



'''simple docstring'''





from __future__ import annotations




def lowerCAmelCase  (__A):



     """simple docstring"""



     _a      =  [True] * limit
     _a      =  False
     _a      =  False
     _a      =  True

     for i in range(3  ,	int(limit**0.5 + 1)  ,	2):
          _a      =  i * 2
          while index < limit:
               _a      =  False
               _a      =  index + i

     _a      =  [2]

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

     return primes




def lowerCAmelCase  (__A = 1_000_000):



     """simple docstring"""



     _a      =  prime_sieve(_A)
     _a      =  0
     _a      =  0

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

               if sol in primes:
                    _a      =  j - i
                    _a      =  sol

     return largest


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




'''simple docstring'''




from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_tf_available,
    is_torch_available,
)


__lowercase          =  {
    '''configuration_resnet''': ['''RESNET_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''ResNetConfig''', '''ResNetOnnxConfig''']
}

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						__lowercase          =  [
						    '''RESNET_PRETRAINED_MODEL_ARCHIVE_LIST''',
						    '''ResNetForImageClassification''',
						    '''ResNetModel''',
						    '''ResNetPreTrainedModel''',
						    '''ResNetBackbone''',
						]

try:
						if not is_tf_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						__lowercase          =  [
						    '''TF_RESNET_PRETRAINED_MODEL_ARCHIVE_LIST''',
						    '''TFResNetForImageClassification''',
						    '''TFResNetModel''',
						    '''TFResNetPreTrainedModel''',
						]

try:
						if not is_flax_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						__lowercase          =  [
						    '''FlaxResNetForImageClassification''',
						    '''FlaxResNetModel''',
						    '''FlaxResNetPreTrainedModel''',
						]

if TYPE_CHECKING:
						from .configuration_resnet import RESNET_PRETRAINED_CONFIG_ARCHIVE_MAP, ResNetConfig, ResNetOnnxConfig

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_resnet import (
												    RESNET_PRETRAINED_MODEL_ARCHIVE_LIST,
												    ResNetBackbone,
												    ResNetForImageClassification,
												    ResNetModel,
												    ResNetPreTrainedModel,
												)

						try:
												if not is_tf_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_tf_resnet import (
												    TF_RESNET_PRETRAINED_MODEL_ARCHIVE_LIST,
												    TFResNetForImageClassification,
												    TFResNetModel,
												    TFResNetPreTrainedModel,
												)

						try:
												if not is_flax_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_flax_resnet import FlaxResNetForImageClassification, FlaxResNetModel, FlaxResNetPreTrainedModel


else:
						import sys

						__lowercase          =  _LazyModule(__name__, globals()['''__file__'''], _import_structure)




