85f894e03d
Fix ViT in21k representation (pre_logits) layer handling across old and new npz checkpoints
2021-06-23 10:38:34 -07:00
b41cffaa93
Fix a few issues loading pretrained vit/bit npz weights w/ num_classes=0 __init__ arg. Missed a few other small classifier handling detail on Mlp, GhostNet, Levit. Should fix #713
2021-06-22 23:16:05 -07:00
9c9755a808
AugReg release
2021-06-20 17:46:06 -07:00
381b279785
Add hybrid model fwds back
2021-06-19 22:28:44 -07:00
26f04a8e3e
Fix a weight link
2021-06-19 16:39:36 -07:00
8f4a0222ed
Add GMixer-24 MLP model weights, trained w/ TPU + PyTorch XLA
2021-06-18 16:49:28 -07:00
4c09a2f169
Bump version 0.4.12
2021-06-18 16:17:34 -07:00
b319eb5b5d
Update ViT weights, more details to be added before merge.
2021-06-18 16:16:49 -07:00
8257b86550
Fix up resnetv2 bit/bitm model default res
2021-06-18 16:16:06 -07:00
1228f5a3d8
Add BiT distilled 50x1 and teacher 152x2 models from 'A good teacher is patient and consistent' paper.
2021-06-18 11:40:33 -07:00
511a8e8c96
Add official ResMLP weights.
2021-06-14 17:03:16 -07:00
b9cfb64412
Support npz custom load for vision transformer hybrid models. Add posembed rescale for npz load.
2021-06-14 12:31:44 -07:00
8319e0c373
Add file docstring to std_conv.py
2021-06-13 12:31:06 -07:00
4d96165989
Merge branch 'master' into cleanup_xla_model_fixes
2021-06-12 23:19:25 -07:00
8880f696b6
Refactoring, cleanup, improved test coverage.
...
* Add eca_nfnet_l2 weights, 84.7 @ 384x384
* All 'non-std' (ie transformer / mlp) models have classifier / default_cfg test added
* Fix #694 reset_classifer / num_features / forward_features / num_classes=0 consistency for transformer / mlp models
* Add direct loading of npz to vision transformer (pure transformer so far, hybrid to come)
* Rename vit_deit* to deit_*
* Remove some deprecated vit hybrid model defs
* Clean up classifier flatten for conv classifiers and unusual cases (mobilenetv3/ghostnet)
* Remove explicit model fns for levit conv, just pass in arg
2021-06-12 16:40:02 -07:00
ba2ca4b464
One codepath for stdconv, switch layernorm to batchnorm so gain included. Tweak epsilon values for nfnet, resnetv2, vit hybrid.
2021-06-12 12:27:43 -07:00
b7a568f065
Fix torchscript issue in bat
2021-06-08 23:19:51 -07:00
d17b374f0f
Minimum input_size needed to be higher
2021-06-08 21:31:39 -07:00
b3b90d944d
Add min_input_size to bat_resnext to prevent test breakage.
2021-06-08 17:32:08 -07:00
d413eef1bf
Add ResMLP-24 model weights that I trained in PyTorch XLA on TPU-VM. 79.2 top-1.
2021-06-08 14:22:05 -07:00
10d8fa4620
Add gc and bat attention resnext26ts variants to byob for test.
2021-06-08 14:21:07 -07:00
2f5ed2dec1
Update `init_values` const for 24 and 36 layer ResMLP models
2021-06-07 17:15:04 -07:00
8e4ac3549f
All ScaledStdConv and StdConv uses default to using F.layernorm so that they work with PyTorch XLA. eps value tweaking is a WIP.
2021-06-07 17:14:19 -07:00
2a63d0246b
Post merge cleanup
2021-06-07 14:38:30 -07:00
45dec179e5
Merge pull request #681 from lmk123568/master
...
Update convit.py
2021-06-07 14:10:53 -07:00
ded1671483
Fix stochastic depth working only with a shortcut
2021-06-07 23:08:55 +09:00
b87d98b238
Update convit.py
...
Cut out the duplicates
2021-06-06 17:58:31 +08:00
02320c3e3d
Bump version to 0.4.11
2021-05-31 15:41:51 -07:00
bda8ab015a
Remove min channels for SelectiveKernel, divisor should cover cases well enough.
2021-05-31 15:38:56 -07:00
a27f4aec4a
Missed args for skresnext w/ refactoring.
2021-05-31 14:06:34 -07:00
307a935b79
Add non-local and BAT attention. Merge attn and self-attn factories into one. Add attention references to README. Add mlp 'mode' to ECA.
2021-05-31 13:18:11 -07:00
8bf63b6c6c
Able to use other attn layer in EfficientNet now. Create test ECA + GC B0 configs. Make ECA more configurable.
