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
a443865876
update naming and scores
2021-04-28 08:57:06 +03:00
cf0e371594
84_0
2021-04-27 22:33:55 +03:00
0968bdeca3
vit, tresnet and mobilenetV3 ImageNet-21K-P weights
2021-04-27 20:54:06 +03:00
1e3b6d4dfc
Update __init__.py
2021-04-24 18:22:59 +05:30
fd022fd6a2
Update __init__.py
2021-04-24 18:22:36 +05:30
c2d5087eae
Add files via upload
2021-04-24 17:47:57 +05:30
79640fcc1f
Enable uniform augmentation magnitude sampling and set AugMix default
2021-04-19 14:21:12 -07:00
c1cf9712fc
Add updated EfficientNet-V2S weights, 83.8 @ 384x384 test. Add PyTorch trained EfficientNet-B4 weights, 83.4 @ 384x384 test. Tweak non TF EfficientNet B1-B4 train/test res scaling.
2021-04-19 10:42:56 -07:00
e8a64fb881
Test input size for efficientnet_v2s was wrong in last results run
2021-04-17 16:17:41 -07:00
2df77ee5cb
Fix torchscript compat and features_only behaviour in GhostNet PR. A few minor formatting changes. Reuse existing layers.
2021-04-15 10:20:26 -07:00
d793deb51a
Merge branch 'master' of https://github.com/iamhankai/pytorch-image-models into iamhankai-master
2021-04-15 09:30:25 -07:00
e685618f45
Merge pull request #550 from amaarora/wandb
...
Wandb Support
2021-04-15 09:26:35 -07:00
f606c45c38
Add Swin Transformer models from https://github.com/microsoft/Swin-Transformer
2021-04-13 12:17:21 -07:00
de445e7827
Add GhostNet
2021-04-13 23:19:51 +08:00
5a196dddf6
Update README.md with latest, bump version to 0.4.8
2021-04-12 13:15:00 -07:00
b3d7580df1
Update ByoaNet comments. Fix first Steam feat chs for ByobNet.
2021-04-12 12:11:35 -07:00
16f7aa9f54
Add default_cfg options for min_input_size / fixed_input_size, queries in model registry, and use for testing self-attn models
2021-04-12 11:54:22 -07:00
4e4b863b15
Missed norm.py
2021-04-12 09:57:56 -07:00
7c97e66f7c
Remove commented code, add more consistent seed fn
2021-04-12 09:51:36 -07:00
364dd6a58e
Merge branch 'master' into byoanet-self_attn
2021-04-12 09:38:59 -07:00
ce62f96d4d
ByoaNet with bottleneck transformer, lambda resnet, and halo net experiments
2021-04-12 09:38:02 -07:00
cd3dc4979f
Fix adabelief imports, remove prints, preserve memory format is the default arg for zeros_like
2021-04-12 08:25:31 -07:00
21812d33aa
Add prelim efficientnet_v2s weights from 224x224 train, eval 83.3 @ 288. Add eca_nfnet_l1 weights, train at 256, eval 84 @ 320.
2021-04-11 23:26:13 -07:00
5772c55c57
Make wandb optional
2021-04-10 01:34:20 -04:00
f54897cc0b
make wandb not required but rather optional as huggingface_hub
2021-04-10 01:27:23 -04:00
3f028ebc0f
import wandb in summary.py
2021-04-08 03:48:51 -04:00
624c9b6949
log to wandb only if using using wandb
2021-04-08 03:40:22 -04:00
addfc7c1ac
adabelief
2021-04-04 23:48:15 -04:00
fb896c0b26
Update some comments re preliminary EfficientNet-V2 assumptions
2021-04-03 12:00:25 -07:00
2b49ab7a36
Fix ResNetV2 pretrained classifier issue. Fixes #540
2021-04-03 11:18:12 -07:00
de9dff933a
EfficientNet-V2S preliminary model def (for experimentation)
2021-04-02 09:36:51 -07:00
37c71a5609
Some further create_optimizer_v2 tweaks, remove some redudnant code, add back safe model str. Benchmark step times per batch.
