


'''simple docstring'''




import json
import os
from pathlib import Path
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple, Union

import sentencepiece

from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging


__snake_case    						=logging.get_logger(__name__)

__snake_case    						="""▁"""

__snake_case    						={
    """vocab_file""": """vocab.json""",
    """spm_file""": """sentencepiece.bpe.model""",
}

__snake_case    						={
    """vocab_file""": {
        """facebook/s2t-small-librispeech-asr""": (
            """https://huggingface.co/facebook/s2t-small-librispeech-asr/resolve/main/vocab.json"""
        ),
    },
    """spm_file""": {
        """facebook/s2t-small-librispeech-asr""": (
            """https://huggingface.co/facebook/s2t-small-librispeech-asr/resolve/main/sentencepiece.bpe.model"""
        )
    },
}

__snake_case    						={
    """facebook/s2t-small-librispeech-asr""": 1_024,
}

__snake_case    						=["""pt""", """fr""", """ru""", """nl""", """ro""", """it""", """es""", """de"""]

__snake_case    						={"""mustc""": MUSTC_LANGS}

class 		UpperCAmelCase_      (  __lowercase		):
     lowerCamelCase				:	int		=     VOCAB_FILES_NAMES
     lowerCamelCase				:	Tuple		=     PRETRAINED_VOCAB_FILES_MAP
     lowerCamelCase				:	Union[str, Any]		=     MAX_MODEL_INPUT_SIZES
     lowerCamelCase				:	List[str]		=     ['''input_ids''', '''attention_mask''']

     lowerCamelCase				:	List[int]		=     []





     def __init__( self       :      Optional[int]    ,      UpperCAmelCase__       :      Any    ,      UpperCAmelCase__       :      int    ,      UpperCAmelCase__       :      List[str]="<s>"    ,      UpperCAmelCase__       :      str="</s>"    ,      UpperCAmelCase__       :      str="<pad>"    ,      UpperCAmelCase__       :      Tuple="<unk>"    ,      UpperCAmelCase__       :      Any=False    ,      UpperCAmelCase__       :      str=False    ,      UpperCAmelCase__       :      Tuple=None    ,      UpperCAmelCase__       :      Optional[Any]=None    ,      UpperCAmelCase__       :      Optional[Dict[str, Any]] = None    ,      **UpperCAmelCase__       :      str    ,      )				->  None:
        lowerCAmelCase     =			{} if sp_model_kwargs is None else sp_model_kwargs

        super().__init__(
            bos_token=UpperCAmelCase__    ,      eos_token=UpperCAmelCase__    ,      unk_token=UpperCAmelCase__    ,      pad_token=UpperCAmelCase__    ,      do_upper_case=UpperCAmelCase__    ,      do_lower_case=UpperCAmelCase__    ,      tgt_lang=UpperCAmelCase__    ,      lang_codes=UpperCAmelCase__    ,      sp_model_kwargs=self.sp_model_kwargs    ,      **UpperCAmelCase__    ,      )
        lowerCAmelCase     =			do_upper_case
        lowerCAmelCase     =			do_lower_case

        lowerCAmelCase     =			load_json(UpperCAmelCase__    )
        lowerCAmelCase     =			{v: k for k, v in self.encoder.items()}
        lowerCAmelCase     =			spm_file
        lowerCAmelCase     =			load_spm(UpperCAmelCase__    ,      self.sp_model_kwargs    )

        if lang_codes is not None:
           lowerCAmelCase     =			lang_codes
           lowerCAmelCase     =			LANGUAGES[lang_codes]
           lowerCAmelCase     =			[F'''<lang:{lang}>''' for lang in self.langs]
           lowerCAmelCase     =			{lang: self.sp_model.PieceToId(F'''<lang:{lang}>'''    ) for lang in self.langs}

           lowerCAmelCase     =			self.lang_tokens
           lowerCAmelCase     =			tgt_lang if tgt_lang is not None else self.langs[0]

           self.set_tgt_lang_special_tokens(self._tgt_lang    )
        else:
           lowerCAmelCase     =			{}





     @property
     def 							__UpperCAmelCase      ( self       :      Optional[int]    )				->  int:
        return len(self.encoder    )





     @property
     def 							__UpperCAmelCase      ( self       :      Tuple    )				->  str:
        return self._tgt_lang





