1334598462
Add support back to EfficientNet to disable head_conv / bn2 so mobilnetv1 can be implemented properly
2024-07-08 13:51:26 -07:00
800405d941
Add conv_large mobilenetv3 aa/blur model defs
2024-07-08 13:50:05 -07:00
f81b094aaa
Add 'qkv_bias_separate' flag for EVA/beit/swinv2 attn modules to allow an override for easy quantization wrappers. Fix #2098
2024-07-08 13:48:38 -07:00
83c2c2f0c5
Add 'Maybe' PIL / image tensor conversions in case image alread in tensor format
2024-07-08 13:43:51 -07:00
c01a47c9e7
Fix typo in type annotations in timm.models.hrnet
2024-07-08 00:53:16 +02:00
197c10463b
Fix jit.script breaking with features_fx
2024-06-28 03:58:51 +00:00
b751da692d
Add latest ix (xavier init for mqa) hybrid medium & large weights for MobileNetV4
2024-06-24 13:49:55 -07:00
d4d4d84fda
Dev version 1.0.8.dev0
2024-06-24 11:34:13 -07:00
f8342a045a
Merge pull request #2213 from huggingface/florence2
...
Fix #2212 map florence2 image tower to davit with a few changes
2024-06-24 11:01:08 -07:00
c33a001397
Fix typo
2024-06-24 21:54:38 +09:00
02d0f27721
cleanup davit padding
2024-06-22 12:06:46 -07:00
c715c724e7
Fix tracing by removing float cast, should end up float anyways
2024-06-22 08:35:30 -07:00
fb58a73033
Fix #2212 map florence2 image tower to davit with a few changes
2024-06-21 15:31:29 -07:00
b28945ff05
Version 1.0.7, prep for release
2024-06-18 16:19:43 -07:00
fb13e6385e
Merge pull request #2203 from huggingface/more_mobile
...
Add mobilenet edgetpu defs for exp, add ol mobilenet v1 back for comp…
2024-06-18 15:20:01 -07:00
16e082e1c2
Add mobilenetv4 hybrid-large weights
2024-06-17 11:08:31 -07:00
e41125cc83
Merge pull request #2209 from huggingface/fcossio-vit-maxpool
...
ViT pooling refactor
2024-06-17 07:51:12 -07:00
a22466852d
Add 2400 epoch mobilenetv4 small weights, almost at paper, rounds to 73.8
2024-06-16 10:51:00 -07:00
b1a6f4a946
Some missed reset_classifier() type annotations
2024-06-16 10:39:27 -07:00
71101ebba0
Refactor vit pooling to add more reduction options, separately callable
2024-06-14 23:16:58 -07:00
a0bb5b4a44
Missing stem_kernel_size argument in EfficientNetFeatures
2024-06-14 13:39:31 -07:00
9567cf6d84
Feature: add option global_pool='max' to VisionTransformer
...
Most of the CNNs have a max global pooling option. I would like to extend ViT to have this option.
2024-06-14 15:24:54 +02:00
9613c76844
Add mobilenet edgetpu defs for exp, add ol mobilenet v1 back for completeness / comparison
2024-06-13 17:33:04 -07:00
22de845add
Prepping for final MobileCLIP weight locations ( #2199 )
...
* Prepping for final MobileCLIP weight locations
* Update weight locations to coreml-projects
* Update mobileclip weight locations with final apple org location
2024-06-13 16:55:49 -07:00
575978ba55
Add mnv4_conv_large 384x384 weight location
2024-06-13 12:58:04 -07:00
7b5f17d1bd
Update README.md, bump dev version 1.0.6
2024-06-12 12:35:44 -07:00
e42e453128
Fix mmnv4 conv_large weight link, reorder mnv4 pretrained cfg for proper precedence
2024-06-12 11:16:49 -07:00
7b0a5321cb
Merge pull request #2198 from huggingface/openai_clip_resnet
...
Mapping OpenAI CLIP Modified ResNet weights -> ByobNet.
2024-06-12 09:33:30 -07:00
57adc1acc8
Fix rotary embed version of attn pool. Bit of cleanup/naming
2024-06-11 23:49:17 -07:00
cdc7bcea69
Make 2d attention pool modules compatible with head interface. Use attention pool in CLIP ResNets as head. Make separate set of GAP models w/ avg pool instead of attn pool.
2024-06-11 21:32:07 -07:00
c63da1405c
Pretrained cfg name mismatch
2024-06-11 21:16:54 -07:00
88efca1be2
First set of MobileNetV4 weights trained in timm
2024-06-11 18:53:01 -07:00
30ffa152de
Fix load of larger ResNet CLIP models, experimenting with making AttentionPool *the* head, seems to fine-tune better, one less layer.
