




from math import ceil



def      __lowerCAmelCase			(					UpperCamelCase = 1001      )     ->	int:
  lowerCAmelCase__				:  List[str]		       =     1

  for i in range(1	,      int(ceil(n / 2.0      )      )      ):
    lowerCAmelCase__				:  List[Any]		       =     2 * i + 1
    lowerCAmelCase__				:  List[Any]		       =     2 * i
    lowerCAmelCase__				:  Optional[int]		       =     total + 4 * odd**2 - 6 * even

  return total


if __name__ == "__main__":
     import sys

     if len(sys.argv) == 1:
          print(solution())
     else:
          try:
               lowerCAmelCase_					    = int(sys.argv[1])
               print(solution(n))
          except ValueError:
               print("""Invalid entry - please enter a number""")







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__)

