






'''simple docstring'''

import argparse
import os
import re


SCREAMING_SNAKE_CASE__     =       'src/transformers/models/auto'


# re pattern that matches mapping introductions:
#    SUPER_MODEL_MAPPING_NAMES = OrderedDict or SUPER_MODEL_MAPPING = OrderedDict
SCREAMING_SNAKE_CASE__     =       re.compile(R'[A-Z_]+_MAPPING(\s+|_[A-Z_]+\s+)=\s+OrderedDict')
# re pattern that matches identifiers in mappings
SCREAMING_SNAKE_CASE__     =       re.compile(R'\s*\(\s*"(\S[^"]+)"')







def    lowercase__			(				__UpperCamelCase		,						__UpperCamelCase = False   )->			Optional[Any]:
      with open(__lowerCamelCase		,						"""r"""		,						encoding="""utf-8"""   ) as f:
            UpperCamelCase      = f.read()

      UpperCamelCase      = content.split("""\n"""   )
      UpperCamelCase      = []
      UpperCamelCase      = 0
      while line_idx < len(__lowerCamelCase   ):
            if _re_intro_mapping.search(lines[line_idx]   ) is not None:
                  UpperCamelCase      = len(re.search(R"""^(\s*)\S"""		,						lines[line_idx]   ).groups()[0]   ) + 8
                  # Start of a new mapping!
                  while not lines[line_idx].startswith(""" """ * indent + """("""   ):
                        new_lines.append(lines[line_idx]   )
                        line_idx += 1

                  UpperCamelCase      = []
                  while lines[line_idx].strip() != "]":
                        # Blocks either fit in one line or not
                        if lines[line_idx].strip() == "(":
                              UpperCamelCase      = line_idx
                              while not lines[line_idx].startswith(""" """ * indent + """)"""   ):
                                    line_idx += 1
                              blocks.append("""\n""".join(lines[start_idx : line_idx + 1]   )   )
                        else:
                              blocks.append(lines[line_idx]   )
                        line_idx += 1

                  # Sort blocks by their identifiers
                  UpperCamelCase      = sorted(__lowerCamelCase		,						key=lambda __UpperCamelCase   : _re_identifier.search(__lowerCamelCase   ).groups()[0]   )
                  new_lines += blocks
            else:
                  new_lines.append(lines[line_idx]   )
                  line_idx += 1

      if overwrite:
            with open(__lowerCamelCase		,						"""w"""		,						encoding="""utf-8"""   ) as f:
                  f.write("""\n""".join(__lowerCamelCase   )   )
      elif "\n".join(__lowerCamelCase   ) != content:
            return True







def    lowercase__			(				__UpperCamelCase = False   )->			Any:
      UpperCamelCase      = [os.path.join(__lowerCamelCase		,						__lowerCamelCase   ) for f in os.listdir(__lowerCamelCase   ) if f.endswith(""".py"""   )]
      UpperCamelCase      = [sort_auto_mapping(__lowerCamelCase		,						overwrite=__lowerCamelCase   ) for fname in fnames]

      if not overwrite and any(__lowerCamelCase   ):
            UpperCamelCase      = [f for f, d in zip(__lowerCamelCase		,						__lowerCamelCase   ) if d]
            raise ValueError(
                F"The following files have auto mappings that need sorting: {', '.join(__lowerCamelCase   )}. Run `make style` to fix"
                """ this."""   )


if __name__ == "__main__":
    SCREAMING_SNAKE_CASE__     =       argparse.ArgumentParser()
    parser.add_argument('--check_only', action='store_true', help='Whether to only check or fix style.')
    SCREAMING_SNAKE_CASE__     =       parser.parse_args()

    sort_all_auto_mappings(not args.check_only)








'''simple docstring'''

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


SCREAMING_SNAKE_CASE__     =       logging.get_logger(__name__)

