




'''simple docstring'''

def 		__magic_name__    (	__UpperCAmelCase = 200_0000	)		->					Any:

					'''simple docstring'''

					snake_case_									=				[0 for i in range(n + 1	)]
					snake_case_									=				1
					snake_case_									=				1

					for i in range(2,      int(n**0.5	) + 1	):
										if primality_list[i] == 0:
															for j in range(i * i,      n + 1,      _A	):
																				snake_case_									=				1
					snake_case_									=				0
					for i in range(_A	):
										if primality_list[i] == 0:
															sum_of_primes += i
					return sum_of_primes


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




from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available


lowerCamelCase           =					{
    '''configuration_canine''': ['''CANINE_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''CanineConfig'''],
    '''tokenization_canine''': ['''CanineTokenizer'''],
}

try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       lowerCamelCase           =					[
           '''CANINE_PRETRAINED_MODEL_ARCHIVE_LIST''',
           '''CanineForMultipleChoice''',
           '''CanineForQuestionAnswering''',
           '''CanineForSequenceClassification''',
           '''CanineForTokenClassification''',
           '''CanineLayer''',
           '''CanineModel''',
           '''CaninePreTrainedModel''',
           '''load_tf_weights_in_canine''',
       ]


if TYPE_CHECKING:
       from .configuration_canine import CANINE_PRETRAINED_CONFIG_ARCHIVE_MAP, CanineConfig
       from .tokenization_canine import CanineTokenizer

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_canine import (
                  CANINE_PRETRAINED_MODEL_ARCHIVE_LIST,
                  CanineForMultipleChoice,
                  CanineForQuestionAnswering,
                  CanineForSequenceClassification,
                  CanineForTokenClassification,
                  CanineLayer,
                  CanineModel,
                  CaninePreTrainedModel,
                  load_tf_weights_in_canine,
              )


else:
       import sys

       lowerCamelCase           =					_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)
