* add DataCollatorBatchFlattening
* Update data_collator.py
* change name
* new FA2 flow if position_ids is provided
* add comments
* minor fix
* minor fix data collator
* add test cases for models
* add test case for data collator
* remove extra code
* formating for ruff check and check_repo.py
* ruff format
ruff format tests src utils
* custom_init_isort.py
* 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>
* Pass datasets trust_remote_code
* Pass trust_remote_code in more tests
* Add trust_remote_dataset_code arg to some tests
* Revert "Temporarily pin datasets upper version to fix CI"
This reverts commit b7672826ca.
* Pass trust_remote_code in librispeech_asr_dummy docstrings
* Revert "Pin datasets<2.20.0 for examples"
This reverts commit 833fc17a3e.
* Pass trust_remote_code to all examples
* Revert "Add trust_remote_dataset_code arg to some tests" to research_projects
* Pass trust_remote_code to tests
* Pass trust_remote_code to docstrings
* Fix flax examples tests requirements
* Pass trust_remote_dataset_code arg to tests
* Replace trust_remote_dataset_code with trust_remote_code in one example
* Fix duplicate trust_remote_code
* Replace args.trust_remote_dataset_code with args.trust_remote_code
* Replace trust_remote_dataset_code with trust_remote_code in parser
* Replace trust_remote_dataset_code with trust_remote_code in dataclasses
* Replace trust_remote_dataset_code with trust_remote_code arg
* 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>
* 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>
* immutability fix for seq2seq as well as immutability tests for the collators
* ensure we don't act on none labels and formatting
* remove tf/pt in respective tests as they are not required
* more type error fixes tf/np
* remove todo
* apply suggestions from code review
* formatting / style
* 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>
* fix seq2seq data collator to respect the given padding strategy
further added tests for the seq2seq data collator in the style of the `data_collator_for_token_classification` (pt, tf, np)
* formatting and change bool equals "==" to "is"
* add missed return types in tests
* update numpy test as it can handle unequal shapes, not like pt or tf
* Introduce saveable callbacks
* Add note
* Test for non-present and flag
* Support early stopping and refusing to train further
* Update docstring
* More saving
* Import oopsie
* Apply suggestions from code review
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Make it go through TrainerArguments
* Document
* Fix test
* Apply suggestions from code review
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Rework to allow for duplicates
* CLean
* Fix failing tests
---------
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* 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 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 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>
* 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>
* 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>
* try to stylify using ruff
* might need to remove these changes?
* use ruf format andruff check
* use isinstance instead of type comparision
* use # fmt: skip
* use # fmt: skip
* nits
* soem styling changes
* update ci job
* nits isinstance
* more files update
* nits
* more nits
* small nits
* check and format
* revert wrong changes
* actually use formatter instead of checker
* nits
* well docbuilder is overwriting this commit
* revert notebook changes
* try to nuke docbuilder
* style
* fix feature exrtaction test
* remve `indent-width = 4`
* fixup
* more nits
* update the ruff version that we use
* style
* nuke docbuilder styling
* leve the print for detected changes
* nits
* Remove file I/O
Co-authored-by: charliermarsh
<charlie.r.marsh@gmail.com>
* style
* nits
* revert notebook changes
* Add # fmt skip when possible
* Add # fmt skip when possible
* Fix
* More ` # fmt: skip` usage
* More ` # fmt: skip` usage
* More ` # fmt: skip` usage
* NIts
* more fixes
* fix tapas
* Another way to skip
* Recommended way
* Fix two more fiels
* Remove asynch
Remove asynch
---------
Co-authored-by: charliermarsh <charlie.r.marsh@gmail.com>
* Have seq2seq just use gather
* Change
* Reset after
* Make slow
* Apply suggestions from code review
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* Clean
* Simplify and just use gather
* Update tests/trainer/test_trainer_seq2seq.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* gather always for seq2seq
---------
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Safetensors serialization by default
* First pass on the tests
* Second pass on the tests
* Third pass on the tests
* Fix TF weight loading from TF-format safetensors
* Specific encoder-decoder fixes for weight crossloading
* Add VisionEncoderDecoder fixes for TF too
* Change filename test for pt-to-tf
* One missing fix for TFVisionEncoderDecoder
* Fix the other crossload test
* Support for flax + updated tests
* Apply suggestions from code review
Co-authored-by: Sanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com>
* Sanchit's comments
* Sanchit's comments 2
* Nico's comments
* Fix tests
* cleanup
* Apply suggestions from code review
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
---------
Co-authored-by: Matt <rocketknight1@gmail.com>
Co-authored-by: Sanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com>
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Support runs/
* Upload runs folder as part of push to hub
* Add a test
* Add to test deps
* Update with proposed solution from Slack
* Ensure that repo gets deleted in tests
* enable optuna multi-objectives feature
Signed-off-by: Wang, Yi A <yi.a.wang@intel.com>
* Apply suggestions from code review
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* update hpo doc
* update docstring
Signed-off-by: Wang, Yi A <yi.a.wang@intel.com>
* extend direction to List[str] type
Signed-off-by: Wang, Yi A <yi.a.wang@intel.com>
* Update src/transformers/integrations/integration_utils.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
---------
Signed-off-by: Wang, Yi A <yi.a.wang@intel.com>
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Make training args fully immutable
* Working tests, PyTorch
* In test_trainer
* during testing
* Use proper dataclass way
* Fix test
* Another one
* Fix tf
* Lingering slow
* Exception
* Clean
* dim, and rm copy
* Don't rm copy for now
* Oops
* pad index
* Should be a working test
* Tickle down ddp timeout
* Put fix back in now that testing locally is done
* Better comment specifying timeout
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
---------
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Fix TypeError: Object of type int64 is not JSON serializable
* Convert numpy.float64 and numpy.int64 to float and int for json serialization
* Black reformatted examples/pytorch/token-classification/run_ner_no_trainer.py
* * make style
* Refactor hyperparameter search backends
* Simpler refactoring without abstract base class
* black
* review comments:
specify name in class
use methods instead of callable class attributes
name constant better
* review comments: safer bool checking, log multiple available backends
* test ALL_HYPERPARAMETER_SEARCH_BACKENDS vs HPSearchBackend in unit test, not module. format with black.
* copyright
* Added lion and paged optimizers and made original tests pass.
* Added tests for paged and lion optimizers.
* Added and fixed optimizer tests.
* Style and quality checks.
---------
Co-authored-by: younesbelkada <younesbelkada@gmail.com>
* Add Trainer support for ReduceLROnPlateau
Fixes#16503
* Remove training argument and add default instance
---------
Co-authored-by: mmeloux <maxime.meloux@loria.fr>
* Result of black 23.1
* Update target to Python 3.7
* Switch flake8 to ruff
* Configure isort
* Configure isort
* Apply isort with line limit
* Put the right black version
* adapt black in check copies
* Fix copies
* Add XLA torchrun support
* Clarify that currently DDP doesn't work with torch.distributed XLA backend yet
* Enable DDP with torchrun and XLA (now available in PT-XLA 1.13)
* Add check for AWS Neuron availability and AWS Neuron specific compiler flag
* Change the new test's name to TestTrainerDistributedNeuronCore
* Remove "assert" and replace raised exception
* Remove compiler flag as it is optional. If needed, will be another PR.
* Use TORCHELASTIC_RUN_ID to determine whether torchrun is used
