






"""simple docstring"""





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

import sentencepiece as spm

from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging


__lowerCamelCase							=  logging.get_logger(__name__)
__lowerCamelCase							=  {'vocab_file': 'spiece.model'}

__lowerCamelCase							=  {
    'vocab_file': {
        'albert-base-v1': 'https://huggingface.co/albert-base-v1/resolve/main/spiece.model',
        'albert-large-v1': 'https://huggingface.co/albert-large-v1/resolve/main/spiece.model',
        'albert-xlarge-v1': 'https://huggingface.co/albert-xlarge-v1/resolve/main/spiece.model',
        'albert-xxlarge-v1': 'https://huggingface.co/albert-xxlarge-v1/resolve/main/spiece.model',
        'albert-base-v2': 'https://huggingface.co/albert-base-v2/resolve/main/spiece.model',
        'albert-large-v2': 'https://huggingface.co/albert-large-v2/resolve/main/spiece.model',
        'albert-xlarge-v2': 'https://huggingface.co/albert-xlarge-v2/resolve/main/spiece.model',
        'albert-xxlarge-v2': 'https://huggingface.co/albert-xxlarge-v2/resolve/main/spiece.model',
    }
}

__lowerCamelCase							=  {
    'albert-base-v1': 5_12,
    'albert-large-v1': 5_12,
    'albert-xlarge-v1': 5_12,
    'albert-xxlarge-v1': 5_12,
    'albert-base-v2': 5_12,
    'albert-large-v2': 5_12,
    'albert-xlarge-v2': 5_12,
    'albert-xxlarge-v2': 5_12,
}

__lowerCamelCase							=  '▁'



class       __A		(   __SCREAMING_SNAKE_CASE			):
					UpperCAmelCase__								=				VOCAB_FILES_NAMES
					UpperCAmelCase__								=				PRETRAINED_VOCAB_FILES_MAP
					UpperCAmelCase__								=				PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES

					def __init__(			self  :      List[str]     ,		__snake_case  :      str     ,		__snake_case  :      Any=True     ,		__snake_case  :      Optional[Any]=True     ,		__snake_case  :      Any=False     ,		__snake_case  :      str="[CLS]"     ,		__snake_case  :      Dict="[SEP]"     ,		__snake_case  :      int="<unk>"     ,		__snake_case  :      Optional[Any]="[SEP]"     ,		__snake_case  :      List[str]="<pad>"     ,		__snake_case  :      Any="[CLS]"     ,		__snake_case  :      List[Any]="[MASK]"     ,		__snake_case  :      Optional[Dict[str, Any]] = None     ,		**__snake_case  :      Any     ,		)			->							None:
											__magic_name__:	str							=       (
											    AddedToken(_SCREAMING_SNAKE_CASE     ,		lstrip=_SCREAMING_SNAKE_CASE     ,		rstrip=_SCREAMING_SNAKE_CASE     ,		normalized=_SCREAMING_SNAKE_CASE					)
											    if isinstance(_SCREAMING_SNAKE_CASE     ,		_SCREAMING_SNAKE_CASE					)
											    else mask_token
											)

											__magic_name__:	int							=       {} if sp_model_kwargs is None else sp_model_kwargs

											super().__init__(
											    do_lower_case=_SCREAMING_SNAKE_CASE     ,		remove_space=_SCREAMING_SNAKE_CASE     ,		keep_accents=_SCREAMING_SNAKE_CASE     ,		bos_token=_SCREAMING_SNAKE_CASE     ,		eos_token=_SCREAMING_SNAKE_CASE     ,		unk_token=_SCREAMING_SNAKE_CASE     ,		sep_token=_SCREAMING_SNAKE_CASE     ,		pad_token=_SCREAMING_SNAKE_CASE     ,		cls_token=_SCREAMING_SNAKE_CASE     ,		mask_token=_SCREAMING_SNAKE_CASE     ,		sp_model_kwargs=self.sp_model_kwargs     ,		**_SCREAMING_SNAKE_CASE     ,		)

