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* Don't use `store_xxx` on optional bools

* Refine test

* Refine test

* Add eval_accumulation_step and clean distributed eval

* Add TPU test

* Add TPU stuff

* Fix arg name

* Fix Seq2SeqTrainer

* Fix total_size

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

* Doc and add test to TPU

* Add unit test

* Adapt name
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>

* Add support for gpt2 batch inferencing

* add test

* remove typo
Co-authored-by: patrickvonplaten <patrick.v.platen@gmail.com>

* fix bert position ids in DPR convert script

* style

* Adding optional trial argument to model_init
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* use DDP no_sync when possible

* fix is_nlp_available addition mistake

* reformat trainer.py

* reformat trainer.py

* drop support for pytorch < 1.2

* return support for pytorch < 1.2

* Do not softmax when num_labels==1

* Update src/transformers/pipelines.py
Co-authored-by: Funtowicz Morgan <mfuntowicz@users.noreply.github.com>
Co-authored-by: Funtowicz Morgan <mfuntowicz@users.noreply.github.com>

* fix rag

* Update tokenizer save_pretrained
Co-authored-by: Thomas Wolf <thomwolf@users.noreply.github.com>

Putting my name on a couple more issues to directly redirect them to me

* Add Documentation for GPT-1 Classification

* Add GPT-1 with Classification head

* Add tests for GPT-1 Classification

* Add GPT-1 For Classification to auto models

* Remove authorized missing keys, change checkpoint to openai-gpt

* Fix test

* fix generic text classification

* fix test

* Fix tests

Fix a bug that happends when subclassing Trainer and
overwriting evaluate() without calling prediciton_loop()

Very often splitting large files to smaller files can prevent tokenizer going out of memory in environment like Colab that does not have swap memory

Minor spelling corrections in docstrings. "information" is uncountable in English and has no plural.

Added is_torch_tpu_available() to the condition
for saving a model as xla model. "xla_device"
property of config can also be True on a non-xla
device, when loading a checkpointthat was trained
on xla before.

Resolves #7695

replace 'men_len' with 'mem_len' to match parameter name

* Import intergration libraries first

* isort and black happiness

* flake8 happiness

* Add a test

* Black reformat

* Ignore import order in tests

* A heavy-handed method of disabling comet for tests

* Remove comet_ml tests

* Run black on setup.py

This reverts commit 76e05518.