



'''simple docstring'''

from typing import TYPE_CHECKING

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


__lowerCAmelCase									=   {'''configuration_beit''': ['''BEIT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''BeitConfig''', '''BeitOnnxConfig''']}

try:
							if not is_vision_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							__lowerCAmelCase									=   ['''BeitFeatureExtractor''']
							__lowerCAmelCase									=   ['''BeitImageProcessor''']

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							__lowerCAmelCase									=   [
							    '''BEIT_PRETRAINED_MODEL_ARCHIVE_LIST''',
							    '''BeitForImageClassification''',
							    '''BeitForMaskedImageModeling''',
							    '''BeitForSemanticSegmentation''',
							    '''BeitModel''',
							    '''BeitPreTrainedModel''',
							]


try:
							if not is_flax_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							__lowerCAmelCase									=   [
							    '''FlaxBeitForImageClassification''',
							    '''FlaxBeitForMaskedImageModeling''',
							    '''FlaxBeitModel''',
							    '''FlaxBeitPreTrainedModel''',
							]

if TYPE_CHECKING:
							from .configuration_beit import BEIT_PRETRAINED_CONFIG_ARCHIVE_MAP, BeitConfig, BeitOnnxConfig

							try:
														if not is_vision_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .feature_extraction_beit import BeitFeatureExtractor
														from .image_processing_beit import BeitImageProcessor

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_beit import (
														    BEIT_PRETRAINED_MODEL_ARCHIVE_LIST,
														    BeitForImageClassification,
														    BeitForMaskedImageModeling,
														    BeitForSemanticSegmentation,
														    BeitModel,
														    BeitPreTrainedModel,
														)

							try:
														if not is_flax_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_flax_beit import (
														    FlaxBeitForImageClassification,
														    FlaxBeitForMaskedImageModeling,
														    FlaxBeitModel,
														    FlaxBeitPreTrainedModel,
														)


else:
							import sys

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









'''simple docstring'''

def      __lowerCamelCase     (      )			->      Tuple:
		for n in range(1						,			1000000  ):
				yield n * (n + 1) // 2



def      __lowerCamelCase     (      lowerCAmelCase_  )			->      List[Any]:
		_a     :      Any        =							1
		_a     :      Tuple        =							2
		while i * i <= n:
				_a     :      Tuple        =							0
				while n % i == 0:
						n //= i
						multiplicity += 1
				divisors_count *= multiplicity + 1
				i += 1
		if n > 1:
				divisors_count *= 2
		return divisors_count



def      __lowerCamelCase     (      )			->      str:
		return next(i for i in triangle_number_generator() if count_divisors(lowerCAmelCase_  ) > 500  )


if __name__ == "__main__":
							print(solution())




