


'''simple docstring'''







from collections.abc import Sequence


def 	SCREAMING_SNAKE_CASE_					(  _UpperCAmelCase	:	Sequence[float]    ,_UpperCAmelCase	:	bool = False  )  ->			float:
       if not arr:
              return 0

       _a    : Dict     					=0 if allow_empty_subarrays else float("""-inf"""  )
       _a    : Optional[int]     					=0.0
       for num in arr:
              _a    : Any     					=max(0 if allow_empty_subarrays else num    ,curr_sum + num  )
              _a    : int     					=max(_UpperCAmelCase    ,_UpperCAmelCase  )

       return max_sum


if __name__ == "__main__":
   from doctest import testmod

   testmod()

   A__:    Tuple					    =       [-2, 1, -3, 4, -1, 2, 1, -5, 4]
   print(F"{max_subarray_sum(nums) = }")






'''simple docstring'''







A__:    Tuple					    =       '''
# Installazione di Transformers
! pip install transformers datasets
# Per installare dalla fonte invece dell\'ultima versione rilasciata, commenta il comando sopra e
# rimuovi la modalità commento al comando seguente.
# ! pip install git+https://github.com/huggingface/transformers.git
'''

A__:    Tuple					    =       [{'''type''': '''code''', '''content''': INSTALL_CONTENT}]
A__:    Any					    =       {
    '''{processor_class}''': '''FakeProcessorClass''',
    '''{model_class}''': '''FakeModelClass''',
    '''{object_class}''': '''FakeObjectClass''',
}


