
'''simple docstring'''

import math


def 	_UpperCAmelCase				(  _lowerCamelCase						:       int		)    ->						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(_lowerCamelCase		) + 1		)  ,      6		):
    if number % i == 0 or number % (i + 2) == 0:
      return False
  return True


def 	_UpperCAmelCase				(  _lowerCamelCase						:       int = 60_08_51_47_51_43		)    ->						int:

  try:
    _lowerCAmelCase       :  Tuple   				=					int(_lowerCamelCase		)
  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."""		)
  _lowerCAmelCase       :  Dict   				=					0
  if is_prime(_lowerCamelCase		):
    return n
  while n % 2 == 0:
    n //= 2
  if is_prime(_lowerCamelCase		):
    return n
  for i in range(3  ,      int(math.sqrt(_lowerCamelCase		)		) + 1  ,      2		):
    if n % i == 0:
      if is_prime(n // i		):
        _lowerCAmelCase       :  Tuple   				=					n // i
        break
      elif is_prime(_lowerCamelCase		):
        _lowerCAmelCase       :  str   				=					i
  return max_number


if __name__ == "__main__":
     print(F'{solution() = }')




'''simple docstring'''

from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_tf_available,
    is_torch_available,
)


UpperCamelCase_     			=       {
    """configuration_gptsan_japanese""": ["""GPTSAN_JAPANESE_PRETRAINED_CONFIG_ARCHIVE_MAP""", """GPTSanJapaneseConfig"""],
    """tokenization_gptsan_japanese""": ["""GPTSanJapaneseTokenizer"""],
}

try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     UpperCamelCase_     			=       [
         """GPTSAN_JAPANESE_PRETRAINED_MODEL_ARCHIVE_LIST""",
         """GPTSanJapaneseForConditionalGeneration""",
         """GPTSanJapaneseModel""",
         """GPTSanJapanesePreTrainedModel""",
     ]
     UpperCamelCase_     			=       [
         """GPTSanJapaneseTokenizer""",
     ]


if TYPE_CHECKING:
     from .configuration_gptsan_japanese import GPTSAN_JAPANESE_PRETRAINED_CONFIG_ARCHIVE_MAP, GPTSanJapaneseConfig
     from .tokenization_gptsan_japanese import GPTSanJapaneseTokenizer

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_gptsan_japanese import (
              GPTSAN_JAPANESE_PRETRAINED_MODEL_ARCHIVE_LIST,
              GPTSanJapaneseForConditionalGeneration,
              GPTSanJapaneseModel,
              GPTSanJapanesePreTrainedModel,
          )
          from .tokenization_gptsan_japanese import GPTSanJapaneseTokenizer


else:
     import sys

     UpperCamelCase_     			=       _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)


