ad94d737b7
Add support to ConvNextBlock for downsample and channel expansion to improve stand alone use. Fix #1699
2023-03-13 14:06:24 -07:00
3a636eee71
Fix #1713 missed assignement in 3-aug level fn, fix few other minor lint complaints in auto_augment.py
2023-03-11 14:32:23 -08:00
992bf7c3d4
chore: Modify the MobileVitV2Block to be coreml exportable
...
based on is_exportable() set variable controlling behaviour of the block
CoreMLTools support im2col from 6.2 version, unfortunately col2im
is still not supported.
Tested with exporting to ONNX, Torchscript, CoreML, and TVM.
2023-03-03 09:38:24 +01:00
4b8cfa6c0a
Add convnext_xxlarge CLIP image tower weights, version 0.8.15dev0
2023-02-26 21:51:48 -08:00
f9b56a1bfa
Version 0.8.14dev0
2023-02-26 13:38:51 -08:00
1c13ef7b46
Add default norm_eps=1e-5 for convnext_xxlarge, improve kwarg merging for all convnext models
2023-02-26 12:11:49 -08:00
a5b01ec04e
Add type annotations to _registry.py
...
Description
Add type annotations to _registry.py so that they will pass mypy
--strict.
Comment
I was reading the code and felt that this module would be easier to
understand with type annotations. Therefore, I went ahead and added the
annotations.
The idea with this PR is to start small to see if we can align on _how_
to annotate types. I've seen people in the past disagree on how strictly
to annotate the code base, so before spending too much time on this, I
wanted to check if you agree, Ross.
Most of the added types should be straightforward. Some notes on the
non-trivial changes:
- I made no assumption about the fn passed to register_model, but maybe
the type could be stricter. Are all models nn.Modules?
- If I'm not mistaken, the type hint for get_arch_name was incorrect
- I had to add a # type: ignore to model.__all__ = ...
- I made some minor code changes to list_models to facilitate the
typing. I think the changes should not affect the logic of the function.
- I removed list from list(sorted(...)) because sorted returns always a
list.
2023-02-22 09:19:30 -08:00
47f1de9bec
Version bump
2023-02-20 10:17:10 -08:00
4d9c3ae2fb
Add laion2b 320x320 ConvNeXt-Large CLIP weights
2023-02-18 16:34:03 -08:00
d0b45c9b4d
Make safetensor import option for now. Improve avg/clean checkpoints ext handling a bit (more consistent).
2023-02-18 16:06:42 -08:00
7d9e321b76
Improve tracing of window attn models with simpler reshape logic
2023-02-17 07:59:06 -08:00
2e38d53dca
Remove dead line
2023-02-16 16:57:42 -08:00
f77c04ff36
Torchscript fixes/hacks for rms_norm, refactor ParallelScalingBlock with manual combination of input projections, closer paper match
2023-02-16 16:57:42 -08:00
122621daef
Add Final annotation to attn_fas to avoid symbol lookup of new scaled_dot_product_attn fn on old PyTorch in jit
2023-02-16 16:57:42 -08:00
621e1b2182
Add ideas from 'Scaling ViT to 22-B Params', testing PyTorch 2.0 fused F.scaled_dot_product_attention impl in vit, vit_relpos, maxxvit / coatnet.
2023-02-16 16:57:42 -08:00
a3d528524a
Version 0.8.12dev0
2023-02-16 16:27:29 -08:00
a09d403c24
changed warning to info
2023-02-16 16:20:31 -08:00
8470e29541
Add support to load safetensors weights
2023-02-16 16:20:31 -08:00
f35d6ea57b
Add multi-tensor (foreach) version of Lion in style of upcoming PyTorch 2.0 optimizers
2023-02-16 15:48:00 -08:00
709d5e0d9d
Add Lion optimizer
2023-02-14 23:55:05 -08:00
624266148d
Remove unused imports from _hub helpers
2023-02-09 17:47:26 -08:00
2cfff0581b
Add grad_checkpointing support to features_only, test in EfficientDet.
