

def      a__	(						UpperCAmelCase				:     Dict = 20     )    ->		int:

  try:
    UpperCAmelCase			:				Dict										=					int(_UpperCAmelCase     )
  except (TypeError, ValueError):
    raise TypeError('''Parameter n must be int or castable to int.'''     )
  if n <= 0:
    raise ValueError('''Parameter n must be greater than or equal to one.'''     )
  UpperCAmelCase			:				Any										=					0
  while 1:
    i += n * (n - 1)
    UpperCAmelCase			:				Optional[int]										=					0
    for j in range(2							,					_UpperCAmelCase     ):
      if i % j != 0:
        UpperCAmelCase			:				str										=					1
        break
    if nfound == 0:
      if i == 0:
        UpperCAmelCase			:				List[Any]										=					1
      return i
  return None


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












from typing import TYPE_CHECKING

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


UpperCAmelCase__    :      Optional[Any]       					={
    '''configuration_donut_swin''': ['''DONUT_SWIN_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''DonutSwinConfig'''],
    '''processing_donut''': ['''DonutProcessor'''],
}

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							UpperCAmelCase__    :      Any       					=[
							    '''DONUT_SWIN_PRETRAINED_MODEL_ARCHIVE_LIST''',
							    '''DonutSwinModel''',
							    '''DonutSwinPreTrainedModel''',
							]

try:
							if not is_vision_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							UpperCAmelCase__    :      Tuple       					=['''DonutFeatureExtractor''']
							UpperCAmelCase__    :      List[str]       					=['''DonutImageProcessor''']


if TYPE_CHECKING:
							from .configuration_donut_swin import DONUT_SWIN_PRETRAINED_CONFIG_ARCHIVE_MAP, DonutSwinConfig
							from .processing_donut import DonutProcessor

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_donut_swin import (
														    DONUT_SWIN_PRETRAINED_MODEL_ARCHIVE_LIST,
														    DonutSwinModel,
														    DonutSwinPreTrainedModel,
														)

							try:
														if not is_vision_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .feature_extraction_donut import DonutFeatureExtractor
														from .image_processing_donut import DonutImageProcessor

else:
							import sys

							UpperCAmelCase__    :      int       					=_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)





