import os 
from typing import Union, List, Optional, Tuple

from transformers import PreTrainedTokenizer, PreTrainedTokenizerFast

class SentencePieceJA(PreTrainedTokenizer):
    def __init__(self, model_path, **kwargs):
        super().__init__(**kwargs)
        from tokenizers import Tokenizer
        self._tokenizer = Tokenizer.from_file(model_path)        
        self.__pad_id = self._tokenize("<PAD>")[0]
        self.__bos_id = self._tokenize("<BOS>")[0]
        self.__eos_id = self._tokenize("<EOS>")[0]
        self.__unk_id = self._tokenize("<UNK>")[0]
        self.__mask_id = self._tokenize("<MASK>")[0]

    def get_vocab(self) -> int:
        return self._tokenizer.get_vocab()

    def vocab_size(self) -> int:
        return self._tokenizer.get_vocab_size()

    def _tokenize(self, text, **kwargs):    
        return self._tokenizer.encode(text).ids

    def _convert_token_to_id(self, token):
        return token
        
    def _convert_id_to_token(self, index: int) -> str:    
        return self._tokenizer.decode(index)
        # return self._tokenizer.id_to_token(index)

    def convert_tokens_to_ids(self, tokens: Union[str, List[str]]) -> Union[int, List[int]]:    
        return tokens
    
    def convert_ids_to_tokens(
        self, ids: Union[int, List[int]], skip_special_tokens: bool = False
    ) -> Union[str, List[str]]:        
        decoded = self._tokenizer.decode(ids)    
        return decoded
    
    def save_vocabulary(self, save_directory: str, filename_prefix: Optional[str] = None) -> Tuple[str]:
        index = 0
        if os.path.isdir(save_directory):
            vocab_file = os.path.join(
                save_directory, (filename_prefix + "-" if filename_prefix else "") + 'vocab.txt'
            )
        else:
            vocab_file = (filename_prefix + "-" if filename_prefix else "") + save_directory        
        with open(vocab_file, "w", encoding="utf-8") as writer:
            for token, token_index in sorted(self.get_vocab().items(), key=lambda kv: kv[1]):
                if index != token_index:
                    index = token_index
                writer.write(token + "\n")
                index += 1
        return (vocab_file,)