Make templates valid Pytrees

pennylane/templates/subroutines/amplitude_amplification.py

@@ -101,16 +101,12 @@ def circuit():
 
     def _flatten(self):
         data = (self.hyperparameters["U"], self.hyperparameters["O"])
-        metadata = tuple(
-            (key, value) for key, value in self.hyperparameters.items() if key not in ["O", "U"]
-        )
+        metadata = tuple(item for item in self.hyperparameters.items() if item[0] not in ["O", "U"])
         return data, metadata
 
     @classmethod
     def _unflatten(cls, data, metadata):
-        U, O = (data[0], data[1])
-        hyperparams_dict = dict(metadata)
-        return cls(U, O, **hyperparams_dict)
+        return cls(*data, **dict(metadata))
 
     def __init__(
         self, U, O, iters=1, fixed_point=False, work_wire=None, p_min=0.9, reflection_wires=None
@@ -169,6 +165,8 @@ def compute_decomposition(**kwargs):
         else:
             for _ in range(iters):
                 ops.append(O)
+                if qml.QueuingManager.recording():
+                    qml.apply(O)
                 ops.append(qml.Reflection(U, np.pi, reflection_wires=reflection_wires))
 
         return ops

pennylane/templates/subroutines/kupccgsd.py

@@ -205,11 +205,10 @@ def ansatz(weights):
     grad_method = None
 
     def _flatten(self):
-        hyperparameters = (
-            ("k", self.hyperparameters["k"]),
-            ("delta_sz", self.hyperparameters["delta_sz"]),
-            # tuple version of init_state is essentially identical, but is hashable
-            ("init_state", tuple(self.hyperparameters["init_state"])),
+
+        # Do not need to flatten s_wires or d_wires because they are derived hyperparameters
+        hyperparameters = tuple(
+            (key, self.hyperparameters[key]) for key in ["k", "delta_sz", "init_state"]
         )
         return self.data, (self.wires, hyperparameters)
 
@@ -242,7 +241,7 @@ def __init__(self, weights, wires, k=1, delta_sz=0, init_state=None, id=None):
             raise ValueError(f"Elements of 'init_state' must be integers; got {init_state.dtype}")
 
         self._hyperparameters = {
-            "init_state": init_state,
+            "init_state": tuple(init_state),
             "s_wires": s_wires,
             "d_wires": d_wires,
             "k": k,

pennylane/templates/subroutines/qdrift.py

@@ -144,6 +144,17 @@ def my_circ(time):
 
     """
 
+    def _flatten(self):
+        h = self.hyperparameters["base"]
+        hashable_hyperparameters = tuple(
+            item for item in self.hyperparameters.items() if item[0] != "base"
+        )
+        return (h, self.data[-1]), hashable_hyperparameters
+
+    @classmethod
+    def _unflatten(cls, data, metadata):
+        return cls(*data, **dict(metadata))
+
     def __init__(  # pylint: disable=too-many-arguments
         self, hamiltonian, time, n=1, seed=None, decomposition=None, id=None
     ):
@@ -178,7 +189,7 @@ def __init__(  # pylint: disable=too-many-arguments
                 "coefficients of the input Hamiltonian."
             )
 
-        if decomposition is None:  # need to do this to allow flatten and _unflatten
+        if decomposition is None:  # need to do this to allow flatten and unflatten
             unwrapped_coeffs = unwrap(coeffs)
             decomposition = _sample_decomposition(unwrapped_coeffs, ops, time, n=n, seed=seed)
 
@@ -188,42 +199,13 @@ def __init__(  # pylint: disable=too-many-arguments
             "base": hamiltonian,
             "decomposition": decomposition,
         }
-        super().__init__(time, wires=hamiltonian.wires, id=id)
+        super().__init__(*hamiltonian.data, time, wires=hamiltonian.wires, id=id)
 
     def queue(self, context=qml.QueuingManager):
         context.remove(self.hyperparameters["base"])
         context.append(self)
         return self
 
