"""simple docstring"""







import os



def 			A__						(  )     ->       int:
   __lowerCamelCase								=				os.path.dirname(os.path.realpath(lowercase_	)	)
   __lowerCamelCase								=				os.path.join(lowercase_			,   'triangle.txt'	)

   with open(lowercase_	) as in_file:
      __lowerCamelCase								=				[[int(lowercase_	) for i in line.split()] for line in in_file]

   while len(lowercase_	) != 1:
      __lowerCamelCase								=				triangle.pop()
      __lowerCamelCase								=				triangle[-1]
      for j in range(len(lowercase_	) - 1	):
         curr_row[j] += max(last_row[j]			,   last_row[j + 1]	)
   return triangle[0][0]


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







"""simple docstring"""







# 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/






