a5310a3451
Merge remote-tracking branch 'origin/benchmark-fixes-vit_hybrids' into pit_and_vit_update
4 years ago
d584e7f617
Support for huggingface hub via create_model and default_cfgs.
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* 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
4 years ago
2db2d87ff7
Add epoch-repeats arg to multiply the number of dataset passes per epoch. Currently for iterable datasets (read TFDS wrapper) only.
4 years ago
d8e69206be
Merge pull request #419 from rwightman/byob_vgg_models
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More models, GPU-Efficient Nets, RepVGG, classic VGG, and flexible Byob backbone.
4 years ago
0356e773f5
Default to native PyTorch AMP instead of APEX amp. Too many APEX issues cropping up lately.
4 years ago
b4e216e377
Fix a few small things.
4 years ago
5114c214fc
Change the Python interpreter to Python 3.x in the scripts
4 years ago
2a8c4dc63b
Add validation script update for using test_input_size in model default_cfgs
4 years ago
38d8f67570
Fix potential issue with change to num_classes arg in train/validate.py defaulting to None (rely on model def / default_cfg)
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
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
ce69de70d3
Add 21k weight urls to vision_transformer. Cleanup feature_info for preact ResNetV2 (BiT) models
4 years ago
de6046e213
Initial commit for dataset / parser reorg to support additional datasets / types
4 years ago
8ffdc5910a
test_time_pool would be set to a non-False value even if test-time pooling is not available
4 years ago
e8ca45854c
More models in sotabench, more control over sotabench run, dataset filename extraction consistency
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
ad150e7018
Update results csv file rank/diff script and small validate script tweak for batch validation
4 years ago
ecdeb470f2
Cleanup real labels in validate.py, no need to track original, will do that via exteran script
4 years ago
c53ec33ae0
Add synset/label indices for results generation. Add 'valid labels' to validation script to support imagenet-a/r label subsets properly.
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
4e61c6a12d
Cleanup, refactoring of Feature extraction code, add tests, fix tests, non hook feature extraction working with torchscript
4 years ago
d23a2697d0
Working on feature extraction, interfaces refined, a number of models working, some in progress.
4 years ago
d3ee3de96a
Update validation script first batch prime and clear cuda cache between multi-model runs
4 years ago
78fa0772cc
Leverage python hierachical logger
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with this update one can tune the kind of logs generated by timm but
training and inference traces are unchanged
5 years ago
88129b2569
Add set_layer_config contextmgr to adjust all layer configs at once, use in create_module with new args. Remove a few old warning causing constant annotations for jit.
5 years ago
eb7653614f
Monster commit, activation refactor, VoVNet, norm_act improvements, more
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* refactor activations into basic PyTorch, jit scripted, and memory efficient custom auto
* implement hard-mish, better grad for hard-swish
* add initial VovNet V1/V2 impl, fix #151
* VovNet and DenseNet first models to use NormAct layers (support BatchNormAct2d, EvoNorm, InplaceIABN)
* Wrap IABN for any models that use it
* make more models torchscript compatible (DPN, PNasNet, Res2Net, SelecSLS) and add tests
5 years ago
02a30411ad
Replace fp16 with amp support for validate.py script
5 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
5 years ago
53c47479c4
Batch validation batch size adjustment, tweak L2 crop pct
5 years ago
1daa303744
Add support to Dataset for class id mapping file, clean up a bit of old logic. Add results file arg for validation and update script.
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
7a92caa560
Add basic image folder style dataset to read directly out of tar files, example in validate.py
5 years ago
6cdf35e670
Add explicit half/fp16 support to loader and validation script
5 years ago
edb425ea48
Add crop_pct arg to validate, extra fields to csv output, 'all' filters pretrained
5 years ago
c6b32cbe73
A number of tweaks to arguments, epoch handling, config
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* reorganize train args
* allow resolve_data_config to be used with dict args, not just arparse
* stop incrementing epoch before save, more consistent naming vs csv, etc
* update resume and start epoch handling to match above
* stop auto-incrementing epoch in scheduler
5 years ago
171c0b88b6
Add model registry and model listing fns, refactor model_factory/create_model fn
5 years ago
6fc886acaf
Remove all prints, change most to logging calls, tweak alignment of batch logs, improve setup.py
5 years ago
aa4354f466
Big re-org, working towards making pip/module as 'timm'
5 years ago
b9f8d40b10
Fix pretrained override logic for validate, checkpoint always trump pretrained flag during model create
5 years ago
9bcd65181b
Add exponential moving average for model weights + few other additions and cleanup
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* ModelEma class added to track an EMA set of weights for the model being trained
* EMA handling added to train, validation and clean_checkpoint scripts
* Add multi checkpoint or multi-model validation support to validate.py
* Add syncbn option (APEX) to train script for experimentation
* Cleanup interface of CheckpointSaver while adding ema functionality
6 years ago
4bb5e9b224
Ported Tensorflow pretrained EfficientNet weights and some model cleanup
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* B0-B3 weights ported from TF with close to paper accuracy
* Renamed gen_mobilenet to gen_efficientnet since scaling params go well beyond 'mobile' specific
* Add Tensorflow preprocessing option for closer images to source repo
6 years ago
db1fe34d0c
Update a few comment, add some references
6 years ago
0562b91c38
Add per model crop pct, interpolation defaults, tie it all together
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* create one resolve fn to pull together model defaults + cmd line args
* update attribution comments in some models
* test update train/validation/inference scripts
6 years ago
9c3859fb9c
Uniform pretrained model handling.
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* All models have 'default_cfgs' dict
* load/resume/pretrained helpers factored out
* pretrained load operates on state_dict based on default_cfg
* test all models in validate
* schedule, optim factor factored out
* test time pool wrapper applied based on default_cfg
6 years ago
Ross Wightman