-    @classmethod
-    def _unflatten(cls, data, metadata):
-        """Recreate an operation from its serialized format.
-
-        Args:
-            data: the trainable component of the operation
-            metadata: the non-trainable component of the operation
-
-        The output of ``Operator._flatten`` and the class type must be sufficient to reconstruct the original
-        operation with ``Operator._unflatten``.
-
-        **Example:**
-
-        >>> op = qml.Rot(1.2, 2.3, 3.4, wires=0)
-        >>> op._flatten()
-        ((1.2, 2.3, 3.4), (<Wires = [0]>, ()))
-        >>> qml.Rot._unflatten(*op._flatten())
-        >>> op = qml.PauliRot(1.2, "XY", wires=(0,1))
-        >>> op._flatten()
-        ((1.2,), (<Wires = [0, 1]>, (('pauli_word', 'XY'),)))
-        >>> op = qml.ctrl(qml.U2(3.4, 4.5, wires="a"), ("b", "c") )
-        >>> type(op)._unflatten(*op._flatten())
-        Controlled(U2(3.4, 4.5, wires=['a']), control_wires=['b', 'c'])
-
-        """
-        hyperparameters_dict = dict(metadata[1])
-        hamiltonian = hyperparameters_dict.pop("base")
-        return cls(hamiltonian, *data, **hyperparameters_dict)
-
     @staticmethod
     def compute_decomposition(*args, **kwargs):  # pylint: disable=unused-argument
         r"""Representation of the operator as a product of other operators (static method).

pennylane/templates/subroutines/qmc.py

@@ -363,8 +363,8 @@ def __init__(self, probs, func, target_wires, estimation_wires, id=None):
                 "The probability distribution must have a length that is a power of two"
             )
 
-        target_wires = list(target_wires)
-        estimation_wires = list(estimation_wires)
+        target_wires = tuple(target_wires)
+        estimation_wires = tuple(estimation_wires)
         wires = target_wires + estimation_wires
 
         if num_target_wires != len(target_wires):

pennylane/templates/subroutines/qpe.py

@@ -15,10 +15,13 @@
 Contains the QuantumPhaseEstimation template.
 """
 # pylint: disable=too-many-arguments,arguments-differ
+import copy
+
 import pennylane as qml
 from pennylane.operation import AnyWires, Operator
 from pennylane.queuing import QueuingManager
 from pennylane.resource.error import ErrorOperation, SpectralNormError
+from pennylane.wires import Wires
 
 
 class QuantumPhaseEstimation(ErrorOperation):
@@ -232,17 +235,16 @@ def error(self):
 
     # pylint: disable=protected-access
     def map_wires(self, wire_map: dict):
-        new_op = super().map_wires(wire_map)
+        new_op = copy.deepcopy(self)
+        new_op._wires = Wires([wire_map.get(wire, wire) for wire in self.wires])
         new_op._hyperparameters["unitary"] = qml.map_wires(
             new_op._hyperparameters["unitary"], wire_map
         )
 
-        new_op._hyperparameters["estimation_wires"] = [
-            wire_map.get(wire, wire) for wire in self.estimation_wires
-        ]
-        new_op._hyperparameters["target_wires"] = [
-            wire_map.get(wire, wire) for wire in self.target_wires
-        ]
+        for key in ["estimation_wires", "target_wires"]:
+            new_op._hyperparameters[key] = [
+                wire_map.get(wire, wire) for wire in self.hyperparameters[key]
+            ]
 
         return new_op
 

pennylane/templates/subroutines/qubitization.py

@@ -103,16 +103,12 @@ def __init__(self, hamiltonian, control, id=None):
 
     def _flatten(self):
         data = (self.hyperparameters["hamiltonian"],)
-        metadata = tuple(
-            (key, value) for key, value in self.hyperparameters.items() if key != "hamiltonian"
-        )
+        metadata = tuple(item for item in self.hyperparameters.items() if item[0] != "hamiltonian")
         return data, metadata
 
