

def test_2d_array_fanout():

    def fun(x):
        A = np.array([[x, (x * 1.0), (x + 2.5)], [(x ** 2), x, (x / 2.0)]])
        return to_scalar((A + A))
    d_fun = (lambda x: grad(fun)(x))
    check_grads(fun, 3.0)
    check_grads(x, 3.0)

dataset/ETHPy150Open HIPS/autograd/tests/test_numpy.py test_2d_array_fanout/VarMisuse@94/105 `d_fun`->`x`