




import json
from typing import List, Optional, Tuple

from tokenizers import normalizers

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_squeezebert import SqueezeBertTokenizer


SCREAMING_SNAKE_CASE__       :      Optional[Any]  =   logging.get_logger(__name__)

SCREAMING_SNAKE_CASE__       :      Any  =   {'''vocab_file''': '''vocab.txt''', '''tokenizer_file''': '''tokenizer.json'''}

SCREAMING_SNAKE_CASE__       :      str  =   {
    '''vocab_file''': {
        '''squeezebert/squeezebert-uncased''': (
            '''https://huggingface.co/squeezebert/squeezebert-uncased/resolve/main/vocab.txt'''
        ),
        '''squeezebert/squeezebert-mnli''': '''https://huggingface.co/squeezebert/squeezebert-mnli/resolve/main/vocab.txt''',
        '''squeezebert/squeezebert-mnli-headless''': (
            '''https://huggingface.co/squeezebert/squeezebert-mnli-headless/resolve/main/vocab.txt'''
        ),
    },
    '''tokenizer_file''': {
        '''squeezebert/squeezebert-uncased''': (
            '''https://huggingface.co/squeezebert/squeezebert-uncased/resolve/main/tokenizer.json'''
        ),
        '''squeezebert/squeezebert-mnli''': (
            '''https://huggingface.co/squeezebert/squeezebert-mnli/resolve/main/tokenizer.json'''
        ),
        '''squeezebert/squeezebert-mnli-headless''': (
            '''https://huggingface.co/squeezebert/squeezebert-mnli-headless/resolve/main/tokenizer.json'''
        ),
    },
}

SCREAMING_SNAKE_CASE__       :      Tuple  =   {
    '''squeezebert/squeezebert-uncased''': 512,
    '''squeezebert/squeezebert-mnli''': 512,
    '''squeezebert/squeezebert-mnli-headless''': 512,
}


SCREAMING_SNAKE_CASE__       :      Optional[Any]  =   {
    '''squeezebert/squeezebert-uncased''': {'''do_lower_case''': True},
    '''squeezebert/squeezebert-mnli''': {'''do_lower_case''': True},
    '''squeezebert/squeezebert-mnli-headless''': {'''do_lower_case''': True},
}




class 		UpperCamelCase__	(snake_case__     ):

    '''simple docstring'''



    lowerCamelCase_      :	str	     =      VOCAB_FILES_NAMES
    lowerCamelCase_      :	List[Any]	     =      PRETRAINED_VOCAB_FILES_MAP
    lowerCamelCase_      :	List[str]	     =      PRETRAINED_INIT_CONFIGURATION
    lowerCamelCase_      :	Union[str, Any]	     =      PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
    lowerCamelCase_      :	Optional[int]	     =      SqueezeBertTokenizer







    def __init__(    self     ,  UpperCamelCase__=None     ,  UpperCamelCase__=None     ,  UpperCamelCase__=True     ,  UpperCamelCase__="[UNK]"     ,  UpperCamelCase__="[SEP]"     ,  UpperCamelCase__="[PAD]"     ,  UpperCamelCase__="[CLS]"     ,  UpperCamelCase__="[MASK]"     ,  UpperCamelCase__=True     ,  UpperCamelCase__=None     ,  **UpperCamelCase__     ,  )     ->      int:
           super().__init__(
               _A     ,  tokenizer_file=_A     ,  do_lower_case=_A     ,  unk_token=_A     ,  sep_token=_A     ,  pad_token=_A     ,  cls_token=_A     ,  mask_token=_A     ,  tokenize_chinese_chars=_A     ,  strip_accents=_A     ,  **_A     ,  )

           lowerCamelCase   :      Dict			 =					json.loads(self.backend_tokenizer.normalizer.__getstate__()     )
           if (
               normalizer_state.get("lowercase"     ,  _A     ) != do_lower_case
               or normalizer_state.get("strip_accents"     ,  _A     ) != strip_accents
               or normalizer_state.get("handle_chinese_chars"     ,  _A     ) != tokenize_chinese_chars
           ):
                  lowerCamelCase   :      Any			 =					getattr(_A     ,  normalizer_state.pop("type"     )     )
                  lowerCamelCase   :      Union[str, Any]			 =					do_lower_case
                  lowerCamelCase   :      List[str]			 =					strip_accents
                  lowerCamelCase   :      Optional[int]			 =					tokenize_chinese_chars
                  lowerCamelCase   :      Union[str, Any]			 =					normalizer_class(**_A     )

           lowerCamelCase   :      Dict			 =					do_lower_case







    def     _lowercase     (    self     ,  UpperCamelCase__     ,  UpperCamelCase__=None     )     ->      Optional[Any]:
           lowerCamelCase   :      int			 =					[self.cls_token_id] + token_ids_a + [self.sep_token_id]

           if token_ids_a:
                  output += token_ids_a + [self.sep_token_id]

           return output







    def     _lowercase     (    self     ,  UpperCamelCase__     ,  UpperCamelCase__ = None     )     ->      List[Any]:
           lowerCamelCase   :      Optional[int]			 =					[self.sep_token_id]
           lowerCamelCase   :      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]







    def     _lowercase     (    self     ,  UpperCamelCase__     ,  UpperCamelCase__ = None     )     ->      Any:
           lowerCamelCase   :      List[str]			 =					self._tokenizer.model.save(_A     ,  name=_A     )
           return tuple(_A     )













import math







def  _SCREAMING_SNAKE_CASE				(   a  )      ->      list[int]:
					__A	:						List[str]       =				[]
					__A	:						Any       =				2
					__A	:						Union[str, Any]       =				int(math.sqrt(a  )  )  # Size of every segment
					__A	:						Any       =				[True] * (end + 1)
					__A	:						List[Any]       =				[]

					while start <= end:
										if temp[start] is True:
															in_prime.append(a  )
															for i in range(start * start					,						end + 1					,						a  ):
																				__A	:						Optional[int]       =				False
										start += 1
					prime += in_prime

					__A	:						Any       =				end + 1
					__A	:						Any       =				min(2 * end					,						a  )

					while low <= n:
										__A	:						List[Any]       =				[True] * (high - low + 1)
										for each in in_prime:
															__A	:						List[str]       =				math.floor(low / each  ) * each
															if t < low:
																				t += each

															for j in range(a					,						high + 1					,						a  ):
																				__A	:						Optional[int]       =				False

										for j in range(len(a  )  ):
															if temp[j] is True:
																				prime.append(j + low  )

										__A	:						Optional[int]       =				high + 1
										__A	:						Tuple       =				min(high + end					,						a  )

					return prime




print(sieve(10**6))




