code: 
  
  
  import math
  from itertools import permutations
  
  
  
  
  
  
  def   __lowerCamelCase	(       lowerCamelCase__		:	int			):
  
  
  
  
  
  			'''simple docstring'''
  
  
  
  
  			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(lowerCamelCase__			) + 1			)     ,       6			):
  						if number % i == 0 or number % (i + 2) == 0:
  									return False
  			return True
  
  
  
  
  
  
  def   __lowerCamelCase	(       lowerCamelCase__		:	int     ,       lowerCamelCase__		:	list			):
  
  
  
  
  
  			'''simple docstring'''
  
  
  
  
  			lowerCamelCase		,		lowerCamelCase								=     0, len(lowerCamelCase__			) - 1
  			while left <= right:
  						lowerCamelCase								=     (left + right) // 2
  						if prime_list[middle] == target:
  									return True
  						elif prime_list[middle] < target:
  									lowerCamelCase								=     middle + 1
  						else:
  									lowerCamelCase								=     middle - 1
  
  			return False
  
  
  
  
  
  
  def   __lowerCamelCase	(       ):
  
  
  
  
  
  			'''simple docstring'''
  
  
  
  
  			lowerCamelCase								=     [n for n in range(1001     ,       10000     ,       2			) if is_prime(lowerCamelCase__			)]
  			lowerCamelCase								=     []
  
  			for number in prime_list:
  						lowerCamelCase								=     []
  
  						for prime_member in permutations(list(str(lowerCamelCase__			)			)			):
  									lowerCamelCase								=     int("""""".join(lowerCamelCase__			)			)
  
  									if prime % 2 == 0:
  												continue
  
  									if search(lowerCamelCase__     ,       lowerCamelCase__			):
  												tmp_numbers.append(lowerCamelCase__			)
  
  						tmp_numbers.sort()
  						if len(lowerCamelCase__			) >= 3:
  									candidates.append(lowerCamelCase__			)
  
  			lowerCamelCase								=     []
  			for candidate in candidates:
  						lowerCamelCase								=     len(lowerCamelCase__			)
  						lowerCamelCase								=     False
  
  						for i in range(lowerCamelCase__			):
  									for j in range(i + 1     ,       lowerCamelCase__			):
  												for k in range(j + 1     ,       lowerCamelCase__			):
  															if (
  															    abs(candidate[i] - candidate[j]			)
  															    == abs(candidate[j] - candidate[k]			)
  															    and len({candidate[i], candidate[j], candidate[k]}			) == 3
  															):
  																		passed.append(
  																		    sorted([candidate[i], candidate[j], candidate[k]]			)			)
  																		lowerCamelCase								=     True
  
  															if found:
  																		break
  												if found:
  															break
  									if found:
  												break
  
  			lowerCamelCase								=     set()
  			for seq in passed:
  						answer.add("""""".join([str(lowerCamelCase__			) for i in seq]			)			)
  
  			return max(int(lowerCamelCase__			) for x in answer			)
  
  
  if __name__ == "__main__":
  			print(solution())
  
  
style_context: 
  
  
  from typing import TYPE_CHECKING
  
  from ...utils import (
      OptionalDependencyNotAvailable,
      _LazyModule,
      is_flax_available,
      is_sentencepiece_available,
      is_tf_available,
      is_tokenizers_available,
      is_torch_available,
  )
  
  
  UpperCAmelCase      :						List[str]    =		{
      "configuration_big_bird": ["BIG_BIRD_PRETRAINED_CONFIG_ARCHIVE_MAP", "BigBirdConfig", "BigBirdOnnxConfig"],
  }
  
  try:
  		if not is_sentencepiece_available():
  				raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
  		pass
  else:
  		UpperCAmelCase      :						str    =		["BigBirdTokenizer"]
  
  try:
  		if not is_tokenizers_available():
  				raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
  		pass
  else:
  		UpperCAmelCase      :						str    =		["BigBirdTokenizerFast"]
  
  try:
  		if not is_torch_available():
  				raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
  		pass
  else:
  		UpperCAmelCase      :						Dict    =		[
  		    "BIG_BIRD_PRETRAINED_MODEL_ARCHIVE_LIST",
  		    "BigBirdForCausalLM",
  		    "BigBirdForMaskedLM",
  		    "BigBirdForMultipleChoice",
  		    "BigBirdForPreTraining",
  		    "BigBirdForQuestionAnswering",
  		    "BigBirdForSequenceClassification",
  		    "BigBirdForTokenClassification",
  		    "BigBirdLayer",
  		    "BigBirdModel",
  		    "BigBirdPreTrainedModel",
  		    "load_tf_weights_in_big_bird",
  		]
  
  try:
  		if not is_flax_available():
  				raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
  		pass
  else:
  		UpperCAmelCase      :						Dict    =		[
  		    "FlaxBigBirdForCausalLM",
  		    "FlaxBigBirdForMaskedLM",
  		    "FlaxBigBirdForMultipleChoice",
  		    "FlaxBigBirdForPreTraining",
  		    "FlaxBigBirdForQuestionAnswering",
  		    "FlaxBigBirdForSequenceClassification",
  		    "FlaxBigBirdForTokenClassification",
  		    "FlaxBigBirdModel",
  		    "FlaxBigBirdPreTrainedModel",
  		]
  
  if TYPE_CHECKING:
  		from .configuration_big_bird import BIG_BIRD_PRETRAINED_CONFIG_ARCHIVE_MAP, BigBirdConfig, BigBirdOnnxConfig
  
  		try:
  				if not is_sentencepiece_available():
  						raise OptionalDependencyNotAvailable()
  		except OptionalDependencyNotAvailable:
  				pass
  		else:
  				from .tokenization_big_bird import BigBirdTokenizer
  
  		try:
  				if not is_tokenizers_available():
  						raise OptionalDependencyNotAvailable()
  		except OptionalDependencyNotAvailable:
  				pass
  		else:
  				from .tokenization_big_bird_fast import BigBirdTokenizerFast
  
  		try:
  				if not is_torch_available():
  						raise OptionalDependencyNotAvailable()
  		except OptionalDependencyNotAvailable:
  				pass
  		else:
  				from .modeling_big_bird import (
  				    BIG_BIRD_PRETRAINED_MODEL_ARCHIVE_LIST,
  				    BigBirdForCausalLM,
  				    BigBirdForMaskedLM,
  				    BigBirdForMultipleChoice,
  				    BigBirdForPreTraining,
  				    BigBirdForQuestionAnswering,
  				    BigBirdForSequenceClassification,
  				    BigBirdForTokenClassification,
  				    BigBirdLayer,
  				    BigBirdModel,
  				    BigBirdPreTrainedModel,
  				    load_tf_weights_in_big_bird,
  				)
  
  		try:
  				if not is_flax_available():
  						raise OptionalDependencyNotAvailable()
  		except OptionalDependencyNotAvailable:
  				pass
  		else:
  				from .modeling_flax_big_bird import (
  				    FlaxBigBirdForCausalLM,
  				    FlaxBigBirdForMaskedLM,
  				    FlaxBigBirdForMultipleChoice,
  				    FlaxBigBirdForPreTraining,
  				    FlaxBigBirdForQuestionAnswering,
  				    FlaxBigBirdForSequenceClassification,
  				    FlaxBigBirdForTokenClassification,
  				    FlaxBigBirdModel,
  				    FlaxBigBirdPreTrainedModel,
  				)
  
  else:
  		import sys
  
  		UpperCAmelCase      :						Dict    =		_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)
  
  