code: 
  
  
  
  
  
  '''simple docstring'''
  
  
  
  
  import math
  
  
  
  
  def 	__lowerCamelCase (  UpperCAmelCase_       )      ->bool:
  
  	if 1 < number < 4:
  		# 2 and 3 are primes
  		return True
  	elif number < 2 or number % 2 == 0 or number % 3 == 0:
  		# Negatives, 0, 1, all even numbers, all multiples of 3 are not primes
  		return False
  
  	# All primes number are in format of 6k +/- 1
  	for i in range(5				,							int(math.sqrt(UpperCAmelCase_       ) + 1       )				,							6       ):
  		if number % i == 0 or number % (i + 2) == 0:
  			return False
  	return True
  
  
  
  
  def 	__lowerCamelCase (  UpperCAmelCase_ = 60_08_51_47_51_43       )      ->int:
  
  	try:
  		snake_case__  					=      int(UpperCAmelCase_       )
  	except (TypeError, ValueError):
  		raise TypeError('Parameter n must be int or castable to int.'       )
  	if n <= 0:
  		raise ValueError('Parameter n must be greater than or equal to one.'       )
  	snake_case__  					=      0
  	if is_prime(UpperCAmelCase_       ):
  		return n
  	while n % 2 == 0:
  		n //= 2
  	if is_prime(UpperCAmelCase_       ):
  		return n
  	for i in range(3				,							int(math.sqrt(UpperCAmelCase_       )       ) + 1				,							2       ):
  		if n % i == 0:
  			if is_prime(n // i       ):
  				snake_case__  					=      n // i
  				break
  			elif is_prime(UpperCAmelCase_       ):
  				snake_case__  					=      i
  	return max_number
  
  
  if __name__ == "__main__":
  			print(f"""{solution() = }""")
  
  
  
  
style_context: 
  
  
  
  
  
  '''simple docstring'''
  
  
  
  
  from collections import OrderedDict
  from typing import Mapping
  
  from packaging import version
  
  from ...configuration_utils import PretrainedConfig
  from ...onnx import OnnxConfig
  from ...utils import logging
  
  
  a__				: Dict									=    logging.get_logger(__name__)
  
  a__				: Tuple									=    {
      '''apple/mobilevitv2-1.0''': '''https://huggingface.co/apple/mobilevitv2-1.0/resolve/main/config.json''',
  }
  
  
  
  
  
  
  class 							__snake_case    (				__magic_name__       ):
  	__lowerCAmelCase						=     '''mobilevitv2'''
  
  
  
  
  
  	def __init__(		self			,					UpperCamelCase_=3			,					UpperCamelCase_=256			,					UpperCamelCase_=2			,					UpperCamelCase_=2.0			,					UpperCamelCase_="swish"			,					UpperCamelCase_=3			,					UpperCamelCase_=32			,					UpperCamelCase_=0.1			,					UpperCamelCase_=0.0_2			,					UpperCamelCase_=1E-5			,					UpperCamelCase_=512			,					UpperCamelCase_=[6, 12, 18]			,					UpperCamelCase_=0.1			,					UpperCamelCase_=255			,					UpperCamelCase_=[2, 4, 3]			,					UpperCamelCase_=[128, 192, 256]			,					UpperCamelCase_=1.0			,					UpperCamelCase_=2			,					UpperCamelCase_=0.0			,					UpperCamelCase_=0.0			,					**UpperCamelCase_			,					)			->		Union[str, Any]:
  		super().__init__(**UpperCamelCase_		)
  
  		snake_case__  					=      num_channels
  		snake_case__  					=      image_size
  		snake_case__  					=      patch_size
  		snake_case__  					=      expand_ratio
  		snake_case__  					=      hidden_act
  		snake_case__  					=      conv_kernel_size
  		snake_case__  					=      output_stride
  		snake_case__  					=      initializer_range
  		snake_case__  					=      layer_norm_eps
  		snake_case__  					=      n_attn_blocks
  		snake_case__  					=      base_attn_unit_dims
  		snake_case__  					=      width_multiplier
  		snake_case__  					=      ffn_multiplier
  		snake_case__  					=      ffn_dropout
  		snake_case__  					=      attn_dropout
  		snake_case__  					=      classifier_dropout_prob
  
  		# decode head attributes for semantic segmentation
  		snake_case__  					=      aspp_out_channels
  		snake_case__  					=      atrous_rates
  		snake_case__  					=      aspp_dropout_prob
  		snake_case__  					=      semantic_loss_ignore_index
  
  
  
  
  
  
  class 							__snake_case    (				__magic_name__       ):
  	__lowerCAmelCase						=     version.parse('''1.11'''       )
  
  
  
  
  
  	@property
  	def      _snake_case      (		self		)			->		Mapping[str, Mapping[int, str]]:
  		return OrderedDict([('pixel_values', {0: 'batch', 1: 'num_channels', 2: 'height', 3: 'width'})]		)
  
  
  
  
  
  	@property
  	def      _snake_case      (		self		)			->		Mapping[str, Mapping[int, str]]:
  		if self.task == "image-classification":
  			return OrderedDict([('logits', {0: 'batch'})]		)
  		else:
  			return OrderedDict([('last_hidden_state', {0: 'batch'}), ('pooler_output', {0: 'batch'})]		)
  
  
  
  
  
  	@property
  	def      _snake_case      (		self		)			->		float:
  		return 1E-4
  
  
  
  