
from __future__ import annotations

lowerCamelCase_  :       Union[str, Any]					      =     {1: 1}







def 				A__    (  lowerCamelCase  )     ->		int:
				if n in COLLATZ_SEQUENCE_LENGTHS:
								return COLLATZ_SEQUENCE_LENGTHS[n]
				UpperCamelCase_:							Dict		=  n // 2 if n % 2 == 0 else 3 * n + 1
				UpperCamelCase_:							Optional[Any]		=  collatz_sequence_length(lowerCamelCase  ) + 1
				UpperCamelCase_:							List[Any]		=  sequence_length
				return sequence_length







def 				A__    (  lowerCamelCase = 1_00_00_00  )     ->		int:
				UpperCamelCase_:							Tuple		=  max((collatz_sequence_length(lowerCamelCase  ), i) for i in range(1   ,			lowerCamelCase  )  )
				return result[1]


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








import warnings

from ...utils import logging
from .image_processing_mobilenet_va import MobileNetVaImageProcessor


lowerCamelCase_  :       List[Any]					      =     logging.get_logger(__name__)

class 				_UpperCamelCase (    _A     ):






			'''simple docstring'''

			def __init__(				self       :				Dict  ,		*snake_case_       :				Optional[int]  ,		**snake_case_       :				List[Any]					):
							warnings.warn(
							    """The class MobileNetV2FeatureExtractor is deprecated and will be removed in version 5 of Transformers."""
							    """ Please use MobileNetV2ImageProcessor instead."""  ,		snake_case_  ,		)
							super().__init__(*snake_case_  ,		**snake_case_					)