     @classmethod
     def _unflatten(cls, data, metadata):
-        hamiltonian = data[0]
-        hyperparams_dict = dict(metadata)
-        return cls(hamiltonian, **hyperparams_dict)
+        return cls(*data, **dict(metadata))
 
     def __copy__(self):
 

pennylane/templates/subroutines/reflection.py

@@ -40,7 +40,8 @@ class Reflection(Operation):
     Args:
         U (Operator): the operator that prepares the state :math:`|\Psi\rangle`
         alpha (float): the angle of the operator, default is :math:`\pi`
-        reflection_wires (Any or Iterable[Any]): subsystem of wires on which to reflect, the default is ``None`` and the reflection will be applied on the ``U`` wires
+        reflection_wires (Any or Iterable[Any]): subsystem of wires on which to reflect, the
+            default is ``None`` and the reflection will be applied on the ``U`` wires.
 
     **Example**
 
@@ -103,12 +104,11 @@ def circuit():
 
     def _flatten(self):
         data = (self.hyperparameters["base"], self.parameters[0])
-        metadata = tuple(value for key, value in self.hyperparameters.items() if key != "base")
-        return data, metadata
+        return data, (self.hyperparameters["reflection_wires"],)
 
     @classmethod
     def _unflatten(cls, data, metadata):
-        U, alpha = (data[0], data[1])
+        U, alpha = data
         return cls(U, alpha=alpha, reflection_wires=metadata[0])
 
     def __init__(self, U, alpha=np.pi, reflection_wires=None, id=None):
@@ -123,7 +123,7 @@ def __init__(self, U, alpha=np.pi, reflection_wires=None, id=None):
 
         self._hyperparameters = {
             "base": U,
-            "reflection_wires": reflection_wires,
+            "reflection_wires": tuple(reflection_wires),
         }
 
         super().__init__(alpha, wires=wires, id=id)

pennylane/templates/subroutines/trotter.py

@@ -235,7 +235,7 @@ def __init__(  # pylint: disable=too-many-arguments
             "check_hermitian": check_hermitian,
         }
 
-        super().__init__(time, wires=hamiltonian.wires, id=id)
+        super().__init__(*hamiltonian.data, time, wires=hamiltonian.wires, id=id)
 
     def queue(self, context=qml.QueuingManager):
         context.remove(self.hyperparameters["base"])
@@ -288,7 +288,7 @@ def error(
             SpectralNormError: The spectral norm error.
         """
         base_unitary = self.hyperparameters["base"]
-        t, p, n = (self.parameters[0], self.hyperparameters["order"], self.hyperparameters["n"])
+        t, p, n = (self.parameters[-1], self.hyperparameters["order"], self.hyperparameters["n"])
 
         parameters = [t] + base_unitary.parameters
         if any(
@@ -343,10 +343,10 @@ def _flatten(self):
         (<Wires = ['b', 'c']>, (True, True), <Wires = []>))
         """
         hamiltonian = self.hyperparameters["base"]
-        time = self.parameters[0]
+        time = self.data[-1]
 
         hashable_hyperparameters = tuple(
-            (key, value) for key, value in self.hyperparameters.items() if key != "base"
+            item for item in self.hyperparameters.items() if item[0] != "base"
         )
         return (hamiltonian, time), hashable_hyperparameters
 
@@ -375,8 +375,7 @@ def _unflatten(cls, data, metadata):
         Controlled(U2(3.4, 4.5, wires=['a']), control_wires=['b', 'c'])
 
         """
-        hyperparameters_dict = dict(metadata)
-        return cls(*data, **hyperparameters_dict)
+        return cls(*data, **dict(metadata))
 
     @staticmethod
     def compute_decomposition(*args, **kwargs):
@@ -399,7 +398,7 @@ def compute_decomposition(*args, **kwargs):
         Returns:
             list[Operator]: decomposition of the operator
         """
-        time = args[0]
+        time = args[-1]
         n = kwargs["n"]
         order = kwargs["order"]
         ops = kwargs["base"].operands

pennylane/templates/subroutines/uccsd.py

@@ -191,7 +191,11 @@ def __init__(self, weights, wires, s_wires=None, d_wires=None, init_state=None,
         if init_state.dtype != np.dtype("int"):
             raise ValueError(f"Elements of 'init_state' must be integers; got {init_state.dtype}")
 