											__magic_name__:	Any							=       do_lower_case
											__magic_name__:	Any							=       remove_space
											__magic_name__:	Any							=       keep_accents
											__magic_name__:	List[Any]							=       vocab_file

											__magic_name__:	str							=       spm.SentencePieceProcessor(**self.sp_model_kwargs					)
											self.sp_model.Load(_SCREAMING_SNAKE_CASE					)

					@property
					def   lowerCamelCase__   (			self  :      str					)			->							Optional[Any]:
											return len(self.sp_model					)

					def   lowerCamelCase__   (			self  :      int					)			->							List[Any]:
											__magic_name__:	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  :      Union[str, Any]					)			->							List[str]:
											__magic_name__:	Dict							=       self.__dict__.copy()
											__magic_name__:	List[str]							=       None
											return state

					def __setstate__(			self  :      Optional[int]     ,		__snake_case  :      List[str]					)			->							str:
											__magic_name__:	Union[str, Any]							=       d

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

											__magic_name__:	Union[str, Any]							=       spm.SentencePieceProcessor(**self.sp_model_kwargs					)
											self.sp_model.Load(self.vocab_file					)

					def   lowerCamelCase__   (			self  :      Union[str, Any]     ,		__snake_case  :      Tuple					)			->							List[Any]:

											if self.remove_space:
																	__magic_name__:	List[str]							=       " ".join(inputs.strip().split()					)
											else:
																	__magic_name__:	Any							=       inputs
											__magic_name__:	Tuple							=       outputs.replace("""``"""     ,		"""\""""					).replace("""''"""     ,		"""\""""					)

											if not self.keep_accents:
																	__magic_name__:	List[str]							=       unicodedata.normalize("""NFKD"""     ,		_SCREAMING_SNAKE_CASE					)
																	__magic_name__:	Tuple							=       "".join([c for c in outputs if not unicodedata.combining(_SCREAMING_SNAKE_CASE					)]					)
											if self.do_lower_case:
																	__magic_name__:	Optional[Any]							=       outputs.lower()

											return outputs

					def   lowerCamelCase__   (			self  :      Dict     ,		__snake_case  :      str					)			->							List[str]:
											__magic_name__:	Optional[int]							=       self.preprocess_text(_SCREAMING_SNAKE_CASE					)
											__magic_name__:	Optional[Any]							=       self.sp_model.encode(_SCREAMING_SNAKE_CASE     ,		out_type=_SCREAMING_SNAKE_CASE					)
											__magic_name__:	Tuple							=       []
											for piece in pieces:
																	if len(_SCREAMING_SNAKE_CASE					) > 1 and piece[-1] == str(""","""					) and piece[-2].isdigit():
																							__magic_name__:	Union[str, Any]							=       self.sp_model.EncodeAsPieces(piece[:-1].replace(_SCREAMING_SNAKE_CASE     ,		""""""					)					)
																							if piece[0] != SPIECE_UNDERLINE and cur_pieces[0][0] == SPIECE_UNDERLINE:
																													if len(cur_pieces[0]					) == 1:
																																			__magic_name__:	int							=       cur_pieces[1:]
																													else:
																																			__magic_name__:	int							=       cur_pieces[0][1:]
																							cur_pieces.append(piece[-1]					)
																							new_pieces.extend(_SCREAMING_SNAKE_CASE					)
																	else:
																							new_pieces.append(_SCREAMING_SNAKE_CASE					)

											return new_pieces

					def   lowerCamelCase__   (			self  :      Tuple     ,		__snake_case  :      int					)			->							Union[str, Any]:
											return self.sp_model.PieceToId(_SCREAMING_SNAKE_CASE					)

					def   lowerCamelCase__   (			self  :      Any     ,		__snake_case  :      str					)			->							Tuple:
											return self.sp_model.IdToPiece(_SCREAMING_SNAKE_CASE					)

