






"""simple docstring"""
snake_case   :   List[str]    		=		1_0**8


def        A	(							__snake_case:   int     )						->		bool:

       """simple docstring"""





       if n % 1_0 == 0:
              return False
       __magic_name__										=						str(snake_case__     )
       return s == s[::-1]


def        A	(							)						->		int:

       """simple docstring"""





       __magic_name__										=						set()
       __magic_name__										=						1
       __magic_name__										=						5
       while sum_squares < LIMIT:
              __magic_name__										=						first_square + 1
              while sum_squares < LIMIT:
                     if is_palindrome(snake_case__     ):
                            answer.add(snake_case__     )
                     last_square += 1
                     sum_squares += last_square**2
              first_square += 1
              __magic_name__										=						first_square**2 + (first_square + 1) ** 2

       return sum(snake_case__     )


if __name__ == "__main__":
 print(solution())









"""simple docstring"""
from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available


snake_case   :   Optional[int]    		=		{
    """configuration_splinter""": ["""SPLINTER_PRETRAINED_CONFIG_ARCHIVE_MAP""", """SplinterConfig"""],
    """tokenization_splinter""": ["""SplinterTokenizer"""],
}

try:
 if not is_tokenizers_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 snake_case   :   Dict    		=		["""SplinterTokenizerFast"""]

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 snake_case   :   Dict    		=		[
     """SPLINTER_PRETRAINED_MODEL_ARCHIVE_LIST""",
     """SplinterForQuestionAnswering""",
     """SplinterForPreTraining""",
     """SplinterLayer""",
     """SplinterModel""",
     """SplinterPreTrainedModel""",
 ]


if TYPE_CHECKING:
 from .configuration_splinter import SPLINTER_PRETRAINED_CONFIG_ARCHIVE_MAP, SplinterConfig
 from .tokenization_splinter import SplinterTokenizer

 try:
  if not is_tokenizers_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .tokenization_splinter_fast import SplinterTokenizerFast

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_splinter import (
      SPLINTER_PRETRAINED_MODEL_ARCHIVE_LIST,
      SplinterForPreTraining,
      SplinterForQuestionAnswering,
      SplinterLayer,
      SplinterModel,
      SplinterPreTrainedModel,
  )


else:
 import sys

 snake_case   :   List[str]    		=		_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)