
'''simple docstring'''

from __future__ import annotations

UpperCAmelCase__				:	List[str]					=						{1: 1}







def 					A       ( UpperCamelCase_   :       int )   ->    int:







			'''simple docstring'''



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







def 					A       ( UpperCamelCase_   :       int = 1_00_00_00 )   ->    int:







			'''simple docstring'''



			lowerCAmelCase__									=							max((collatz_sequence_length(UpperCamelCase_ ), i) for i in range(1  ,		UpperCamelCase_ ) )
			return result[1]


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







'''simple docstring'''

# this script builds a small sample spm file tests/fixtures/test_sentencepiece_no_bos.model, with features needed by pegasus

# 1. pip install sentencepiece
#
# 2. wget https://raw.githubusercontent.com/google/sentencepiece/master/data/botchan.txt

# 3. build
import sentencepiece as spm

# pegasus:
# 1. no bos
# 2. eos_id is 1
# 3. unk_id is 2
# build a sample spm file accordingly
spm.SentencePieceTrainer.train(
    "--input=botchan.txt --model_prefix=test_sentencepiece_no_bos --bos_id=-1 --unk_id=2  --eos_id=1  --vocab_size=1000"
)

# 4. now update the fixture
# mv test_sentencepiece_no_bos.model ../../tests/fixtures/





