




'''simple docstring'''


def 	snake_case_					(UpperCamelCase :						int = 10				,		UpperCamelCase :						int = 1000				,		UpperCamelCase :						bool = True   ):





							'''simple docstring'''


							assert (
							    isinstance(UpperCamelCase				,		UpperCamelCase   )
							    and isinstance(UpperCamelCase				,		UpperCamelCase   )
							    and isinstance(UpperCamelCase				,		UpperCamelCase   )
							), "Invalid type of value(s) specified to function!"

							if min_val > max_val:
														raise ValueError('''Invalid value for min_val or max_val (min_value < max_value)'''   )
							return min_val if option else max_val





def 	snake_case_					(UpperCamelCase :						int				,		UpperCamelCase :						int   ):





							'''simple docstring'''


							return int((number_a + number_a) / 2   )





def 	snake_case_					(UpperCamelCase :						int				,		UpperCamelCase :						int				,		UpperCamelCase :						int   ):





							'''simple docstring'''


							assert (
							    isinstance(UpperCamelCase				,		UpperCamelCase   ) and isinstance(UpperCamelCase				,		UpperCamelCase   ) and isinstance(UpperCamelCase				,		UpperCamelCase   )
							), 'argument values must be type of "int"'

							if lower > higher:
														raise ValueError('''argument value for lower and higher must be(lower > higher)'''   )

							if not lower < to_guess < higher:
														raise ValueError(
														    '''guess value must be within the range of lower and higher value'''   )

							def answer(UpperCamelCase :						int   ) -> str:
														if number > to_guess:
																					return "high"
														elif number < to_guess:
																					return "low"
														else:
																					return "same"

							print('''started...'''   )

							_a			  =       lower
							_a			  =       higher

							_a			  =       []

							while True:
														_a			  =       get_avg(UpperCamelCase				,		UpperCamelCase   )
														last_numbers.append(UpperCamelCase   )

														if answer(UpperCamelCase   ) == "low":
																					_a			  =       number
														elif answer(UpperCamelCase   ) == "high":
																					_a			  =       number
														else:
																					break

							print(f'guess the number : {last_numbers[-1]}'   )
							print(f'details : {last_numbers!s}'   )





def 	snake_case_					():





							'''simple docstring'''


							_a			  =       int(input('''Enter lower value : '''   ).strip()   )
							_a			  =       int(input('''Enter high value : '''   ).strip()   )
							_a			  =       int(input('''Enter value to guess : '''   ).strip()   )
							guess_the_number(UpperCamelCase				,		UpperCamelCase				,		UpperCamelCase   )


if __name__ == "__main__":
				main()







'''simple docstring'''


from typing import TYPE_CHECKING

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


_snake_case   :   List[Any]     							=	{'configuration_beit': ['BEIT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'BeitConfig', 'BeitOnnxConfig']}

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

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


try:
				if not is_flax_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				_snake_case   :   List[str]     							=	[
				    '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

				_snake_case   :   Union[str, Any]     							=	_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)

