o ̳i@s4ddlmZmZmZddlmZGdddeZdS))AnyDictList)SentencePieceBaseTokenizerc steZdZdZddededeffdd Zd ed eeffd d Z dde ee fded e ee ffddZ Z S) T5Tokenizerz Text tokenizer for T5. Args: path (str): the path to the T5 sentencepiece tokenizer file max_seq_len (int): the context length truncate (bool): whether to truncate the token sequence when longer than max_seq_len Tpath max_seq_lentruncatecst|||_||_dS)N)super__init__r r )selfrr r  __class__R/home/ubuntu/.local/lib/python3.10/site-packages/torchtune/models/t5/_tokenizer.pyr s  zT5Tokenizer.__init__textreturncsNtj|ddddd}t||jkr%|jsJd|d|j}|j|d<|S)z Given a string, return the encoded list of token ids. Args: text (str): The text to encode. Returns: List[int]: The encoded list of token ids. FTN)add_bosadd_eostrim_leading_whitespaceprefixzWTokenized text is larger than the maximum sequence length but truncate is set to False.)r encodelenr r eos_id)r rtokensrrrrs  zT5Tokenizer.encodeFsample inferencecCs|d}|||d<|S)aW Tokenize the "text" field in the sample. Args: sample (Dict[str, Any]): A sample with a "text" field containing a string to tokenize inference (bool): Unused by this tokenizer Returns: Dict[str, Any]: The sample with added "tokens" field and the "messages" field removed. rr)popr)r rrrrrr__call__6s zT5Tokenizer.__call__)rT)F)__name__ __module__ __qualname____doc__strintboolr rrrrr __classcell__rrrrr s   rN)typingrrr6torchtune.modules.transforms.tokenizers._sentencepiecerrrrrrs