

"""simple docstring"""
import json
from typing import List, Optional, Tuple

from tokenizers import normalizers

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_mobilebert import MobileBertTokenizer


_A							=  logging.get_logger(__name__)

_A							=  {"""vocab_file""": """vocab.txt""", """tokenizer_file""": """tokenizer.json"""}

_A							=  {
    """vocab_file""": {"""mobilebert-uncased""": """https://huggingface.co/google/mobilebert-uncased/resolve/main/vocab.txt"""},
    """tokenizer_file""": {
        """mobilebert-uncased""": """https://huggingface.co/google/mobilebert-uncased/resolve/main/tokenizer.json"""
    },
}

_A							=  {"""mobilebert-uncased""": 5_12}


_A							=  {}

class       lowerCamelCase	(       lowerCAmelCase__   ):


  '''simple docstring'''







  SCREAMING_SNAKE_CASE					      =  VOCAB_FILES_NAMES
  SCREAMING_SNAKE_CASE					      =  PRETRAINED_VOCAB_FILES_MAP
  SCREAMING_SNAKE_CASE					      =  PRETRAINED_INIT_CONFIGURATION
  SCREAMING_SNAKE_CASE					      =  PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
  SCREAMING_SNAKE_CASE					      =  MobileBertTokenizer



  def __init__(self							,       _lowerCamelCase=None							,       _lowerCamelCase=None							,       _lowerCamelCase=True							,       _lowerCamelCase="[UNK]"							,       _lowerCamelCase="[SEP]"							,       _lowerCamelCase="[PAD]"							,       _lowerCamelCase="[CLS]"							,       _lowerCamelCase="[MASK]"							,       _lowerCamelCase=True							,       _lowerCamelCase=None							,       **_lowerCamelCase							,       ):


        """simple docstring"""

        super().__init__(
            _lowerCamelCase							,       tokenizer_file=_lowerCamelCase							,       do_lower_case=_lowerCamelCase							,       unk_token=_lowerCamelCase							,       sep_token=_lowerCamelCase							,       pad_token=_lowerCamelCase							,       cls_token=_lowerCamelCase							,       mask_token=_lowerCamelCase							,       tokenize_chinese_chars=_lowerCamelCase							,       strip_accents=_lowerCamelCase							,       **_lowerCamelCase							,       )

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

        UpperCAmelCase__			:							Tuple							=    do_lower_case



  def  _a      (self							,       _lowerCamelCase							,       _lowerCamelCase=None	):


        """simple docstring"""

        UpperCAmelCase__			:							Tuple							=    [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  _a      (self							,       _lowerCamelCase							,       _lowerCamelCase = None	):


        """simple docstring"""

        UpperCAmelCase__			:							Tuple							=    [self.sep_token_id]
        UpperCAmelCase__			:							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  _a      (self							,       _lowerCamelCase							,       _lowerCamelCase = None	):


        """simple docstring"""

        UpperCAmelCase__			:							Any							=    self._tokenizer.model.save(_lowerCamelCase							,       name=_lowerCamelCase	)
        return tuple(_lowerCamelCase	)




"""simple docstring"""
import math




def 					a__						(						lowerCAmelCase    )	-> list[int]:
      UpperCAmelCase__			:							Optional[int]							=    []
      UpperCAmelCase__			:							Union[str, Any]							=    2
      UpperCAmelCase__			:							List[Any]							=    int(math.sqrt(lowerCAmelCase    )    )  # Size of every segment
      UpperCAmelCase__			:							Dict							=    [True] * (end + 1)
      UpperCAmelCase__			:							str							=    []

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

      UpperCAmelCase__			:							Optional[Any]							=    end + 1
      UpperCAmelCase__			:							Dict							=    min(2 * end			,	lowerCAmelCase    )

      while low <= n:
            UpperCAmelCase__			:							Optional[int]							=    [True] * (high - low + 1)
            for each in in_prime:
                  UpperCAmelCase__			:							Optional[int]							=    math.floor(low / each    ) * each
                  if t < low:
                        t += each

                  for j in range(lowerCAmelCase			,	high + 1			,	lowerCAmelCase    ):
                        UpperCAmelCase__			:							int							=    False

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

            UpperCAmelCase__			:							Dict							=    high + 1
            UpperCAmelCase__			:							int							=    min(high + end			,	lowerCAmelCase    )

      return prime





print(sieve(10**6))