-        self._hyperparameters = {"init_state": init_state, "s_wires": s_wires, "d_wires": d_wires}
+        self._hyperparameters = {
+            "init_state": tuple(init_state),
+            "s_wires": tuple(tuple(w) for w in s_wires),
+            "d_wires": tuple(tuple(tuple(w) for w in dw) for dw in d_wires),
+        }
 
         super().__init__(weights, wires=wires, id=id)
 

tests/templates/test_subroutines/test_amplitude_amplification.py

@@ -64,6 +64,13 @@ def test_error_wrong_work_wire(self, wires, fixed_point, work_wire):
         with pytest.raises(ValueError, match="work_wire must be different from the wires of O."):
             qml.AmplitudeAmplification(U, O, iters=3, fixed_point=fixed_point, work_wire=work_wire)
 
+    def test_standard_validity(self):
+        """Test standard validity using assert_valid."""
+        U = generator(wires=range(3))
+        O = oracle([0, 2], wires=range(3))
+        op = qml.AmplitudeAmplification(U, O, iters=3, fixed_point=False)
+        qml.ops.functions.assert_valid(op)
+
 
 @pytest.mark.parametrize(
     "n_wires, items, iters",
@@ -257,23 +264,6 @@ def circuit3():
     assert np.allclose(circuit1(), circuit3())
 
 
-# pylint: disable=protected-access
-def test_flatten_and_unflatten():
-    """Test the _flatten and _unflatten methods for AmplitudeAmplification."""
-
-    op = qml.AmplitudeAmplification(qml.RX(0.25, wires=0), qml.PauliZ(0))
-    data, metadata = op._flatten()
-
-    assert len(data) == 2
-    assert len(metadata) == 5
-
-    new_op = type(op)._unflatten(*op._flatten())
-    assert qml.equal(op, new_op)
-    assert op is not new_op
-
-    assert hash(metadata)
-
-
 def test_amplification():
     """Test that AmplitudeAmplification amplifies a marked element."""
 

tests/templates/test_subroutines/test_approx_time_evolution.py

@@ -29,25 +29,6 @@ def test_standard_validity():
     qml.ops.functions.assert_valid(op)
 
 
-# pylint: disable=protected-access
-def test_flatten_unflatten():
-    """Tests the _flatten and _unflatten methods."""
-    H = 2.0 * qml.PauliX(0) + 3.0 * qml.PauliY(0)
-    t = 0.1
-    op = qml.ApproxTimeEvolution(H, t, n=20)
-    data, metadata = op._flatten()
-    assert data[0] is H
-    assert data[1] == t
-    assert metadata == (20,)
-
-    # check metadata hashable
-    assert hash(metadata)
-
-    new_op = type(op)._unflatten(*op._flatten())
-    assert qml.equal(op, new_op)
-    assert new_op is not op
-
-
 def test_queuing():
     """Test that ApproxTimeEvolution de-queues the input hamiltonian."""
 

tests/templates/test_subroutines/test_commuting_evolution.py

@@ -32,28 +32,6 @@ def test_standard_validity():
     qml.ops.functions.assert_valid(op)
 
 
-# pylint: disable=protected-access
-def test_flatten_unflatten():
-    """Unit tests for the flatten and unflatten methods."""
-    H = 2.0 * qml.PauliX(0) @ qml.PauliY(1) + 3.0 * qml.PauliY(0) @ qml.PauliZ(1)
-    time = 0.5
-    frequencies = (2, 4)
-    shifts = (1, 0.5)
-    op = qml.CommutingEvolution(H, time, frequencies=frequencies, shifts=shifts)
-    data, metadata = op._flatten()
-
-    assert hash(metadata)
-
-    assert len(data) == 2
-    assert data[1] is H
-    assert data[0] == time
-    assert metadata == (frequencies, shifts)
-
-    new_op = type(op)._unflatten(*op._flatten())
-    assert qml.equal(op, new_op)
-    assert op is not new_op
-
-
 def test_adjoint():
     """Tests the CommutingEvolution.adjoint method provides the correct adjoint operation."""