GitLab

* Run new isort

* More changes

* Update CI, CONTRIBUTING and benchmarks

* 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

* 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>

* remove references to old API in docstring - update data processors

* style

* fix tests - better type checking error messages

* better type checking

* include awesome fix by @LysandreJik for #5310

* updated doc and examples

* Remove unused arguments

* Formatting

* Remove second todo comment

* 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

* catch gpu len 1 set to gpu0

* Add mpc to trainer

* Add MPC for TF

* fix TF automodel for MPC and add Albert

* Apply style

* Fix import

* Note to self: double check

* Make shape None, None for datasetgenerator output shapes

* Add from_pt bool which doesnt seem to work

* Original checkpoint dir

* Fix docstrings for automodel

* Update readme and apply style

* Colab should probably not be from users

* Colabs should probably not be from users

* Add colab

* Update README.md

* Update README.md

* Cleanup __intit__

* Cleanup flake8 trailing comma

* Update src/transformers/training_args_tf.py

* Update src/transformers/modeling_tf_auto.py
Co-authored-by: Viktor Alm <viktoralm@pop-os.localdomain>
Co-authored-by: Julien Chaumond <chaumond@gmail.com>

* [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