     @tgt_lang.setter
     def 							__UpperCAmelCase      ( self       :      Dict    ,      UpperCAmelCase__       :      Tuple    )				->  None:
        lowerCAmelCase     =			new_tgt_lang
        self.set_tgt_lang_special_tokens(UpperCAmelCase__    )





     def 							__UpperCAmelCase      ( self       :      int    ,      UpperCAmelCase__       :      str    )				->  None:
        lowerCAmelCase     =			self.lang_code_to_id[tgt_lang]
        lowerCAmelCase     =			[lang_code_id]





     def 							__UpperCAmelCase      ( self       :      Optional[int]    ,      UpperCAmelCase__       :      str    )				->  List[str]:
        return self.sp_model.encode(UpperCAmelCase__    ,      out_type=UpperCAmelCase__    )





     def 							__UpperCAmelCase      ( self       :      int    ,      UpperCAmelCase__       :      Dict    )				->  Optional[int]:
        return self.encoder.get(UpperCAmelCase__    ,      self.encoder[self.unk_token]    )





     def 							__UpperCAmelCase      ( self       :      Optional[Any]    ,      UpperCAmelCase__       :      int    )				->  str:
        return self.decoder.get(UpperCAmelCase__    ,      self.unk_token    )





     def 							__UpperCAmelCase      ( self       :      Tuple    ,      UpperCAmelCase__       :      List[str]    )				->  str:
        lowerCAmelCase     =			[]
        lowerCAmelCase     =			''
        for token in tokens:
           # make sure that special tokens are not decoded using sentencepiece model
           if token in self.all_special_tokens:
              lowerCAmelCase     =			self.sp_model.decode(UpperCAmelCase__    )
              out_string += (decoded.upper() if self.do_upper_case else decoded) + token + " "
              lowerCAmelCase     =			[]
           else:
              current_sub_tokens.append(UpperCAmelCase__    )
        lowerCAmelCase     =			self.sp_model.decode(UpperCAmelCase__    )
        out_string += decoded.upper() if self.do_upper_case else decoded
        return out_string.strip()





     def 							__UpperCAmelCase      ( self       :      Any    ,      UpperCAmelCase__       :      int    ,      UpperCAmelCase__       :      Dict=None    )				->  List[int]:
        if token_ids_a is None:
           return self.prefix_tokens + token_ids_a + [self.eos_token_id]
        # We don't expect to process pairs, but leave the pair logic for API consistency
        return self.prefix_tokens + token_ids_a + token_ids_a + [self.eos_token_id]





     def 							__UpperCAmelCase      ( self       :      Optional[int]    ,      UpperCAmelCase__       :      List[int]    ,      UpperCAmelCase__       :      Optional[List[int]] = None    ,      UpperCAmelCase__       :      bool = False    )				->  List[int]:

        if already_has_special_tokens:
           return super().get_special_tokens_mask(
               token_ids_a=UpperCAmelCase__    ,      token_ids_a=UpperCAmelCase__    ,      already_has_special_tokens=UpperCAmelCase__    )

        lowerCAmelCase     =			[1] * len(self.prefix_tokens    )
        lowerCAmelCase     =			[1]
        if token_ids_a is None:
           return prefix_ones + ([0] * len(UpperCAmelCase__    )) + suffix_ones
        return prefix_ones + ([0] * len(UpperCAmelCase__    )) + ([0] * len(UpperCAmelCase__    )) + suffix_ones





     def 							__UpperCAmelCase      ( self       :      str    )				->  Dict:
        lowerCAmelCase     =			self.encoder.copy()
        vocab.update(self.added_tokens_encoder    )
        return vocab





     def __getstate__( self       :      int    )				->  Dict:
        lowerCAmelCase     =			self.__dict__.copy()
        lowerCAmelCase     =			None
        return state





     def __setstate__( self       :      Optional[Any]    ,      UpperCAmelCase__       :      Dict    )				->  None:
        lowerCAmelCase     =			d