2024-06-10 12:07:14 -07:00
5e9ff5798f
Adding pos embed resize fns to FX autowrap exceptions
2024-06-10 12:06:47 -07:00
f0fb471b26
Remove separate ConvNormActAa class, merge with ConvNormAct
2024-06-10 12:05:35 -07:00
5efa15b2a2
Mapping OpenAI CLIP Modified ResNet weights -> ByobNet. Improve AttentionPool2d layers. Fix #1731
2024-06-09 16:54:48 -07:00
7702d9afa1
ViTamin in_chans !=3 weight load fix
2024-06-07 20:39:23 -07:00
66a0eb4673
Experimenting with tiny test models, how small can they go and be useful for regression tests?
2024-06-07 16:09:25 -07:00
5ee06760dc
Fix classifier input dim for mnv3 after last changes
2024-06-07 13:53:13 -07:00
a5a2ad2e48
Fix consistency, testing for forward_head w/ pre_logits, reset_classifier, models with pre_logits size != unpooled feature size
...
* add test that model supports forward_head(x, pre_logits=True)
* add head_hidden_size attr to all models and set differently from num_features attr when head has hidden layers
* test forward_features() feat dim == model.num_features and pre_logits feat dim == self.head_hidden_size
* more consistency in reset_classifier signature, add typing
* asserts in some heads where pooling cannot be disabled
Fix #2194
2024-06-07 13:53:00 -07:00
4535a5412a
Change default serialization for push_to_hf_hub to 'both'
2024-06-07 13:40:31 -07:00
5cce2185e1
Update version.py
2024-06-07 13:13:23 -07:00
7ccb10ebff
Disable efficient_builder debug flag
2024-06-06 21:50:27 -07:00
ad026e6e33
Fix in_chans switching on create
2024-06-06 17:56:14 -07:00
fc1b66a51d
Fix first conv name for mci vit-b
2024-06-06 13:42:26 -07:00
88a1006e02
checkpoint filter fns with consistent name, add mobileclip-b pretrained cfgs
2024-06-06 12:38:52 -07:00
7d4ada6d16
Update ViTamin model defs
2024-06-06 09:16:43 -07:00
cc8a03daac
Add ConvStem and MobileCLIP hybrid model for B variant. Add full norm disable support to ConvNormAct layers
2024-06-06 09:15:27 -07:00
3c9d8e5b33
Merge remote-tracking branch 'origin/efficientnet_x' into fastvit_mobileclip
2024-06-05 17:35:15 -07:00
5756a81c55
Merge remote-tracking branch 'origin/Beckschen-vitamin' into fastvit_mobileclip
2024-06-05 15:20:54 -07:00
58591a97f7
Enable features_only properly
2024-06-04 16:57:16 -07:00
1b66ec7cf3
Fixup ViTamin, add hub weight reference
2024-06-03 17:14:03 -07:00
b2c0aeb0ec
Merge branch 'main' of https://github.com/Beckschen/pytorch-image-models into Beckschen-vitamin
2024-06-02 14:16:30 -07:00
7f96538052
Add missing lkc act for mobileclip fastvits
2024-05-31 11:59:51 -07:00
a503639bcc
Add mobileclip fastvit model defs, support extra SE. Add forward_intermediates API to fastvit
2024-05-30 10:17:38 -07:00
5fa6efa158
Add anti-aliasing support to mobilenetv3 and efficientnet family models. Update MobileNetV4 model defs, resolutions. Fix #599
...
* create_aa helper function centralized for all timm uses (resnet, convbnact helper)
* allow BlurPool w/ pre-defined channels (expand)
* mobilenetv4 UIB block using ConvNormAct layers for improved clarity, esp with AA added
* improve more mobilenetv3 and efficientnet related type annotations
2024-05-27 22:06:22 -07:00
5dce710101
Add vit_little in12k + in12k-ft-in1k weights
2024-05-27 14:56:03 -07:00
3c0283f9ef
Fix reparameterize for NextViT. Fix #2187
2024-05-27 14:48:58 -07:00
4ff7c25766
Pass layer_scale_init_value to Mnv3Features module
2024-05-24 16:44:50 -07:00
a12b72b5c4
Fix missing head_norm arg pop for feature model
2024-05-24 15:50:34 -07:00
7fe96e7a92
More MobileNet-v4 fixes
...