2021-04-01 22:34:55 -07:00
2bb65bd875
Wrong default_cfg pool_size for L1
2021-04-01 20:00:41 -07:00
bf2ca6bdf4
Merge jax and original weight init
2021-04-01 18:11:51 -07:00
acbd698c83
Update README.md with updates. Small tweak to head_dist handling.
2021-04-01 17:49:05 -07:00
9071568f0e
Add weights for SE NFNet-L0 model, rename nfnet_l0b -> nfnet_l0. 82.75 top-1 @ 288. Add nfnet_l1 model def for training.
2021-04-01 17:22:27 -07:00
c468c47a9c
Add regnety_160 weights from DeiT teacher model, update that and my regnety_032 weights to use higher test size.
2021-04-01 16:41:04 -07:00
288682796f
Update benchmark script to add precision arg. Fix some downstream (DeiT) compat issues with latest changes. Bump version to 0.4.7
2021-04-01 16:40:12 -07:00
ea9c9550b2
Fully move ViT hybrids to their own file, including embedding module. Remove some extra DeiT models that were for benchmarking only.
2021-04-01 14:17:38 -07:00
a5310a3451
Merge remote-tracking branch 'origin/benchmark-fixes-vit_hybrids' into pit_and_vit_update
2021-04-01 12:15:34 -07:00
7953e5d11a
Fix pos_embed scaling for ViT and num_classes != 1000 for pretrained distilled deit and pit models. Fix #426 and fix #433
2021-03-31 23:11:28 -07:00
a760a4c3f4
Some ViT cleanup, merge distilled model with main, fixup torchscript support for distilled models
2021-03-31 18:21:02 -07:00
0dfc5a66bb
Add PiT model from https://github.com/naver-ai/pit
2021-03-31 18:20:14 -07:00
51febd869b
Small tweak to tests for tnt model, reorder model imports.
2021-03-29 11:33:08 -07:00
b27a4e0d88
Merge branch 'master' of https://github.com/contrastive/pytorch-image-models into contrastive-master
2021-03-29 10:37:05 -07:00
6b18061773
Add GIST to docstring for quick access
2021-03-29 15:33:31 +11:00
de86314655
Update TNT
2021-03-29 08:23:34 +08:00
92b1db9a79
update docstrings and add check on and
2021-03-29 10:04:51 +11:00
b85be24054
update to work with fnmatch
2021-03-29 09:36:31 +11:00
cfc15283a4
Update TNT url
2021-03-28 23:19:15 +08:00
4a09bc851e
Add TNT model
2021-03-28 19:53:42 +08:00
20626e8387
Add to extract stats for SPP
2021-03-27 05:40:04 +11:00
cf5fec5047
Cleanup experimental vit weight init a bit
2021-03-20 09:44:24 -07:00
f42f1df26c
Improve evenness of per-worker split for validation set with TFDS
2021-03-18 23:16:14 -07:00
cbcb76d72c
Should have included Conv2d layers in original weight init. Lets see what the impact is...
2021-03-18 23:15:48 -07:00
4de57ccf01
Add weight init scheme that's closer to JAX impl
2021-03-18 15:35:22 -07:00
14ac4abf74
Change huggingface hub revision delimiter to '@', add hf_hub reference for eca_nfnet_l0 model as an example.
2021-03-18 11:38:06 -07:00
740f32c96a
Add ECA-NFNet-L0 weights and update model name. Update README and bump version to 0.4.6
2021-03-17 13:55:32 -07:00
5e2e4e7fb6
Merge pull request #502 from khatami-mehrdad/efficientnet_dg
...
adding efficientnet_el, efficientnet_es_pruned and efficientnet_el_pruned pre-trained models
2021-03-17 13:35:22 -07:00
45c048ba13
A few minor fixes and bit more cleanup on the huggingface hub integration.
