





# 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/








def 				__UpperCamelCase  (		snake_case = 1_0_0     )  ->						int:


   '''simple docstring'''







   __A				 =       [[0 for _ in range(snake_case     )] for _ in range(m + 1     )]
   for i in range(m + 1     ):
      __A				 =       1

   for n in range(m + 1     ):
      for k in range(1    ,	snake_case     ):
         memo[n][k] += memo[n][k - 1]
         if n > k:
            memo[n][k] += memo[n - k - 1][k]

   return memo[m][m - 1] - 1


if __name__ == "__main__":
    print(solution(int(input("""Enter a number: """).strip())))

