



UpperCamelCase__  =		1_0**8






def       snake_case      (							A    )							->							List[str]:




	'''simple docstring'''


	if n % 10 == 0:
		return False
	lowerCamelCase_							:	Optional[int]							     =							str(lowercase_    )
	return s == s[::-1]






def       snake_case      (							)							->							List[Any]:




	'''simple docstring'''


	lowerCamelCase_							:	Union[str, Any]							     =							set()
	lowerCamelCase_							:	Tuple							     =							1
	lowerCamelCase_							:	int							     =							5
	while sum_squares < LIMIT:
		lowerCamelCase_							:	int							     =							first_square + 1
		while sum_squares < LIMIT:
			if is_palindrome(lowercase_    ):
				answer.add(lowercase_    )
			last_square += 1
			sum_squares += last_square**2
		first_square += 1
		lowerCamelCase_							:	List[Any]							     =							first_square**2 + (first_square + 1) ** 2

	return sum(lowercase_    )


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






# this script builds a small sample spm file tests/fixtures/test_sentencepiece_no_bos.model, with features needed by pegasus

# 1. pip install sentencepiece
#
# 2. wget https://raw.githubusercontent.com/google/sentencepiece/master/data/botchan.txt

# 3. build
import sentencepiece as spm

# pegasus:
# 1. no bos
# 2. eos_id is 1
# 3. unk_id is 2
# build a sample spm file accordingly
spm.SentencePieceTrainer.train(
    '--input=botchan.txt --model_prefix=test_sentencepiece_no_bos --bos_id=-1 --unk_id=2  --eos_id=1  --vocab_size=1000'
)

# 4. now update the fixture
# mv test_sentencepiece_no_bos.model ../../tests/fixtures/