SCREAMING_SNAKE_CASE__     =       {'vocab_file': 'spm_char.model'}

SCREAMING_SNAKE_CASE__     =       {
    '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',
    }
}

SCREAMING_SNAKE_CASE__     =       {
    'microsoft/speecht5_asr': 1_0_2_4,
    'microsoft/speecht5_tts': 1_0_2_4,
    'microsoft/speecht5_vc': 1_0_2_4,
}






class     a_						(      lowerCamelCase    ):
  lowercase							=				VOCAB_FILES_NAMES
  lowercase							=				PRETRAINED_VOCAB_FILES_MAP
  lowercase							=				PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
  lowercase							=				["""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      ,		)  ->				None:



        """simple docstring"""






        UpperCamelCase      = {} 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      ,		)

        UpperCamelCase      = vocab_file

        UpperCamelCase      = spm.SentencePieceProcessor(**self.sp_model_kwargs				)
        self.sp_model.Load(_SCREAMING_SNAKE_CASE				)

  @property
  def   A__						(				self				)  ->				Tuple:



        """simple docstring"""






        return self.sp_model.get_piece_size()

  def   A__						(				self				)  ->				Tuple:



        """simple docstring"""






        UpperCamelCase      = {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				)  ->				List[Any]:



        """simple docstring"""






        UpperCamelCase      = self.__dict__.copy()
        UpperCamelCase      = None
        return state

  def __setstate__(				self      ,		_SCREAMING_SNAKE_CASE				)  ->				Union[str, Any]:



        """simple docstring"""






        UpperCamelCase      = d

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

        UpperCamelCase      = spm.SentencePieceProcessor(**self.sp_model_kwargs				)
        self.sp_model.Load(self.vocab_file				)

  def   A__						(				self      ,		_SCREAMING_SNAKE_CASE				)  ->				List[str]:



        """simple docstring"""






        return self.sp_model.encode(_SCREAMING_SNAKE_CASE      ,		out_type=_SCREAMING_SNAKE_CASE				)

  def   A__						(				self      ,		_SCREAMING_SNAKE_CASE				)  ->				Tuple:



        """simple docstring"""






        return self.sp_model.piece_to_id(_SCREAMING_SNAKE_CASE				)

  def   A__						(				self      ,		_SCREAMING_SNAKE_CASE				)  ->				List[Any]:



        """simple docstring"""






        UpperCamelCase      = self.sp_model.IdToPiece(_SCREAMING_SNAKE_CASE				)
        return token

  def   A__						(				self      ,		_SCREAMING_SNAKE_CASE				)  ->				List[str]:



        """simple docstring"""






        UpperCamelCase      = []
        UpperCamelCase      = """"""
        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
                    UpperCamelCase      = []
              else:
                    current_sub_tokens.append(_SCREAMING_SNAKE_CASE				)
        out_string += self.sp_model.decode(_SCREAMING_SNAKE_CASE				)
        return out_string.strip()

  def   A__						(				self      ,		_SCREAMING_SNAKE_CASE      ,		_SCREAMING_SNAKE_CASE=None				)  ->				List[int]:



        """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   A__						(				self      ,		_SCREAMING_SNAKE_CASE      ,		_SCREAMING_SNAKE_CASE = None      ,		_SCREAMING_SNAKE_CASE = False				)  ->				List[int]:



        """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				)

        UpperCamelCase      = [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   A__						(				self      ,		_SCREAMING_SNAKE_CASE      ,		_SCREAMING_SNAKE_CASE = None				)  ->				Tuple[str]:



        """simple docstring"""






        if not os.path.isdir(_SCREAMING_SNAKE_CASE				):
              logger.error(F"Vocabulary path ({save_directory}) should be a directory"				)
              return
        UpperCamelCase      = 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:
                    UpperCamelCase      = self.sp_model.serialized_model_proto()
                    fi.write(_SCREAMING_SNAKE_CASE				)

        return (out_vocab_file,)
