

"""simple docstring"""

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"""

from itertools import product



def 			SCREAMING_SNAKE_CASE       (   lowercase__ = 1_5      ) ->	int:
 lowerCAmelCase__      :							float    =							0.0
 lowerCAmelCase__      :							float
 lowerCAmelCase__      :							int
 lowerCAmelCase__      :							int
 lowerCAmelCase__      :							int
 lowerCAmelCase__      :							int
 lowerCAmelCase__      :							tuple[int, ...]

 for series in product(range(2      )				,				repeat=lowercase__      ):
  lowerCAmelCase__      :							Optional[int]    =							series.count(1      )
  lowerCAmelCase__      :							Dict    =							num_turns - num_blue
  if num_red >= num_blue:
   continue
  lowerCAmelCase__      :							Dict    =							1.0
  for ind, col in enumerate(lowercase__				,				2      ):
   if col == 0:
    prob *= (ind - 1) / ind
   else:
    prob *= 1 / ind

  total_prob += prob

 return int(1 / total_prob      )


if __name__ == "__main__":
    print(f"{solution() = }")






