def test_qr_modes():
rng = np.random.RandomState(utt.fetch_seed())
A = tensor.matrix("A", dtype=theano.config.floatX)
a = rng.rand(4, 4).astype(theano.config.floatX)
f = function([A], qr(A))
t_qr = f(a)
n_qr = np.linalg.qr(a)
assert _allclose(n_qr, t_qr)
for mode in ["reduced", "r", "raw"]:
f = function([A], qr(A, mode))
t_qr = f(a)
n_qr = np.linalg.qr(a, mode)
if isinstance(n_qr, (list, tuple)):
assert _allclose(n_qr[0], t_qr[0])
assert _allclose(n_qr[1], t_qr[1])
else:
assert _allclose(n_qr, t_qr)
try:
n_qr = np.linalg.qr(a, "complete")
f = function([A], qr(A, "complete"))
t_qr = f(a)
assert _allclose(n_qr, t_qr)
except TypeError as e:
assert "name 'complete' is not defined" in str(e)
def test_qr_modes():
rng = np.random.RandomState(utt.fetch_seed())
A = tensor.matrix("A", dtype=theano.config.floatX)
a = rng.rand(4, 4).astype(theano.config.floatX)
f = function([A], qr(A))
t_qr = f(a)
n_qr = np.linalg.qr(a)
assert _allclose(n_qr, t_qr)
for mode in ["reduced", "r", "raw"]:
f = function([A], qr(A, mode))
t_qr = f(a)
n_qr = np.linalg.qr(a, mode)
if isinstance(n_qr, (list, tuple)):
assert _allclose(n_qr[0], t_qr[0])
assert _allclose(n_qr[1], t_qr[1])
else:
assert _allclose(n_qr, t_qr)
try:
n_qr = np.linalg.qr(a, "complete")
f = function([A], qr(A, "complete"))
t_qr = f(a)
assert _allclose(n_qr, t_qr)
except TypeError as e:
assert "name 'complete' is not defined" in str(e)
def test_gpu_qr_incomplete_opt(self):
A = theano.tensor.fmatrix("A")
fn = theano.function([A], qr(A, mode="r"), mode=mode_with_gpu)
assert any([
isinstance(node.op, GpuMagmaQR) and not node.op.complete
for node in fn.maker.fgraph.toposort()
])
def test_gpu_qr_incomplete_opt(self):
A = theano.tensor.fmatrix("A")
fn = theano.function([A], qr(A, mode='r'), mode=mode_with_gpu)
assert any([
isinstance(node.op, GpuMagmaQR) and not node.op.complete
for node in fn.maker.fgraph.toposort()
])
