





from typing import TYPE_CHECKING

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


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

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


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

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








import random

from .binary_exp_mod import bin_exp_mod






def 					lowerCamelCase_   (	_a     ,       _a=1_000	):




		"""simple docstring"""






		if n < 2:
				return False

		if n % 2 == 0:
				return n == 2

		# this means n is odd
		lowerCAmelCase__       :      int   					= n - 1
		lowerCAmelCase__       :      Any   					= 0
		while d % 2 == 0:
				d /= 2
				exp += 1

		# n - 1=d*(2**exp)
		lowerCAmelCase__       :      Optional[Any]   					= 0
		while count < prec:
				lowerCAmelCase__       :      Optional[Any]   					= random.randint(2     ,       n - 1	)
				lowerCAmelCase__       :      List[Any]   					= bin_exp_mod(_a     ,       _a     ,       _a	)
				if b != 1:
						lowerCAmelCase__       :      Dict   					= True
						for _ in range(_a	):
								if b == n - 1:
										lowerCAmelCase__       :      Union[str, Any]   					= False
										break
								lowerCAmelCase__       :      Tuple   					= b * b
								b %= n
						if flag:
								return False
						count += 1
		return True


if __name__ == "__main__":
		lowerCamelCase						=		abs(int(input('''Enter bound : ''').strip()))
		print('''Here\'s the list of primes:''')
		print(''', '''.join(str(i) for i in range(n + 1) if is_prime_big(i)))




