



"""simple docstring"""


from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available


snake_case_								=			{'''configuration_hubert''': ['''HUBERT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''HubertConfig''']}

try:
				if not is_torch_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				snake_case_								=			[
				    '''HUBERT_PRETRAINED_MODEL_ARCHIVE_LIST''',
				    '''HubertForCTC''',
				    '''HubertForSequenceClassification''',
				    '''HubertModel''',
				    '''HubertPreTrainedModel''',
				]


try:
				if not is_tf_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				snake_case_								=			[
				    '''TF_HUBERT_PRETRAINED_MODEL_ARCHIVE_LIST''',
				    '''TFHubertForCTC''',
				    '''TFHubertModel''',
				    '''TFHubertPreTrainedModel''',
				]

if TYPE_CHECKING:
				from .configuration_hubert import HUBERT_PRETRAINED_CONFIG_ARCHIVE_MAP, HubertConfig

				try:
								if not is_torch_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_hubert import (
								    HUBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
								    HubertForCTC,
								    HubertForSequenceClassification,
								    HubertModel,
								    HubertPreTrainedModel,
								)

				try:
								if not is_tf_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_tf_hubert import (
								    TF_HUBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
								    TFHubertForCTC,
								    TFHubertModel,
								    TFHubertPreTrainedModel,
								)


else:
				import sys

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










from __future__ import annotations

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





def 	__snake_case      (     _UpperCAmelCase							):
    if n in COLLATZ_SEQUENCE_LENGTHS:
        return COLLATZ_SEQUENCE_LENGTHS[n]
    __a					=							n // 2 if n % 2 == 0 else 3 * n + 1
    __a					=							collatz_sequence_length(_UpperCAmelCase							) + 1
    __a					=							sequence_length
    return sequence_length





def 	__snake_case      (     _UpperCAmelCase = 1000000							):
    __a					=							max((collatz_sequence_length(_UpperCAmelCase							), i) for i in range(1  ,					_UpperCAmelCase							)							)
    return result[1]


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





