test_slinalg.py 文件源码

def test_eigvalsh_grad():
    if not imported_scipy:
        raise SkipTest("Scipy needed for the geigvalsh op.")
    import scipy.linalg

    rng = numpy.random.RandomState(utt.fetch_seed())
    a = rng.randn(5, 5)
    a = a + a.T
    b = 10 * numpy.eye(5, 5) + rng.randn(5, 5)
    tensor.verify_grad(lambda a, b: eigvalsh(a, b).dot([1, 2, 3, 4, 5]),
                       [a, b], rng=numpy.random)