* fix for ragged list
* unpin numba
* make style
* np.object -> object
* propagate changes to tokenizer as well
* np.long -> "long"
* revert tokenization changes
* check with tokenization changes
* list/tuple logic
* catch numpy
* catch else case
* clean up
* up
* better check
* trigger ci
* Empty commit to trigger CI
* initial work
* Add other classes
* Refactor code
* Move warning and fix dynamic pipeline
* Issue warning when necessary
* Add test
* Do not skip auto tests
* Fix failing tests
* Refactor and address review comments
* Address review comments
* add draft changes
* fix failing wav2vec
* style
* make sure that the argument is saved + add tests
* style
* fixup
* update test
* default clean_up_tokenization_spaces to False for Bloom and Llama
* Update code based on review
Co-authored-by: Nicolas Patry <patry.nicolas@gmail.com>
* style
* quality
---------
Co-authored-by: Nicolas Patry <patry.nicolas@gmail.com>
* Result of black 23.1
* Update target to Python 3.7
* Switch flake8 to ruff
* Configure isort
* Configure isort
* Apply isort with line limit
* Put the right black version
* adapt black in check copies
* Fix copies
* add warning to let the user know that the method is slower that for a fast tokenizer
* user warnings
* fix layoutlmv2
* fix layout*
* change warnings into logger.warning
* Draft new cached_file
* Initial draft for config and model
* Small fixes
* Fix first batch of tests
* Look in cache when internet is down
* Fix last tests
* Bad black, not fixing all quality errors
* Make diff less
* Implement change for TF and Flax models
* Add tokenizer and feature extractor
* For compatibility with main
* Add utils to move the cache and auto-do it at first use.
* Quality
* Deal with empty commit shas
* Deal with empty etag
* Address review comments
Fix#18385
I don't know whether `use_auth_token`, `cache_dir` and `local_files_only` should be passed to `(cls.slow_tokenizer_class)._from_pretrained`, but I guess it should.
* More informative error message
* raise dynamic error
* remove_excess_nesting application
* incorrect shape assertion for collator & function to remove excess nesting from DatasetDict
* formatting
* eliminating datasets import
* removed and relocated remove_excess_nesting to the datasets library and updated docs accordingly
* independent assert instructions
* inform user of excess nesting
* [Json dump] Make json prettier
* correct more tokenizeirs
* more patterns
* add aggressive test
* the aggressive test was actually useful :-)
* more tests
* Apply suggestions from code review
* Accumulate tokens into batches in PreTrainedTokenizerBase.add_tokens()
For tokenizers with a small number of special tokens or special tokens
with consecutive token IDs, this reduces the time complexity of creating
the trie from quadratic to linear, see also #16936.
* Extend explanation of batching added tokens
* [T5 Tokenizer] Model has no fixed position ids - there is no hardcoded max length
* [T5 Tokenizer] Model has no fixed position ids - there is no hardcoded max length
* correct t5 tokenizer
* correct t5 tokenizer
* fix test
* Apply suggestions from code review
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* finish
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.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
* Make Transformers use cache files when hf.co is down
* Fix tests
* Was there a random circleCI failure?
* Isolate patches
* Style
* Comment out the failure since it doesn't fail anymore
* Better comment
