





'''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/







'''simple docstring'''
def     lowercase__       (       __lowercase						:  str    ,  __lowercase						:  Tuple					)			->				str:



       """simple docstring"""






       sequence.append(__lowercase					)

       __UpperCamelCase	=  0
       while sequence[index] != target:
              index += 1

       sequence.pop()

       if index == len(__lowercase					):
              return None

       return index


if __name__ == "__main__":
    a__							:							Any			=input('''Enter numbers separated by comma:\n''').strip()
    a__							:							Any			=[int(item) for item in user_input.split(''',''')]

    a__							:							Tuple			=input('''Enter a single number to be found in the list:\n''')
    a__							:							List[Any]			=int(target_input)
    a__							:							List[Any]			=sentinel_linear_search(sequence, target)
    if result is not None:
        print(f'{target} found at positions: {result}')
    else:
        print('''Not found''')
