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>
* 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
* [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>
