GitLab

Co-authored-by: Sam Shleifer <sshleifer@gmail.com>

* Remove mentions of  RAG from the docs

* Deactivate check

* Formatter

* Docs

* remote debugging

* remote debugging

* moved _store_flos call

* moved _store_flos call

* moved _store_flos call

* removed debugging artefacts

* Clean RAG docs and template docs

* Fix typo

* Better doc

* Refacto the models to remove their interdependencies

* Fix Flaubert model

* Fix Flaubert

* Fix XLM

* Fix Albert

* Fix Roberta

* Fix Albert

* Fix Flaubert

* Apply style + remove unused imports

* Fix Distilbert

* remove unused import

* fix Distilbert

* Fix Flaubert

* Apply style

* Fix Flaubert

* Add the copy comments for the check_copies script

* Fix MobileBert model name

* Address Morgan's comments

* Fix typo

* Oops typo

Updata tokenization_auto.py to handle Inherited tokenizer

correct a very small mistake

* Check decorator order

* Adapt for parametrized decorators

* Fix typos

Previously, the TFTrainingArguments object did a check to see if XLA was enabled, but did this by referencing `self.args.xla`, when it should be `self.xla`, because it is the args object. This can be verified a few lines above, where the XLA field is set.

* Changed name to all no_... arguments and all references to them, inverting the boolean condition

* Change benchmark tests to use new Benchmark Args

* Update src/transformers/benchmark/benchmark_args_utils.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Update src/transformers/benchmark/benchmark.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Fix Style. Add --no options in help

* fix some part of tests

* Update src/transformers/benchmark/benchmark_args_utils.py

* Update src/transformers/benchmark/benchmark_args_utils.py

* Update src/transformers/benchmark/benchmark_args_utils.py

* fix all tests

* make style

* add backwards compability

* make backwards compatible
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: fmcurti <fcurti@DESKTOP-RRQURBM.localdomain>

* Ensure that intergrations are imported before transformers or ml libs

* Black reformatter wanted a newline

* isort requests

* black requests

* flake8 requests

* Clean up model documentation

* Formatting

* Preparation work

* Long lines

* Main work on rst files

* Cleanup all config files

* Syntax fix

* Clean all tokenizers

* Work on first models

* Models beginning

* FaluBERT

* All PyTorch models

* All models

* Long lines again

* Fixes

* More fixes

* Update docs/source/model_doc/bert.rst
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>

* Update docs/source/model_doc/electra.rst
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>

* Last fixes
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>

* Fixed evaluation_strategy on epoch end bug

move the evaluation script outside the the iteration loop

* black formatting

* skip decorators: docs, tests, bugs

* another important note

* style

* bloody style

* add @pytest.mark.parametrize

* add note

* no idea what it wants :(

* fix confused flake

We run `black  --target-version py35 ...` but flake8 doesn't know that, so currently with py38 flake8 fails suggesting that black should have reformatted 63 files. Indeed if I run:

```
black --line-length 119 --target-version py38 examples templates tests src utils
```
it indeed reformats 63 files.

The only solution I found is to create a black config file as explained at https://github.com/psf/black#configuration-format, which is what this PR adds.

Now flake8 knows that py35 is the standard and no longer gets confused regardless of the user's python version.

* adjust the other files that will now rely on black's config file

* Add dataloader_num_workers to TrainingArguments

This argument is meant to be used to set the
number of workers for the PyTorch DataLoader.

* Pass num_workers argument on DataLoader init

The score for the F1 metric was reported as the Exact Match and vice-versa.

* [bug fix] fixed the bug that the actual batch_size is inconsistent with the parameter settings

* reformat

* reformat

* reformat

* add support for dict and BatchEncoding

* add support for dict and BatchEncoding

* add documentation for DataCollatorForNextSentencePrediction

* Some more nits for the docstring
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Some more nits for the docstring
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Some more nits for the docstring
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Some more nits for the docstring
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Some more nits for the docstring
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* rename variables
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* added rag WIP

