

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


__lowercase     : List[str]       =						logging.get_logger(__name__)

__lowercase     : List[str]       =						'''▁'''

__lowercase     : str       =						{
    '''vocab_file''': '''vocab.json''',
    '''spm_file''': '''sentencepiece.bpe.model''',
}

__lowercase     : List[str]       =						{
    '''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'''
        )
    },
}

__lowercase     : Union[str, Any]       =						{
    '''facebook/s2t-small-librispeech-asr''': 1_024,
}

__lowercase     : List[Any]       =						['''pt''', '''fr''', '''ru''', '''nl''', '''ro''', '''it''', '''es''', '''de''']

__lowercase     : Optional[int]       =						{'''mustc''': MUSTC_LANGS}



class 						_A     (				snake_case				):





  '''simple docstring'''



  __lowerCamelCase			:      Tuple					=   VOCAB_FILES_NAMES
  __lowerCamelCase			:      Dict					=   PRETRAINED_VOCAB_FILES_MAP
  __lowerCamelCase			:      Optional[int]					=   MAX_MODEL_INPUT_SIZES
  __lowerCamelCase			:      Tuple					=   ['''input_ids''', '''attention_mask''']

  __lowerCamelCase			:      List[int]					=   []





  def __init__(  self   ,SCREAMING_SNAKE_CASE_   ,SCREAMING_SNAKE_CASE_   ,SCREAMING_SNAKE_CASE_="<s>"   ,SCREAMING_SNAKE_CASE_="</s>"   ,SCREAMING_SNAKE_CASE_="<pad>"   ,SCREAMING_SNAKE_CASE_="<unk>"   ,SCREAMING_SNAKE_CASE_=False   ,SCREAMING_SNAKE_CASE_=False   ,SCREAMING_SNAKE_CASE_=None   ,SCREAMING_SNAKE_CASE_=None   ,SCREAMING_SNAKE_CASE_ = None   ,**SCREAMING_SNAKE_CASE_   ,):

      '''simple docstring'''
      snake_case							:		Optional[int]        =		{} if sp_model_kwargs is None else sp_model_kwargs

      super().__init__(
          bos_token=SCREAMING_SNAKE_CASE_   ,eos_token=SCREAMING_SNAKE_CASE_   ,unk_token=SCREAMING_SNAKE_CASE_   ,pad_token=SCREAMING_SNAKE_CASE_   ,do_upper_case=SCREAMING_SNAKE_CASE_   ,do_lower_case=SCREAMING_SNAKE_CASE_   ,tgt_lang=SCREAMING_SNAKE_CASE_   ,lang_codes=SCREAMING_SNAKE_CASE_   ,sp_model_kwargs=self.sp_model_kwargs   ,**SCREAMING_SNAKE_CASE_   ,)
      snake_case							:		Optional[int]        =		do_upper_case
      snake_case							:		Optional[Any]        =		do_lower_case

      snake_case							:		Optional[Any]        =		load_json(SCREAMING_SNAKE_CASE_    )
      snake_case							:		Union[str, Any]        =		{v: k for k, v in self.encoder.items()}
      snake_case							:		Tuple        =		spm_file
      snake_case							:		Optional[Any]        =		load_spm(SCREAMING_SNAKE_CASE_   ,self.sp_model_kwargs    )

      if lang_codes is not None:
          snake_case							:		List[Any]        =		lang_codes
          snake_case							:		str        =		LANGUAGES[lang_codes]
          snake_case							:		Tuple        =		[F"""<lang:{lang}>""" for lang in self.langs]
          snake_case							:		List[str]        =		{lang: self.sp_model.PieceToId(F"""<lang:{lang}>"""    ) for lang in self.langs}

          snake_case							:		Dict        =		self.lang_tokens
          snake_case							:		Tuple        =		tgt_lang if tgt_lang is not None else self.langs[0]

          self.set_tgt_lang_special_tokens(self._tgt_lang    )
      else:
          snake_case							:		str        =		{}





  @property
  def    snake_case_       (  self    ):

      '''simple docstring'''
      return len(self.encoder    )





  @property
  def    snake_case_       (  self    ):

      '''simple docstring'''
      return self._tgt_lang





  @tgt_lang.setter
  def    snake_case_       (  self   ,SCREAMING_SNAKE_CASE_    ):

      '''simple docstring'''
      snake_case							:		Optional[int]        =		new_tgt_lang
      self.set_tgt_lang_special_tokens(SCREAMING_SNAKE_CASE_    )





  def    snake_case_       (  self   ,SCREAMING_SNAKE_CASE_    ):

      '''simple docstring'''
      snake_case							:		Dict        =		self.lang_code_to_id[tgt_lang]
      snake_case							:		Union[str, Any]        =		[lang_code_id]





  def    snake_case_       (  self   ,SCREAMING_SNAKE_CASE_    ):

      '''simple docstring'''
      return self.sp_model.encode(SCREAMING_SNAKE_CASE_   ,out_type=SCREAMING_SNAKE_CASE_    )





  def    snake_case_       (  self   ,SCREAMING_SNAKE_CASE_    ):

      '''simple docstring'''
      return self.encoder.get(SCREAMING_SNAKE_CASE_   ,self.encoder[self.unk_token]    )





  def    snake_case_       (  self   ,SCREAMING_SNAKE_CASE_    ):

      '''simple docstring'''
      return self.decoder.get(SCREAMING_SNAKE_CASE_   ,self.unk_token    )





  def    snake_case_       (  self   ,SCREAMING_SNAKE_CASE_    ):

