求偏导数

#derivative 导数
def g(x1,x2):
    return x1*(x2**3)
def approximate_derivative(f,x,eps=1e-3):
    return ((f(x+eps)-f(x))/eps)
def approximate_gradient(g,x1,x2,eps=1e-3):
    dg_x1=approximate_derivative(lambda x:g(x,x2),x1,eps)
    dg_x2=approximate_derivative(lambda x:g(x1,x),x2,eps)
    return dg_x1,dg_x2
print(approximate_gradient(g,1.,2.))
#输出结果
(7.999999999999119, 12.006000999997823)