* trainer and finetune_trainer enhancements and fixes
* add fallback default
* move the fixing of incorrect keys back into finetune trainer
* s/eval/val/ to match the split
* trainer can now use a different prefix than eval_ for metrics
* document new arg
* Apply suggestions from code review
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* use 'eval' as the default for metric_key_prefix
* complete adjust var names + disambiguate
* fix logger
* add clarifying comment
* add clarifying comment
* style
* Apply suggestions from code review
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update src/transformers/trainer.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* complete removal of optional for metric_key_prefix
* Apply suggestions from code review
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Reorganize example folder
* Continue reorganization
* Change requirements for tests
* Final cleanup
* Finish regroup with tests all passing
* Copyright
* Requirements and readme
* Make a full link for the documentation
* Address review comments
* Apply suggestions from code review
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
* Add symlink
* Reorg again
* Apply suggestions from code review
Co-authored-by: Thomas Wolf <thomwolf@users.noreply.github.com>
* Adapt title
* Update to new strucutre
* Remove test
* Update READMEs
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
Co-authored-by: Thomas Wolf <thomwolf@users.noreply.github.com>
* Remove "Model" suffix from Flax models to look more 🤗
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>
* Initial working (forward + backward) for Flax MLM training example.
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>
* Simply code
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>
* Addressing comments, using module and moving to LM task.
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>
* Restore parameter name "module" wrongly renamed model.
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>
* Restore correct output ordering...
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>
* Actually commit the example 😅
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>
* Add FlaxBertModelForMaskedLM after rebasing.
Signed-off-by: Morgan Funtowicz <funtowiczmo@gmail.com>
* Make it possible to initialize the training from scratch
Signed-off-by: Morgan Funtowicz <funtowiczmo@gmail.com>
* Reuse flax linen example of cross entropy loss
Signed-off-by: Morgan Funtowicz <funtowiczmo@gmail.com>
* Added specific data collator for flax
Signed-off-by: Morgan Funtowicz <funtowiczmo@gmail.com>
* Remove todo for data collator
Signed-off-by: Morgan Funtowicz <funtowiczmo@gmail.com>
* Added evaluation step
Signed-off-by: Morgan Funtowicz <funtowiczmo@gmail.com>
* Added ability to provide dtype to support bfloat16 on TPU
Signed-off-by: Morgan Funtowicz <funtowiczmo@gmail.com>
* Enable flax tensorboard output
Signed-off-by: Morgan Funtowicz <funtowiczmo@gmail.com>
* Enable jax.pmap support.
Signed-off-by: Morgan Funtowicz <funtowiczmo@gmail.com>
* Ensure batches are correctly sized to be dispatched with jax.pmap
Signed-off-by: Morgan Funtowicz <funtowiczmo@gmail.com>
* Enable bfloat16 with --fp16 cmdline args
Signed-off-by: Morgan Funtowicz <funtowiczmo@gmail.com>
* Correctly export metrics to tensorboard
Signed-off-by: Morgan Funtowicz <funtowiczmo@gmail.com>
* Added dropout and ability to use it.
Signed-off-by: Morgan Funtowicz <funtowiczmo@gmail.com>
* Effectively enable & disable during training and evaluation steps.
Signed-off-by: Morgan Funtowicz <funtowiczmo@gmail.com>
* Oops.
Signed-off-by: Morgan Funtowicz <funtowiczmo@gmail.com>
* Enable specifying kernel initializer scale
Signed-off-by: Morgan Funtowicz <funtowiczmo@gmail.com>
* Style.
Signed-off-by: Morgan Funtowicz <funtowiczmo@gmail.com>
* Added warmup step to the learning rate scheduler.
Signed-off-by: Morgan Funtowicz <funtowiczmo@gmail.com>
* Fix typo.