2023-02-09 17:45:40 -08:00
45af496197
Version 0.8.11dev0
2023-02-08 08:29:29 -08:00
9c14654a0d
Improve support for custom dataset label name/description through HF hub export, via pretrained_cfg
2023-02-08 08:29:20 -08:00
497be8343c
Update README and version
2023-02-06 23:43:14 -08:00
0d33127df2
Add 384x384 convnext_large_mlp laion2b fine-tune on in1k
2023-02-06 22:01:04 -08:00
7a0bd095cb
Update model prune loader to use pkgutil
2023-02-06 17:45:16 -08:00
0f2803de7a
Move ImageNet metadata (aka info) files to timm/data/_info. Add helper classes to make info available for labelling. Update inference.py for first use.
2023-02-06 17:45:03 -08:00
7a13be67a5
Update version.py
2023-02-05 10:06:15 -08:00
13acac8c5e
Update head metadata for effformerv2
2023-02-04 23:11:51 -08:00
8682528096
Add first conv metadata for efficientformer_v2
2023-02-04 23:02:02 -08:00
72fba669a8
is_scripting() guard on checkpoint_seq
2023-02-04 14:21:49 -08:00
95ec255f7f
Finish timm mode api for efficientformer_v2, add grad checkpointing support to both efficientformers
2023-02-03 21:21:23 -08:00
9d03c6f526
Merge remote-tracking branch 'origin/main' into levit_efficientformer_redux
2023-02-03 14:47:01 -08:00
086bd55a94
Add EfficientFormer-V2, refactor EfficientFormer and Levit for more uniformity across the 3 related arch. Add features_out support to levit conv models and efficientformer_v2. All weights on hub.
2023-02-03 14:12:29 -08:00
2cb2699dc8
Apply fix from #1649 to main
2023-02-03 11:28:57 -08:00
b3042081b4
Add laion -> in1k fine-tuned base and large_mlp weights for convnext
2023-02-03 10:58:02 -08:00
316bdf8955
Add mlp head support for convnext_large, add laion2b CLIP weights, prep fine-tuned weight tags
2023-02-01 08:27:02 -08:00
6f28b562c6
Factor NormMlpClassifierHead from MaxxViT and use across MaxxViT / ConvNeXt / DaViT, refactor some type hints & comments
2023-01-27 14:57:01 -08:00
9a53c3f727
Finalize DaViT, some formatting and modelling simplifications (separate PatchEmbed to Stem + Downsample, weights on HF hub.
2023-01-27 13:54:04 -08:00
fb717056da
Merge remote-tracking branch 'upstream/main'
2023-01-26 10:49:15 -08:00
2bbc26dd82
version 0.8.8dev0
2023-01-25 18:02:48 -08:00
64667bfa0e
Add 'gigantic' vit clip variant for feature extraction and future fine-tuning
2023-01-25 18:02:10 -08:00
c2822568ec
Update version to 0.8.7dev0
2023-01-20 15:01:10 -08:00
36989cfae4
Factor out readme generation in hub helper, add more readme fields
2023-01-20 14:49:40 -08:00
32f252381d
Change order of checkpoitn filtering fn application in builder, try dict, model variant first
2023-01-20 14:48:54 -08:00
e9f1376cde
Cleanup resolve data config fns, add 'model' variant that takes model as first arg, make 'args' arg optional in original fn
2023-01-20 14:47:55 -08:00
bed350f5e5
Push all MaxxViT weights to HF hub, cleanup impl, add feature map extraction support and prompote to 'std' architecture. Fix norm head for proper embedding / feat map output. Add new in12k + ft 1k weights.
2023-01-20 14:45:25 -08:00
ca38e1e73f
Update ClassifierHead module, add reset() method, update in_chs -> in_features for consistency
2023-01-20 14:44:05 -08:00
8ab573cd26
Add convnext_tiny and convnext_small 384x384 fine-tunes of in12k weights, fix pool size for laion CLIP convnext weights
2023-01-20 14:40:16 -08:00
Ross Wightman
Piotr Sebastian Kluska
Benjamin Bossan
testbot
Ross Wightman
Fredo Guan