2021-03-17 13:18:52 -07:00
97f49d163c
adding efficientnet_el, efficientnet_es_prunedefficientnet_es_pruned and efficientnet_el_pruned pretrained models to timm/models
2021-03-17 10:51:51 -07:00
ead80d33c5
Fix typo, naming consistency
2021-03-16 23:02:51 -07:00
d584e7f617
Support for huggingface hub via create_model and default_cfgs.
...
* improve consistency of model creation helper fns
* add comments to some of the model helpers
* support passing external default_cfgs so they can be sourced from hub
2021-03-16 22:48:26 -07:00
1f799afcb3
Remove capital letters in model names
2021-03-15 10:20:34 -07:00
82c1fe958a
added hardcorenas model
...
refactoring to support feature extraction
2021-03-15 08:06:34 +02:00
f57db99101
Update README, fix iabn pip version print.
2021-03-07 16:17:06 -08:00
7ef7788ee9
Fix CUDA crash w/ channels-last + CSP models. Remove use of chunk()
2021-03-06 16:56:34 -08:00
317ea3e599
Tweak NFNet, ResNetV2, RexNet feature extraction, use pre-act features for simplicty. Update tests for pytorch 1.8. 0.4.5 version bump.
2021-03-06 12:48:06 -08:00
17cdee7354
Fix C&P patch_size error, and order of op patch_size arg resolution bug. Remove a test vit model.
2021-03-01 16:53:32 -08:00
0706d05d52
Benchmark models listed in txt file. Add more hybrid vit variants for testing
2021-02-28 16:00:33 -08:00
2db2d87ff7
Add epoch-repeats arg to multiply the number of dataset passes per epoch. Currently for iterable datasets (read TFDS wrapper) only.
2021-02-23 17:31:42 -08:00
de97be9146
Spell out diff between my small and deit small vit models.
2021-02-23 16:22:55 -08:00
f0ffdf89b3
Add numerous experimental ViT Hybrid models w/ ResNetV2 base. Update the ViT naming for hybrids. Fix #426 for pretrained vit resizing.
2021-02-23 15:54:55 -08:00
0e16d4e9fb
Add benchmark.py script, and update optimizer factory to be more friendly to use outside of argparse interface.
2021-02-23 15:38:12 -08:00
4bc103f504
Fix CUDA crash w/ channels-last + CSP models. Remove use of chunk()
2021-02-23 13:15:52 -08:00
8563609b28
Update notes in ScaledStdConv impl
2021-02-18 12:44:08 -08:00
678ba4e0a2
Add NFNet-F model weights ported from DeepMind Haiku impl and new set of models w/ compatible config.
2021-02-18 12:28:46 -08:00
9de2ec5e44
Update README for AGC and bump version to 0.4.4
2021-02-16 09:13:03 -08:00
4f49b94311
Initial AGC impl. Still testing.
2021-02-15 23:22:44 -08:00
5f9aff395c
Fix stem width in NFNet-F models, add some more comments, add some 'light' NFNet models for testing.
2021-02-13 16:58:51 -08:00
d86dbe45c2
Update README.md and few more comments
2021-02-12 22:07:18 -08:00
0d253e2c5e
Fix issue with nfnet tests, bit more cleanup.
2021-02-12 21:05:41 -08:00
cb06c7a910
Add NFNet-F models and tweak existing NF models.
2021-02-12 18:28:56 -08:00
e4de077021
Add first 'Normalizer Free' models. nf_regnet_b1 79.3 @ 288x288 test, and nf_resnet50 80.3 @ 256x256 test (80.68 @ 288x288).
2021-02-11 13:20:11 -08:00
d8e69206be
Merge pull request #419 from rwightman/byob_vgg_models
...
More models, GPU-Efficient Nets, RepVGG, classic VGG, and flexible Byob backbone.
2021-02-10 15:44:09 -08:00
ca9b078ac7
Update README.md and docs. Version bumped to 0.4.3
2021-02-10 14:46:07 -08:00
6853b07bbd
Improve RegVGG block identity/vs non for clariy and fix attn usage. Add comments.
