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@@ -152,7 +152,7 @@ def _const_mul(constant, array): | |
| "Identity", | ||
| "Projector", | ||
| "Sum", | ||
| "Sprod", | ||
| "SProd", | ||
| "Prod", | ||
| } | ||
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| Original file line number | Diff line number | Diff line change |
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| @@ -0,0 +1,201 @@ | ||
| # Copyright 2024 Xanadu Quantum Technologies Inc. | ||
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| # Licensed under the Apache License, Version 2.0 (the "License"); | ||
| # you may not use this file except in compliance with the License. | ||
| # You may obtain a copy of the License at | ||
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| # http://www.apache.org/licenses/LICENSE-2.0 | ||
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| # Unless required by applicable law or agreed to in writing, software | ||
| # distributed under the License is distributed on an "AS IS" BASIS, | ||
| # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | ||
| # See the License for the specific language governing permissions and | ||
| # limitations under the License. | ||
| """Tests trainable circuits using the Autograd interface.""" | ||
| # pylint:disable=no-self-use | ||
| import pytest | ||
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| import numpy as np | ||
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| import pennylane as qml | ||
| from pennylane import numpy as pnp | ||
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| @pytest.mark.usefixtures("validate_diff_method") | ||
| @pytest.mark.parametrize("diff_method", ["backprop", "parameter-shift", "hadamard"]) | ||
| class TestGradients: | ||
| """Test various gradient computations.""" | ||
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| def test_basic_grad(self, diff_method, device, tol): | ||
| """Test a basic function with one RX and one expectation.""" | ||
| wires = 2 if diff_method == "hadamard" else 1 | ||
| dev = device(wires=wires) | ||
| tol = tol(dev.shots) | ||
| if diff_method == "hadamard": | ||
| tol += 0.01 | ||
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| @qml.qnode(dev, diff_method=diff_method) | ||
| def circuit(x): | ||
| qml.RX(x, 0) | ||
| return qml.expval(qml.Z(0)) | ||
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| x = pnp.array(0.5) | ||
| res = qml.grad(circuit)(x) | ||
| assert np.isclose(res, -pnp.sin(x), atol=tol, rtol=0) | ||
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| def test_backprop_state(self, diff_method, device, tol): | ||
| """Test the trainability of parameters in a circuit returning the state.""" | ||
| if diff_method != "backprop": | ||
| pytest.skip(reason="test only works with backprop") | ||
| dev = device(2) | ||
| if dev.shots: | ||
| pytest.skip("test uses backprop, must be in analytic mode") | ||
| if "mixed" in dev.name: | ||
| pytest.skip("mixed-state simulator will wrongly use grad on non-scalar results") | ||
| tol = tol(dev.shots) | ||
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| x = pnp.array(0.543) | ||
| y = pnp.array(-0.654) | ||
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| @qml.qnode(dev, diff_method=diff_method, grad_on_execution=True) | ||
| def circuit(x, y): | ||
| qml.RX(x, wires=[0]) | ||
| qml.RY(y, wires=[1]) | ||
| qml.CNOT(wires=[0, 1]) | ||
| return qml.state() | ||
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| def cost_fn(x, y): | ||
| res = circuit(x, y) | ||
| probs = pnp.abs(res) ** 2 | ||
| return probs[0] + probs[2] | ||
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| res = qml.grad(cost_fn)(x, y) | ||
| expected = np.array([-np.sin(x) * np.cos(y) / 2, -np.cos(x) * np.sin(y) / 2]) | ||
| assert np.allclose(res, expected, atol=tol, rtol=0) | ||
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| y = pnp.array(-0.654, requires_grad=False) | ||
| res = qml.grad(cost_fn)(x, y) | ||
| assert np.allclose(res, expected[0], atol=tol, rtol=0) | ||
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| def test_parameter_shift(self, diff_method, device, tol): | ||
| """Test a multi-parameter circuit with parameter-shift.""" | ||
| if diff_method != "parameter-shift": | ||
| pytest.skip(reason="test only works with parameter-shift") | ||
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| a = pnp.array(0.1) | ||
| b = pnp.array(0.2) | ||
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| dev = device(2) | ||
| tol = tol(dev.shots) | ||
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| @qml.qnode(dev, diff_method="parameter-shift", grad_on_execution=False) | ||
| def circuit(a, b): | ||
| qml.RY(a, wires=0) | ||
| qml.RX(b, wires=1) | ||
| qml.CNOT(wires=[0, 1]) | ||
