




from __future__ import annotations

_lowerCAmelCase    : Any		= {1: 1}



def     lowerCAmelCase		(		_lowerCAmelCase				: Optional[Any]						):




 """simple docstring"""







 if n in COLLATZ_SEQUENCE_LENGTHS:
  return COLLATZ_SEQUENCE_LENGTHS[n]
 UpperCAmelCase__							=    n // 2 if n % 2 == 0 else 3 * n + 1
 UpperCAmelCase__							=    collatz_sequence_length(SCREAMING_SNAKE_CASE_						) + 1
 UpperCAmelCase__							=    sequence_length
 return sequence_length



def     lowerCAmelCase		(		_lowerCAmelCase				: List[Any] = 100_0000						):




 """simple docstring"""







 UpperCAmelCase__							=    max((collatz_sequence_length(SCREAMING_SNAKE_CASE_						), i) for i in range(1    ,				SCREAMING_SNAKE_CASE_						)						)
 return result[1]


if __name__ == "__main__":
  print(solution(int(input().strip())))












import sys

from transformers import AutoTokenizer


snake_case_				=      sys.argv[1]
snake_case_				=      sys.argv[2]
snake_case_				=      int(sys.argv[3])

snake_case_				=      0

snake_case_				=      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:
								snake_case_				=      line.rstrip()

								if not line:
												print(line)
												snake_case_				=      0
												continue

								snake_case_				=      line.split()[0]

								snake_case_				=      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)
												snake_case_				=      current_subwords_len
												continue

								subword_len_counter += current_subwords_len

								print(line)

