* Optimize causal mask using torch.where
Instead of multiplying by 1.0 float mask, use torch.where with a bool mask for increased performance.
* Maintain compatiblity with torch 1.0.0 - thanks for PR feedback
* Fix typo
* reformat line for CI
* Renamed num_added_tokens to num_special_tokens_to_add
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>
* Cherry-Pick: Partially fix space only input without special tokens added to the output #3091
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>
* Added property is_fast on PretrainedTokenizer and PretrainedTokenizerFast
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>
* Make fast tokenizers unittests work on Windows.
* Entirely refactored unittest for tokenizers fast.
* Remove ABC class for CommonFastTokenizerTest
* Added embeded_special_tokens tests from allenai @dirkgr
* Make embeded_special_tokens tests from allenai more generic
* Uniformize vocab_size as a property for both Fast and normal tokenizers
* Move special tokens handling out of PretrainedTokenizer (SpecialTokensMixin)
* Ensure providing None input raise the same ValueError than Python tokenizer + tests.
* Fix invalid input for assert_padding when testing batch_encode_plus
* Move add_special_tokens from constructor to tokenize/encode/[batch_]encode_plus methods parameter.
* Ensure tokenize() correctly forward add_special_tokens to rust.
* Adding None checking on top on encode / encode_batch for TransfoXLTokenizerFast.
Avoid stripping on None values.
* unittests ensure tokenize() also throws a ValueError if provided None
* Added add_special_tokens unittest for all supported models.
* Style
* Make sure TransfoXL test run only if PyTorch is provided.
* Split up tokenizers tests for each model type.
* Fix invalid unittest with new tokenizers API.
* Filter out Roberta openai detector models from unittests.
* Introduce BatchEncoding on fast tokenizers path.
This new structure exposes all the mappings retrieved from Rust.
It also keeps the current behavior with model forward.
* Introduce BatchEncoding on slow tokenizers path.
Backward compatibility.
* Improve error message on BatchEncoding for slow path
* Make add_prefix_space True by default on Roberta fast to match Python in majority of cases.
* Style and format.
* Added typing on all methods for PretrainedTokenizerFast
* Style and format
* Added path for feeding pretokenized (List[str]) input to PretrainedTokenizerFast.
* Style and format
* encode_plus now supports pretokenized inputs.
* Remove user warning about add_special_tokens when working on pretokenized inputs.
* Always go through the post processor.
* Added support for pretokenized input pairs on encode_plus
* Added is_pretokenized flag on encode_plus for clarity and improved error message on input TypeError.
* Added pretokenized inputs support on batch_encode_plus
* Update BatchEncoding methods name to match Encoding.
* Bump setup.py tokenizers dependency to 0.7.0rc1
* Remove unused parameters in BertTokenizerFast
* Make sure Roberta returns token_type_ids for unittests.
* Added missing typings
* Update add_tokens prototype to match tokenizers side and allow AddedToken
* Bumping tokenizers to 0.7.0rc2
* Added documentation for BatchEncoding
* Added (unused) is_pretokenized parameter on PreTrainedTokenizer encode_plus/batch_encode_plus methods.
* Added higher-level typing for tokenize / encode_plus / batch_encode_plus.
* Fix unittests failing because add_special_tokens was defined as a constructor parameter on Rust Tokenizers.
* Fix text-classification pipeline using the wrong tokenizer
* Make pipelines works with BatchEncoding
* Turn off add_special_tokens on tokenize by default.
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>
* Remove add_prefix_space from tokenize call in unittest.
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>
* Style and quality
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>
* Correct message for batch_encode_plus none input exception.
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>
* Fix invalid list comprehension for offset_mapping overriding content every iteration.
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>
* TransfoXL uses Strip normalizer.
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>
* Bump tokenizers dependency to 0.7.0rc3
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>
* Support AddedTokens for special_tokens and use left stripping on mask for Roberta.
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>
* SpecilaTokenMixin can use slots to faster access to underlying attributes.
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>
* Remove update_special_tokens from fast tokenizers.
* Ensure TransfoXL unittests are run only when torch is available.
* Style.
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>
* Style
* Style 🙏🙏
* Remove slots on SpecialTokensMixin, need deep dive into pickle protocol.
* Remove Roberta warning on __init__.
* Move documentation to Google style.
Co-authored-by: LysandreJik <lysandre.debut@reseau.eseo.fr>
* Fix RoBERTa/XLNet Pad Token in run_multiple_choice.py
`convert_examples_to_fes atures` sets `pad_token=0` by default, which is correct for BERT but incorrect for RoBERTa (`pad_token=1`) and XLNet (`pad_token=5`). I think the other arguments to `convert_examples_to_features` are correct, but it might be helpful if someone checked who is more familiar with this part of the codebase.
* Simplifying change to match recent commits
Teven