GitLab

* Cleanup and unify Trainer/TFTrainer

* Forgot to adapt TFTrainingArgs

* In tf scripts n_gpu -> n_replicas

* Update src/transformers/training_args.py
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>

* Address review comments

* Formatting

* Fix typo
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>

* Add support for past states

* Style and forgotten self

* You mean, documenting is not enough? I have to actually add it too?

* Add memory support during evaluation

* Fix tests in eval and add TF support

* No need to change this line anymore

* Documentation for the Trainer API

* Address review comments

* Address comments

* manually set device in trainer args

* check if current device is cuda before set_device

* Explicitly set GPU ID when using single GPU

This addresses https://github.com/huggingface/transformers/issues/4657#issuecomment-642228099

* add tpu and torchscipt for benchmark

* fix name in tests

* "fix email"

* make style

* better log message for tpu

* add more print and info for tpu

* allow possibility to print tpu metrics

* correct cpu usage

* fix test for non-install

* remove bugus file

* include psutil in testing

* run a couple of times before tracing in torchscript

* do not allow tpu memory tracing for now

* make style

* add torchscript to env

* better name for torch tpu
Co-authored-by: Patrick von Platen <patrick@huggingface.co>

* Better None gradients handling

* Apply Style

* Apply Style

* Create a loss class per task to compute its respective loss

* Add loss classes to the ALBERT TF models

* Add loss classes to the BERT TF models

* Add question answering and multiple choice to TF Camembert

* Remove prints

* Add multiple choice model to TF DistilBERT + loss computation

* Add question answering model to TF Electra + loss computation

* Add token classification, question answering and multiple choice models to TF Flaubert

* Add multiple choice model to TF Roberta + loss computation

* Add multiple choice model to TF XLM + loss computation

* Add multiple choice and question answering models to TF XLM-Roberta

* Add multiple choice model to TF XLNet + loss computation

* Remove unused parameters

* Add task loss classes

* Reorder TF imports + add new model classes

* Add new model classes

* Bugfix in TF T5 model

* Bugfix for TF T5 tests

* Bugfix in TF T5 model

* Fix TF T5 model tests

* Fix T5 tests + some renaming

* Fix inheritance issue in the AutoX tests

* Add tests for TF Flaubert and TF XLM Roberta

* Add tests for TF Flaubert and TF XLM Roberta

* Remove unused piece of code in the TF trainer

* bugfix and remove unused code

* Bugfix for TF 2.2

* Apply Style

* Divide TFSequenceClassificationAndMultipleChoiceLoss into their two respective name

* Apply style

* Mirror the PT Trainer in the TF one: fp16, optimizers and tb_writer as class parameter and better dataset handling

* Fix TF optimizations tests and apply style

* Remove useless parameter

* Bugfix and apply style

* Fix TF Trainer prediction

* Now the TF models return the loss such as their PyTorch couterparts

* Apply Style

* Ignore some tests output

* Take into account the SQuAD cls_index, p_mask and is_impossible parameters for the QuestionAnswering task models.

* Fix names for SQuAD data

* Apply Style

* Fix conflicts with 2.11 release

* Fix conflicts with 2.11

* Fix wrongname

* Add better documentation on the new create_optimizer function

* Fix isort

* logging_dir: use same default as PyTorch
Co-authored-by: Julien Chaumond <chaumond@gmail.com>

* per_device instead of per_gpu/error thrown when argument unknown

* [docs] Restore examples.md symlink

* Correct absolute links so that symlink to the doc works correctly

* Update src/transformers/hf_argparser.py
Co-authored-by: Julien Chaumond <chaumond@gmail.com>

* Warning + reorder

* Docs

* Style

* not for squad
Co-authored-by: Julien Chaumond <chaumond@gmail.com>

* wip

* wip

* a last wip

* Better logging when using TPUs

* Correct argument name

* Tests

* fix

* Metrics in evaluation

* Update src/transformers/training_args.py

* [tpu] Use launcher script instead

* [tpu] lots of tweaks

* Fix formatting
Co-authored-by: Julien Chaumond <chaumond@gmail.com>

* feat: add logging through Weights & Biases

* feat(wandb): make logging compatible with all scripts

* style(trainer.py): fix formatting

* [Trainer] Tweak wandb integration
Co-authored-by: Julien Chaumond <chaumond@gmail.com>

* Continue training args

* Continue training args

* added explaination

* added explaination

* added explaination

* Fixed tqdm auto

* Update src/transformers/training_args.py
Co-Authored-By: Julien Chaumond <chaumond@gmail.com>

* Update src/transformers/training_args.py

* Update src/transformers/training_args.py
Co-authored-by: Julien Chaumond <chaumond@gmail.com>

* doc

* [tests] Add sample files for a regression task

* [HUGE] Trainer

* Feedback from @sshleifer

* Feedback from @thomwolf + logging tweak

* [file_utils] when downloading concurrently, get_from_cache will use the cached file for subsequent processes

* [glue] Use default max_seq_length of 128 like before

* [glue] move DataTrainingArguments around

* [ner] Change interface of InputExample, and align run_{tf,pl}

* Re-align the pl scripts a little bit

* ner

* [ner] Add integration test

* Fix language_modeling with API tweak

* [ci] Tweak loss target

* Don't break console output

* amp.initialize: model must be on right device before

* [multiple-choice] update for Trainer

* Re-align to 827d6d6e

* [examples] Generate argparsers from type hints on dataclasses

* [HfArgumentParser] way simpler API

* Restore run_language_modeling.py for easier diff

* [HfArgumentParser] final tweaks from code review