"""simple docstring"""


import sys

from transformers import AutoTokenizer


__UpperCamelCase       :    List[Any]         =		sys.argv[1]
__UpperCamelCase       :    Dict         =		sys.argv[2]
__UpperCamelCase       :    Dict         =		int(sys.argv[3])

__UpperCamelCase       :    List[Any]         =		0

__UpperCamelCase       :    Optional[int]         =		AutoTokenizer.from_pretrained(model_name_or_path)
max_len -= tokenizer.num_special_tokens_to_add()

with open(dataset, "rt") as f_p:
  for line in f_p:
    __UpperCamelCase       :    Tuple         =		line.rstrip()

    if not line:
      print(line)
      __UpperCamelCase       :    Dict         =		0
      continue

    __UpperCamelCase       :    Any         =		line.split()[0]

    __UpperCamelCase       :    str         =		len(tokenizer.tokenize(token))

    # Token contains strange control characters like \x96 or \x95
    # Just filter out the complete line
    if current_subwords_len == 0:
      continue

    if (subword_len_counter + current_subwords_len) > max_len:
      print("")
      print(line)
      __UpperCamelCase       :    Dict         =		current_subwords_len
      continue

    subword_len_counter += current_subwords_len

    print(line)




import math





def 				A      (	_UpperCAmelCase							:  int       )							->					int:







			'''simple docstring'''
			return sum(int(_UpperCAmelCase       ) for digit in str(_UpperCAmelCase       )       )





def 				A      (	_UpperCAmelCase							:  int = 30       )							->					int:







			'''simple docstring'''
			_UpperCAmelCase									=  []
			for digit in range(2				,  100       ):
						for power in range(2				,  100       ):
									_UpperCAmelCase									=  int(math.pow(_UpperCAmelCase				,  _UpperCAmelCase       )       )
									if digit == digit_sum(_UpperCAmelCase       ):
												digit_to_powers.append(_UpperCAmelCase       )

			digit_to_powers.sort()
			return digit_to_powers[n - 1]


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