GitLab

* fix galore lr display with lr schedulers

* style

* add some tests to check for displayed lrs

* copy-paste err for warmup steps

* standardize the default lr to be only in the optimizer

* trying out my luck with the reads

* add gather_use_object arguments

* fix name and pass the CI test for Seq2SeqTrainer

* make style

* make it to functools

* fix typo

* add accelerate version:

* adding warning

* Update src/transformers/trainer.py
Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com>

* make style

* Update src/transformers/training_args.py

* check function move to initial part

* add test for eval_use_gather_object

---------
Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com>

* Skip tests properly

* [test_all]

* Add 'reason' as kwarg for skipTest

* [test_all] Fix up

* [test_all]

* Support multiple validation datasets when dataloader_persistent_workers=True

* Test support of multiple validation datasets

* Implement JSON dump conversion for torch_dtype in TrainingArguments

* Add unit test for converting torch_dtype in TrainingArguments to JSON

* move unit test for converting torch_dtype into TrainerIntegrationTest class

* reformating using ruff

* convert dict_torch_dtype_to_str to private method _dict_torch_dtype_to_str

---------
Co-authored-by: jun.4 <jun.4@kakaobrain.com>

* Enforce saving at end of training

* Fix test

* Rework test

* Fixup tests'

* Update comment based on sourab feedback

* Clean

* add fix

* update import

* updated dicts and comments

* remove prints

* Update testing_utils.py

* add V1 - adalomo not working yet

* add todo docs + refactor from comments

* adjust LR

* add docs

* add more elaborated test

* Apply suggestions from code review
Co-authored-by: Zach Mueller <muellerzr@gmail.com>

* fix

* push

* add accelerate check

* fix DDP case

* Apply suggestions from code review
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* fix

* init kwargs

* safely add attribute

* revert to enum logic

* Update src/transformers/trainer.py

---------
Co-authored-by: Zach Mueller <muellerzr@gmail.com>
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Introduce configured_state

* Include note on tuning

* Allow for users to have defined a state already

* Include tests

* Add note on hpam tune

* Guard a bit better

* Update src/transformers/training_args.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Update src/transformers/training_args.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Finish rebase

* Finish rebase

* Guard carefully

* Fixup test

* Refactor

* Fin refactor

* Comment

* Update wrt feedback

---------
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* update to ROCm 6.0.2 and test MI300

* add callers for mi300

* update dockerfile

* fix trainer tests

* remove apex

* style

* Update tests/trainer/test_trainer_seq2seq.py

* Update tests/trainer/test_trainer_seq2seq.py

* Update tests/trainer/test_trainer_seq2seq.py

* Update tests/trainer/test_trainer_seq2seq.py

* update to torch 2.3

* add workflow dispatch target

* we may need branches: mi300-ci after all

* nit

* fix docker build

* nit

* add check runner

* remove docker-gpu

* fix issues

* fix

---------
Co-authored-by: Yih-Dar <2521628+ydshieh@users.noreply.github.com>
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>

* Added cache clearing for GPU efficiency.

* Added cache clearing for GPU efficiency.

* Added batch_eval_metrics capability

* Ran make fixup

* Fixed bug

* Fixed whitespace issue

* Fixed outdated condition

* Updated docstrings with instructions for batch_eval_metrics. Updated end of dataloader logic

* Added first version of batch_eval_metrics Trainer test

* Fixed batch_eval_metrics Trainer tests for both eval and predict

* Fixed batch_eval_metrics behavior for new Trainer variables

* Fixed batch_eval_metrics Trainer tests

* Ran fixup

* Trainer: load checkpoint model with multiple adapters

* Trainer._load_from_checkpoint support multiple active adapters

* PeftModel.set_adapter does not support multiple adapters yet

* Trainer._load_from_checkpoint test multiple adapters

---------
Co-authored-by: Clara Luise Pohland <clara-luise.pohland@telekom.de>

* Use unwrap with the one in accelerate

* oups

* update unwrap

* fix

* wording

* raise error instead

* comment

* doc

* Update src/transformers/modeling_utils.py
Co-authored-by: Zach Mueller <muellerzr@gmail.com>

* style

* put else

---------
Co-authored-by: Zach Mueller <muellerzr@gmail.com>

* Alias

* Note alias

* Tests and src

* Rest

* Clean

* Change typing?

* Fix tests

* Deprecation versions

* Raise relevent err

* Use type instead

* Start rework

* Fix failing test

* Include max

* Update src/transformers/trainer.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

---------
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

* add gradient_accumulation_kwargs to AcceleratorConfig

* add suggestions from @muellerzr to docstrings, new behavior and tests

* Documentation suggestions from @muellerz
Co-authored-by: Zach Mueller <muellerzr@gmail.com>

* addressed @muellerzr comments regarding tests and test utils

* moved accelerate version to top of file.

