
from __future__ import annotations






def 						lowerCamelCase__							(      a	,	a	,	a	,	a   )   ->     None:
   _A    ,						_A:						str	    = m - 1, 0
   while i >= 0 and j < n:
      if key == mat[i][j]:
         print(f"""Key {key} found at row- {i + 1} column- {j + 1}"""   )
         return
      if key < mat[i][j]:
         i -= 1
      else:
         j += 1
   print(f"""Key {key} not found"""   )






def 						lowerCamelCase__							(      )   ->     None:
   _A:						Optional[int]	    = [[2, 5, 7], [4, 8, 13], [9, 11, 15], [12, 17, 20]]
   _A:						str	    = int(input('''Enter the element to be searched:'''   )   )
   print(a   )
   search_in_a_sorted_matrix(a	,	len(a   )	,	len(mat[0]   )	,	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/



