da06cc61d4
ResNetV2 seems to work best without zero_init residual
2021-09-23 15:43:22 -07:00
8e11da0ce3
Add experimental RegNetZ(ish) models for training / perf trials.
2021-09-23 15:42:57 -07:00
3d9c23af87
Merge pull request #875 from alexander-soare/effnets-norm-layer
...
make it possible to provide norm_layer via create_model
2021-09-21 07:17:52 -07:00
6bbc50beb4
make it possible to provide norm_layer via create_model
2021-09-21 10:19:04 +01:00
a6e8598aaf
Merge pull request #821 from rwightman/attn_update
...
Update attention / self-attn based models from a series of experiments
2021-09-13 17:49:34 -07:00
cf5ac2800c
BotNet models were still off, remove weights for bad configs. Add good SE-HaloNet33-TS weights.
2021-09-13 17:18:59 -07:00
24720abe3b
Merge branch 'master' into attn_update
2021-09-13 16:51:10 -07:00
1c9284c640
Add BeiT 'finetuned' 1k weights and pretrained 22k weights, pretraining specific (masked) model excluded for now
2021-09-13 16:38:23 -07:00
f8a215cfe6
A few more crossvit tweaks, fix training w/ no_weight_decay names, add crop option for scaling, adjust default crop_pct for large img size to 1.0 for better results
2021-09-13 14:17:34 -07:00
7ab2491ab7
Better handling of crossvit for tests / forward_features, fix torchscript regression in my changes
2021-09-13 13:01:05 -07:00
702982d8af
Merge branch 'chunfuchen-feature/crossvit'
2021-09-13 11:50:58 -07:00
f1808e0970
Post crossvit merge cleanup, change model names to reflect input size, cleanup img size vs scale handling, fix tests
2021-09-13 11:49:54 -07:00
a897e0ebcc
Merge branch 'feature/crossvit' of https://github.com/chunfuchen/pytorch-image-models into chunfuchen-feature/crossvit
2021-09-10 17:38:37 -07:00
4027412757
Add resnet33ts weights, update resnext26ts baseline weights
2021-09-09 14:46:41 -07:00
9fe5798bee
fix bug for reset classifier and fix for validating the dimension
2021-09-08 21:58:17 -04:00
3718c5a5bd
fix loading pretrained model
2021-09-08 11:53:05 -04:00
bb50b69a57
fix for torch script
2021-09-08 11:20:59 -04:00
5bd04714e4
Cleanup weight init for byob/byoanet and related
2021-09-05 15:34:05 -07:00
8642401e88
Swap botnet 26/50 weights/models after realizing a mistake in arch def, now figuring out why they were so low...
2021-09-05 15:17:19 -07:00
5f12de4875
Add initial AttentionPool2d that's being trialed. Fix comment and still trying to improve reliability of sgd test.
2021-09-05 12:41:14 -07:00
76881d207b
Add baseline resnet26t @ 256x256 weights. Add 33ts variant of halonet with at least one halo in stage 2,3,4
2021-09-04 14:52:54 -07:00
54e90e82a5
Another attempt at sgd momentum test passing...
2021-09-03 20:50:26 -07:00
484e61648d
Adding the attn series weights, tweaking model names, comments...
2021-09-03 18:09:42 -07:00
0639d9a591
Fix updated validation_batch_size fallback
2021-09-02 14:44:53 -07:00
5db057dca0
Fix misnamed arg, tweak other train script args for better defaults.
2021-09-02 14:15:49 -07:00
fb94350896
Update training script and loader factory to allow use of scheduler updates, repeat augment, and bce loss
2021-09-01 17:46:40 -07:00
f262137ff2
Add RepeatAugSampler as per DeiT RASampler impl, showing promise for current (distributed) training experiments.
2021-09-01 17:40:53 -07:00
ba9c1108a1
Add a BCE loss impl that converts dense targets to sparse /w smoothing as an alternate to CE w/ smoothing. For training experiments.
2021-09-01 17:39:28 -07:00
29a37e23ee
LR scheduler update:
...
* add polynomial decay 'poly'
* cleanup cycle specific args for cosine, poly, and tanh sched, t_mul -> cycle_mul, decay -> cycle_decay, default cycle_limit to 1 in each opt
* add k-decay for cosine and poly sched as per https://arxiv.org/abs/2004.05909
* change default tanh ub/lb to push inflection to later epochs
2021-09-01 17:33:11 -07:00
492c0a4e20
Update HaloAttn comment
2021-09-01 17:14:31 -07:00
7ab9d4555c
add crossvit
2021-09-01 17:13:12 -04:00
3b9032ea48
Use Tensor.unfold().unfold() for HaloAttn, fast like as_strided but more clarity
2021-08-27 12:45:53 -07:00
fc894c375c
Another attempt at sgd momentum test passing...
2021-08-27 10:39:31 -07:00
78933122c9
Fix silly typo
2021-08-27 09:22:20 -07:00
2568ffc5ef
Merge branch 'master' into attn_update
2021-08-27 09:21:22 -07:00
708d87a813
Fix ViT SAM weight compat as weights at URL changed to not use repr layer. Fix #825 . Tweak optim test.
2021-08-27 09:20:13 -07:00
8449ba210c
Improve performance of HaloAttn, change default dim calc. Some cleanup / fixes for byoanet. Rename resnet26ts to tfs to distinguish (extra fc).
2021-08-26 21:56:44 -07:00
a8b65695f1
Add resnet26ts and resnext26ts models for non-attn baselines
2021-08-21 12:42:10 -07:00
a5a542f17d
Fix typo
2021-08-20 17:47:23 -07:00
925e102982
Update attention / self-attn based models from a series of experiments:
...
* remove dud attention, involution + my swin attention adaptation don't seem worth keeping
* add or update several new 26/50 layer ResNe(X)t variants that were used in experiments
* remove models associated with dead-end or uninteresting experiment results
* weights coming soon...
2021-08-20 16:13:11 -07:00
acd6c687fd
git push origin masterMerge branch 'yohann84L-fix_accuracy'
2021-08-19 14:26:23 -07:00
d667351eac
Tweak accuracy topk safety. Fix #807
2021-08-19 14:18:53 -07:00
35c9740826
Fix accuracy when topk > num_classes
2021-08-19 11:58:59 +02:00
a16a753852
Add lamb/lars to optim init imports, remove stray comment
2021-08-18 22:55:02 -07:00
c207e02782
MOAR optimizer changes. Woo!
2021-08-18 22:20:35 -07:00
42c1f0cf6c
Fix lars tests
2021-08-18 21:05:34 -07:00
a426511c95
More optimizer cleanup. Change all to no longer use .data. Improve (b)float16 use with adabelief. Add XLA compatible Lars.
2021-08-18 17:21:56 -07:00
9541f4963b
One more scalar -> tensor fix for lamb optimizer
2021-08-18 11:20:25 -07:00
8f68193c91
Update lamp.py comment
2021-08-18 09:27:40 -07:00
4d284017b8
Merge pull request #813 from rwightman/opt_cleanup
...
Optimizer cleanup and additions
2021-08-18 09:12:00 -07:00
Ross Wightman
Ross Wightman
Alexander Soare
Richard Chen
Yohann Lereclus