cb4cea561a
add arguments to the respective argument groups
2025-01-20 10:54:35 -08:00
634b68ae50
Fix metavar for --input-size
2025-01-20 10:53:46 -08:00
eeee38e972
Avoid unecessary compat break btw train script and nearby timm versions w/ dtype addition.
2025-01-08 21:10:15 -08:00
c173886e75
Merge branch 'main' into caojiaolong-main
2025-01-08 09:11:50 -08:00
1969528296
Fix dtype log when default (None) is used w/o AMP
2025-01-07 11:47:22 -08:00
92f610c982
Add half-precision (bfloat16, float16) support to train & validate scripts. Should push dtype handling into model factory / pretrained load at some point...
2025-01-07 10:25:14 -08:00
40c19f3939
Add wandb project name argument and allow change wandb run name
2025-01-07 16:43:34 +08:00
95d903fd87
Merge branch 'main' of github.com:grodino/pytorch-image-models into grodino-dataset_trust_remote
2024-12-06 11:14:26 -08:00
3a6cc4fb17
Improve wandb logging
2024-11-20 21:04:07 -08:00
620cb4f3cb
Improve the parsable results dump at end of train, stop excessive output, only display top-10.
2024-11-20 16:47:06 -08:00
36b5d1adaa
In dist training, update loss running avg every step, only sync on log updates / final.
2024-11-20 16:47:06 -08:00
ee5f6e76bb
A bit of an optimizer overhaul, added an improved factory, list_optimizers, class helper and add info classes with descriptions, arg configs
2024-11-12 20:49:01 -08:00
9f5c279bad
Update log to describe scheduling behaviour diff w/ warmup_prefix
2024-11-08 11:01:11 -08:00
2dff16fa58
Add --dataset-trust-remote-code to the train.py and validate.py scripts
2024-11-08 18:15:10 +01:00
51ac8d2efb
fix typo in train.py: bathes > batches
2024-11-05 08:53:55 -08:00
015fbe457a
Merge branch 'MengqingCao-npu_support' into device_amp_cleanup
2024-10-18 14:50:44 -07:00
1766a01f96
Cleanup some amp related behaviour to better support different (non-cuda) devices
2024-10-18 13:54:16 -07:00
234f975787
add npu support
2024-10-16 07:13:45 +00:00
4d4bdd64a9
Add --torchcompile-mode args to train, validation, inference, benchmark scripts
2024-10-02 15:17:53 -07:00
4ed93fce93
Fix LR scheduler help in train.py
...
The default is and always has been the cosine scheduler, yet the help states that the default would be the step scheduler. Whatever the intended one was, for backwards compatibility the default should definitely remain cosine, which is why I changed the help comment to reflect that.
2024-07-22 23:04:00 +02:00
d3ce5a8665
Avoid zero division error
2024-07-15 12:45:46 +10:00
e25bbfceec
Fix #2097 a small typo in train.py
2024-04-10 09:40:14 -07:00
5a58f4d3dc
Remove test MESA support, no signal that it's helpful so far
2024-02-10 14:38:01 -08:00
c7ac37693d
Add device arg to validate() calls in train.py
2024-02-04 10:14:57 -08:00
bee0471f91
forward() pass through for ema model, flag for ema warmup, comment about warmup
2024-02-03 16:24:45 -08:00
5e4a4b2adc
Merge branch 'device_flex' into mesa_ema
2024-02-02 09:45:30 -08:00
dd84ef2cd5
ModelEmaV3 and MESA experiments
2024-02-02 09:45:04 -08:00
809a9e14e2
Pass train-crop-mode to create_loader/transforms from train.py args
2024-01-24 16:19:02 -08:00
a48ab818f5
Improving device flexibility in train. Fix #2081
2024-01-20 15:10:20 -08:00
8c663c4b86
Fixed index out of range in case of resume
2024-01-12 23:33:32 -08:00
c50004db79
Allow training w/o validation split set
2024-01-08 09:38:42 -08:00
be0944edae
Significant transforms, dataset, dataloading enhancements.
2024-01-08 09:38:42 -08:00
b5a4fa9c3b
Add pos_weight and support for summing over classes to BCE impl in train scripts
2023-12-30 12:13:06 -08:00
f2fdd97e9f
Add parsable json results output for train.py, tweak --pretrained-path to force head adaptation
2023-12-22 11:18:25 -08:00
60b170b200
Add --pretrained-path arg to train script to allow passing local checkpoint as pretrained. Add missing/unexpected keys log.
2023-12-11 12:10:29 -08:00
a83e9f2d3b
forward & backward in same no_sync context, slightly easier to read that splitting
2023-04-20 08:14:05 -07:00
4cd7fb88b2
clip gradients with update
2023-04-19 23:36:20 -07:00
df81d8d85b
Cleanup gradient accumulation, fix a few issues, a few other small cleanups in related code.
2023-04-19 23:11:00 -07:00
ab7ca62a6e
Merge branch 'main' of github.com:rwightman/pytorch-image-models into wip-voidbag-accumulate-grad
2023-04-19 11:08:12 -07:00
ec6cca4b37
Add head-init-scale and head-init-bias args that works for all models, fix #1718
2023-04-14 17:59:23 -07:00
43e6143bef
Fix #1712 broken support for AMP w/ PyTorch < 1.10. Disable loss scaler for bfloat16
2023-03-11 15:26:09 -08:00
7f29a46d44
Add gradient accumulation option to train.py
...
option: iters-to-accum(iterations to accmulate)
Gradient accumulation improves training performance(samples/s).
It can reduce the number of parameter sharing between each node.
This option can be helpful when network is bottleneck.
Signed-off-by: Taeksang Kim <voidbag@puzzle-ai.com>
2023-02-06 09:24:48 +09:00
81ca323751
Davit update formatting and fix grad checkpointing ( #7 )
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fixed head to gap->norm->fc as per convnext, along with option for norm->gap->fc
failed tests due to clip convnext models, davit tests passed
2023-01-15 14:34:56 -08:00
d5e7d6b27e
Merge remote-tracking branch 'origin/main' into refactor-imports
2022-12-09 14:49:44 -08:00
3d6bc42aa1
Put validation loss under amp_autocast
...
Secured the loss evaluation under the amp, avoiding function to operate on float16
2022-12-09 12:03:23 +01:00
927f031293
Major module / path restructure, timm.models.layers -> timm.layers, add _ prefix to all non model modules in timm.models
2022-12-06 15:00:06 -08:00
dbe7531aa3
Update scripts to support torch.compile(). Make --results_file arg more consistent across benchmark/validate/inference. Fix #1570
2022-12-05 10:21:34 -08:00
9da7e3a799
Add crop_mode for pretraind config / image transforms. Add support for dynamo compilation to benchmark/train/validate
2022-12-05 10:21:34 -08:00
4714a4910e
Merge pull request #1525 from TianyiFranklinWang/main
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✏️ fix typo
2022-11-03 20:55:43 -07:00
ddd6361904
Update train.py
...
fix typo args.in_chanes
2022-11-01 16:55:05 +09:00
Josua Rieder
Ross Wightman
Jiao-Long Cao
Sina Hajimiri
Augustin Godinot
MengqingCao
Zirunis
Tianyi Wang
lorenzbaraldi
Taeksang Kim
Fredo Guan
Ross Wightman
klae01