| return qml.expval(qml.Hamiltonian([1, 1], [qml.Z(0), qml.Y(1)])) | ||
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| res = qml.grad(circuit)(a, b) | ||
| expected = [-np.sin(a) + np.sin(a) * np.sin(b), -np.cos(a) * np.cos(b)] | ||
| assert np.allclose(res, expected, atol=tol, rtol=0) | ||
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| # make the second QNode argument a constant | ||
| b = pnp.array(0.2, requires_grad=False) | ||
| res = qml.grad(circuit)(a, b) | ||
| assert np.allclose(res, expected[0], atol=tol, rtol=0) | ||
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| def test_probs(self, diff_method, device, tol): | ||
| """Test differentiation of a circuit returning probs().""" | ||
| wires = 3 if diff_method == "hadamard" else 2 | ||
| dev = device(wires=wires) | ||
| tol = tol(dev.shots) | ||
| x = pnp.array(0.543) | ||
| y = pnp.array(-0.654) | ||
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| @qml.qnode(dev, diff_method=diff_method) | ||
| def circuit(x, y): | ||
| qml.RX(x, wires=[0]) | ||
| qml.RY(y, wires=[1]) | ||
| qml.CNOT(wires=[0, 1]) | ||
| return qml.probs(wires=[1]) | ||
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| res = qml.jacobian(circuit)(x, y) | ||
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| expected = np.array( | ||
| [ | ||
| [-np.sin(x) * np.cos(y) / 2, -np.cos(x) * np.sin(y) / 2], | ||
| [np.cos(y) * np.sin(x) / 2, np.cos(x) * np.sin(y) / 2], | ||
| ] | ||
| ) | ||
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| assert isinstance(res, tuple) | ||
| assert len(res) == 2 | ||
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| assert isinstance(res[0], pnp.ndarray) | ||
| assert res[0].shape == (2,) | ||
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| assert isinstance(res[1], pnp.ndarray) | ||
| assert res[1].shape == (2,) | ||
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| if diff_method == "hadamard" and "raket" in dev.name: | ||
| pytest.xfail(reason="braket gets wrong results for hadamard here") | ||
| assert np.allclose(res[0], expected.T[0], atol=tol, rtol=0) | ||
| assert np.allclose(res[1], expected.T[1], atol=tol, rtol=0) | ||
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| def test_multi_meas(self, diff_method, device, tol): | ||
| """Test differentiation of a circuit with both scalar and array-like returns.""" | ||
| wires = 3 if diff_method == "hadamard" else 2 | ||
| dev = device(wires=wires) | ||
| tol = tol(dev.shots) | ||
| x = pnp.array(0.543) | ||
| y = pnp.array(-0.654, requires_grad=False) | ||
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| @qml.qnode(dev, diff_method=diff_method) | ||
| def circuit(x, y): | ||
| qml.RX(x, wires=[0]) | ||
| qml.RY(y, wires=[1]) | ||
| qml.CNOT(wires=[0, 1]) | ||
| return qml.expval(qml.Z(0)), qml.probs(wires=[1]) | ||
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| def cost_fn(x, y): | ||
| return pnp.hstack(circuit(x, y)) | ||
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| jac = qml.jacobian(cost_fn)(x, y) | ||
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| expected = [-np.sin(x), -np.sin(x) * np.cos(y) / 2, np.cos(y) * np.sin(x) / 2] | ||
| assert isinstance(jac, pnp.ndarray) | ||
| assert np.allclose(jac, expected, atol=tol, rtol=0) | ||
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| def test_hessian(self, diff_method, device, tol): | ||
| """Test hessian computation.""" | ||
| wires = 3 if diff_method == "hadamard" else 1 | ||
| dev = device(wires=wires) | ||
| tol = tol(dev.shots) | ||
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| @qml.qnode(dev, diff_method=diff_method, max_diff=2) | ||
| def circuit(x): | ||
| qml.RY(x[0], wires=0) | ||
| qml.RX(x[1], wires=0) | ||
| return qml.expval(qml.Z(0)) | ||
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| x = pnp.array([1.0, 2.0]) | ||
| res = circuit(x) | ||
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| a, b = x | ||
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| expected_res = np.cos(a) * np.cos(b) | ||
| assert np.allclose(res, expected_res, atol=tol, rtol=0) | ||
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| grad_fn = qml.grad(circuit) | ||
| g = grad_fn(x) | ||
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| expected_g = [-np.sin(a) * np.cos(b), -np.cos(a) * np.sin(b)] | ||
| assert np.allclose(g, expected_g, atol=tol, rtol=0) | ||
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| hess = qml.jacobian(grad_fn)(x) | ||
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| expected_hess = [ | ||
| [-np.cos(a) * np.cos(b), np.sin(a) * np.sin(b)], | ||
| [np.sin(a) * np.sin(b), -np.cos(a) * np.cos(b)], | ||
| ] | ||
| assert np.allclose(hess, expected_hess, atol=tol, rtol=0) |
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