* missed final norm after post pooling 1x1 PW head conv
* improve repr of model by flipping a few modules to None when not used, nn.Sequential for MultiQueryAttention query/key/value/output
* allow layer scaling to be enabled/disabled at model variant level, conv variants don't use it
2024-05-24 15:09:29 -07:00
28d76a97db
Mixed up kernel size for last blocks in mnv4-conv-small
2024-05-24 11:50:42 -07:00
0c6a69e7ef
Add comments to MNV4 model defs with block variants
2024-05-23 15:54:05 -07:00
cb33956b20
Fix some mistakes in mnv4 model defs
2024-05-23 14:24:32 -07:00
70176a2dae
torchscript typing fixes
2024-05-23 11:43:05 -07:00
2a1a6b1236
Adding missing attention2d.py
2024-05-23 11:06:32 -07:00
cee79dada0
Merge remote-tracking branch 'origin/main' into efficientnet_x
2024-05-23 11:01:39 -07:00
6a8bb03330
Initial MobileNetV4 pass
2024-05-23 10:49:18 -07:00
e748805be3
Add regex matching support to AttentionExtract. Add return_dict support to graph extractors and use returned output in AttentionExtractor
2024-05-22 14:33:39 -07:00
44f72c04b3
Change node/module name matching for AttentionExtract so it keeps outputs in order. #1232
2024-05-22 13:45:25 -07:00
84cb225ecb
Add in12k + 12k_ft_in1k vit_medium weights
2024-05-20 15:52:46 -07:00
4634c3e134
Version 1.0.4.dev0
2024-05-20 15:52:27 -07:00
7a2ad6bce1
Add link to model weights on Hugging Face
2024-05-17 06:51:35 -04:00
530fb49e7e
Add link to model weights on Hugging Face
2024-05-17 06:48:59 -04:00
9b11801cb4
Credit earlier work with the same idea.
...
Hi, this earlier work has the same name and idea behind this layer. It could be useful for readers to keep both links here if they want to see the effects of introducing this layer on a very different domain. 😄
2024-05-16 22:50:34 +02:00
cb0e4391be
Release 1.0.3
2024-05-15 11:06:22 -07:00
27fd2f35d3
Merge pull request #2181 from huggingface/Delaunay-dist-backend
...
Delaunay dist backend flag
2024-05-15 10:00:59 -07:00
e57625e814
Tweak dist_backend to use device_type (before possible :)
2024-05-15 08:49:25 -07:00
6ca92570f7
Merge branch 'patch-1' of https://github.com/Delaunay/pytorch-image-models into Delaunay-dist-backend
2024-05-15 08:40:58 -07:00
cd0e7b11ff
Merge pull request #2180 from yvonwin/main
...
Remove a duplicate function in mobilenetv3.py
2024-05-15 07:54:17 -07:00
83aee5c28c
Add explicit GAP (avg pool) variants of other SigLIP models.
2024-05-15 07:53:19 -07:00
58f2f79b04
Remove a duplicate function in mobilenetv3.py: `_gen_lcnet` is repeated in mobilenetv3.py.Remove the duplicate code.
2024-05-15 17:59:34 +08:00
7b3b11b63f
Support loading of paligemma weights into GAP variants of SigLIP ViT. Minor tweak to npz loading for packed transformer weights.
2024-05-14 15:44:37 -07:00
df304ffbf2
the dataclass init needs to use the default factory pattern, according to Ross
2024-05-14 15:10:05 -04:00
cc5f2f6f70
version 1.0.2dev0
2024-05-13 15:25:15 -07:00
3bfd036b58
Add normalize flag to transforms factory, allow return of non-normalized native dtype torch.Tensors
2024-05-13 15:23:25 -07:00
a69863ad61
Merge pull request #2156 from huggingface/hiera
...
WIP Hiera implementation.
2024-05-13 14:58:12 -07:00
8848dad362
Update distributed.py
2024-05-13 16:55:42 -04:00
f7aa0a1a71
Add missing vit_wee weight
2024-05-13 12:05:47 -07:00
7a4e987b9f
Hiera weights on hub
2024-05-13 11:43:22 -07:00
23f09af08e
Merge branch 'main' into efficientnet_x
2024-05-12 21:31:08 -07:00
c838c4233f
Add typing to reset_classifier() on other models
2024-05-12 11:12:00 -07:00
3e03b2bf3f
Fix a few more hiera API issues
2024-05-12 11:11:45 -07:00
211d18d8ac
Move norm & pool into Hiera ClassifierHead. Misc fixes, update features_intermediate() naming
2024-05-11 23:37:35 -07:00
2ca45a4ff5
Merge remote-tracking branch 'upstream/main' into hiera
2024-05-11 15:43:05 -07:00
1d3ab176bc
Remove debug / staging code
2024-05-10 22:16:34 -07:00
aa4d06a11c
sbb vit weights on hub, testing
2024-05-10 17:15:01 -07:00
3582ca499e
Prepping weight push, benchmarking.
2024-05-10 14:14:06 -07:00
2bfa5e5d74
Remove JIT activations, take jit out of ME activations. Remove other instances of torch.jit.script. Breaks torch.compile and is much less performant. Remove SpaceToDepthModule
2024-05-06 16:32:49 -07:00
99d4c7d202
add ViTamin models
2024-05-05 02:50:14 -04:00
Ross Wightman
Steffen Schneider
Daniel Suess
Ross Wightman
Sejik
Fernando Cossio
Beckschen
yvonwin
Setepenre