human
Solve the following python programming problem given the following code:
def perform(self, node, inputs, outputs) : 
    '
        Implements the "reverse-mode" gradient for the eigensystem of
        a square matrix.

        ' 
    (x, w, v, W, V) = inputs 
    N = x.shape [0] 
    outer = numpy.outer 
    def G(n) : 
        return sum ((((v [:, m] * V.T [n].dot (v [:, m])) / (w [n] - w [m])) for m in xrange (N) if (m != n))) 
g = sum ((outer (v [:, N], ((v [:, n] * W [n]) + G (n))) for n in xrange (N))) 
    out = (self.tri0 (g) + self.tri1 (g).T) 
    outputs [0] [0] = numpy.asarray (out, dtype = node.outputs [0].dtype) 

    
    

    Fix the buggy line: g = sum ((outer (v [:, N], ((v [:, n] * W [n]) + G (n))) for n in xrange (N)))
assistant
#Here is Python program to fix the buggy line: g = sum ((outer (v [:, N], ((v [:, n] * W [n]) + G (n))) for n in xrange (N)))
.

g = sum ((outer (v [:, n], ((v [:, n] * W [n]) + G (n))) for n in xrange (N)))