


def  SCREAMING_SNAKE_CASE_		(    __A				:    int = 1_00       )			->	int:

       """simple docstring"""

       a_      :	Dict							=						set()

       a_      :	Union[str, Any]							=						0

       a_      :	str							=						n + 1  # maximum limit

       for a in range(2						,					__A       ):
              for b in range(2						,					__A       ):
                     a_      :	str							=						a**b  # calculates the current power
                     collect_powers.add(__A       )  # adds the result to the set
       return len(__A       )


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






UpperCAmelCase_   :				Optional[int]						      = '\n# Transformers installation\n! pip install transformers datasets\n# To install from source instead of the last release, comment the command above and uncomment the following one.\n# ! pip install git+https://github.com/huggingface/transformers.git\n'

UpperCAmelCase_   :				List[str]						      = [{'type': 'code', 'content': INSTALL_CONTENT}]
UpperCAmelCase_   :				int						      = {
    '{processor_class}': 'FakeProcessorClass',
    '{model_class}': 'FakeModelClass',
    '{object_class}': 'FakeObjectClass',
}


