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* Add self-training code for text-classification

* Add self-training code for text-classification

* Add self-training code for text-classification

* Add self-training code for text-classification

* Add self-training code for text-classification

* Delete strata

* Add defensive check for config num_labels and id2label

* Actually check value...

* Only warning inside init plus better error message

* Make Funnel Test less flaky
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>

* Setup-dependent pip cache

* Do not restore from old versions

* Improve CTRL doctests

* Fix `CTRLForSequenceClassification` flakiness with inconsistent losses

* Remove unused

* Fixup

* Add CTRL to documentation_tests.txt

* Fix control code not being first

* Add output assertions

* Change from sshleifer/tiny-ctrl -> ctrl

* Run `make fixup`

* apply `list` to output logits shape for clarity

* Reduce output loss precision to make assertion more robust

* Add assertion of control code being first

* Fix docstyle

* upper case sentence following control code

* Weird bug fixes

* Add a better generation example
Co-authored-by: Yih-Dar <2521628+ydshieh@users.noreply.github.com>

* Required the values GPTJ unfortunately cannot run the model =)

* Added the file to the doc tests

* Run Fixup and Style

* Fixed with the test versions of gptj. Ran Style and Fixup.

* Trigger ci

* A Minor Change to License

* Fixed spacing added to the benchmark_utils. Then refactored tests to const variables.

* Removed strings that were included as default parameters anyways.
Co-authored-by: ArEnSc <xx.mike.chung.xx@gmail.com>

* Fix setters of *_token_id properties of SpecialTokensMixin

* Test setters of common tokens ids

* Move to a separate test checks of setters of tokens ids

* Add independent test for ByT5

* Add Canine test

* Test speech to text

* [Doctests] Fix all T5 doc tests

* make style

* Update docs/source/en/model_doc/t5.mdx
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Apply Sylvains comments

* Apply suggestions from code review
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Normalize using a logits warper

* Add a flag in `generate` to support the logit renormalization

* Add in RAG

* add Bigbird ONNX config

* [FlaxWav2Vec2Model] Fix bug in attention mask

* more fixes

* add (Flax)SpeechEncoderDecoderModel PT-FX cross-test

* [FlaxSpeechEncoderDecoder] Fix input shape bug in weights init

* make style

* start working

* fix: ReformerForQA doctest

* fix: ReformerModelWithLMHead doctest

* fix: ReformerModelForSC doctest

* fix: ReformerModelForMLM doctest

* add: documentation_tests.txt

* make fixup

* change: ReformerModelForSC doctest

* change: checkpoint

* Moved functions to pytorch_utils.py

* isort formatting

* Reverted tf changes

* isort, make fix-copies

* documentation fix

* Fixed Conv1D import

* Reverted research examples file

* backward compatibility for pytorch_utils

* missing import

* isort fix

* Change the chunk_iter function to handle

the subtle cases where the last chunk gets ignored since all the
data is in the `left_strided` data.

We need to remove the right striding on the previous item.

* Remove commented line.

* Updated assertions to exceptions

* updated assertions to exceptions

* bug fixes

* fix-copies

* Update modeling_ctrl.py

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

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

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

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

* Update modeling_led.py

* Update modeling_led.py

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

* add ort-trt benchmark script

* Update README.md

* ort version can be newer

* formatting

* specify ORT version

args.model_name_or_path -> args.config_name
fix it

This avoids an unnecessary call and avoids problems during
initialization of class hierarchies.
Co-authored-by: Samuel Melm <samuel.melm@stud.uni-heidelberg.de>

* First Pass All Tests Pass

* WIP

* Adding file to documentation tests

* Change the base model for the example in the doc test.

* Fix Code Styling by running
make fixup

* Called Style

* Reverted to gpt2 model rather than distill gpt2
Then used a token classification model over a sequence model for an example.

* Fix Styling Issue

* Hopefully ignores the formatting issue.
Co-authored-by: ArEnSc <xx.mike.chung.xx@gmail.com>

Move declaration of log streams to before tests, so that results won't get compounded on top of each other

* add error message

* Use names in the error message

* allow ModelOutput

* rename to check_pt_tf_outputs and move outside

* fix style

* skip past_key_values in a better way

* Add comments

* improve code for label/loss

* make the logic clear by moving the ignore keys out

* fix _postprocessing_to_ignore

* fix _postprocessing_to_ignore: create new outputs from the remaining fields

* ignore past_key_values in TFGPT2 models for now

* make check_pt_tf_outputs better regarding names

* move check_pt_tf_models outside

* rename methods

* remove test_pt_tf_model_equivalence in TFCLIPModelTest

* Reduce TFViTMAEModelTest.test_pt_tf_model_equivalence

* move prepare_pt_inputs_from_tf_inputs outside check_pt_tf_models

* Fix quality

* Clean-up TFLxmertModelTester.test_pt_tf_model_equivalence

* Fix quality

* fix

* fix style

* Clean-up TFLEDModelTest.test_pt_tf_model_equivalence

* Fix quality

* add docstring

* improve comment
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>

* update

* batch_size -> text_batch_size
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>

* private repo argument to trainer

* format
Co-authored-by: Nicholas Broad <nicholas@nmbroad.com>

Adds checkpoint prefixes to the gitignore if `push_to_hub` is used along with `checkpointint_steps`

* update _create_and_check_torchscript

* Enable test_torchscript

* clear_class_registry
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>

Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>

Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>

Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>

* Fix t5 shard on TPU Pods

The current script doesn't work properly on a TPU pod because the global batch is not divided correctly per host.
This pull request fixes this issue by dividing the global batch to each host before it is shared on each host.

* fix style
Co-authored-by: ahmed-elnaggar <ahmed.elnaggar@allianz.com>

* Add doctest BERT

* make fixup

* fix typo

* change checkpoints

* make fixup

* define doctest output value, update doctest for mobilebert

* solve fix-copies

* update QA target start index and end index

* change checkpoint for docs and reuse defined variable

* Update src/transformers/models/bert/modeling_tf_bert.py
Co-authored-by: Yih-Dar <2521628+ydshieh@users.noreply.github.com>

* Apply suggestions from code review
Co-authored-by: Yih-Dar <2521628+ydshieh@users.noreply.github.com>

* Apply suggestions from code review
Co-authored-by: Yih-Dar <2521628+ydshieh@users.noreply.github.com>

* make fixup
Co-authored-by: Yih-Dar <2521628+ydshieh@users.noreply.github.com>

I create an archive of older checkpoints during training the checkpoint has a  name with `f"{checkpoint_prefix}-*.zip/.tar ` 
previously `glob(f"{checkpoint_prefix}-*")` takes all files/folders starting with the name checkpoint, and later `shutil.rmtree(checkpoint)` takes a folder name; since at some point it my get a zip file; it crashes training; adding this `if os.path.isdir(x)` allows only folders on `glob_checkpoints`