






"""simple docstring"""

import argparse

from transformers import TaConfig, TaForConditionalGeneration, load_tf_weights_in_ta
from transformers.utils import logging


logging.set_verbosity_info()






def _lowerCAmelCase						(	__lowerCamelCase:Optional[Any]			,    __lowerCamelCase:List[Any]			,    __lowerCamelCase:Tuple ):

						'''simple docstring'''






						__magic_name__      =  TaConfig.from_json_file(__lowerCamelCase )
						print(f'''Building PyTorch model from configuration: {config}''' )
						__magic_name__      =  TaForConditionalGeneration(__lowerCamelCase )

						# Load weights from tf checkpoint
						load_tf_weights_in_ta(__lowerCamelCase			,    __lowerCamelCase			,    __lowerCamelCase )

						# Save pytorch-model
						print(f'''Save PyTorch model to {pytorch_dump_path}''' )
						model.save_pretrained(__lowerCamelCase )


if __name__ == "__main__":
			lowercase           =							argparse.ArgumentParser()
			# Required parameters
			parser.add_argument(
			    '''--tf_checkpoint_path''', default=None, type=str, required=True, help='''Path to the TensorFlow checkpoint path.'''
			)
			parser.add_argument(
			    '''--config_file''',
			    default=None,
			    type=str,
			    required=True,
			    help=(
			        '''The config json file corresponding to the pre-trained T5 model. \nThis specifies the model architecture.'''
			    ),
			)
			parser.add_argument(
			    '''--pytorch_dump_path''', default=None, type=str, required=True, help='''Path to the output PyTorch model.'''
			)
			lowercase           =							parser.parse_args()
			convert_tf_checkpoint_to_pytorch(args.tf_checkpoint_path, args.config_file, args.pytorch_dump_path)











"""simple docstring"""

from __future__ import annotations

lowercase           =							{1: 1}






def _lowerCAmelCase						(	__lowerCamelCase:int ):

						'''simple docstring'''






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






def _lowerCAmelCase						(	__lowerCamelCase:int = 1_0_0_0_0_0_0 ):

						'''simple docstring'''






						__magic_name__      =  max((collatz_sequence_length(__lowerCamelCase ), i) for i in range(1			,    __lowerCamelCase ) )
						return result[1]


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