Signed-off-by: Morgan Funtowicz <funtowiczmo@gmail.com>
* Print training loss
Signed-off-by: Morgan Funtowicz <funtowiczmo@gmail.com>
* Make style
Signed-off-by: Morgan Funtowicz <funtowiczmo@gmail.com>
* fix linter issue (flake8)
Signed-off-by: Morgan Funtowicz <funtowiczmo@gmail.com>
* Fix model matching
Signed-off-by: Morgan Funtowicz <funtowiczmo@gmail.com>
* Fix dummies
Signed-off-by: Morgan Funtowicz <funtowiczmo@gmail.com>
* Fix non default dtype on Flax models
Signed-off-by: Morgan Funtowicz <funtowiczmo@gmail.com>
* Use the same create_position_ids_from_input_ids for FlaxRoberta
Signed-off-by: Morgan Funtowicz <funtowiczmo@gmail.com>
* Make Roberta attention as Bert
Signed-off-by: Morgan Funtowicz <funtowiczmo@gmail.com>
* fix copy
Signed-off-by: Morgan Funtowicz <funtowiczmo@gmail.com>
* Wording.
Co-authored-by: Marc van Zee <marcvanzee@gmail.com>
Co-authored-by: Marc van Zee <marcvanzee@gmail.com>
* Add new SQUAD example
* Same with a task-specific Trainer
* Address review comment.
* Small fixes
* Initial work for XLNet
* Apply suggestions from code review
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Final clean up and working XLNet script
* Test and debug
* Final working version
* Add new SQUAD example
* Same with a task-specific Trainer
* Address review comment.
* Small fixes
* Initial work for XLNet
* Apply suggestions from code review
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Final clean up and working XLNet script
* Test and debug
* Final working version
* Add tick
* Update README
* Address review comments
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Without this fix, training a `BARTForSequenceClassification` model with `run_pl_glue.py` gives `TypeError: forward() got an unexpected keyword argument 'token_type_ids'`, because BART does not have token_type_ids. I've solved this issue in the same way as it's solved for the "distilbert" model, and I can train BART models on SNLI without errors now.
* fix DP case on multi-gpu
* make executable
* test all 3 modes
* use the correct check for distributed
* dp doesn't need a special case
* restore original name
* cleanup
* implement support for run-time dependency version checking
* try not escaping !
* use findall that works on py36
* small tweaks
* autoformatter worship
* simplify
* shorter names
* add support for non-versioned checks
* add deps
* revert
* tokenizers not required, check version only if installed
* make a proper distutils cmd and add make target
* tqdm must be checked before tokenizers
* workaround the DistributionNotFound peculiar setup
* handle the rest of packages in setup.py
* fully sync setup.py's install_requires - to check them all
* nit
* make install_requires more readable
* typo
* Update setup.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* restyle
* add types
* simplify
* simplify2
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Support BERT relative position embeddings
* Fix typo in README.md
* Address review comment
* Fix failing tests
* [tiny] Fix style_doc.py check by adding an empty line to configuration_bert.py
* make fix copies
* fix configs of electra and albert and fix longformer
* remove copy statement from longformer
* fix albert
* fix electra
* Add bert variants forward tests for various position embeddings
* [tiny] Fix style for test_modeling_bert.py
* improve docstring
* [tiny] improve docstring and remove unnecessary dependency
* [tiny] Remove unused import
* re-add to ALBERT
* make embeddings work for ALBERT
* add test for albert
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* replace init_ddp_connection for index init
* style
* add finetune test
* add test data
* move generate tensors to device
* add test on EM metric
* style
* allow multi process test
* keep gloo process group for retrieval
* add multi-gpu test
* use custom accelerator
* clean test finetune
* minor
* style
* style
* typo
* use python call instead of imported main fumction
* return_dict fix in modeling_rag
* use float32 in retrieval
* store as float32 as well in the custom knowledge dataset example
* style
* rename to finetune_rag
* style
* update readme
* rename utils and callbacks to utils_rag and callbacks_rag
* fix test
* patrick's comments
* generate dummy data in the finetue test script
* remove dummy data files
* style
* <small>tiny typo</small>
* Tokenizers: ability to load from model subfolder
* use subfolder for local files as well
* Uniformize model shortcut name => model id
* from s3 => from huggingface.co
Co-authored-by: Quentin Lhoest <lhoest.q@gmail.com>
* Put models in subfolders
* Styling
* Fix imports in tests
* More fixes in test imports
* Sneaky hidden imports
* Fix imports in doc files
* More sneaky imports
* Finish fixing tests
* Fix examples
* Fix path for copies
* More fixes for examples
* Fix dummy files
* More fixes for example
* More model import fixes
* Is this why you're unhappy GitHub?