2021-02-10 14:40:29 -08:00
0356e773f5
Default to native PyTorch AMP instead of APEX amp. Too many APEX issues cropping up lately.
2021-02-10 14:31:18 -08:00
94ca140b67
update collections.abc import
2021-02-10 23:54:35 +11:00
b4e216e377
Fix a few small things.
2021-02-09 17:33:43 -08:00
dc85e5a237
Add ByobNet w/ GPU-EfficientNets and RepVGG. Also add classic vgg models.
2021-02-09 16:22:52 -08:00
1bcc69e0ad
Use in_channels for depthwise groups, allows using `out_channels=N * in_channels` (does not impact existing models). Fix #354 .
2021-02-09 16:22:52 -08:00
9811e229f7
Fix regression in models with 1001 class pretrained weights. Improve batchnorm arg and BatchNormAct layer handling in several models.
2021-02-09 16:22:52 -08:00
a39c3ee216
Merge branch 'master' into eca-weights
2021-02-08 11:52:31 -08:00
e9d6fe293c
Update README for new weights. Version 0.4.2
2021-02-08 11:51:16 -08:00
666de85cf1
Move stride in EdgeResidual block to 3x3 expansion conv. Fix #414
2021-02-07 22:10:18 -08:00
3b57490a63
Fix some half removed resnet model defs, pooling for ecaresnet269d
2021-02-07 22:09:25 -08:00
68a4144882
Add new weights for ecaresnet26t/50t/269d models. Remove distinction between 't' and 'tn' (tiered models), tn is now t. Add test time img size spec to default cfg.
2021-02-06 16:30:02 -08:00
b9843f954b
Merge pull request #282 from tigert1998/patch-1
...
Add symbolic for SwishJitAutoFn to support onnx
2021-02-04 12:18:40 -08:00
7a4be5c035
add operator HardSwishJitAutoFn export to onnx
2021-02-03 09:06:53 +08:00
4203efa36d
Fix #387 so that checkpoint saver works with max history of 1. Add checkpoint-hist arg to train.py.
2021-01-31 20:14:51 -08:00
f0e65e37b7
Fix NF-ResNet101 model defs
2021-01-30 23:26:19 -08:00
2c988c3b6e
Update README.md for NF-nets, bump version to 0.4.1 for merge
2021-01-30 23:19:45 -08:00
2de54d174a
Fix pool size defs for NFNet models, add a comment.
2021-01-30 18:02:33 -08:00
90980de4a9
Fix up a few details in NFResNet models, managed stable training. Add support for gamma gain to be applied in activation or ScaleStdConv. Some tweaks to ScaledStdConv.
2021-01-30 16:32:07 -08:00
5a8e1e643e
Initial Normalizer-Free Reg/ResNet impl. A bit of related layer refactoring.
2021-01-27 22:06:57 -08:00
38d8f67570
Fix potential issue with change to num_classes arg in train/validate.py defaulting to None (rely on model def / default_cfg)
2021-01-25 11:53:34 -08:00
587780e56b
Update README.md and bump version to 0.4.0
2021-01-25 11:22:11 -08:00
bb50ac4708
Add DeiT distilled weights and distilled model def. Remove some redudant ViT model args.
2021-01-25 11:05:23 -08:00
c16e965037
Add some ViT comments and fix a few minor issues.
2021-01-24 23:18:35 -08:00
22748f1a2d
Convert samples/targets in ParserImageInTar to numpy arrays, slightly less mem usage for massive datasets. Add a few more se/eca model defs to resnet.py
2021-01-22 16:54:33 -08:00
5d4c3d0af3
Add enhanced ParserImageInTar that can read images from tars within tars, folders with multiple tars, etc. Additional comment cleanup.
2021-01-22 10:52:04 -08:00
55f7dfa9ea
Refactor vision_transformer entrpy fns, add pos embedding resize support for fine tuning, add some deit models for testing
2021-01-18 16:11:02 -08:00
d55bcc0fee
Finishing adding stochastic depth support to BiT ResNetV2 models
2021-01-16 16:32:03 -08:00
855d6cc217
More dataset work including factories and a tensorflow datasets (TFDS) wrapper
...
