import math
from decimal import Decimal, getcontext
def 					UpperCamelCase__		(							A__ = 400_0000       )  ->   int:

				try:
								snake_case__   :      List[str]   				= int(A__       )
				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.'       )
				snake_case__   :      List[Any]   				= 100
				snake_case__   :      int   				= (Decimal(5       ) ** Decimal(0.5       ) + 1) / Decimal(2       )

				snake_case__   :      Any   				= (math.floor(math.log(n * (phi + 2)     ,					A__       ) - 1       ) // 3) * 3 + 2
				snake_case__   :      List[str]   				= Decimal(round(phi ** Decimal(index + 1       )       )       ) / (phi + 2)
				snake_case__   :      Tuple   				= num // 2
				return int(A__       )


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



from typing import TYPE_CHECKING

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


lowerCAmelCase__	:  int						=  {
    '''configuration_deta''': ['''DETA_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''DetaConfig'''],
}

try:
				if not is_vision_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				lowerCAmelCase__	:  Union[str, Any]						=  ['''DetaImageProcessor''']

try:
				if not is_torch_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				lowerCAmelCase__	:  Optional[int]						=  [
				    '''DETA_PRETRAINED_MODEL_ARCHIVE_LIST''',
				    '''DetaForObjectDetection''',
				    '''DetaModel''',
				    '''DetaPreTrainedModel''',
				]


if TYPE_CHECKING:
				from .configuration_deta import DETA_PRETRAINED_CONFIG_ARCHIVE_MAP, DetaConfig

				try:
								if not is_vision_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .image_processing_deta import DetaImageProcessor

				try:
								if not is_torch_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_deta import (
								    DETA_PRETRAINED_MODEL_ARCHIVE_LIST,
								    DetaForObjectDetection,
								    DetaModel,
								    DetaPreTrainedModel,
								)

else:
				import sys

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


