
"""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


UpperCamelCase__          =	logging.get_logger(__name__)

UpperCamelCase__          =	{"""vocab_file""": """spm_char.model"""}

UpperCamelCase__          =	{
    """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""",
    }
}

UpperCamelCase__          =	{
    """microsoft/speecht5_asr""": 10_24,
    """microsoft/speecht5_tts""": 10_24,
    """microsoft/speecht5_vc""": 10_24,
}





class 				a			(					_UpperCamelCase      ):
      UpperCamelCase							:   str           =     VOCAB_FILES_NAMES
      UpperCamelCase							:   Any           =     PRETRAINED_VOCAB_FILES_MAP
      UpperCamelCase							:   Tuple           =     PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
      UpperCamelCase							:   str           =     ["""input_ids""", """attention_mask"""]



      def __init__(   self     ,	UpperCamelCase_     ,	UpperCamelCase_="<s>"     ,	UpperCamelCase_="</s>"     ,	UpperCamelCase_="<unk>"     ,	UpperCamelCase_="<pad>"     ,	UpperCamelCase_ = None     ,	**UpperCamelCase_     ,	):
          UpperCAmelCase__	:      int     							=					{} if sp_model_kwargs is None else sp_model_kwargs

          super().__init__(
              bos_token=UpperCamelCase_     ,	eos_token=UpperCamelCase_     ,	unk_token=UpperCamelCase_     ,	pad_token=UpperCamelCase_     ,	sp_model_kwargs=self.sp_model_kwargs     ,	**UpperCamelCase_     ,	)

          UpperCAmelCase__	:      str     							=					vocab_file

          UpperCAmelCase__	:      Optional[int]     							=					spm.SentencePieceProcessor(**self.sp_model_kwargs      )
          self.sp_model.Load(UpperCamelCase_      )



      @property
      def  __snake_case							(   self      ):
          return self.sp_model.get_piece_size()



      def  __snake_case							(   self      ):
          UpperCAmelCase__	:      Optional[Any]     							=					{self.convert_ids_to_tokens(UpperCamelCase_      ): i for i in range(self.vocab_size      )}
          vocab.update(self.added_tokens_encoder      )
          return vocab



      def __getstate__(   self      ):
          UpperCAmelCase__	:      List[Any]     							=					self.__dict__.copy()
          UpperCAmelCase__	:      Union[str, Any]     							=					None
          return state



      def __setstate__(   self     ,	UpperCamelCase_      ):
          UpperCAmelCase__	:      Optional[int]     							=					d

          # for backward compatibility
          if not hasattr(self     ,	'sp_model_kwargs'      ):
              UpperCAmelCase__	:      List[Any]     							=					{}

          UpperCAmelCase__	:      Tuple     							=					spm.SentencePieceProcessor(**self.sp_model_kwargs      )
          self.sp_model.Load(self.vocab_file      )



      def  __snake_case							(   self     ,	UpperCamelCase_      ):
          return self.sp_model.encode(UpperCamelCase_     ,	out_type=UpperCamelCase_      )



      def  __snake_case							(   self     ,	UpperCamelCase_      ):
          return self.sp_model.piece_to_id(UpperCamelCase_      )



      def  __snake_case							(   self     ,	UpperCamelCase_      ):
          UpperCAmelCase__	:      int     							=					self.sp_model.IdToPiece(UpperCamelCase_      )
          return token



      def  __snake_case							(   self     ,	UpperCamelCase_      ):
          UpperCAmelCase__	:      Dict     							=					[]
          UpperCAmelCase__	:      List[str]     							=					""
          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(UpperCamelCase_      ) + token
                  UpperCAmelCase__	:      Any     							=					[]
              else:
                  current_sub_tokens.append(UpperCamelCase_      )
          out_string += self.sp_model.decode(UpperCamelCase_      )
          return out_string.strip()



      def  __snake_case							(   self     ,	UpperCamelCase_     ,	UpperCamelCase_=None      ):





          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     ,	UpperCamelCase_     ,	UpperCamelCase_ = None     ,	UpperCamelCase_ = False      ):





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

          UpperCAmelCase__	:      Any     							=					[1]
          if token_ids_a is None:
              return ([0] * len(UpperCamelCase_      )) + suffix_ones
          return ([0] * len(UpperCamelCase_      )) + ([0] * len(UpperCamelCase_      )) + suffix_ones



      def  __snake_case							(   self     ,	UpperCamelCase_     ,	UpperCamelCase_ = None      ):





          if not os.path.isdir(UpperCamelCase_      ):
              logger.error(F'''Vocabulary path ({save_directory}) should be a directory'''      )
              return
          UpperCAmelCase__	:      List[Any]     							=					os.path.join(
              UpperCamelCase_     ,	(filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file']      )

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

          return (out_vocab_file,)








# Function to print upper half of diamond (pyramid)






def    _A	(   lowerCamelCase ):
   for i in range(0				,			lowerCamelCase ):
      for _ in range(0				,			n - i - 1 ):  # printing spaces
         print(" "				,			end="" )
      for _ in range(0				,			i + 1 ):  # printing stars
         print("* "				,			end="" )
      print()






def    _A	(   lowerCamelCase ):
   for i in range(lowerCamelCase				,			0				,			-1 ):
      for _ in range(lowerCamelCase				,			0				,			-1 ):  # printing stars
         print("* "				,			end="" )
      print()
      for _ in range(n - i + 1				,			0				,			-1 ):  # printing spaces
         print(" "				,			end="" )






def    _A	(   lowerCamelCase ):
   if n <= 0:
      print("       ...       ....        nothing printing :(" )
      return
   floyd(lowerCamelCase )  # upper half
   reverse_floyd(lowerCamelCase )  # lower half


if __name__ == "__main__":
  print(R"""| /\ | |- |  |-  |--| |\  /| |-""")
  print(R"""|/  \| |- |_ |_  |__| | \/ | |_""")
  SCREAMING_SNAKE_CASE__							:      Dict         =    1
  while K:
    SCREAMING_SNAKE_CASE__							:      str         =    int(input("""enter the number and , and see the magic : """))
    print()
    pretty_print(user_number)
    SCREAMING_SNAKE_CASE__							:      Tuple         =    int(input("""press 0 to exit... and 1 to continue..."""))

  print("""Good Bye...""")

