




import math




def     __magic_name__       (				A	:      int     ):






			'''simple docstring'''







			if 1 < number < 4:
						# 2 and 3 are primes
						return True
			elif number < 2 or number % 2 == 0 or number % 3 == 0:
						# Negatives, 0, 1, all even numbers, all multiples of 3 are not primes
						return False

			# All primes number are in format of 6k +/- 1
			for i in range(5,						int(math.sqrt(_lowerCAmelCase     ) + 1     ),						6     ):
						if number % i == 0 or number % (i + 2) == 0:
									return False
			return True




def     __magic_name__       (				A	:      float = 0.1     ):






			'''simple docstring'''







			a					=    3
			a					=    3

			while primes / (2 * j - 1) >= ratio:
						for i in range(j * j + j + 1,						(j + 2) * (j + 2),						j + 1     ):
									primes += is_prime(_lowerCAmelCase     )
						j += 2
			return j


if __name__ == "__main__":
		import doctest

		doctest.testmod()












import os
from shutil import copyfile
from typing import List, Optional, Tuple

from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging


if is_sentencepiece_available():
		from .tokenization_big_bird import BigBirdTokenizer
else:
		__lowerCAmelCase	:       Optional[int]     =	None

__lowerCAmelCase	:       Optional[Any]     =	logging.get_logger(__name__)
__lowerCAmelCase	:       Optional[int]     =	{'vocab_file': 'spiece.model', 'tokenizer_file': 'tokenizer.json'}

__lowerCAmelCase	:       List[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'
        ),
    },
    'tokenizer_file': {
        'google/bigbird-roberta-base': (
            'https://huggingface.co/google/bigbird-roberta-base/resolve/main/tokenizer.json'
        ),
        'google/bigbird-roberta-large': (
            'https://huggingface.co/google/bigbird-roberta-large/resolve/main/tokenizer.json'
        ),
        'google/bigbird-base-trivia-itc': (
            'https://huggingface.co/google/bigbird-base-trivia-itc/resolve/main/tokenizer.json'
        ),
    },
}

__lowerCAmelCase	:       List[str]     =	{
    'google/bigbird-roberta-base': 4096,
    'google/bigbird-roberta-large': 4096,
    'google/bigbird-base-trivia-itc': 4096,
}


__lowerCAmelCase	:       Any     =	'▁'




class 					snake_case__							(_UpperCamelCase     ):
				"""simple docstring"""



				SCREAMING_SNAKE_CASE_ :							Any											=      VOCAB_FILES_NAMES
				SCREAMING_SNAKE_CASE_ :							List[Any]											=      PRETRAINED_VOCAB_FILES_MAP
				SCREAMING_SNAKE_CASE_ :							Dict											=      PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
				SCREAMING_SNAKE_CASE_ :							str											=      BigBirdTokenizer
				SCREAMING_SNAKE_CASE_ :							str											=      ["""input_ids""", """attention_mask"""]
				SCREAMING_SNAKE_CASE_ :							List[int]											=      []





