

def        SCREAMING_SNAKE_CASE__	(  lowerCamelCase__ = 1_0     ,			lowerCamelCase__ = 1_0_0_0     ,			lowerCamelCase__ = True      )  ->					int:
	assert (
	    isinstance(lowerCamelCase__     ,			lowerCamelCase__      )
	    and isinstance(lowerCamelCase__     ,			lowerCamelCase__      )
	    and isinstance(lowerCamelCase__     ,			lowerCamelCase__      )
	), "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        SCREAMING_SNAKE_CASE__	(  lowerCamelCase__     ,			lowerCamelCase__      )  ->					int:
	return int((number_a + number_a) / 2      )






def        SCREAMING_SNAKE_CASE__	(  lowerCamelCase__     ,			lowerCamelCase__     ,			lowerCamelCase__      )  ->					None:
	assert (
	    isinstance(lowerCamelCase__     ,			lowerCamelCase__      ) and isinstance(lowerCamelCase__     ,			lowerCamelCase__      ) and isinstance(lowerCamelCase__     ,			lowerCamelCase__      )
	), '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(lowerCamelCase__      ) -> str:
		if number > to_guess:
			return "high"
		elif number < to_guess:
			return "low"
		else:
			return "same"

	print('started...'      )

	__lowerCamelCase    :    Optional[int] 	=			lower
	__lowerCamelCase    :    Optional[int] 	=			higher

	__lowerCamelCase    :    str 	=			[]

	while True:
		__lowerCamelCase    :    Any 	=			get_avg(lowerCamelCase__     ,			lowerCamelCase__      )
		last_numbers.append(lowerCamelCase__      )

		if answer(lowerCamelCase__      ) == "low":
			__lowerCamelCase    :    int 	=			number
		elif answer(lowerCamelCase__      ) == "high":
			__lowerCamelCase    :    Any 	=			number
		else:
			break

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






def        SCREAMING_SNAKE_CASE__	(  )  ->					None:
	__lowerCamelCase    :    Any 	=			int(input('Enter lower value : '      ).strip()      )
	__lowerCamelCase    :    Optional[int] 	=			int(input('Enter high value : '      ).strip()      )
	__lowerCamelCase    :    Tuple 	=			int(input('Enter value to guess : '      ).strip()      )
	guess_the_number(lowerCamelCase__     ,			lowerCamelCase__     ,			lowerCamelCase__      )


if __name__ == "__main__":
					main()







from typing import TYPE_CHECKING

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


a		={
    """configuration_mask2former""": [
        """MASK2FORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """Mask2FormerConfig""",
    ],
}

try:
					if not is_vision_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					a		=["""Mask2FormerImageProcessor"""]

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					a		=[
					    """MASK2FORMER_PRETRAINED_MODEL_ARCHIVE_LIST""",
					    """Mask2FormerForUniversalSegmentation""",
					    """Mask2FormerModel""",
					    """Mask2FormerPreTrainedModel""",
					]

if TYPE_CHECKING:
					from .configuration_maskaformer import MASK2FORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, MaskaFormerConfig

					try:
										if not is_vision_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .image_processing_maskaformer import MaskaFormerImageProcessor

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_maskaformer import (
										    MASK2FORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
										    MaskaFormerForUniversalSegmentation,
										    MaskaFormerModel,
										    MaskaFormerPreTrainedModel,
										)


else:
					import sys

					a		=_LazyModule(__name__, globals()["""__file__"""], _import_structure)




