def test_contextmanager_nested():
with tn.DefaultBackend("tensorflow"):
a = tn.Node(np.ones((10, )))
assert a.backend.name == "tensorflow"
with tn.DefaultBackend("numpy"):
b = tn.Node(np.ones((10, )))
assert b.backend.name == "numpy"
c = tn.Node(np.ones((10, )))
assert c.backend.name == "tensorflow"
d = tn.Node(np.ones((10, )))
assert d.backend.name == "numpy"
def test_operator_kron(backend):
with tn.DefaultBackend(backend):
X = np.array([[0, 1], [1, 0]], dtype=np.float32)
Z = np.array([[1, 0], [0, -1]], dtype=np.float32)
expected = np.kron(X, Z).reshape(2, 2, 2, 2)
result = tn.kron([tn.Node(X), tn.Node(Z)])
np.testing.assert_allclose(result.tensor, expected)
def test_kron_raises(backend):
with tn.DefaultBackend(backend):
A = tn.Node(np.ones((2, 2, 2)))
B = tn.Node(np.ones((2, 2, 2)))
with pytest.raises(
ValueError,
match="All operator tensors must have an even order."):
tn.kron([A, B])
def test_get_neighbors(backend):
with tn.DefaultBackend(backend):
a = tn.Node(np.ones((2, 2)))
b = tn.Node(np.ones((2, 2, 2, 2)))
c = tn.Node(np.ones((2, 2, 2)))
d = tn.Node(np.ones((2, 2)))
b[0] ^ a[1]
b[3] ^ c[2]
a[0] ^ d[1]
b[1] ^ b[2]
result = tn.get_neighbors(b)
assert result == [a, c]
def test_contextmanager_simple():
with tn.DefaultBackend("tensorflow"):
a = tn.Node(np.ones((10, )))
b = tn.Node(np.ones((10, )))
assert a.backend.name == b.backend.name
def test_contextmanager_BaseBackend():
tn.set_default_backend("pytorch")
a = tn.Node(np.ones((10, )))
with tn.DefaultBackend(a.backend):
b = tn.Node(np.ones((10, )))
assert b.backend.name == "pytorch"
def test_contextmanager_wrong_item():
a = tn.Node(np.ones((10, )))
with pytest.raises(ValueError):
tn.DefaultBackend(a) # pytype: disable=wrong-arg-types
def test_contextmanager_interruption():
tn.set_default_backend("pytorch")
with pytest.raises(AssertionError):
with tn.DefaultBackend("numpy"):
tn.set_default_backend("tensorflow")
def test_contextmanager_default_backend():
tn.set_default_backend("pytorch")
with tn.DefaultBackend("numpy"):
assert _default_backend_stack.default_backend == "pytorch"
