgenext models do benefit from larger test input size
2 years ago
a8e34051c1
Unbreak gamma remap impacting beit checkpoint load, version bump to 0.6.4
2 years ago
a1cb25066e
Add edgnext_small_rw weights trained with swin like recipe. Better than original 'small' but not the recent 'USI' distilled weights.
2 years ago
7c7ecd2492
Add --use-train-size flag to force use of train input_size (over test input size) for validation. Default test-time pooling to use train input size (fixes issues).
2 years ago
ce65a7b29f
Update vit_relpos w/ some additional weights, some cleanup to match recent vit updates, more MLP log coord experiments.
2 years ago
58621723bd
Add CrossStage3 DarkNet (cs3) weights
2 years ago
db0cee9910
Refactor cspnet configuration using dataclasses, update feature extraction for new cs3 variants.
2 years ago
eca09b8642
Add MobileVitV2 support. Fix #1332 . Move GroupNorm1 to common layers (used in poolformer + mobilevitv2). Keep ol custom ConvNeXt LayerNorm2d impl as LayerNormExp2d for reference.
2 years ago
06307b8b41
Remove experimental downsample in block support in ConvNeXt. Experiment further before keeping it in.
2 years ago
7d4b3807d5
Support DeiT-3 (Revenge of the ViT) checkpoints. Add non-overlapping (w/ class token) pos-embed support to vit.
3 years ago
d0c5bd5722
Rename cs2->cs3 for darknets. Fix features_only for cs3 darknets.
3 years ago
d765305821
Remove first_conv for resnetaa50 def
3 years ago
dd9b8f57c4
Add feature_info to edgenext for features_only support, hopefully fix some fx / test errors
3 years ago
377e9bfa21
Add TPU trained darknet53 weights. Add mising pretrain_cfg for some csp/darknet models.
3 years ago
c170ba3173
Add weights for resnet10t, resnet14t, and resnetaa50 models. Fix #1314
3 years ago
188c194b0f
Left some experiment stem code in convnext by mistake
3 years ago
6064d16a2d
Add initial EdgeNeXt import. Significant cleanup / reorg (like ConvNeXt). Fix #1320
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* edgenext refactored for torchscript compat, stage base organization
* slight refactor of ConvNeXt to match some EdgeNeXt additions
* remove use of funky LayerNorm layer in ConvNeXt and just use nn.LayerNorm and LayerNorm2d (permute)
3 years ago
7a9c6811c9
Add eps arg to LayerNorm2d, add 'tf' (tensorflow) variant of trunc_normal_ that applies scale/shift after sampling (instead of needing to move a/b)
3 years ago
82c311d082
Add more experimental darknet and 'cs2' darknet variants (different cross stage setup, closer to newer YOLO backbones) for train trials.
3 years ago
a050fde5cd
Add resnet10t (basic block) and resnet14t (bottleneck) with 1,1,1,1 repeats
3 years ago
e6d7df40ec
no longer a point using kwargs for pretrain_cfg resolve, just pass explicit arg
3 years ago
07d0c4ae96
Improve repr for DropPath module
3 years ago
e27c16b8a0
Remove unecessary code for synbn guard
3 years ago
0da3c9ebbf
Remove SiLU layer in default args that breaks import on old old PyTorch
3 years ago
7d657d2ef4
Improve resolve_pretrained_cfg behaviour when no cfg exists, warn instead of crash. Improve usability ex #1311
3 years ago
879df47c0a
Support BatchNormAct2d for sync-bn use. Fix #1254
3 years ago
4b30bae67b
Add updated vit_relpos weights, and impl w/ support for official swin-v2 differences for relpos. Add bias control support for MLP layers
3 years ago
d4c0588012
Remove persistent buffers from Swin-V2. Change SwinV2Cr cos attn + tau/logit_scale to match official, add ckpt convert, init_value zeros resid LN weight by default
3 years ago
27c42f0830
Fix torchscript use for offician Swin-V2, add support for non-square window/shift to WindowAttn/Block
3 years ago
c0211b0bf7
Swin-V2 test fixes, typo
3 years ago
9a86b900fa
Official SwinV2 models
3 years ago
d07d015173
Merge pull request #1249 from okojoalg/sequencer
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Add Sequencer
3 years ago
39b725e1c9
Fix tests for rank-4 output where feature channels dim is -1 (3) and not 1
3 years ago
78a32655fa
Fix poolformer group_matcher to merge proj downsample with previous block, support coarse
3 years ago
d79f3d9d1e
Fix torchscript use for sequencer, add group_matcher, forward_head support, minor formatting
3 years ago
37b6920df3
Fix group_matcher regex for regnet.py
3 years ago
93a79a3dd9
Fix num_features in Sequencer
3 years ago
578d52e752
Add Sequencer
3 years ago
Ross Wightman