




def       snake_case      (							A		,     A = 13    )							->							str:




	'''simple docstring'''


	lowerCamelCase_							:	Tuple							     =							''
	for c in s:
		if "A" <= c <= "Z":
			out += chr(ord('A'    ) + (ord(A    ) - ord('A'    ) + n) % 26    )
		elif "a" <= c <= "z":
			out += chr(ord('a'    ) + (ord(A    ) - ord('a'    ) + n) % 26    )
		else:
			out += c
	return out






def       snake_case      (							)							->							None:




	'''simple docstring'''


	lowerCamelCase_							:	Optional[int]							     =							input('Enter message: '    )

	lowerCamelCase_							:	Tuple							     =							dencrypt(A		,     13    )
	print('Encryption:'		,     A    )

	lowerCamelCase_							:	Dict							     =							dencrypt(A		,     13    )
	print('Decryption: '		,     A    )


if __name__ == "__main__":
							import doctest

							doctest.testmod()
							main()






# 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/
