
"""simple docstring"""





def 				lowerCamelCase__		(      __snake_case = 1_00_00_00     )							->		int:


					"""simple docstring"""





					_UpperCamelCase										=  1
					_UpperCamelCase										=  1
					_UpperCamelCase										=  {1: 1}

					for inputa in range(2,					__snake_case     ):
										_UpperCamelCase										=  0
										_UpperCamelCase										=  inputa

										while True:
															if number in counters:
																				counter += counters[number]
																				break
															if number % 2 == 0:
																				number //= 2
																				counter += 1
															else:
																				_UpperCamelCase										=  (3 * number) + 1
																				counter += 1

										if inputa not in counters:
															_UpperCamelCase										=  counter

										if counter > pre_counter:
															_UpperCamelCase										=  inputa
															_UpperCamelCase										=  counter
					return largest_number


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








"""simple docstring"""





from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_sentencepiece_available,
    is_speech_available,
    is_torch_available,
)


_a														=		{
    """configuration_trocr""": ["""TROCR_PRETRAINED_CONFIG_ARCHIVE_MAP""", """TrOCRConfig"""],
    """processing_trocr""": ["""TrOCRProcessor"""],
}


try:
				if not is_torch_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				_a														=		[
				    """TROCR_PRETRAINED_MODEL_ARCHIVE_LIST""",
				    """TrOCRForCausalLM""",
				    """TrOCRPreTrainedModel""",
				]


if TYPE_CHECKING:
				from .configuration_trocr import TROCR_PRETRAINED_CONFIG_ARCHIVE_MAP, TrOCRConfig
				from .processing_trocr import TrOCRProcessor

				try:
								if not is_torch_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_trocr import TROCR_PRETRAINED_MODEL_ARCHIVE_LIST, TrOCRForCausalLM, TrOCRPreTrainedModel

else:
				import sys

				_a														=		_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)