				def __init__(   self       :  int      ,   __lowerCamelCase       :  Any=None      ,   __lowerCamelCase       :  List[str]=None      ,   __lowerCamelCase       :  Optional[int]="<unk>"      ,   __lowerCamelCase       :  int="<s>"      ,   __lowerCamelCase       :  Optional[Any]="</s>"      ,   __lowerCamelCase       :  Tuple="<pad>"      ,   __lowerCamelCase       :  Tuple="[SEP]"      ,   __lowerCamelCase       :  Dict="[MASK]"      ,   __lowerCamelCase       :  Tuple="[CLS]"      ,   **__lowerCamelCase       :  Optional[Any]      ,   )      ->  List[Any]:
							a					=    AddedToken(__lowerCamelCase      ,   lstrip=__lowerCamelCase      ,   rstrip=__lowerCamelCase							) if isinstance(__lowerCamelCase      ,   __lowerCamelCase							) else bos_token
							a					=    AddedToken(__lowerCamelCase      ,   lstrip=__lowerCamelCase      ,   rstrip=__lowerCamelCase							) if isinstance(__lowerCamelCase      ,   __lowerCamelCase							) else eos_token
							a					=    AddedToken(__lowerCamelCase      ,   lstrip=__lowerCamelCase      ,   rstrip=__lowerCamelCase							) if isinstance(__lowerCamelCase      ,   __lowerCamelCase							) else unk_token
							a					=    AddedToken(__lowerCamelCase      ,   lstrip=__lowerCamelCase      ,   rstrip=__lowerCamelCase							) if isinstance(__lowerCamelCase      ,   __lowerCamelCase							) else pad_token
							a					=    AddedToken(__lowerCamelCase      ,   lstrip=__lowerCamelCase      ,   rstrip=__lowerCamelCase							) if isinstance(__lowerCamelCase      ,   __lowerCamelCase							) else cls_token
							a					=    AddedToken(__lowerCamelCase      ,   lstrip=__lowerCamelCase      ,   rstrip=__lowerCamelCase							) if isinstance(__lowerCamelCase      ,   __lowerCamelCase							) else sep_token

							# Mask token behave like a normal word, i.e. include the space before it
							a					=    AddedToken(__lowerCamelCase      ,   lstrip=__lowerCamelCase      ,   rstrip=__lowerCamelCase							) if isinstance(__lowerCamelCase      ,   __lowerCamelCase							) else mask_token

							super().__init__(
							    __lowerCamelCase      ,   tokenizer_file=__lowerCamelCase      ,   bos_token=__lowerCamelCase      ,   eos_token=__lowerCamelCase      ,   unk_token=__lowerCamelCase      ,   sep_token=__lowerCamelCase      ,   pad_token=__lowerCamelCase      ,   cls_token=__lowerCamelCase      ,   mask_token=__lowerCamelCase      ,   **__lowerCamelCase      ,   )

							a					=    vocab_file
							a					=    False if not self.vocab_file else True





				def 							__UpperCAmelCase							(   self       :  str      ,   __lowerCamelCase       :  List[int]      ,   __lowerCamelCase       :  Optional[List[int]] = None							)      ->  List[int]:
							a					=    [self.sep_token_id]
							a					=    [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 							__UpperCAmelCase							(   self       :  List[str]      ,   __lowerCamelCase       :  List[int]      ,   __lowerCamelCase       :  Optional[List[int]] = None      ,   __lowerCamelCase       :  bool = False							)      ->  List[int]:

							if already_has_special_tokens:
										if token_ids_a is not None:
													raise ValueError(
													    "You should not supply a second sequence if the provided sequence of "
													    "ids is already formatted with special tokens for the model."							)
										return [1 if x in [self.sep_token_id, self.cls_token_id] else 0 for x in token_ids_a]

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





				def 							__UpperCAmelCase							(   self       :  Optional[int]      ,   __lowerCamelCase       :  List[int]      ,   __lowerCamelCase       :  Optional[List[int]] = None							)      ->  List[int]:
							a					=    [self.sep_token_id]
							a					=    [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 							__UpperCAmelCase							(   self       :  Tuple      ,   __lowerCamelCase       :  str      ,   __lowerCamelCase       :  Optional[str] = None							)      ->  Tuple[str]:
							if not self.can_save_slow_tokenizer:
										raise ValueError(
										    "Your fast tokenizer does not have the necessary information to save the vocabulary for a slow "
										    "tokenizer."							)

							if not os.path.isdir(__lowerCamelCase							):
										logger.error(f"""Vocabulary path ({save_directory}) should be a directory"""							)
										return
							a					=    os.path.join(
							    __lowerCamelCase      ,   (filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]							)

							if os.path.abspath(self.vocab_file							) != os.path.abspath(__lowerCamelCase							):
										copyfile(self.vocab_file      ,   __lowerCamelCase							)

							return (out_vocab_file,)






