QNSPSA bugfix (#4421)

* qnspsa bugfix * Update doc/releases/changelog-dev.md * Update tests/optimize/test_qnspsa.py Co-authored-by: Matthew Silverman <[email protected]> --------- Co-authored-by: Matthew Silverman <[email protected]>
PennyLaneAI · Aug 2, 2023 · c6865ea · c6865ea
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diff --git a/doc/releases/changelog-dev.md b/doc/releases/changelog-dev.md
@@ -196,6 +196,9 @@
   `Tensor.sparse_matrix()`, it is recommended to use the `wire_order` keyword argument over `wires`. 
   [(#4424)](https://github.com/PennyLaneAI/pennylane/pull/4424)
 
+* Replace `op.adjoint` with `qml.adjoint` in `QNSPSAOptimizer`.
+  [(#4421)](https://github.com/PennyLaneAI/pennylane/pull/4421)
+
 * Replace deprecated `jax.ad` by `jax.interpreters.ad`.
   [(#4403)](https://github.com/PennyLaneAI/pennylane/pull/4403)
 

diff --git a/pennylane/optimize/qnspsa.py b/pennylane/optimize/qnspsa.py
@@ -408,7 +408,7 @@ def _get_overlap_tape(self, cost, args1, args2, kwargs):
         op_forward = self._get_operations(cost, args1, kwargs)
         op_inv = self._get_operations(cost, args2, kwargs)
 
-        new_ops = op_forward + [op.adjoint() for op in reversed(op_inv)]
+        new_ops = op_forward + [qml.adjoint(op) for op in reversed(op_inv)]
         return qml.tape.QuantumScript(new_ops, [qml.probs(wires=cost.tape.wires.labels)])
 
     @staticmethod

diff --git a/tests/optimize/test_qnspsa.py b/tests/optimize/test_qnspsa.py
@@ -418,3 +418,20 @@ def test_blocking(self, finite_diff_step, seed):
         # blocking should stop params from updating from this minimum
         new_params, _ = opt.step_and_cost(qnode, params)
         assert np.allclose(new_params, params)
+
+
+def test_template_no_adjoint():
+    """Test that qnspsa iterates when the operations do not have a custom adjoint."""
+
+    num_qubits = 2
+    dev = qml.device("default.qubit", wires=num_qubits)
+
+    @qml.qnode(dev)
+    def cost(params):
+        qml.RandomLayers(weights=params, wires=range(num_qubits), seed=42)
+        return qml.expval(qml.PauliZ(0) @ qml.PauliZ(1))
+
+    params = np.random.normal(0, np.pi, (2, 4))
+    opt = qml.QNSPSAOptimizer(stepsize=5e-2)
+    assert opt.step_and_cost(cost, params)  # just checking it runs without error
+    assert not qml.RandomLayers.has_adjoint