def test_scalar_jacobian(self, execute_kwargs, tol):
"""Test scalar jacobian calculation"""
a = tf.Variable(0.1, dtype=tf.float64)
dev = qml.device("default.qubit", wires=2)
with tf.GradientTape() as t:
with qml.tape.JacobianTape() as tape:
qml.RY(a, wires=0)
qml.expval(qml.PauliZ(0))
res = execute([tape], dev, **execute_kwargs)[0]
res = t.jacobian(res, a)
assert res.shape == (1, )
# compare to standard tape jacobian
with qml.tape.JacobianTape() as tape:
qml.RY(a, wires=0)
qml.expval(qml.PauliZ(0))
tape.trainable_params = {0}
tapes, fn = param_shift(tape)
expected = fn(dev.batch_execute(tapes))
assert expected.shape == (1, 1)
assert np.allclose(res, np.squeeze(expected), atol=tol, rtol=0)
def test_scalar_jacobian(self, execute_kwargs, tol):
"""Test scalar jacobian calculation"""
a = np.array(0.1, requires_grad=True)
dev = qml.device("default.qubit", wires=2)
def cost(a):
with qml.tape.JacobianTape() as tape:
qml.RY(a, wires=0)
qml.expval(qml.PauliZ(0))
return execute([tape], dev, **execute_kwargs)[0]
res = qml.jacobian(cost)(a)
assert res.shape == (1, )
# compare to standard tape jacobian
with qml.tape.JacobianTape() as tape:
qml.RY(a, wires=0)
qml.expval(qml.PauliZ(0))
tape.trainable_params = {0}
tapes, fn = param_shift(tape)
expected = fn(dev.batch_execute(tapes))
assert expected.shape == (1, 1)
assert np.allclose(res, np.squeeze(expected), atol=tol, rtol=0)
def cost_fn(params):
with qml.tape.JacobianTape() as tape:
qml.RX(params[0], wires=[0])
RY(params[1], wires=[1])
qml.CNOT(wires=[0, 1])
qml.expval(qml.PauliZ(0))
qml.var(qml.PauliX(1))
tapes, fn = param_shift(tape,
fallback_fn=qml.gradients.finite_diff)
assert len(tapes) == 5
# check that the fallback method was called for the specified argnums
spy.assert_called()
assert spy.call_args[1]["argnum"] == {1}
return fn(dev.batch_execute(tapes))
def test_all_fallback(self, mocker, tol):
"""Test that *only* the fallback logic is called if no parameters
support the parameter-shift rule"""
spy_fd = mocker.spy(qml.gradients, "finite_diff")
spy_ps = mocker.spy(qml.gradients.parameter_shift,
"expval_param_shift")
dev = qml.device("default.qubit.autograd", wires=2)
x = 0.543
y = -0.654
params = np.array([x, y], requires_grad=True)
class RY(qml.RY):
grad_method = "F"
class RX(qml.RX):
grad_method = "F"
with qml.tape.JacobianTape() as tape:
RX(x, wires=[0])
RY(y, wires=[1])
qml.CNOT(wires=[0, 1])
qml.expval(qml.PauliZ(0) @ qml.PauliX(1))
tapes, fn = param_shift(tape, fallback_fn=qml.gradients.finite_diff)
assert len(tapes) == 1 + 2
# check that the fallback method was called for all argnums
spy_fd.assert_called()
spy_ps.assert_not_called()
res = fn(dev.batch_execute(tapes))
assert res.shape == (1, 2)
expected = np.array([[-np.sin(y) * np.sin(x), np.cos(y) * np.cos(x)]])
assert np.allclose(res, expected, atol=tol, rtol=0)