
"""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


_lowercase							      = logging.get_logger(__name__)


_lowercase							      = '''▁'''

_lowercase							      = {'''vocab_file''': '''spiece.model'''}

_lowercase							      = {
    '''vocab_file''': {
        '''google/reformer-crime-and-punishment''': (
            '''https://huggingface.co/google/reformer-crime-and-punishment/resolve/main/spiece.model'''
        )
    }
}

_lowercase							      = {
    '''google/reformer-crime-and-punishment''': 52_42_88,
}







class  lowerCAmelCase_ (					_lowercase			):



						'''simple docstring'''


						_lowerCamelCase:			Any					=			VOCAB_FILES_NAMES
						_lowerCamelCase:			List[str]					=			PRETRAINED_VOCAB_FILES_MAP
						_lowerCamelCase:			int					=			PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
						_lowerCamelCase:			Any					=			['''input_ids''', '''attention_mask''']


						def __init__(       self   :					Tuple     ,A_   :					Optional[Any]     ,A_   :					Optional[Any]="</s>"     ,A_   :					Union[str, Any]="<unk>"     ,A_   :					Dict=[]     ,A_   :					Optional[Dict[str, Any]] = None     ,**A_   :					str     ,)   ->      None:
							A        =      {} if sp_model_kwargs is None else sp_model_kwargs

							super().__init__(
							    eos_token=A_     ,unk_token=A_     ,additional_special_tokens=A_     ,sp_model_kwargs=self.sp_model_kwargs     ,**A_     ,)

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


						@property
						def   _SCREAMING_SNAKE_CASE					(       self   :					Union[str, Any]					)   ->      List[Any]:
							return self.sp_model.get_piece_size()


						def   _SCREAMING_SNAKE_CASE					(       self   :					Optional[int]					)   ->      Dict[str, int]:
							A        =      {self.convert_ids_to_tokens(A_					): i for i in range(self.vocab_size					)}
							vocab.update(self.added_tokens_encoder					)
							return vocab


						def __getstate__(       self   :					str					)   ->      Tuple:
							A        =      self.__dict__.copy()
							A        =      None
							return state


						def __setstate__(       self   :					int     ,A_   :					str					)   ->      str:
							A        =      d

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

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


						def   _SCREAMING_SNAKE_CASE					(       self   :					List[Any]     ,A_   :					str					)   ->      List[str]:
							return self.sp_model.encode(A_     ,out_type=A_					)


						def   _SCREAMING_SNAKE_CASE					(       self   :					Optional[Any]     ,A_   :					Optional[Any]					)   ->      Optional[Any]:
							return self.sp_model.piece_to_id(A_					)


						def   _SCREAMING_SNAKE_CASE					(       self   :					Optional[int]     ,A_   :					Optional[int]					)   ->      Dict:
							if index < self.sp_model.get_piece_size():
								A        =      self.sp_model.IdToPiece(A_					)
							return token


						def   _SCREAMING_SNAKE_CASE					(       self   :					Tuple     ,A_   :					int					)   ->      Dict:
							A        =      []
							A        =      ''
							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(A_					) + token
									A        =      []
								else:
									current_sub_tokens.append(A_					)
							out_string += self.sp_model.decode(A_					)
							return out_string.strip()




						def   _SCREAMING_SNAKE_CASE					(       self   :					Optional[int]     ,A_   :					str     ,A_   :					Optional[str] = None					)   ->      Tuple[str]:
							if not os.path.isdir(A_					):
								logger.error(F'Vocabulary path ({save_directory}) should be a directory'					)
								return
							A        =      os.path.join(
							    A_     ,(filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file']					)

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

							return (out_vocab_file,)



def 							_UpperCAmelCase				(UpperCamelCase__     :  Optional[Any]				,							UpperCamelCase__     :  Union[str, Any]						):
       # "extended trapezoidal rule"
       # int(f) = dx/2 * (f1 + 2f2 + ... + fn)
       _A      :       int				    = (boundary[1] - boundary[0]) / steps
       _A      :       Any				    = boundary[0]
       _A      :       List[Any]				    = boundary[1]
       _A      :       str				    = make_points(UpperCamelCase__				,							UpperCamelCase__				,							UpperCamelCase__						)
       _A      :       str				    = 0.0
       y += (h / 2.0) * f(UpperCamelCase__						)
       for i in x_i:
              # print(i)
              y += h * f(UpperCamelCase__						)
       y += (h / 2.0) * f(UpperCamelCase__						)
       return y
def 							_UpperCAmelCase				(UpperCamelCase__     :  List[str]				,							UpperCamelCase__     :  Optional[int]				,							UpperCamelCase__     :  Any						):
       _A      :       Optional[int]				    = a + h
       while x < (b - h):
              yield x
              _A      :       Dict				    = x + h
def 							_UpperCAmelCase				(UpperCamelCase__     :  Optional[int]						):  # enter your function here
       _A      :       Any				    = (x - 0) * (x - 0)
       return y
def 							_UpperCAmelCase				():
       _A      :       Optional[Any]				    = 0.0  # Lower bound of integration
       _A      :       Optional[int]				    = 1.0  # Upper bound of integration
       _A      :       List[Any]				    = 10.0  # define number of steps or resolution
       _A      :       Any				    = [a, b]  # define boundary of integration
       _A      :       Tuple				    = method_a(UpperCamelCase__				,							UpperCamelCase__						)
       print(f"y = {y}"						)


if __name__ == "__main__":
    main()
