



"""simple docstring"""
import math





def  lowerCamelCase_						(UpperCamelCase__		:		int							):
    _UpperCAmelCase							:  Optional[int]											=    []
    _UpperCAmelCase							:  int											=    2
    _UpperCAmelCase							:  List[Any]											=    int(math.sqrt(UpperCamelCase__							)							)  # Size of every segment
    _UpperCAmelCase							:  Optional[Any]											=    [True] * (end + 1)
    _UpperCAmelCase							:  Optional[Any]											=    []

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

    _UpperCAmelCase							:  Any											=    end + 1
    _UpperCAmelCase							:  List[Any]											=    min(2 * end     ,       UpperCamelCase__							)

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

            for j in range(UpperCamelCase__     ,       high + 1     ,       UpperCamelCase__							):
                _UpperCAmelCase							:  str											=    False

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

        _UpperCAmelCase							:  str											=    high + 1
        _UpperCAmelCase							:  Optional[int]											=    min(high + end     ,       UpperCamelCase__							)

    return prime


print(sieve(10**6))







"""simple docstring"""
import warnings

from ...utils import logging
from .image_processing_donut import DonutImageProcessor


_lowerCAmelCase    :Optional[int]     =					logging.get_logger(__name__)
class 							_UpperCAmelCase							( a      ):





     '''simple docstring'''



     def __init__(					self       ,	*A       ,	**A		)							->					None:
         warnings.warn(
             '''The class DonutFeatureExtractor is deprecated and will be removed in version 5 of Transformers. Please'''
             ''' use DonutImageProcessor instead.'''       ,	A       ,	)
         super().__init__(*A       ,	**A		)


