





from itertools import product


def 			SCREAMING_SNAKE_CASE__     (					_lowercase    :   int = 15 )      ->       int:




		'''simple docstring'''
		lowercase__				:			float            =		0.0
		lowercase__				:			float
		lowercase__				:			int
		lowercase__				:			int
		lowercase__				:			int
		lowercase__				:			int
		lowercase__				:			tuple[int, ...]

		for series in product(range(2 )      ,						repeat=_lowercase ):
				lowercase__				:			List[Any]            =		series.count(1 )
				lowercase__				:			List[str]            =		num_turns - num_blue
				if num_red >= num_blue:
						continue
				lowercase__				:			Tuple            =		1.0
				for ind, col in enumerate(_lowercase      ,						2 ):
						if col == 0:
								prob *= (ind - 1) / ind
						else:
								prob *= 1 / ind

				total_prob += prob

		return int(1 / total_prob )


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









from typing import TYPE_CHECKING

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


__UpperCamelCase:  Any   =   {
    """configuration_deta""": ["""DETA_PRETRAINED_CONFIG_ARCHIVE_MAP""", """DetaConfig"""],
}

try:
			if not is_vision_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			__UpperCamelCase:  Tuple   =   ["""DetaImageProcessor"""]

try:
			if not is_torch_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			__UpperCamelCase:  List[str]   =   [
			    """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

			__UpperCamelCase:  int   =   _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)