					def   lowerCamelCase__   (			self  :      Any     ,		__snake_case  :      Any					)			->							Any:
											__magic_name__:	Dict							=       []
											__magic_name__:	Tuple							=       ""
											__magic_name__:	Dict							=       False
											for token in tokens:
																	# make sure that special tokens are not decoded using sentencepiece model
																	if token in self.all_special_tokens:
																							if not prev_is_special:
																													out_string += " "
																							out_string += self.sp_model.decode(_SCREAMING_SNAKE_CASE					) + token
																							__magic_name__:	List[str]							=       True
																							__magic_name__:	Optional[int]							=       []
																	else:
																							current_sub_tokens.append(_SCREAMING_SNAKE_CASE					)
																							__magic_name__:	Union[str, Any]							=       False
											out_string += self.sp_model.decode(_SCREAMING_SNAKE_CASE					)
											return out_string.strip()

					def   lowerCamelCase__   (			self  :      Tuple     ,		__snake_case  :      List[int]     ,		__snake_case  :      Optional[List[int]] = None					)			->							List[int]:
											__magic_name__:	List[str]							=       [self.sep_token_id]
											__magic_name__:	List[Any]							=       [self.cls_token_id]
											if token_ids_a is None:
																	return cls + token_ids_a + sep
											return cls + token_ids_a + sep + token_ids_a + sep

					def   lowerCamelCase__   (			self  :      Dict     ,		__snake_case  :      List[int]     ,		__snake_case  :      Optional[List[int]] = None     ,		__snake_case  :      bool = False					)			->							List[int]:

											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					)

											if token_ids_a is not None:
																	return [1] + ([0] * len(_SCREAMING_SNAKE_CASE					)) + [1] + ([0] * len(_SCREAMING_SNAKE_CASE					)) + [1]
											return [1] + ([0] * len(_SCREAMING_SNAKE_CASE					)) + [1]

					def   lowerCamelCase__   (			self  :      Optional[Any]     ,		__snake_case  :      List[int]     ,		__snake_case  :      Optional[List[int]] = None					)			->							List[int]:
											__magic_name__:	List[str]							=       [self.sep_token_id]
											__magic_name__:	int							=       [self.cls_token_id]

											if token_ids_a is None:
																	return len(cls + token_ids_a + sep					) * [0]
											return len(cls + token_ids_a + sep					) * [0] + len(token_ids_a + sep					) * [1]






					def   lowerCamelCase__   (			self  :      Dict     ,		__snake_case  :      str     ,		__snake_case  :      Optional[str] = None					)			->							Tuple[str]:

											if not os.path.isdir(_SCREAMING_SNAKE_CASE					):
																	logger.error(F'Vocabulary path ({save_directory}) should be a directory'					)
																	return
											__magic_name__:	List[str]							=       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:
																							__magic_name__:	List[Any]							=       self.sp_model.serialized_model_proto()
																							fi.write(_SCREAMING_SNAKE_CASE					)

											return (out_vocab_file,)








"""simple docstring"""






def      _lowercase							(    __snake_case      )		->  float:
			return 10 - x * x


def      _lowercase							(    __snake_case   ,__snake_case      )		->  float:
			# Bolzano theory in order to find if there is a root between a and b
			if equation(__snake_case      ) * equation(__snake_case      ) >= 0:
						raise ValueError("Wrong space!"      )

			__lowerCAmelCase :    List[Any]				=			a
			while (b - a) >= 0.01:
						# Find middle point
						__lowerCAmelCase :    str				=			(a + b) / 2
						# Check if middle point is root
						if equation(__snake_case      ) == 0.0:
									break
						# Decide the side to repeat the steps
						if equation(__snake_case      ) * equation(__snake_case      ) < 0:
									__lowerCAmelCase :    List[Any]				=			c
						else:
									__lowerCAmelCase :    List[str]				=			c
			return c


if __name__ == "__main__":
	import doctest

	doctest.testmod()

	print(bisection(-2, 5))
	print(bisection(0, 6))