* path fix

* Formatting / renaming prior to actual work

* added rag WIP

* path fix

* Formatting / renaming prior to actual work

* added rag WIP

* path fix

* Formatting / renaming prior to actual work

* added rag WIP

* Formatting / renaming prior to actual work

* First commit

* improve comments

* Retrieval evaluation scripts

* refactor to include modeling outputs + MPI retriever

* Fix rag-token model + refactor

* Various fixes + finetuning logic

* use_bos fix

* Retrieval refactor

* Finetuning refactoring and cleanup

* Add documentation and cleanup

* Remove set_up_rag_env.sh file

* Fix retrieval wit HF index

* Fix import errors

* Fix quality errors

* Refactor as per suggestions in https://github.com/huggingface/transformers/pull/6813#issuecomment-687208867



* fix quality

* Fix RAG Sequence generation

* minor cleanup plus initial tests

* fix test

* fix tests 2

* Comments fix

* post-merge fixes

* Improve readme + post-rebase refactor

* Extra dependencied for tests

* Fix tests

* Fix tests 2

* Refactor test requirements

* Fix tests 3

* Post-rebase refactor

* rename nlp->datasets

* RAG integration tests

* add tokenizer to slow integration test and allow retriever to run on cpu

* add tests; fix position ids warning

* change structure

* change structure

* add from encoder generator

* save working solution

* make all integration tests pass

* add RagTokenizer.save/from_pretrained and RagRetriever.save/from_pretrained

* don't save paths

* delete unnecessary imports

* pass config to AutoTokenizer.from_pretrained for Rag tokenizers

* init wiki_dpr only once

* hardcode legacy index and passages paths (todo: add the right urls)

* finalize config

* finalize retriver api and config api

* LegacyIndex index download refactor

* add dpr to autotokenizer

* make from pretrained more flexible

* fix ragfortokengeneration

* small name changes in tokenizer

* add labels to models

* change default index name

* add retrieval tests

* finish token generate

* align test with previous version and make all tests pass

* add tests

* finalize tests

* implement thoms suggestions

* add first version of test

* make first tests work

* make retriever platform agnostic

* naming

* style

* add legacy index URL

* docstrings + simple retrieval test for distributed

* clean model api

* add doc_ids to retriever's outputs

* fix retrieval tests

* finish model outputs

* finalize model api

* fix generate problem for rag

* fix generate for other modles

* fix some tests

* save intermediate

* set generate to default

* big refactor generate

* delete rag_api

* correct pip faiss install

* fix auto tokenization test

* fix faiss install

* fix test

* move the distributed logic to examples

* model page

* docs

* finish tests

* fix dependencies

* fix import in __init__

* Refactor eval_rag and finetune scripts

* start docstring

* add psutil to test

* fix tf test

* move require torch to top

* fix retrieval test

* align naming

* finish automodel

* fix repo consistency

* test ragtokenizer save/load

* add rag model output docs

* fix ragtokenizer save/load from pretrained

* fix tokenizer dir

* remove torch in retrieval

* fix docs

* fixe finetune scripts

* finish model docs

* finish docs

* remove auto model for now

* add require torch

* remove solved todos

* integrate sylvains suggestions

* sams comments

* correct mistake on purpose

* improve README

* Add generation test cases

* fix rag token

* clean token generate

* fix test

* add note to test

* fix attention mask

* add t5 test for rag

* Fix handling prefix in finetune.py

* don't overwrite index_name
Co-authored-by: Patrick Lewis <plewis@fb.com>
Co-authored-by: Aleksandra Piktus <piktus@devfair0141.h2.fair>
Co-authored-by: Aleksandra Piktus <piktus@learnfair5102.h2.fair>
Co-authored-by: Aleksandra Piktus <piktus@learnfair5067.h2.fair>
Co-authored-by: Your Name <you@example.com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Quentin Lhoest <lhoest.q@gmail.com>

* Make big downloads as slow

* Add import

* Right order for slow decorator

* More slow tests

* Add new example with nlp

* Update README

* replace nlp by datasets

* Update examples/text-classification/README.md

Add Lysandre's suggestion.
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>

* Create an XLA parameter and fix mixed precision creation

* Fix issue brought by intellisense

* Complete docstring

* Add possibility to evaluate every epoch

* Remove multitype arg

* Remove needless import

* Use a proper enum

* Apply suggestions from @LysandreJik
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>

* One else and formatting
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>

* is_pretokenized -> is_split_into_words

* Fix tests

* Fix #7277

* Apply style

* Add a full training pipeline test

* Apply style