5d4c3d0af3
Add enhanced ParserImageInTar that can read images from tars within tars, folders with multiple tars, etc. Additional comment cleanup.
3 years ago
9d5d4b8df6
Fix silly train.py typo during dataset work
4 years ago
855d6cc217
More dataset work including factories and a tensorflow datasets (TFDS) wrapper
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* 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
4 years ago
fd9061dbf7
Remove debug print from train.py
4 years ago
59ec7e6a53
Merge branch 'master' into imagenet21k_datasets_more
4 years ago
e42b140ade
Add --input-size option to scripts to specify full input dimensions from command-line
4 years ago
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.
4 years ago
de6046e213
Initial commit for dataset / parser reorg to support additional datasets / types
4 years ago
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.
4 years ago
460eba7f24
Work around casting issue with combination of native torch AMP and torchscript for Linear layers
4 years ago
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.
4 years ago
9214ca0716
Simplifying EMA...
4 years ago
80078c47bb
Add Adafactor and Adahessian optimizers, cleanup optimizer arg passing, add gradient clipping support.
4 years ago
47a7b3b5b1
More flexible mixup mode, add 'half' mode.
4 years ago
532e3b417d
Reorg of utils into separate modules
4 years ago
751b0bba98
Add global_pool (--gp) arg changes to allow passing 'fast' easily for train/validate to avoid channels_last issue with AdaptiveAvgPool
4 years ago
9c297ec67d
Cleanup Apex vs native AMP scaler state save/load. Cleanup CheckpointSaver a bit.
4 years ago
c2cd1a332e
Improve torch amp support and add channels_last support for train/validate scripts
4 years ago
5f563ca4df
fix save_checkpoint bug with native amp
4 years ago
d98967ed5d
add support for native torch AMP in torch 1.6
4 years ago
8c9814e3f5
Final cleanup of mixup/cutmix. Element/batch modes working with both collate (prefetcher active) and without prefetcher.
4 years ago
f471c17c9d
More cutmix/mixup overhaul, ready to kick-off some trials.
4 years ago
92f2d0d65d
Merge branch 'master' into cutmix. Fixup a few issues.
4 years ago
fa28067704
Add more augmentation arguments, including a no_aug disable flag. Fix #209
4 years ago
7995295968
Merge branch 'logger' into features. Change 'logger' to '_logger'.
4 years ago
1998bd3180
Merge branch 'feature/AB/logger' of https://github.com/antoinebrl/pytorch-image-models into logger
4 years ago
6c17d57a2c
Fix some attributions, add copyrights to some file docstrings
4 years ago
78fa0772cc
Leverage python hierachical logger
...
with this update one can tune the kind of logs generated by timm but
training and inference traces are unchanged
4 years ago
6441e9cc1b
Fix memory_efficient mode for DenseNets. Add AntiAliasing (Blur) support for DenseNets and create one test model. Add lr cycle/mul params to train args.
4 years ago
a7f570c9b7
added MultiEpochsDataLoader
4 years ago
13cf68850b
Remove poorly named metrics from torch imagenet example origins. Use top1/top5 in csv output for consistency with existing validation results files, acc elsewhere. Fixes #111
4 years ago
27b3680d49
Revamp LR noise, move logic to scheduler base. Fixup PlateauLRScheduler and add it as an option.
4 years ago
514b0938c4
Experimenting with per-epoch learning rate noise w/ step scheduler
4 years ago
43225d110c
Unify drop connect vs drop path under 'drop path' name, switch all EfficientNet/MobilenetV3 refs to 'drop_path'. Update factory to handle new drop args.
4 years ago
b3cb5f3275
Working on CutMix impl as per #8 , integrating with Mixup, currently experimenting...
4 years ago
b72013def8
Added commandline argument validation-batch-size-multiplier with default set to 1.
4 years ago
5b7cc16ac9
Add warning about using sync-bn with zero initialized BN layers. Fixes #54
4 years ago
d9a6a9d0af
Merge pull request #74 from rwightman/augmix-jsd
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AugMix, JSD loss, SplitBatchNorm (Auxiliary BN), and more
5 years ago
3eb4a96eda
Update AugMix, JSD, etc comments and references
5 years ago
7547119891
Add SplitBatchNorm. AugMix, Rand/AutoAugment, Split (Aux) BatchNorm, Jensen-Shannon Divergence, RandomErasing all working together
5 years ago
40fea63ebe
Add checkpoint averaging script. Add headers, shebangs, exec perms to all scripts
5 years ago
4666cc9aed
Add --pin-mem arg to enable dataloader pin_memory (showing more benefit in some scenarios now), also add --torchscript arg to validate.py for testing models with jit.script
5 years ago
232ab7fb12
Working on an implementation of AugMix with JensenShannonDivergence loss that's compatible with my AutoAugment and RandAugment impl
5 years ago
5719b493ad
Missed update dist-bn logic for EMA model
5 years ago
a435ea1327
Change reduce_bn to distribute_bn, add ability to choose between broadcast and reduce (mean). Add crop_pct arg to allow selecting validation crop while training.
5 years ago
3bff2b21dc
Add support for keeping running bn stats the same across distributed training nodes before eval/save
5 years ago
1f39d15f15
Allow float decay epochs arg for training, works out with step lr math
5 years ago
7b83e67f77
Pass drop connect arg through to EfficientNet models
5 years ago
4748c6dff2
Fix non-prefetch variant of Mixup. Fixes #50
5 years ago
187ecbafbe
Add support for loading args from yaml file (and saving them with each experiment)
5 years ago
Ross Wightman
Csaba Kertesz
datamining99
Antoine Broyelle
AFLALO, Jonathan Isaac
Andrew Lavin
Ross Wightman