





'''simple docstring'''







import os
import re
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


snake_case_     :       Dict						=  logging.get_logger(__name__)

snake_case_     :       Optional[Any]						=  {"vocab_file": "spiece.model"}

snake_case_     :       Union[str, Any]						=  {
    "vocab_file": {
        "google/bigbird-roberta-base": "https://huggingface.co/google/bigbird-roberta-base/resolve/main/spiece.model",
        "google/bigbird-roberta-large": (
            "https://huggingface.co/google/bigbird-roberta-large/resolve/main/spiece.model"
        ),
        "google/bigbird-base-trivia-itc": (
            "https://huggingface.co/google/bigbird-base-trivia-itc/resolve/main/spiece.model"
        ),
    }
}

snake_case_     :       Any						=  {
    "google/bigbird-roberta-base": 40_96,
    "google/bigbird-roberta-large": 40_96,
    "google/bigbird-base-trivia-itc": 40_96,
}


class 					__a      (lowerCamelCase     ):
							__a					:   int									=       VOCAB_FILES_NAMES
							__a					:   Any									=       PRETRAINED_VOCAB_FILES_MAP
							__a					:   List[str]									=       PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
							__a					:   Any									=       ["input_ids", "attention_mask"]
							__a					:   List[int]									=       []

							def __init__(							self							:     Optional[int]       ,     __magic_name__							:     Optional[int]       ,     __magic_name__							:     List[Any]="<unk>"       ,     __magic_name__							:     int="<s>"       ,     __magic_name__							:     int="</s>"       ,     __magic_name__							:     Dict="<pad>"       ,     __magic_name__							:     Dict="[SEP]"       ,     __magic_name__							:     Dict="[MASK]"       ,     __magic_name__							:     List[str]="[CLS]"       ,     __magic_name__							:     Optional[Dict[str, Any]] = None       ,     **__magic_name__							:     Optional[int]       ,     )					->       None:







													"""simple docstring"""
													UpperCAmelCase_			:      Dict     						=  AddedToken(__magic_name__       ,     lstrip=__magic_name__       ,     rstrip=__magic_name__   ) if isinstance(__magic_name__       ,     __magic_name__   ) else bos_token
													UpperCAmelCase_			:      Optional[Any]     						=  AddedToken(__magic_name__       ,     lstrip=__magic_name__       ,     rstrip=__magic_name__   ) if isinstance(__magic_name__       ,     __magic_name__   ) else eos_token
													UpperCAmelCase_			:      int     						=  AddedToken(__magic_name__       ,     lstrip=__magic_name__       ,     rstrip=__magic_name__   ) if isinstance(__magic_name__       ,     __magic_name__   ) else unk_token
													UpperCAmelCase_			:      Any     						=  AddedToken(__magic_name__       ,     lstrip=__magic_name__       ,     rstrip=__magic_name__   ) if isinstance(__magic_name__       ,     __magic_name__   ) else pad_token
													UpperCAmelCase_			:      List[Any]     						=  AddedToken(__magic_name__       ,     lstrip=__magic_name__       ,     rstrip=__magic_name__   ) if isinstance(__magic_name__       ,     __magic_name__   ) else cls_token
													UpperCAmelCase_			:      Any     						=  AddedToken(__magic_name__       ,     lstrip=__magic_name__       ,     rstrip=__magic_name__   ) if isinstance(__magic_name__       ,     __magic_name__   ) else sep_token

													# Mask token behave like a normal word, i.e. include the space before it
													UpperCAmelCase_			:      List[Any]     						=  AddedToken(__magic_name__       ,     lstrip=__magic_name__       ,     rstrip=__magic_name__   ) if isinstance(__magic_name__       ,     __magic_name__   ) else mask_token

													UpperCAmelCase_			:      List[Any]     						=  {} if sp_model_kwargs is None else sp_model_kwargs

													super().__init__(
													    bos_token=__magic_name__       ,     eos_token=__magic_name__       ,     unk_token=__magic_name__       ,     pad_token=__magic_name__       ,     sep_token=__magic_name__       ,     mask_token=__magic_name__       ,     cls_token=__magic_name__       ,     sp_model_kwargs=self.sp_model_kwargs       ,     **__magic_name__       ,     )

													UpperCAmelCase_			:      Optional[Any]     						=  vocab_file

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

							@property
							def     UpperCAmelCase__	(							self							:     Optional[Any]   )					->       Union[str, Any]:







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

							def     UpperCAmelCase__	(							self							:     List[Any]   )					->       int:







													"""simple docstring"""
													UpperCAmelCase_			:      Union[str, Any]     						=  {self.convert_ids_to_tokens(__magic_name__   ): i for i in range(self.vocab_size   )}
													vocab.update(self.added_tokens_encoder   )
													return vocab

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







													"""simple docstring"""
													UpperCAmelCase_			:      List[str]     						=  self.__dict__.copy()
													UpperCAmelCase_			:      Optional[Any]     						=  None
													return state

							def __setstate__(							self							:     int       ,     __magic_name__							:     List[str]   )					->       List[str]:







													"""simple docstring"""
													UpperCAmelCase_			:      int     						=  d

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

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

							def     UpperCAmelCase__	(							self							:     Any       ,     __magic_name__							:     str   )					->       List[str]:







													"""simple docstring"""
													return self.sp_model.encode(__magic_name__       ,     out_type=__magic_name__   )

							def     UpperCAmelCase__	(							self							:     Optional[int]       ,     __magic_name__							:     List[str]   )					->       Optional[int]:







													"""simple docstring"""
													return self.sp_model.piece_to_id(__magic_name__   )

							def     UpperCAmelCase__	(							self							:     List[str]       ,     __magic_name__							:     Optional[int]   )					->       str:







