

import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple

import sentencepiece as spm

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


__lowercase     : Optional[int]       =						logging.get_logger(__name__)

__lowercase     : Any       =						{'''vocab_file''': '''spm_char.model'''}

__lowercase     : Tuple       =						{
    '''vocab_file''': {
        '''microsoft/speecht5_asr''': '''https://huggingface.co/microsoft/speecht5_asr/resolve/main/spm_char.model''',
        '''microsoft/speecht5_tts''': '''https://huggingface.co/microsoft/speecht5_tts/resolve/main/spm_char.model''',
        '''microsoft/speecht5_vc''': '''https://huggingface.co/microsoft/speecht5_vc/resolve/main/spm_char.model''',
    }
}

__lowercase     : Optional[int]       =						{
    '''microsoft/speecht5_asr''': 1_024,
    '''microsoft/speecht5_tts''': 1_024,
    '''microsoft/speecht5_vc''': 1_024,
}



class 						_A     (				snake_case				):





  '''simple docstring'''



  __lowerCamelCase			:      List[str]					=   VOCAB_FILES_NAMES
  __lowerCamelCase			:      str					=   PRETRAINED_VOCAB_FILES_MAP
  __lowerCamelCase			:      List[str]					=   PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
  __lowerCamelCase			:      Union[str, Any]					=   ['''input_ids''', '''attention_mask''']





  def __init__(  self   ,SCREAMING_SNAKE_CASE_   ,SCREAMING_SNAKE_CASE_="<s>"   ,SCREAMING_SNAKE_CASE_="</s>"   ,SCREAMING_SNAKE_CASE_="<unk>"   ,SCREAMING_SNAKE_CASE_="<pad>"   ,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_   ,sp_model_kwargs=self.sp_model_kwargs   ,**SCREAMING_SNAKE_CASE_   ,)

      snake_case							:		Optional[Any]        =		vocab_file

      snake_case							:		Tuple        =		spm.SentencePieceProcessor(**self.sp_model_kwargs    )
      self.sp_model.Load(SCREAMING_SNAKE_CASE_    )





  @property
  def    snake_case_       (  self    ):

      '''simple docstring'''
      return self.sp_model.get_piece_size()





  def    snake_case_       (  self    ):

      '''simple docstring'''
      snake_case							:		List[str]        =		{self.convert_ids_to_tokens(SCREAMING_SNAKE_CASE_    ): i for i in range(self.vocab_size    )}
      vocab.update(self.added_tokens_encoder    )
      return vocab





  def __getstate__(  self    ):

      '''simple docstring'''
      snake_case							:		Dict        =		self.__dict__.copy()
      snake_case							:		Dict        =		None
      return state





  def __setstate__(  self   ,SCREAMING_SNAKE_CASE_    ):

      '''simple docstring'''
      snake_case							:		Tuple        =		d

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

      snake_case							:		List[Any]        =		spm.SentencePieceProcessor(**self.sp_model_kwargs    )
      self.sp_model.Load(self.vocab_file    )





  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.sp_model.piece_to_id(SCREAMING_SNAKE_CASE_    )





  def    snake_case_       (  self   ,SCREAMING_SNAKE_CASE_    ):

      '''simple docstring'''
      snake_case							:		Optional[Any]        =		self.sp_model.IdToPiece(SCREAMING_SNAKE_CASE_    )
      return token





  def    snake_case_       (  self   ,SCREAMING_SNAKE_CASE_    ):

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





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

      '''simple docstring'''
      if token_ids_a is None:
          return token_ids_a + [self.eos_token_id]
      # We don't expect to process pairs, but leave the pair logic for API consistency
      return 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							:		Optional[int]        =		[1]
      if token_ids_a is None:
          return ([0] * len(SCREAMING_SNAKE_CASE_    )) + suffix_ones
      return ([0] * len(SCREAMING_SNAKE_CASE_    )) + ([0] * len(SCREAMING_SNAKE_CASE_    )) + suffix_ones





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

      '''simple docstring'''
      if not os.path.isdir(SCREAMING_SNAKE_CASE_    ):
          logger.error(F"""Vocabulary path ({save_directory}) should be a directory"""    )
          return
      snake_case							:		Tuple        =		os.path.join(
          SCREAMING_SNAKE_CASE_   ,(filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab_file"""]    )

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

      return (out_vocab_file,)






"""simple docstring"""
def 					a__						(						lowerCAmelCase			,	lowerCAmelCase    )	-> str:
      if a < 0 or b < 0:
            raise ValueError("""the value of both inputs must be positive"""    )

      UpperCAmelCase__			:							Dict							=    str(bin(lowerCAmelCase    )    )[2:]  # remove the leading "0b"
      UpperCAmelCase__			:							Any							=    str(bin(lowerCAmelCase    )    )[2:]  # remove the leading "0b"

      UpperCAmelCase__			:							Optional[Any]							=    max(len(lowerCAmelCase    )			,	len(lowerCAmelCase    )    )

      return "0b" + "".join(
          str(int(char_a != char_b    )    )
          for char_a, char_b in zip(a_binary.zfill(lowerCAmelCase    )			,	b_binary.zfill(lowerCAmelCase    )    )    )


if __name__ == "__main__":
    import doctest

    doctest.testmod()