        # for backward compatibility
        if not hasattr(self    ,      'sp_model_kwargs'    ):
           lowerCAmelCase     =			{}

        lowerCAmelCase     =			load_spm(self.spm_file    ,      self.sp_model_kwargs    )





     def 							__UpperCAmelCase      ( self       :      int    ,      UpperCAmelCase__       :      str    ,      UpperCAmelCase__       :      Optional[str] = None    )				->  Tuple[str]:
        lowerCAmelCase     =			Path(UpperCAmelCase__    )
        assert save_dir.is_dir(), F'''{save_directory} should be a directory'''
        lowerCAmelCase     =			save_dir / (
            (filename_prefix + '-' if filename_prefix else '') + self.vocab_files_names['vocab_file']
        )
        lowerCAmelCase     =			save_dir / (
            (filename_prefix + '-' if filename_prefix else '') + self.vocab_files_names['spm_file']
        )

        save_json(self.encoder    ,      UpperCAmelCase__    )

        if os.path.abspath(self.spm_file    ) != os.path.abspath(UpperCAmelCase__    ) and os.path.isfile(self.spm_file    ):
           copyfile(self.spm_file    ,      UpperCAmelCase__    )
        elif not os.path.isfile(self.spm_file    ):
           with open(UpperCAmelCase__    ,      'wb'    ) as fi:
              lowerCAmelCase     =			self.sp_model.serialized_model_proto()
              fi.write(UpperCAmelCase__    )

        return (str(UpperCAmelCase__    ), str(UpperCAmelCase__    ))





def 	a_					( lowerCamelCase	:     str	, lowerCamelCase	:     Dict[str, Any]				):
   lowerCAmelCase     =			sentencepiece.SentencePieceProcessor(**lowerCamelCase				)
   spm.Load(str(lowerCamelCase				)				)
   return spm





def 	a_					( lowerCamelCase	:     str				):
   with open(lowerCamelCase	, 'r'				) as f:
      return json.load(lowerCamelCase				)





def 	a_					( lowerCamelCase	:     Tuple	, lowerCamelCase	:     str				):
   with open(lowerCamelCase	, 'w'				) as f:
      json.dump(lowerCamelCase	, lowerCamelCase	, indent=2				)









'''simple docstring'''




def 	a_					( lowerCamelCase	:     Optional[Any]				):
   return [
       {
           0: [1, 2],
           1: [0, 2],
           2: [0, 1, 3, 5],
           3: [2, 4],
           4: [3],
           5: [2, 6, 8],
           6: [5, 7],
           7: [6, 8],
           8: [5, 7],
       },
       {
           0: [6],
           1: [9],
           2: [4, 5],
           3: [4],
           4: [2, 3],
           5: [2],
           6: [0, 7],
           7: [6],
           8: [],
           9: [1],
       },
       {
           0: [4],
           1: [6],
           2: [],
           3: [5, 6, 7],
           4: [0, 6],
           5: [3, 8, 9],
           6: [1, 3, 4, 7],
           7: [3, 6, 8, 9],
           8: [5, 7],
           9: [5, 7],
       },
       {
           0: [1, 3],
           1: [0, 2, 4],
           2: [1, 3, 4],
           3: [0, 2, 4],
           4: [1, 2, 3],
       },
   ][index]





def 	a_					( lowerCamelCase	:     dict[int, list[int]]				):
   lowerCAmelCase     =			0
   lowerCAmelCase     =			len(lowerCamelCase				)  # No of vertices in graph
   lowerCAmelCase     =			[0] * n
   lowerCAmelCase     =			[False] * n

   def dfs(lowerCamelCase	:     Tuple	, lowerCamelCase	:     str	, lowerCamelCase	:     Dict	, lowerCamelCase	:     str				):
      lowerCAmelCase     =			True
      lowerCAmelCase     =			id_
      id_ += 1
      for to in graph[at]:
         if to == parent:
            pass
         elif not visited[to]:
            dfs(lowerCamelCase	, lowerCamelCase	, lowerCamelCase	, id_				)
            lowerCAmelCase     =			min(low[at]	, low[to]				)
            if id_ <= low[to]:
               bridges.append((at, to) if at < to else (to, at)				)
         else:
            # This edge is a back edge and cannot be a bridge
            lowerCAmelCase     =			min(low[at]	, low[to]				)

   lowerCAmelCase     =			[]
   for i in range(lowerCamelCase				):
      if not visited[i]:
         dfs(lowerCamelCase	, -1	, lowerCamelCase	, id_				)
   return bridges


if __name__ == "__main__":
       import doctest

       doctest.testmod()





