GitLab

* Run new isort

* More changes

* Update CI, CONTRIBUTING and benchmarks

* Add more token classification examples

* POS tagging example

* Phrase chunking example

* PR review fixes

* Add conllu to third party list (used in token classification examples)

* Fully rework training/prediction loops

* fix method name

* Fix variable name

* Fix property name

* Fix scope

* Fix method name

* Fix tuple index

* Fix tuple index

* Fix indentation

* Fix variable name

* fix eval before log

* Add drop remainder for test dataset

* Fix step number + fix logging datetime

* fix eval loss value

* use global step instead of step + fix logging at step 0

* Fix logging datetime

* Fix global_step usage

* Fix breaking loop + logging datetime

* Fix step in prediction loop

* Fix step breaking

* Fix train/test loops

* Force TF at least 2.2 for the trainer

* Use assert_cardinality to facilitate the dataset size computation

* Log steps per epoch

* Make tfds compliant with TPU

* Make tfds compliant with TPU

* Use TF dataset enumerate instead of the Python one

* revert previous commit

* Fix data_dir

* Apply style

* rebase on master

* Address Sylvain's comments

* Address Sylvain's and Lysandre comments

* Trigger CI

* Remove unused import

[Almost all TF models] TF clean up: add missing CLM / MLM loss; fix T5 naming and keras compile (#5395)

* add first version of clm tf

* make style

* add more tests for bert

* update tf clm loss

* fix tests

* correct tf ner script

* add mlm loss

* delete bogus file

* clean tf auto model + add tests

* finish adding clm loss everywhere

* fix training in distilbert

* fix flake8

* save intermediate

* fix tf t5 naming

* remove prints

* finish up

* up

* fix tf gpt2

* fix new test utils import

* fix flake8

* keep backward compatibility

* Update src/transformers/modeling_tf_albert.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Update src/transformers/modeling_tf_auto.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Update src/transformers/modeling_tf_electra.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Update src/transformers/modeling_tf_roberta.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Update src/transformers/modeling_tf_mobilebert.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Update src/transformers/modeling_tf_auto.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Update src/transformers/modeling_tf_bert.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Update src/transformers/modeling_tf_distilbert.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* apply sylvains suggestions
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* 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>

Otherwise, if label is not specified, the following error occurs:

	Traceback (most recent call last):
	  File "run_ner.py", line 303, in <module>
	    main()
	  File "run_ner.py", line 101, in main
	    model_args, data_args, training_args = parser.parse_json_file(json_file=os.path.abspath(sys.argv[1]))
	  File "/home/user/anaconda3/envs/bert/lib/python3.7/site-packages/transformers/hf_argparser.py", line 159, in parse_json_file
	    obj = dtype(**inputs)
	TypeError: __init__() missing 1 required positional argument: 'labels'

* utils_ner: do not add extra sep token for RoBERTa model

* run_pl_ner: do not add extra sep token for RoBERTa model

* ner: add preprocessing script for examples that splits longer sentences

* ner: example shell scripts use local preprocessing now

* ner: add new example section for WNUT’17 NER task. Remove old English CoNLL-03 results

* ner: satisfy black and isort

* Kill model archive maps

* Fixup

* Also kill model_archive_map for MaskedBertPreTrainedModel

* Unhook config_archive_map

* Tokenizers: align with model id changes

* make style && make quality

* Fix CI

* 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>

* Distributed eval: SequentialDistributedSampler + gather all results

* For consistency only write to disk from world_master

Close https://github.com/huggingface/transformers/issues/4272

* Working distributed eval

* Hook into scripts

* Fix #3721 again

* TPU.mesh_reduce: stay in tensor space

Thanks @jysohn23

* Just a small comment

* whitespace

* torch.hub: pip install packaging

* Add test scenarii

see context in https://github.com/huggingface/transformers/pull/4223

* Improvements to the wandb integration

* small reorg + no global necessary

* feat(trainer): log epoch and final metrics

* Simplify logging a bit

* Fixup

* Fix crash when just running eval
Co-authored-by: Chris Van Pelt <vanpelt@gmail.com>
Co-authored-by: Boris Dayma <boris.dayma@gmail.com>

* docs: fix link to token classification (NER) example

* examples: fix links to NER scripts

* [TPU] Doc, fix xla_spawn.py, only preprocess dataset once

* Update examples/README.md

* [xla_spawn] Add `_mp_fn` to other Trainer scripts

* [TPU] Fix: eval dataloader was None

* Created using Colaboratory

* [examples] reorganize files

* remove run_tpu_glue.py as superseded by TPU support in Trainer

* Bugfix: int, not tuple

* move files around