2021-05-30 12:47:02 -07:00
bcec14d3b5
Bring EfficientNet SE layer in line with others, pull se_ratio outside of blocks. Allows swapping w/ other attn layers.
2021-05-29 23:41:38 -07:00
9611458e19
Throw in some FBNetV3 code I had lying around, some refactoring of SE reduction channel calcs for all EffNet archs.
2021-05-28 20:47:24 -07:00
01b9108619
Merge branch 'master' into more_attn
2021-05-28 11:09:37 -07:00
d7bab8a6c5
Fix strict flag change for checkpoint load.
2021-05-28 09:54:50 -07:00
02f9d4bc34
Add weights for resnet51q model, add 61q def.
2021-05-28 09:53:16 -07:00
f615474be3
Fix broken test, repvgg block doesn't have attn_last attr.
2021-05-27 18:12:22 -07:00
742c2d5247
Add Gather-Excite and Global Context attn modules. Refactor existing SE-like attn for consistency and refactor byob/byoanet for less redundancy.
2021-05-27 18:03:29 -07:00
9c78de8c02
Fix #661 , move hardswish out of default args for LeViT. Enable native torch support for hardswish, hardsigmoid, mish if present.
2021-05-26 15:28:42 -07:00
5db7452173
Fix visformer in_chans stem handling
2021-05-25 14:11:36 -07:00
318360c3f9
Update README.md before merge. Bump version to 0.4.10
2021-05-25 12:26:16 -07:00
11ae795e99
Redo LeViT attention bias caching in a way that works with both torchscript and DataParallel
2021-05-25 10:15:32 -07:00
d400f1dbdd
Filter test models before creation for backward/torchscript tests
2021-05-25 10:14:45 -07:00
c4572cc5aa
Add Visformer-small weighs, tweak torchscript jit test img size.
2021-05-24 22:50:12 -07:00
bfc72f75d3
Expand scope of testing for non-std vision transformer / mlp models. Some related cleanup and create fn cleanup for all vision transformer and mlp models. More CoaT weights.
2021-05-24 21:13:26 -07:00
18bf520ad1
Add eca_nfnet_l2/l3 defs for future training
2021-05-22 21:55:37 -07:00
f45de37690
Merge branch 'master' into levit_visformer_rednet
2021-05-22 16:34:31 -07:00
23c18a33e4
Add efficientnetv2_rw_m weights trained in PyTorch. 84.8 top-1 @ 416 test. 53M params.
2021-05-21 21:16:25 -07:00
c2ba229d99
Prep for effcientnetv2_rw_m model weights that started training before official release..
2021-05-21 17:47:49 -07:00
30b9880d06
Minor adjustment, mutable default arg, extra check of valid len...
2021-05-21 17:20:51 -07:00
be0abfbcce
Merge branch 'master' of https://github.com/alexander-soare/pytorch-image-models into alexander-soare-master
2021-05-21 17:10:11 -07:00
b7de82e835
ConViT cleanup, fix torchscript, bit of reformatting, reuse existing layers.
2021-05-21 17:04:23 -07:00
306c86b668
Merge branch 'convit' of https://github.com/amaarora/pytorch-image-models into amaarora-convit
2021-05-21 16:27:10 -07:00
a569635045
Update twin weights to a copy in GitHub releases for faster dl. Tweak model class comment.
2021-05-21 16:23:14 -07:00
be99eef9c1
Remove redundant code, cleanup, fix torchscript.
2021-05-20 23:38:35 -07:00
5ab372a3ec
Merge branch 'master' of https://github.com/abcdvzz/pytorch-image-models into abcdvzz-master
2021-05-20 23:37:50 -07:00
5db1eb6ba5
Add defaults
2021-05-21 02:11:20 +00:00
8b1f2e8e1f
remote unused matplotlib import
2021-05-20 23:42:42 +00:00
40c506ba1e
Add ConViT
2021-05-20 23:17:28 +00:00
7976019864
extend positional embedding resizing functionality to tnt
2021-05-20 11:55:48 +01:00
8086943b6f
allow resize positional embeddings to non-square grid
2021-05-20 11:27:58 +01:00
dc1a4efd28
mixer_b16_224_miil, mixer_b16_224_miil_in21k models
2021-05-20 10:35:50 +03:00
7b799c4e79
add latest code
2021-05-20 11:15:49 +08:00
d5af752117
Add preliminary gMLP and ResMLP impl to Mlp-Mixer
2021-05-19 09:55:05 -07:00
00548b8427
Add Twins
2021-05-18 19:21:53 +08:00
e7f0db8664
Fix drop/drop_path arg on MLP-Mixer model. Fix #641
2021-05-16 08:31:52 -07:00
9a3ae97311
Another set of byoanet models w/ ECA channel + SA + groups
2021-05-15 22:56:51 -07:00
d53e91218e
Fix tf.data options setting for newer TF versions
2021-05-15 22:56:12 -07:00
7077f16c6a
Change 21k model naming from _21k to _in21k for consistency with existing 21k models.
