

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      :    Dict   		=   None

__lowerCamelCase      :    Tuple   		=   logging.get_logger(__name__)
__lowerCamelCase      :    Dict   		=   {"""vocab_file""": """spiece.model""", """tokenizer_file""": """tokenizer.json"""}

__lowerCamelCase      :    Optional[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      :    int   		=   {
    """google/bigbird-roberta-base""": 4096,
    """google/bigbird-roberta-large""": 4096,
    """google/bigbird-base-trivia-itc""": 4096,
}


__lowerCamelCase      :    List[str]   		=   """▁"""



class 							SCREAMING_SNAKE_CASE__		(       UpperCamelCase_		):





					"""simple docstring"""






					a_			=	VOCAB_FILES_NAMES
					a_			=	PRETRAINED_VOCAB_FILES_MAP
					a_			=	PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
					a_			=	BigBirdTokenizer
					a_			=	["input_ids", "attention_mask"]
					a_			=	[]



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

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

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

						snake_case__				:   List[Any]     =						vocab_file
						snake_case__				:   Tuple     =						False if not self.vocab_file else True



					def  _lowercase  (      self  :						Any							,	__A  :						List[int]							,	__A  :						Optional[List[int]] = None ):
						snake_case__				:   str     =						[self.sep_token_id]
						snake_case__				:   List[str]     =						[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  _lowercase  (      self  :						int							,	__A  :						List[int]							,	__A  :						Optional[List[int]] = None							,	__A  :						bool = False ):

						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(__A )) + [1]
						return [1] + ([0] * len(__A )) + [1] + ([0] * len(__A )) + [1]



					def  _lowercase  (      self  :						Any							,	__A  :						List[int]							,	__A  :						Optional[List[int]] = None ):
						snake_case__				:   Union[str, Any]     =						[self.sep_token_id]
						snake_case__				:   List[str]     =						[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  _lowercase  (      self  :						List[Any]							,	__A  :						str							,	__A  :						Optional[str] = None ):
						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(__A ):
							logger.error(f'''Vocabulary path ({save_directory}) should be a directory''' )
							return
						snake_case__				:   Any     =						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 ):
							copyfile(self.vocab_file							,	__A )

						return (out_vocab_file,)











from __future__ import annotations







def   SCREAMING_SNAKE_CASE       (				snake_case_      :							int     ):
	snake_case__				:   str     =						[True] * limit
	snake_case__				:   str     =						False
	snake_case__				:   str     =						False
	snake_case__				:   str     =						True

	for i in range(3  ,						int(limit**0.5 + 1     )  ,						2     ):
		snake_case__				:   Optional[Any]     =						i * 2
		while index < limit:
			snake_case__				:   Union[str, Any]     =						False
			snake_case__				:   Any     =						index + i

	snake_case__				:   Optional[Any]     =						[2]

	for i in range(3  ,						snake_case_  ,						2     ):
		if is_prime[i]:
			primes.append(snake_case_     )

	return primes







def   SCREAMING_SNAKE_CASE       (				snake_case_      :							int = 1000000     ):
	snake_case__				:   Optional[int]     =						prime_sieve(snake_case_     )
	snake_case__				:   List[Any]     =						0
	snake_case__				:   List[str]     =						0

	for i in range(len(snake_case_     )     ):
		for j in range(i + length  ,						len(snake_case_     )     ):
			snake_case__				:   Dict     =						sum(primes[i:j]     )
			if sol >= ceiling:
				break

			if sol in primes:
				snake_case__				:   Tuple     =						j - i
				snake_case__				:   str     =						sol

	return largest


if __name__ == "__main__":
	print(f"{solution() = }")



