def test_tensorsolve():
rng = np.random.RandomState(utt.fetch_seed())
A = tensor.tensor4("A", dtype=theano.config.floatX)
B = tensor.matrix("B", dtype=theano.config.floatX)
X = tensorsolve(A, B)
fn = function([A, B], [X])
# slightly modified example from np.linalg.tensorsolve docstring
a = np.eye(2 * 3 * 4).astype(theano.config.floatX)
a.shape = (2 * 3, 4, 2, 3 * 4)
b = rng.rand(2 * 3, 4).astype(theano.config.floatX)
n_x = np.linalg.tensorsolve(a, b)
t_x = fn(a, b)
assert _allclose(n_x, t_x)
# check the type upcast now
C = tensor.tensor4("C", dtype='float32')
D = tensor.matrix("D", dtype='float64')
Y = tensorsolve(C, D)
fn = function([C, D], [Y])
c = np.eye(2 * 3 * 4, dtype='float32')
c.shape = (2 * 3, 4, 2, 3 * 4)
d = rng.rand(2 * 3, 4).astype('float64')
n_y = np.linalg.tensorsolve(c, d)
t_y = fn(c, d)
assert _allclose(n_y, t_y)
assert n_y.dtype == Y.dtype
# check the type upcast now
E = tensor.tensor4("E", dtype='int32')
F = tensor.matrix("F", dtype='float64')
Z = tensorsolve(E, F)
fn = function([E, F], [Z])
e = np.eye(2 * 3 * 4, dtype='int32')
e.shape = (2 * 3, 4, 2, 3 * 4)
f = rng.rand(2 * 3, 4).astype('float64')
n_z = np.linalg.tensorsolve(e, f)
t_z = fn(e, f)
assert _allclose(n_z, t_z)
assert n_z.dtype == Z.dtype
def test_tensorsolve():
rng = np.random.RandomState(utt.fetch_seed())
A = tensor.tensor4("A", dtype=theano.config.floatX)
B = tensor.matrix("B", dtype=theano.config.floatX)
X = tensorsolve(A, B)
fn = function([A, B], [X])
# slightly modified example from np.linalg.tensorsolve docstring
a = np.eye(2 * 3 * 4).astype(theano.config.floatX)
a.shape = (2 * 3, 4, 2, 3 * 4)
b = rng.rand(2 * 3, 4).astype(theano.config.floatX)
n_x = np.linalg.tensorsolve(a, b)
t_x = fn(a, b)
assert _allclose(n_x, t_x)
# check the type upcast now
C = tensor.tensor4("C", dtype='float32')
D = tensor.matrix("D", dtype='float64')
Y = tensorsolve(C, D)
fn = function([C, D], [Y])
c = np.eye(2 * 3 * 4, dtype='float32')
c.shape = (2 * 3, 4, 2, 3 * 4)
d = rng.rand(2 * 3, 4).astype('float64')
n_y = np.linalg.tensorsolve(c, d)
t_y = fn(c, d)
assert _allclose(n_y, t_y)
assert n_y.dtype == Y.dtype
# check the type upcast now
E = tensor.tensor4("E", dtype='int32')
F = tensor.matrix("F", dtype='float64')
Z = tensorsolve(E, F)
fn = function([E, F], [Z])
e = np.eye(2 * 3 * 4, dtype='int32')
e.shape = (2 * 3, 4, 2, 3 * 4)
f = rng.rand(2 * 3, 4).astype('float64')
n_z = np.linalg.tensorsolve(e, f)
t_z = fn(e, f)
assert _allclose(n_z, t_z)
assert n_z.dtype == Z.dtype
