



from typing import TYPE_CHECKING

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


lowercase_	       =			{
    '''configuration_maskformer''': ['''MASKFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''MaskFormerConfig'''],
    '''configuration_maskformer_swin''': ['''MaskFormerSwinConfig'''],
}

try:
				if not is_vision_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				lowercase_	       =			['''MaskFormerFeatureExtractor''']
				lowercase_	       =			['''MaskFormerImageProcessor''']


try:
				if not is_torch_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				lowercase_	       =			[
				    '''MASKFORMER_PRETRAINED_MODEL_ARCHIVE_LIST''',
				    '''MaskFormerForInstanceSegmentation''',
				    '''MaskFormerModel''',
				    '''MaskFormerPreTrainedModel''',
				]
				lowercase_	       =			[
				    '''MaskFormerSwinBackbone''',
				    '''MaskFormerSwinModel''',
				    '''MaskFormerSwinPreTrainedModel''',
				]

if TYPE_CHECKING:
				from .configuration_maskformer import MASKFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, MaskFormerConfig
				from .configuration_maskformer_swin import MaskFormerSwinConfig

				try:
								if not is_vision_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .feature_extraction_maskformer import MaskFormerFeatureExtractor
								from .image_processing_maskformer import MaskFormerImageProcessor
				try:
								if not is_torch_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_maskformer import (
								    MASKFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
								    MaskFormerForInstanceSegmentation,
								    MaskFormerModel,
								    MaskFormerPreTrainedModel,
								)
								from .modeling_maskformer_swin import (
								    MaskFormerSwinBackbone,
								    MaskFormerSwinModel,
								    MaskFormerSwinPreTrainedModel,
								)


else:
				import sys

				lowercase_	       =			_LazyModule(__name__, globals()['''__file__'''], _import_structure)









def 					__lowerCAmelCase		(  __lowerCamelCase	:    int = 3				,   __lowerCamelCase	:    int = 7				,   __lowerCamelCase	:    int = 1000000	)  ->						int:
					__lowerCAmelCase	   =0
					__lowerCAmelCase	   =1

					for current_denominator in range(1				,   limit + 1	):
										__lowerCAmelCase	   =current_denominator * numerator // denominator
										if current_denominator % denominator == 0:
															current_numerator -= 1
										if current_numerator * max_denominator > current_denominator * max_numerator:
															__lowerCAmelCase	   =current_numerator
															__lowerCAmelCase	   =current_denominator
					return max_numerator


if __name__ == "__main__":
				print(solution(numerator=3, denominator=7, limit=1_00_00_00))




