
"""simple docstring"""




def lowercase_  (   _snake_case = 100						):
							SCREAMING_SNAKE_CASE__						:       Union[str, Any]           =   set()

							SCREAMING_SNAKE_CASE__						:       str           =   0

							SCREAMING_SNAKE_CASE__						:       Tuple           =   n + 1  # maximum limit

							for a in range(2   ,_snake_case						):
														for b in range(2   ,_snake_case						):
																					SCREAMING_SNAKE_CASE__						:       Optional[Any]           =   a**b  # calculates the current power
																					collect_powers.add(_snake_case						)  # adds the result to the set
							return len(_snake_case						)


if __name__ == "__main__":
					print('Number of terms ', solution(int(str(input()).strip())))






"""simple docstring"""




import pickle
import unittest

import torch

from accelerate import Accelerator
from accelerate.state import AcceleratorState
from accelerate.test_utils import require_cpu



@require_cpu
class 	lowerCAmelCase_						(unittest.TestCase  ):


				"""simple docstring"""



				def 	__magic_name__    (self    )					->		Union[str, Any]:



											"""simple docstring"""




											SCREAMING_SNAKE_CASE__						:       List[Any]           =   torch.nn.Linear(10   ,       10    )
											SCREAMING_SNAKE_CASE__						:       Optional[int]           =   torch.optim.SGD(model.parameters()   ,       0.1    )
											SCREAMING_SNAKE_CASE__						:       int           =   Accelerator()
											SCREAMING_SNAKE_CASE__						:       List[Any]           =   accelerator.prepare(SCREAMING_SNAKE_CASE__    )
											try:
																		pickle.loads(pickle.dumps(SCREAMING_SNAKE_CASE__    )    )
											except Exception as e:
																		self.fail(F'''Accelerated optimizer pickling failed with {e}'''    )
											AcceleratorState._reset_state()