* Add parser/dataset factory methods for more flexible dataset & parser creation
* Add dataset parser that wraps TFDS image classification datasets
* Tweak num_classes handling bug for 21k models
* Add initial deit models so they can be benchmarked in next csv results runs
2021-01-15 17:26:20 -08:00
20516abc18
Fix some broken tests for ResNetV2 BiT models
2021-01-04 23:21:39 -08:00
59ec7e6a53
Merge branch 'master' into imagenet21k_datasets_more
2021-01-04 12:11:05 -08:00
e7a9ddf982
Merge pull request #334 from kecsap/links
...
Follow symbolic links during dataset scanning
2021-01-04 10:30:58 -08:00
7cae7e7035
Follow links during dataset scanning
2021-01-04 00:16:45 +02:00
c96e9f99a0
Update version to 0.3.3
2021-01-03 12:43:44 -08:00
4e2533db77
Add 320x320 model default cfgs for 101D and 152D ResNets. Add SEResNet-152D weights and 320x320 cfg.
2021-01-03 12:10:25 -08:00
0167f749d3
Remove some old __future__ imports
2021-01-03 11:24:16 -08:00
e35e9760a6
More work on dataset / parser split and imagenet21k (tar) support
2020-12-28 16:59:15 -08:00
ce69de70d3
Add 21k weight urls to vision_transformer. Cleanup feature_info for preact ResNetV2 (BiT) models
2020-12-28 16:59:15 -08:00
231d04e91a
ResNetV2 pre-act and non-preact model, w/ BiT pretrained weights and support for ViT R50 model. Tweaks for in21k num_classes passing. More to do... tests failing.
2020-12-28 16:59:15 -08:00
de6046e213
Initial commit for dataset / parser reorg to support additional datasets / types
2020-12-28 16:59:15 -08:00
392595c7eb
Add pool_size to default cfgs for new models to prevent tests from failing. Add explicit 200D_320 model entrypoint for next benchmark run.
2020-12-18 21:28:47 -08:00
b1f1228a41
Add ResNet101D, 152D, and 200D weights, remove meh 66d model
2020-12-18 17:13:37 -08:00
7c56c718f3
Configure create_optimizer with args.opt_args
...
Closes #301
2020-12-08 00:03:09 -06:00
9a25fdf3ad
Merge pull request #297 from rwightman/ema_simplify
...
Simplified JIT compatible Ema module. Fixes for SiLU export and torchscript training w/ Linear layer.
2020-12-05 11:42:45 -08:00
de15b43865
Fix a bug with accuracy retrieving from RealLabels
2020-12-04 16:12:50 +01:00
cd72e66eff
Bug in last mod for features_only default_cfg
2020-12-03 12:33:01 -08:00
867a0e5a04
Add default_cfg back to models wrapped in feature extraction module as per discussion in #294 .
2020-12-03 10:24:35 -08:00
4ca52d73d8
Add separate set and update method to ModelEmaV2
2020-12-03 10:05:09 -08:00
2ed8f24715
A few more changes for 0.3.2 maint release. Linear layer change for mobilenetv3 and inception_v3, support no bias for linear wrapper.
2020-11-30 16:19:52 -08:00
6504a42832
Version 0.3.2
2020-11-30 13:39:08 -08:00
460eba7f24
Work around casting issue with combination of native torch AMP and torchscript for Linear layers
2020-11-30 13:30:51 -08:00
5f4b6076d8
Fix inplace arg compat for GELU and PreLU via activation factory
2020-11-30 13:27:40 -08:00
fd962c4b4a
Native SiLU (Swish) op doesn't export to ONNX
2020-11-29 21:56:55 -08:00
27bbc70d71
Add back old ModelEma and rename new one to ModelEmaV2 to avoid compat breaks in dependant code. Shuffle train script, add a few comments, remove DataParallel support, support experimental torchscript training.
