o ۷i@sddZddlZddlmZddlmZddlmZee Z ddiZ d d Z Gd d d eZ d gZdS) zTokenization classes for ESM.N)Optional)PreTrainedTokenizer)logging vocab_file vocab.txtcCsHt|d}|}dd|DWdS1swYdS)NrcSsg|]}|qS)strip).0lr r ^/home/ubuntu/vllm_env/lib/python3.10/site-packages/transformers/models/esm/tokenization_esm.py sz#load_vocab_file..)openread splitlines)rflinesr r r load_vocab_files   $rc seZdZdZeZddgZ     d'fd d Zd ed e fd dZ de d efddZ ddZ ddZ de d efddZd ed e fddZ d(deedeeed eefddZ d)dedeed ed eefd!d"Zd#d$Zed efd%d&ZZS)* EsmTokenizerz& Constructs an ESM tokenizer. input_idsattention_maskc sft||_tt|j|_ddt|jD|_tjd|||||d||j|_| |jdS)NcSsi|]\}}||qSr r )r indtokr r r 7sz)EsmTokenizer.__init__..) unk_token cls_token pad_token mask_token eos_tokenr ) r all_tokensdict enumerate _id_to_token _token_to_idsuper__init__unique_no_split_tokens _update_trie)selfrr r!r"r#r$kwargs __class__r r r++s  zEsmTokenizer.__init__indexreturncC|j||jSNr(getr r.r2r r r _convert_id_to_tokenGz!EsmTokenizer._convert_id_to_tokentokencC|j||j|jSr5r)r7r r.r;r r r _convert_token_to_idJz!EsmTokenizer._convert_token_to_idcKs|Sr5)split)r.textr/r r r _tokenizeMszEsmTokenizer._tokenizecCs|j}||j|Sr5)r)copyupdateadded_tokens_encoder)r. base_vocabr r r get_vocabPs  zEsmTokenizer.get_vocabcCr<r5r=r>r r r token_to_idUr@zEsmTokenizer.token_to_idcCr4r5r6r8r r r id_to_tokenXr:zEsmTokenizer.id_to_tokenN token_ids_0 token_ids_1cCs\|jg}|jg}|dur|jdur||S|||S|jdur$td|||||S)Nz=Cannot tokenize multiple sequences when EOS token is not set!) cls_token_id eos_token_id ValueError)r.rKrLclssepr r r build_inputs_with_special_tokens[s   z-EsmTokenizer.build_inputs_with_special_tokensFalready_has_special_tokenscsd|r|dur tdfdd|DSdgdgt|dg}|dur0|dgt|dg7}|S)a Retrieves 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` or `encode_plus` methods. Args: token_ids_0 (`list[int]`): List of ids of the first sequence. token_ids_1 (`list[int]`, *optional*): List of ids of the second sequence. 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: A list of integers in the range [0, 1]: 1 for a special token, 0 for a sequence token. NzYou should not supply a second sequence if the provided sequence of ids is already formatted with special tokens for the model.csg|] }|jvr dndqS)r)all_special_ids)r r;r.r r rsz8EsmTokenizer.get_special_tokens_mask..rTr)rOlen)r.rKrLrSmaskr rVr get_special_tokens_maskisz$EsmTokenizer.get_special_tokens_maskcCsdtj||r |dndd}t|d}|d|jWd|fS1s*wY|fS)N-rw )ospathjoinrwriter%)r.save_directoryfilename_prefixrrr r r save_vocabularys  zEsmTokenizer.save_vocabularycCs t|jSr5)rWr%rVr r r vocab_sizes zEsmTokenizer.vocab_size)rrrrrr5)NF)__name__ __module__ __qualname____doc__VOCAB_FILES_NAMESvocab_files_namesmodel_input_namesr+intstrr9r?rCrHrIrJlistrrRboolrYrdpropertyre __classcell__r r r0r r#sJ   r)rir^typingrtokenization_utilsrutilsr get_loggerrfloggerrjrr__all__r r r r s     p