													"""simple docstring"""
													UpperCAmelCase_			:      str     						=  self.sp_model.IdToPiece(__magic_name__   )
													return token

							def     UpperCAmelCase__	(							self							:     Optional[Any]       ,     __magic_name__							:     str   )					->       Any:







													"""simple docstring"""
													UpperCAmelCase_			:      Any     						=  []
													UpperCAmelCase_			:      List[str]     						=  ''''''
													UpperCAmelCase_			:      Optional[int]     						=  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(__magic_name__   ) + token
																									UpperCAmelCase_			:      Tuple     						=  True
																									UpperCAmelCase_			:      List[str]     						=  []
																			else:
																									current_sub_tokens.append(__magic_name__   )
																									UpperCAmelCase_			:      Any     						=  False
													out_string += self.sp_model.decode(__magic_name__   )
													return out_string.strip()

							def     UpperCAmelCase__	(							self							:     List[str]       ,     __magic_name__							:     List[int]       ,     __magic_name__							:     bool = False       ,     __magic_name__							:     bool = None       ,     __magic_name__							:     bool = True       ,     **__magic_name__							:     List[Any]       ,     )					->       str:







													"""simple docstring"""
													UpperCAmelCase_			:      Tuple     						=  kwargs.pop('''use_source_tokenizer'''       ,     __magic_name__   )

													UpperCAmelCase_			:      str     						=  self.convert_ids_to_tokens(__magic_name__       ,     skip_special_tokens=__magic_name__   )

													# To avoid mixing byte-level and unicode for byte-level BPT
													# we need to build string separately for added tokens and byte-level tokens
													# cf. https://github.com/huggingface/transformers/issues/1133
													UpperCAmelCase_			:      int     						=  []
													UpperCAmelCase_			:      Dict     						=  []
													for token in filtered_tokens:
																			if skip_special_tokens and token in self.all_special_ids:
																									continue
																			if token in self.added_tokens_encoder:
																									if current_sub_text:
																															sub_texts.append(self.convert_tokens_to_string(__magic_name__   )   )
																															UpperCAmelCase_			:      List[Any]     						=  []
																									sub_texts.append(__magic_name__   )
																			else:
																									current_sub_text.append(__magic_name__   )
													if current_sub_text:
																			sub_texts.append(self.convert_tokens_to_string(__magic_name__   )   )

													# Mimic the behavior of the Rust tokenizer:
													# No space before [MASK] and [SEP]
													if spaces_between_special_tokens:
																			UpperCAmelCase_			:      List[str]     						=  re.sub(R''' (\[(MASK|SEP)\])'''       ,     R'''\1'''       ,     ''' '''.join(__magic_name__   )   )
													else:
																			UpperCAmelCase_			:      Union[str, Any]     						=  ''''''.join(__magic_name__   )

													UpperCAmelCase_			:      Optional[int]     						=  (
													    clean_up_tokenization_spaces
													    if clean_up_tokenization_spaces is not None
													    else self.clean_up_tokenization_spaces
													)
													if clean_up_tokenization_spaces:
																			UpperCAmelCase_			:      Any     						=  self.clean_up_tokenization(__magic_name__   )
																			return clean_text
													else:
																			return text

							def     UpperCAmelCase__	(							self							:     str       ,     __magic_name__							:     str       ,     __magic_name__							:     Optional[str] = None   )					->       Tuple[str]:







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

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

													return (out_vocab_file,)

							def     UpperCAmelCase__	(							self							:     Tuple       ,     __magic_name__							:     List[int]       ,     __magic_name__							:     Optional[List[int]] = None   )					->       List[int]:







													"""simple docstring"""
													if token_ids_a is None:
																			return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
													UpperCAmelCase_			:      List[Any]     						=  [self.cls_token_id]
													UpperCAmelCase_			:      List[str]     						=  [self.sep_token_id]
													return cls + token_ids_a + sep + token_ids_a + sep

							def     UpperCAmelCase__	(							self							:     List[str]       ,     __magic_name__							:     List[int]       ,     __magic_name__							:     Optional[List[int]] = None       ,     __magic_name__							:     bool = False   )					->       List[int]:







													"""simple docstring"""
													if already_has_special_tokens:
																			return super().get_special_tokens_mask(
																			    token_ids_a=__magic_name__       ,     token_ids_a=__magic_name__       ,     already_has_special_tokens=__magic_name__   )

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



							def     UpperCAmelCase__	(							self							:     Optional[int]       ,     __magic_name__							:     List[int]       ,     __magic_name__							:     Optional[List[int]] = None   )					->       List[int]:







													"""simple docstring"""
													UpperCAmelCase_			:      Optional[int]     						=  [self.sep_token_id]
													UpperCAmelCase_			:      Dict     						=  [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]












'''simple docstring'''







def        lowerCamelCase_      (  SCREAMING_SNAKE_CASE__      :			int   ) ->	str:
						if number > 0:
												raise ValueError('''input must be a negative integer'''   )
						UpperCAmelCase_			:      Union[str, Any]     						=  len(bin(SCREAMING_SNAKE_CASE__   )[3:]   )
						UpperCAmelCase_			:      Union[str, Any]     						=  bin(abs(SCREAMING_SNAKE_CASE__   ) - (1 << binary_number_length)   )[3:]
						UpperCAmelCase_			:      Optional[Any]     						=  (
						    (
						        '''1'''
						        + '''0''' * (binary_number_length - len(SCREAMING_SNAKE_CASE__   ))
						        + twos_complement_number
						    )
						    if number < 0
						    else '''0'''
						)
						return "0b" + twos_complement_number


if __name__ == "__main__":
					import doctest

					doctest.testmod()