2021-05-15 12:42:26 -07:00
94d4b53352
Add temporary default_cfgs to visformer models so they pass tests
2021-05-15 08:41:31 -07:00
3bffc701f1
Merge branch 'master' into levit_visformer_rednet
2021-05-14 23:02:12 -07:00
ecc7552c5c
Add levit, levit_c, and visformer model defs. Largely untested and not finished cleanup.
2021-05-14 17:16:34 -07:00
165fb354b2
Add initial RedNet model / Involution layer impl for testing
2021-05-14 17:16:34 -07:00
328249f11a
Update README, tweak fine-tune effv2 model names.
2021-05-14 16:37:43 -07:00
c4f482a08b
EfficientNetV2 official impl w/ weights ported from TF. Cleanup/refactor of related EfficientNet classes and models.
2021-05-14 15:50:00 -07:00
4fbc32d3d0
Fix crop_pct for cait models.
2021-05-11 10:50:15 -07:00
715519a5ef
Rethink name of patch embed grid info
2021-05-06 14:08:20 -07:00
b2c305c2aa
Move Mlp and PatchEmbed modules into layers. Being used in lots of models now...
2021-05-06 14:03:23 -07:00
3ba6b55cb2
More adjustments to ByoaNet models for further experiments.
2021-05-06 13:59:44 -07:00
5fcddb96a8
Merge branch 'master' into cait
2021-05-05 17:29:38 -07:00
3db12b4b6a
Finish CaiT cleanup
2021-05-05 17:28:19 -07:00
2d8b09fe8b
Add official pretrained weights to MLP-Mixer, complete model cfgs.
2021-05-05 15:59:40 -07:00
12efffa6b1
Initial MLP-Mixer attempt...
2021-05-05 00:59:45 -07:00
0721559511
Improved (hopefully) init for SA/SA-like layers used in ByoaNets
2021-05-04 21:40:39 -07:00
d5473c17f7
Fix incorrect name of shortcut/identity paths in many residual nets. Inherited from naming in old old torchvision, long fixed there.
2021-05-04 21:27:15 -07:00
0d87650fea
Remove filter hack from BlurPool w/ non-persistent buffer. Use BlurPool2d instead of AntiAliasing.. for TResNet. Breaks PyTorch < 1.6.
2021-05-04 16:56:28 -07:00
ddc743fdf8
Update ResNet-RS models to EMA weights
2021-05-04 16:16:55 -07:00
08d60f4a9a
resnetrs50 pool sizing wrong
2021-05-04 12:41:09 -07:00
1daa15ecc3
Initial Cait commit. Still some cleanup to do.
2021-05-04 11:19:27 -07:00
67d0665b46
Post ResNet-RS merge cleanup. Add weight urls, adjust train/test/crop pct.
2021-05-04 11:04:23 -07:00
560eae38f5
[WIP] Add ResNet-RS models ( #554 )
...
* Add ResNet-RS models
* Only include resnet-rs changes
* remove whitespace diff
* EOF newline
* Update time
* increase time
* Add first conv
* Try running only resnetv2_101x1_bitm on Linux runner
* Add to exclude filter
* Run test_model_forward_features for all
* Add to exclude ftrs
* back to defaults
* only run test_forward_features
* run all tests
* Run all tests
* Add bigger resnetrs to model filters to fix Github CLI
* Remove resnetv2_101x1_bitm from exclude feat features
* Remove hardcoded values
* Make sure reduction ratio in resnetrs is 0.25
* There is no bias in replaced maxpool so remove it
2021-05-04 10:59:44 -07:00
9cc7dda6e5
Fixup byoanet configs to pass unit tests. Add swin_attn and swinnet26t model for testing.
2021-04-29 21:08:37 -07:00
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.
2021-04-29 10:58:49 -07:00
e5e15754c9
Fix coat first conv ident
2021-04-28 18:09:23 -07:00
76739a7589
CoaT merge. Bit of formatting, fix torchscript (for non features), remove einops/einsum dep, add pretrained weight hub (url) support.
2021-04-28 16:31:35 -07:00
026430c083
Merge branch 'master' of https://github.com/morizin/pytorch-image-models-1 into morizin-master
2021-04-28 11:24:27 -07:00
a0492e3b48
A few miil weights naming tweaks to improve compat with model registry and filtering wildcards.
2021-04-28 10:33:02 -07:00
8c1f03e56c
comment
2021-04-28 09:04:10 +03:00
19e1b67a84
old spaces
2021-04-28 09:01:29 +03:00
Ross Wightman
Ross Wightman
Dongyoon Han
Mike
Aman Arora
Alexander Soare
talrid
李鑫杰
Aman Arora