      '''simple docstring'''
      snake_case							:		List[str]        =		[]
      snake_case							:		int        =		""""""
      for token in tokens:
          # make sure that special tokens are not decoded using sentencepiece model
          if token in self.all_special_tokens:
              snake_case							:		Tuple        =		self.sp_model.decode(SCREAMING_SNAKE_CASE_    )
              out_string += (decoded.upper() if self.do_upper_case else decoded) + token + " "
              snake_case							:		Optional[int]        =		[]
          else:
              current_sub_tokens.append(SCREAMING_SNAKE_CASE_    )
      snake_case							:		str        =		self.sp_model.decode(SCREAMING_SNAKE_CASE_    )
      out_string += decoded.upper() if self.do_upper_case else decoded
      return out_string.strip()





  def    snake_case_       (  self   ,SCREAMING_SNAKE_CASE_   ,SCREAMING_SNAKE_CASE_=None    ):

      '''simple docstring'''
      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    snake_case_       (  self   ,SCREAMING_SNAKE_CASE_   ,SCREAMING_SNAKE_CASE_ = None   ,SCREAMING_SNAKE_CASE_ = False    ):

      '''simple docstring'''

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

      snake_case							:		Union[str, Any]        =		[1] * len(self.prefix_tokens    )
      snake_case							:		Tuple        =		[1]
      if token_ids_a is None:
          return prefix_ones + ([0] * len(SCREAMING_SNAKE_CASE_    )) + suffix_ones
      return prefix_ones + ([0] * len(SCREAMING_SNAKE_CASE_    )) + ([0] * len(SCREAMING_SNAKE_CASE_    )) + suffix_ones





  def    snake_case_       (  self    ):

      '''simple docstring'''
      snake_case							:		Union[str, Any]        =		self.encoder.copy()
      vocab.update(self.added_tokens_encoder    )
      return vocab





  def __getstate__(  self    ):

      '''simple docstring'''
      snake_case							:		Tuple        =		self.__dict__.copy()
      snake_case							:		List[Any]        =		None
      return state





  def __setstate__(  self   ,SCREAMING_SNAKE_CASE_    ):

      '''simple docstring'''
      snake_case							:		int        =		d

      # for backward compatibility
      if not hasattr(self   ,"""sp_model_kwargs"""    ):
          snake_case							:		List[str]        =		{}

      snake_case							:		Dict        =		load_spm(self.spm_file   ,self.sp_model_kwargs    )





  def    snake_case_       (  self   ,SCREAMING_SNAKE_CASE_   ,SCREAMING_SNAKE_CASE_ = None    ):

      '''simple docstring'''
      snake_case							:		Union[str, Any]        =		Path(SCREAMING_SNAKE_CASE_    )
      assert save_dir.is_dir(), F"""{save_directory} should be a directory"""
      snake_case							:		List[Any]        =		save_dir / (
          (filename_prefix + """-""" if filename_prefix else """""") + self.vocab_files_names["""vocab_file"""]
      )
      snake_case							:		List[Any]        =		save_dir / (
          (filename_prefix + """-""" if filename_prefix else """""") + self.vocab_files_names["""spm_file"""]
      )

      save_json(self.encoder   ,SCREAMING_SNAKE_CASE_    )

      if os.path.abspath(self.spm_file    ) != os.path.abspath(SCREAMING_SNAKE_CASE_    ) and os.path.isfile(self.spm_file    ):
          copyfile(self.spm_file   ,SCREAMING_SNAKE_CASE_    )
      elif not os.path.isfile(self.spm_file    ):
          with open(SCREAMING_SNAKE_CASE_   ,"""wb"""    ) as fi:
              snake_case							:		List[Any]        =		self.sp_model.serialized_model_proto()
              fi.write(SCREAMING_SNAKE_CASE_    )

      return (str(SCREAMING_SNAKE_CASE_    ), str(SCREAMING_SNAKE_CASE_    ))







def       lowercase					(	__A :					str ,    __A :					Dict[str, Any]		)				->			sentencepiece.SentencePieceProcessor:





    '''simple docstring'''




    snake_case							:		Optional[int]        =		sentencepiece.SentencePieceProcessor(**__A		)
    spm.Load(str(__A		)		)
    return spm







def       lowercase					(	__A :					str		)				->			Union[Dict, List]:





    '''simple docstring'''




    with open(__A ,    """r"""		) as f:
        return json.load(__A		)







def       lowercase					(	__A :					str ,    __A :					str		)				->			None:





    '''simple docstring'''




    with open(__A ,    """w"""		) as f:
        json.dump(__A ,    __A ,    indent=2		)








'''simple docstring'''





import random
from typing import Any

def 			a_	(				_lowerCAmelCase			) -> list[Any]:
  for _ in range(len(_lowerCAmelCase			)			):
    __lowerCamelCase			:			Optional[Any]       			=					random.randint(0			,len(_lowerCAmelCase			) - 1			)
    __lowerCamelCase			:			str       			=					random.randint(0			,len(_lowerCAmelCase			) - 1			)
    __lowerCamelCase			,__lowerCamelCase			:			List[Any]       			=					data[b], data[a]
  return data


if __name__ == "__main__":
   _UpperCamelCase											=		[0, 1, 2, 3, 4, 5, 6, 7]
   _UpperCamelCase											=		['python', 'says', 'hello', '!']
   print('Fisher-Yates Shuffle:')
   print('List', integers, strings)
   print('FY Shuffle', fisher_yates_shuffle(integers), fisher_yates_shuffle(strings))






