U ,-e$ @sUdZddlmZmZmZddlmZmZddlm Z e e Z ddiZ dZdZd Zd Zd Zd Zd ZedededededediZeeefed<ddeDZeeefed<GdddeZdS)z Tokenization classes for CANINE.)DictListOptional) AddedTokenPreTrainedTokenizer)loggingznielsr/canine-siiiiiiz[CLS]z[SEP]z[BOS]z[MASK]z[PAD]z [RESERVED]SPECIAL_CODEPOINTScCsi|]\}}||qSr ).0 codepointnamer r o/var/www/html/Darija-Ai-Train/env/lib/python3.8/site-packages/transformers/models/canine/tokenization_canine.py ;srSPECIAL_CODEPOINTS_BY_NAMEcs,eZdZdZeZeeeeeeeeee ee ddffdd Z e e dddZd d Zeeed d d Zee dddZe edddZddZd"ee eee ee dddZd#ee eee eee dfdd Zd$ee eee ee dddZd%eeedd d!ZZS)&CanineTokenizera Construct a CANINE tokenizer (i.e. a character splitter). It turns text into a sequence of characters, and then converts each character into its Unicode code point. [`CanineTokenizer`] inherits from [`PreTrainedTokenizer`]. Refer to superclass [`PreTrainedTokenizer`] for usage examples and documentation concerning parameters. Args: model_max_length (`int`, *optional*, defaults to 2048): The maximum sentence length the model accepts. Fr c st|trt|dddn|}t|tr4t|dddn|}t|trPt|dddn|}t|trlt|dddn|}t|trt|dddn|}t|trt|dddn|}i|_tD]\} } | |j| <qdd|jD|_t|_t |j|_ t j f||||||||d| dS)NF)lstriprstripTcSsi|]\}}||qSr r )r rr r r rrisz,CanineTokenizer.__init__..) bos_token eos_token sep_token cls_token pad_token mask_tokenadd_prefix_spacemodel_max_length) isinstancestrrZ_special_codepointsr itemsZ_special_codepoint_stringsUNICODE_VOCAB_SIZE_unicode_vocab_sizelenZ_num_special_tokenssuper__init__) selfrrrrrrrrkwargsr r __class__r rr$Ns4    zCanineTokenizer.__init__)returncCs|jS)N)r!)r%r r r vocab_size|szCanineTokenizer.vocab_sizecCs$ddt|jD}||j|S)NcSsi|]}t||qSr )chr)r ir r rrsz-CanineTokenizer.get_vocab..)ranger*updateZadded_tokens_encoder)r%Zvocabr r r get_vocabs zCanineTokenizer.get_vocab)textr)cCst|S)z5Tokenize a string (i.e. perform character splitting).)list)r%r0r r r _tokenizeszCanineTokenizer._tokenize)tokenr)cCs4z t|WStk r.td|dYnXdS)zaConverts a token (i.e. a Unicode character) in an id (i.e. its integer Unicode code point value).zinvalid token: ''N)ord TypeError ValueError)r%r3r r r_convert_token_to_ids z$CanineTokenizer._convert_token_to_id)indexr)cCsDz|tkrt|WSt|WStk r>td|YnXdS)z Converts a Unicode code point (integer) in a token (str). In case it's a special code point, convert to human-readable format. z invalid id: N)r r+r6r7)r%r9r r r_convert_id_to_tokens   z$CanineTokenizer._convert_id_to_tokencCs d|S)N)join)r%tokensr r rconvert_tokens_to_stringsz(CanineTokenizer.convert_tokens_to_stringN) token_ids_0 token_ids_1r)cCs4|jg}|jg}|||}|dk r0|||7}|S)a Build model inputs from a sequence or a pair of sequence for sequence classification tasks by concatenating and adding special tokens. A CANINE sequence has the following format: - single sequence: `[CLS] X [SEP]` - pair of sequences: `[CLS] A [SEP] B [SEP]` 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) sep_token_id cls_token_idr%r?r@sepclsresultr r r build_inputs_with_special_tokenss   z0CanineTokenizer.build_inputs_with_special_tokens)r?r@already_has_special_tokensr)csT|rtj||ddSdgdgt|dg}|dk rP|dgt|dg7}|S)a Retrieve sequence ids from a token list that has no special tokens added. This method is called when adding special tokens using the tokenizer `prepare_for_model` method. Args: token_ids_0 (`List[int]`): List of IDs. token_ids_1 (`List[int]`, *optional*): Optional second list of IDs for sequence pairs. already_has_special_tokens (`bool`, *optional*, defaults to `False`): Whether or not the token list is already formatted with special tokens for the model. Returns: `List[int]`: A list of integers in the range [0, 1]: 1 for a special token, 0 for a sequence token. T)r?r@rHrN)r#get_special_tokens_maskr")r%r?r@rHrFr'r rrJsz'CanineTokenizer.get_special_tokens_maskcCsH|jg}|jg}t|||dg}|dk rD|t||dg7}|S)a Create a mask from the two sequences passed to be used in a sequence-pair classification task. A CANINE sequence pair mask has the following format: ``` 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 1 | first sequence | second sequence | ``` If `token_ids_1` is `None`, this method only returns the first portion of the mask (0s). 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 [token type IDs](../glossary#token-type-ids) according to the given sequence(s). rNrI)rArBr"rCr r r$create_token_type_ids_from_sequencess z4CanineTokenizer.create_token_type_ids_from_sequences)save_directoryfilename_prefixcCsdS)Nr r )r%rLrMr r rsave_vocabularyszCanineTokenizer.save_vocabulary)N)NF)N)N)__name__ __module__ __qualname____doc__&PRETRAINED_POSITIONAL_EMBEDDINGS_SIZESZmax_model_input_sizesr+CLSSEPPADMASKr$propertyintr*r/rrr2r8r:r>rrGboolrJrKrN __classcell__r r r'rr>sN .      rN)rRtypingrrrZtokenization_utilsrrutilsrZ get_loggerrOloggerrSr rVrTrUZBOSrWZRESERVEDr rYr__annotations__rrrr r r rs:   "