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fix the `tokenizer_config.json` file for the slow tokenizer when a fast version is available (#15319)

* add new test

* update test

* remove `tokenizer_file` from `additional_files_names` in `tokenization_utils_base.py`

* add `tokenizer_file` for the fast only tokenizer

* change global variables layoutxml

* remove `"tokenizer_file"` from DPR tokenizer's Global variables

* remove `tokenizer_file` from herbert slow tokenizer init

* `"tokenizer_file"` from LED tokenizer's Global variables

* remove `tokenizer_file` from mbart slow tokenizer init

* remove `tokenizer_file` from slow tokenizer template

* adapt to versioning

* adapt the `test_tokenizer_mismatch_warning` test

* clean test

* clarify `VOCAB_FILES_NAMES` in tokenization_utils_fast.py

* Revert "remove `tokenizer_file` from mbart slow tokenizer init"

This reverts commit 0dbb723fa9c7599d4640fe30b3647a74eb4a64e1.

* Revert "`"tokenizer_file"` from LED tokenizer's Global variables"

This reverts commit 5a3f879bdd651233f3d74a3d1146c34cde82b0c2.

* Revert "remove `tokenizer_file` from herbert slow tokenizer init"

This reverts commit f5e10007b7b0ec5345e015b9de7ffec72c5407fd.

* Revert "remove `"tokenizer_file"` from DPR tokenizer's Global variables"

This reverts commit da0895330bedfafc81ae3073470a9348c669f032.

* set `tokenizer_file` in super `__init__` of mbart

* replace assert with exception for `padding_side` arg in `PreTrainedTokenizerBase` `__init__`

* add test

* fix kwargs

* reformat test

* format

* format

* fix typo to render the documentation

fix typo

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

* Fix TF Causal LM models' returned logits

* Fix expected shape in the tests
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>

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

* Update modeling_wav2vec2.py

With very tiny sound files (less than 0.1 seconds) the num_masked_span can be too long. The issue is described in issue #15366 and discussed with @patrickvonplaten.

* correct errors with mask time indices

* remove bogus file

* make fix-copies
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Add 'with torch.no_grad()' to BEiT integration test forward pass

* Fix inconsistent use of tabs and spaces in indentation

* Fix spurious warning in TF TokenClassification models

* Fixing one last spurious warning

* Removing outdated warning altogether

* refactor roberta tokenizer

* refactor fast tokenizer

* remove old comment

* fix tf led

* fix

* fix

* Add test_pt_tf_model_equivalence_extra for TFLED

* add a (temporary) test
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>

* add a section about GPUs

* Apply suggestions from code review
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* [Trainer] suppress warning for length-related columns

* improve message

* Update src/transformers/trainer.py

* Change REALM checkpoint to new ones

* Last checkpoint missing

* Fix loss calculation in TFFunnelForTokenClassification

* revert the change in TFFunnelForTokenClassification

* fix FunnelForTokenClassification loss

* fix other TokenClassification loss

* fix more

* fix more

* add num_labels to ElectraForTokenClassification

* revert the change to research projects
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>

* [deepspeed doc] fix import, extra notes

* typo

* Fix Swin model outputs

* Rename pooler

fix typo

* Add Luke training

* Fix true label tags

* Fix true label tags

* Fix true label tags

* Update the data collator for Luke

* Some training refactor for Luke

* Improve data collator for Luke

* Fix import

* Fix datasets concatenation

* Add the --max_entity_length argument for Luke models

* Remove unused code

* Fix style issues

* Fix style issues

* Move the Luke training into a separate folder

* Fix style

* Fix naming

* Fix filtering

* Fix filtering

* Fix filter

* Update some preprocessing

* Move luke to research_projects

* Checkstyle

* Address comments

* Fix style

(This is an editorial change only)

* Fix the inconsistency of loss calculation between PT/TF XLNetLMHeadModel

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

* add xlm roberta xl

* add convert xlm xl fairseq checkpoint to pytorch

* fix init and documents for xlm-roberta-xl

* fix indention

* add test for XLM-R xl,xxl

* fix model hub name

* fix some stuff

* up

* correct init

* fix more

* fix as suggestions

* add torch_device

* fix default values of doc strings

* fix leftovers

* merge to master

* up

* correct hub names

* fix docs

* fix model

* up

* finalize

* last fix

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

* add copied from

* make style
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* clean commit of changes

* apply review feedback, make edits

* fix backticks, minor formatting

* 🖍 make fixup and minor edits

* 🖍 fix # in header

* 📝 update code sample without from_pt

* 📝 final review

* add model sharing tutorial

* 🖍 apply feedback from review

* 📝 make edits

* 🖍 fix formatting

* 📝 convert from pt checkpoint to flax

* 📝 final review

* fix missing eps

* Same fix for ConvBertGeneratorPredictions

* Same fix for AlbertMLMHead
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>

* [deepspeed] saving checkpoint fallback when fp16 weights aren't saved

* Bump required deepspeed version to match usage when saving checkpoints

* update version
Co-authored-by: Mihai Balint <balint.mihai@gmail.com>