def testValidateArgs(self):
k = psd_kernels.MaternThreeHalves(
amplitude=-1., length_scale=-1., validate_args=True)
with self.assertRaises(tf.errors.InvalidArgumentError):
self.evaluate(k.amplitude)
with self.assertRaises(tf.errors.InvalidArgumentError):
self.evaluate(k.length_scale)
# But `None`'s are ok
k = psd_kernels.MaternThreeHalves(
amplitude=None, length_scale=None, validate_args=True)
self.evaluate(k.apply([1.], [1.]))
def testShapesAreCorrect(self):
k = psd_kernels.MaternThreeHalves(amplitude=1., length_scale=1.)
x = np.ones([4, 3], np.float32)
y = np.ones([5, 3], np.float32)
self.assertAllEqual(k.matrix(x, y).shape, [4, 5])
self.assertAllEqual(
k.matrix(tf.stack([x] * 2), tf.stack([y] * 2)).shape, [2, 4, 5])
k = psd_kernels.MaternThreeHalves(
amplitude=np.ones([2, 1, 1], np.float32),
length_scale=np.ones([1, 3, 1], np.float32))
self.assertAllEqual(
k.matrix(
tf.stack([x] * 2), # shape [2, 4, 3]
tf.stack([y] * 2) # shape [2, 5, 3]
).shape,
[2, 3, 2, 4, 5])
def testValuesAreCorrect(self, feature_ndims, dtype, dims):
amplitude = np.array(5., dtype=dtype)
length_scale = np.array(.2, dtype=dtype)
np.random.seed(42)
k = psd_kernels.MaternThreeHalves(amplitude, length_scale, feature_ndims)
shape = [dims] * feature_ndims
for _ in range(5):
x = np.random.uniform(-1, 1, size=shape).astype(dtype)
y = np.random.uniform(-1, 1, size=shape).astype(dtype)
self.assertAllClose(
self.evaluate(k.apply(x, y)),
self._matern_three_halves(amplitude, length_scale, x, y))
def testMismatchedFloatTypesAreBad(self):
with self.assertRaises(ValueError):
psd_kernels.MaternThreeHalves(np.float32(1.), np.float64(1.))