* Fix imports in conver command
* Use the CI to identify failing tests
* Remove from all examples and tests
* More default switch
* Fixes
* More test fixes
* More fixes
* Last fixes hopefully
* Use the CI to identify failing tests
* Remove from all examples and tests
* More default switch
* Fixes
* More test fixes
* More fixes
* Last fixes hopefully
* Run on the real suite
* Fix slow tests
* Fixing roberta for slow-fast tests
* WIP getting equivalence on pipelines
* slow-to-fast equivalence - working on question-answering pipeline
* optional FAISS tests
* Pipeline Q&A
* Move pipeline tests to their own test job again
* update tokenizer to add sequence id methods
* update to tokenizers 0.9.4
* set sentencepiecce as optional
* clean up squad
* clean up pipelines to use sequence_ids
* style/quality
* wording
* Switch to use_fast = True by default
* update tests for use_fast at True by default
* fix rag tokenizer test
* removing protobuf from required dependencies
* fix NER test for use_fast = True by default
* fixing example tests (Q&A examples use slow tokenizers for now)
* protobuf in main deps extras["sentencepiece"] and example deps
* fix protobug install test
* try to fix seq2seq by switching to slow tokenizers for now
* Update src/transformers/tokenization_utils_base.py
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
* Update src/transformers/tokenization_utils_base.py
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
The new run_ner.py script tries to run prediction on the input
test set `datasets["test"]`, but it should be the tokenized set
`tokenized_datasets["test"]`
* add a multi-gpu job for all example tests
* run only ported tests
* rename
* explain why env is re-activated on each step
* mark all unported/checked tests with @require_torch_non_multigpu_but_fix_me
* style
* Apply suggestions from code review
Co-authored-by: Sam Shleifer <sshleifer@gmail.com>
Co-authored-by: Sam Shleifer <sshleifer@gmail.com>
* add training tests
* correct longformer
* fix docs
* fix some tests
* fix some more train tests
* remove ipdb
* fix multiple edge case model training
* fix funnel and prophetnet
* clean gpt models
* undo renaming of albert
* Add new token classification example
* Remove txt file
* Add test
* With actual testing done
* Less warmup is better
* Update examples/token-classification/run_ner_new.py
Co-authored-by: Thomas Wolf <thomwolf@users.noreply.github.com>
* Address review comments
* Fix test
* Make Lysandre happy
* Last touches and rename
* Rename in tests
* Address review comments
* More run_ner -> run_ner_old
Co-authored-by: Thomas Wolf <thomwolf@users.noreply.github.com>
* use decorator
* remove hardcoded paths
* make the test use more data and do real quality tests
* shave off 10 secs
* add --eval_beams 2, reformat
* reduce train size, use smaller custom dataset
* change TokenClassificationTask class methods to static methods
Since we do not require self in the class methods of TokenClassificationTask we should probably switch to static methods. Also, since the class TokenClassificationTask does not contain a constructor it is currently unusable as is. By switching to static methods this fixes the issue of having to document the intent of the broken class.
Also, since the get_labels and read_examples_from_file methods are ought to be implemented. Static method definitions are unchanged even after inheritance, which means that it can be overridden, similar to other class methods.
* Trigger Build
Co-authored-by: Lysandre <lysandre.debut@reseau.eseo.fr>
* make it possible to invoke testconf.py in both test suites without crashing on having the same option added
* perl -pi -e 's|--make_reports|--make-reports|' to be consistent with other opts
* add `pytest --make-reports` to all CIs (and artifacts)
* fix
* Make line by line optional in run_mlm
* Add option to disable dynamic padding
* Add option to plm too and update README
* Typos
* More typos
* Even more typos
* Apply suggestions from code review
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
* Finish the cleanup of the language-modeling examples
* Update main README
* Apply suggestions from code review
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
* Apply suggestions from code review
Co-authored-by: Thomas Wolf <thomwolf@users.noreply.github.com>
* Propagate changes
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
Co-authored-by: Thomas Wolf <thomwolf@users.noreply.github.com>
* Add a template for example scripts and apply it to mlm
* Formatting
* Fix test
* Add plm script
* Add a template for example scripts and apply it to mlm
* Formatting
* Fix test
* Add plm script
* Add a template for example scripts and apply it to mlm
* Formatting
* Fix test
* Add plm script
* Styling