* @muellerzr's variable fix
Co-authored-by: Zach Mueller <muellerzr@gmail.com>

* address @amyeroberts. fix tests and docstrings

* address @amyeroberts additional suggestions

---------
Co-authored-by: Yu Chin Fabian Lim <flim@sg.ibm.com>
Co-authored-by: Zach Mueller <muellerzr@gmail.com>

* add functions to get number of params which require grad, get optimizer group for parameters and get learning rates of param groups to trainer.py

* add tests and raise ValueError when optimizer is None

* add second layer to test and freeze its weigths

* check if torch is available before running tests

* use decorator to check if torch is available
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* fix test indentation
Co-authored-by: Zach Mueller <muellerzr@gmail.com>

---------
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
Co-authored-by: Zach Mueller <muellerzr@gmail.com>

* Add cosine_with_min_lr scheduler

* Update error message for missing min_lr or min_lr_rate

* add warnings if training args differ from checkpoint args stored in trainer_state.json

* run formatting and styling

* add a test

* format and styling

---------
Co-authored-by: Jonathan Flynn <jonl.flynn@guardian.co.uk>

* add galore v1

* add import

* add tests and doc

* fix doctest

* forward contrib credits from discussions

* forward contrib credits from discussions

* Apply suggestions from code review
Co-authored-by: Zach Mueller <muellerzr@gmail.com>

* fix failing tests'

* switch to `optim_target_modules` and clarify docs

* more clarification

* enhance lookup logic

* update a test to add peak memory

* add regex, all-linear and single string support

* add layer-wise optimization through DummyOptimizers and LRSchedulers

* forward contrib credits from discussions and original idea

* add a section about DDP not supported in layerwise

* Update src/transformers/trainer.py
Co-authored-by: Zach Mueller <muellerzr@gmail.com>

* fix self

* check only if layer_wise

* Update src/transformers/training_args.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* oops

* make use of intervals

* clarify comment

* add matching tests

* GaLoRe -> GaLore

* move to `get_scheduler`

* add note on docs

* add a warning

* adapt a bit the docs

* update docstring

* support original API

* Update docs/source/en/trainer.md

* slightly refactor

* Update docs/source/en/trainer.md
Co-authored-by: Matthew Douglas <38992547+matthewdouglas@users.noreply.github.com>

* Update src/transformers/training_args.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* fix args parsing and add tests

* remove warning for regex

* fix type hint

* add note about extra args

* make `is_regex` return optional

---------

Co-authored-by: Maxime <maximegmd @users.noreply.github.com>
Co-authored-by: Wing Lian <winglian @users.noreply.github.com>
Co-authored-by: Zach Mueller <muellerzr@gmail.com>
Co-authored-by: hiyouga <hiyouga@users.noreply.github.com>
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
Co-authored-by: Matthew Douglas <38992547+matthewdouglas@users.noreply.github.com>

[tests] use the correct `n_gpu` in `TrainerIntegrationTest::test_train_and_eval_dataloaders` for XPU (#29307)

* fix n_gpu

* fix style

Fully revert atomic checkpointing

* Fix deprecated arg issue

* Trainer check too

* Check for dict or dataclass

* Simplify, make config always AcceleratorConfig

* Upstream to Trainer

* handle peft + compiled models

* add tests

* fixup

* adapt from suggestions

* clarify comment

* add RMSProp to Trainer

* revert some change

* Update src/transformers/trainer.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

---------
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* FIx trainer test

* Update tests/trainer/test_trainer.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

---------
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Script & Manual edition

* Update

FIX [`Trainer` / tags]: Fix trainer + tags when users do not pass `"tags"` to `trainer.push_to_hub()` (#29009)

* fix trainer tags

* add test

* Introduce acceleratorconfig dataclass

* Extra second warn

* Move import

* Try moving import under is_accelerate_available

* Quality

* Apply suggestions from code review
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Clean

* Remove to_kwargs

* Change version

* Improve tests by including dispatch and split batches

* Improve reliability

* Update tests/trainer/test_trainer.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Fixup tests and review nits

* Make tests pass

* protect import

* Protect import

* Empty-Commit

* Make training_args.to_dict handle the AcceleratorConfig

---------
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

Co-authored-by: unit_test <test@unit.com>

* avoid root logger's level being changed

---------
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>

Fixup test

* Fix test

* Skip

* move code to Trainer.evaluate to enable use of that function with multiple datasets

* test

* update doc string

* and a tip

* forgot the type

---------
Co-authored-by: Prof. Peter Schneider-Kamp <jps@ordbogen.com>

* Fix test for multi-GPU

* WIth CPU handle

* Fuffill request

* Add test

* Better test

* Apply suggestions from code review
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

* Better test

* Better test

* MOre comments

---------
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

* Fix passing scheduler-specific kwargs through TrainingArguments `lr_scheduler_kwargs`

* Added test for lr_scheduler_kwargs

* dvclive callback: warn instead of fail when logging non-scalars

* tests: log lr as scalar