U 4Af@sdZddlZddlmZddlmZmZmZddlm Z ddl m Z ddl m Z mZe rhd d lmZndZeeZd d d ZdZGddde ZdS)z+Tokenization classes for the BARThez model.N)copyfile)ListOptionalTuple) AddedToken)PreTrainedTokenizerFast)is_sentencepiece_availablelogging)BarthezTokenizerzsentencepiece.bpe.modelztokenizer.json) vocab_filetokenizer_fileu▁c seZdZdZeZddgZeZdfd d Z e e d d dZ de eee ee edddZde eee ee edddZdeeeeedddZZS)BarthezTokenizerFasta Adapted from [`CamembertTokenizer`] and [`BartTokenizer`]. Construct a "fast" BARThez tokenizer. Based on [SentencePiece](https://github.com/google/sentencepiece). This tokenizer inherits from [`PreTrainedTokenizerFast`] which contains most of the main methods. Users should refer to this superclass for more information regarding those methods. Args: vocab_file (`str`): [SentencePiece](https://github.com/google/sentencepiece) file (generally has a *.spm* extension) that contains the vocabulary necessary to instantiate a tokenizer. bos_token (`str`, *optional*, defaults to `""`): The beginning of sequence token that was used during pretraining. Can be used a sequence classifier token. When building a sequence using special tokens, this is not the token that is used for the beginning of sequence. The token used is the `cls_token`. eos_token (`str`, *optional*, defaults to `""`): The end of sequence token. When building a sequence using special tokens, this is not the token that is used for the end of sequence. The token used is the `sep_token`. sep_token (`str`, *optional*, defaults to `""`): The separator token, which is used when building a sequence from multiple sequences, e.g. two sequences for sequence classification or for a text and a question for question answering. It is also used as the last token of a sequence built with special tokens. cls_token (`str`, *optional*, defaults to `""`): The classifier token which is used when doing sequence classification (classification of the whole sequence instead of per-token classification). It is the first token of the sequence when built with special tokens. unk_token (`str`, *optional*, defaults to `""`): The unknown token. A token that is not in the vocabulary cannot be converted to an ID and is set to be this token instead. pad_token (`str`, *optional*, defaults to `""`): The token used for padding, for example when batching sequences of different lengths. mask_token (`str`, *optional*, defaults to `""`): The token used for masking values. This is the token used when training this model with masked language modeling. This is the token which the model will try to predict. additional_special_tokens (`List[str]`, *optional*, defaults to `["NOTUSED", "NOTUSED"]`): Additional special tokens used by the tokenizer. Z input_idsZattention_maskNc sLt| trt| dddn| } tj|f|||||||| d| ||_dS)NTF)lstriprstrip)r bos_token eos_token unk_token sep_token cls_token pad_token mask_token) isinstancestrrsuper__init__r ) selfr rrrrrrrrkwargs __class__Y/tmp/pip-unpacked-wheel-zw5xktn0/transformers/models/barthez/tokenization_barthez_fast.pyr!^s   zBarthezTokenizerFast.__init__)returncCs|jrtj|jSdS)NF)r ospathisfile)r"r&r&r'can_save_slow_tokenizer}sz,BarthezTokenizerFast.can_save_slow_tokenizer) token_ids_0 token_ids_1r(cCsD|dkr|jg||jgS|jg}|jg}||||||S)a Build model inputs from a sequence or a pair of sequence for sequence classification tasks by concatenating and adding special tokens. A BARThez sequence has the following format: - single sequence: ` X ` - pair of sequences: ` A B ` Args: token_ids_0 (`List[int]`): List of IDs to which the special tokens will be added. token_ids_1 (`List[int]`, *optional*): Optional second list of IDs for sequence pairs. Returns: `List[int]`: List of [input IDs](../glossary#input-ids) with the appropriate special tokens. N) cls_token_id sep_token_id)r"r-r.clssepr&r&r' build_inputs_with_special_tokenss z5BarthezTokenizerFast.build_inputs_with_special_tokenscCsP|jg}|jg}|dkr.t|||dgSt||||||dgS)ap Create a mask from the two sequences passed to be used in a sequence-pair classification task. Args: token_ids_0 (`List[int]`): List of IDs. token_ids_1 (`List[int]`, *optional*): Optional second list of IDs for sequence pairs. Returns: `List[int]`: List of zeros. Nr)r0r/len)r"r-r.r2r1r&r&r'$create_token_type_ids_from_sequencess z9BarthezTokenizerFast.create_token_type_ids_from_sequences)save_directoryfilename_prefixr(cCs~|jstdtj|s0td|ddStj||rD|dndtd}tj |j tj |krxt |j ||fS)NzhYour fast tokenizer does not have the necessary information to save the vocabulary for a slow tokenizer.zVocabulary path (z) should be a directory-r ) r, ValueErrorr)r*isdirloggererrorjoinVOCAB_FILES_NAMESabspathr r)r"r6r7Zout_vocab_filer&r&r'save_vocabularys  z$BarthezTokenizerFast.save_vocabulary) NNrrrrrrr)N)N)N)__name__ __module__ __qualname____doc__r?Zvocab_files_namesZmodel_input_namesr Zslow_tokenizer_classr!propertyboolr,rintrr3r5rrrA __classcell__r&r&r$r'r's:2    r)rEr)shutilrtypingrrrZtokenization_utilsrZtokenization_utils_fastrutilsr r Ztokenization_barthezr Z get_loggerrBr<r?ZSPIECE_UNDERLINErr&r&r&r's