2020-11-29 16:22:19 -08:00
43f2500c26
Add symbolic for SwishJitAutoFn to support onnx
2020-11-18 14:36:12 +08:00
9214ca0716
Simplifying EMA...
2020-11-16 12:51:52 -08:00
53aeed3499
ver 0.3.1
2020-10-31 18:14:58 -07:00
30ab4a1494
Fix issue in optim factory with sgd / eps flag. Bump version to 0.3.1
2020-10-31 18:05:30 -07:00
741572dc9d
Bump version to 0.3.0 for pending PyPi push
2020-10-29 17:31:39 -07:00
b401952caf
Add newly added vision transformer large/base 224x224 weights ported from JAX official repo
2020-10-29 17:31:01 -07:00
61200db0ab
in_chans=1 working w/ pretrained weights for vision_transformer
2020-10-29 15:49:36 -07:00
e90edce438
Support native silu activation (aka swish). An optimized ver is available in PyTorch 1.7.
2020-10-29 15:45:17 -07:00
da6cd2cc1f
Fix regression for pretrained classifier loading when using entrypt functions directly
2020-10-29 15:43:39 -07:00
f591e90b0d
Make sure num_features attr is present in vit models as with others
2020-10-29 15:33:47 -07:00
4a3df7842a
Fix topn metric view regression on PyTorch 1.7
2020-10-29 14:04:15 -07:00
f944242cb0
Fix #262 , num_classes arg mixup. Make vision_transformers a bit closer to other models wrt get/reset classfier/forward_features. Fix torchscript for ViT.
2020-10-29 13:58:28 -07:00
736f209e7d
Update vision transformers to be compatible with official code. Port official ViT weights from jax impl.
2020-10-26 18:42:11 -07:00
477a78ed81
Fix optimizer factory regressin for optimizers like sgd/momentum that don't have an eps arg
2020-10-22 15:59:47 -07:00
27a93e9de7
Improve test crop for ViT models. Small now 77.85, added base weights at 79.35 top-1.
2020-10-21 23:35:25 -07:00
d4db9e7977
Add small vision transformer weights. 77.42 top-1.
2020-10-21 12:14:12 -07:00
27fadaa922
asymmetric_loss
2020-10-16 17:12:28 +03:00
f31933cb37
Initial Vision Transformer impl w/ patch and hybrid variants. Refactor tuple helpers.
2020-10-13 13:33:44 -07:00
a4d8fea61e
Add model based wd skip support. Improve cross version compat of optimizer factory. Fix #247
2020-10-13 12:49:47 -07:00
80078c47bb
Add Adafactor and Adahessian optimizers, cleanup optimizer arg passing, add gradient clipping support.
2020-10-09 17:24:43 -07:00
fcb6258877
Add missing leaky_relu layer factory defn, update Apex/Native loss scaler interfaces to support unscaled grad clipping. Bump ver to 0.2.2 for pending release.
2020-10-02 16:19:39 -07:00
e8e2d9cabf
Add DropPath (stochastic depth) to ReXNet and VoVNet. RegNet DropPath impl tweak and dedupe se args.
2020-09-24 18:20:36 -07:00
e8ca45854c
More models in sotabench, more control over sotabench run, dataset filename extraction consistency
2020-09-24 15:56:57 -07:00
9c406532bd
Add EfficientNet-EdgeTPU-M (efficientnet_em) model trained natively in PyTorch. More sotabench fiddling.
2020-09-23 17:12:07 -07:00
c40384f5bd
Add ResNet weights. 80.5 (top-1) ResNet-50-D, 77.1 ResNet-34-D, 72.7 ResNet-18-D.
2020-09-18 12:05:37 -07:00
李鑫杰
Ross Wightman
Aman Arora
talrid
morizin
Norman Mu
Ross Wightman
iamhankai
Aman Arora
juntang
contrastive
Mehrdad
AFLALO, Jonathan Isaac
Reuben
hwangdeyu
Csaba Kertesz
Jasha
Tymoteusz Wiśniewski
tigertang