





'''simple docstring'''
from math import sqrt
def     lowercase__       (       __lowercase						:  int					)			->				list[int]:



       """simple docstring"""






       __UpperCamelCase	=  [1]
       for i in range(2    ,  int(sqrt(__lowercase					)					) + 1    ,  1					):
              if number % i == 0:
                     values.append(__lowercase					)
                     if int(number // i					) != i:
                            values.append(int(number // i					)					)
       return sorted(__lowercase					)
def     lowercase__       (       __lowercase						:  int					)			->				bool:



       """simple docstring"""






       return sum(factors(__lowercase					)					) > n
def     lowercase__       (       __lowercase						:  int					)			->				bool:



       """simple docstring"""






       __UpperCamelCase	=  factors(__lowercase					)
       __UpperCamelCase	=  len(__lowercase					)
       __UpperCamelCase	=  [[0 for i in range(number + 1					)] for j in range(r + 1					)]
       for i in range(r + 1					):
              __UpperCamelCase	=  True

       for i in range(1    ,  number + 1					):
              __UpperCamelCase	=  False

       for i in range(1    ,  r + 1					):
              for j in range(1    ,  number + 1					):
                     if j < values[i - 1]:
                            __UpperCamelCase	=  subset[i - 1][j]
                     else:
                            __UpperCamelCase	=  subset[i - 1][j] or subset[i - 1][j - values[i - 1]]

       return subset[r][number] != 0
def     lowercase__       (       __lowercase						:  int					)			->				bool:



       """simple docstring"""






       return abundant(__lowercase					) and not semi_perfect(__lowercase					)


if __name__ == "__main__":
    import doctest

    doctest.testmod(verbose=True)
    for number in (69, 70, 71):
        print(f'{number} is {"" if weird(number) else "not "}weird.')







'''simple docstring'''
a__							:							int			='''
# Transformers installation
! pip install transformers datasets evaluate
# To install from source instead of the last release, comment the command above and uncomment the following one.
# ! pip install git+https://github.com/huggingface/transformers.git
'''

a__							:							List[Any]			=[{'''type''': '''code''', '''content''': INSTALL_CONTENT}]
a__							:							Dict			={
    '''{processor_class}''': '''FakeProcessorClass''',
    '''{model_class}''': '''FakeModelClass''',
    '''{object_class}''': '''FakeObjectClass''',
}
