




import math
import sys



def      __lowerCAmelCase			(					UpperCamelCase      )     ->	int:
  if number != int(UpperCamelCase      ):
    raise ValueError('''the value of input must be a natural number'''      )
  if number < 0:
    raise ValueError('''the value of input must not be a negative number'''      )
  if number == 0:
    return 1
  lowerCAmelCase__				:  Any		       =     [-1] * (number + 1)
  lowerCAmelCase__				:  Dict		       =     0
  for i in range(1	,      number + 1      ):
    lowerCAmelCase__				:  Dict		       =     sys.maxsize
    lowerCAmelCase__				:  str		       =     int(math.sqrt(UpperCamelCase      )      )
    for j in range(1	,      root + 1      ):
      lowerCAmelCase__				:  Any		       =     1 + answers[i - (j**2)]
      lowerCAmelCase__				:  Optional[Any]		       =     min(UpperCamelCase	,      UpperCamelCase      )
    lowerCAmelCase__				:  List[Any]		       =     answer
  return answers[number]


if __name__ == "__main__":
     import doctest

     doctest.testmod()







from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


lowerCAmelCase_					    = {
    """configuration_lilt""": ["""LILT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """LiltConfig"""],
}

try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     lowerCAmelCase_					    = [
         """LILT_PRETRAINED_MODEL_ARCHIVE_LIST""",
         """LiltForQuestionAnswering""",
         """LiltForSequenceClassification""",
         """LiltForTokenClassification""",
         """LiltModel""",
         """LiltPreTrainedModel""",
     ]

if TYPE_CHECKING:
     from .configuration_lilt import LILT_PRETRAINED_CONFIG_ARCHIVE_MAP, LiltConfig

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_lilt import (
              LILT_PRETRAINED_MODEL_ARCHIVE_LIST,
              LiltForQuestionAnswering,
              LiltForSequenceClassification,
              LiltForTokenClassification,
              LiltModel,
              LiltPreTrainedModel,
          )

else:
     import sys

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

