black

pennylane/devices/qubit/apply_operation.py

@@ -264,30 +264,41 @@ def apply_cnot(op: qml.CNOT, state, is_state_batched: bool = False, debugger=Non
 
 
 @apply_operation.register
-def apply_multicontrolledx(op: qml.MultiControlledX, state, is_state_batched: bool = False, debugger=None):
+def apply_multicontrolledx(
+    op: qml.MultiControlledX, state, is_state_batched: bool = False, debugger=None
+):
     r"""Apply MultiControlledX to state by composing transpositions, rolling of control axes
     and the CNOT logic above."""
     if len(op.wires) < 8:
         return apply_operation_einsum(op, state, is_state_batched)
 
     ctrl_wires = [w + is_state_batched for w in op.hyperparameters["control_wires"]]
     # apply x on all "wrong" controls
-    roll_axes = [w for val, w in zip(op.hyperparameters["control_values"], ctrl_wires) if val=="0"]
+    roll_axes = [
+        w for val, w in zip(op.hyperparameters["control_values"], ctrl_wires) if val == "0"
+    ]
     state = math.roll(state, 1, roll_axes)
 
     orig_shape = math.shape(state)
     # Move the axes into the order [(batch), other, target, controls]
-    transpose_axes = np.array([w for w in range(len(orig_shape)) if w not in op.wires] + [op.total_wires[-1]] + op.total_wires[:-1].tolist()) + is_state_batched
-    #transpose_axes =  + is_state_batched for w in transpose_axes]
+    transpose_axes = (
+        np.array(
+            [w for w in range(len(orig_shape)) if w not in op.wires]
+            + [op.total_wires[-1]]
+            + op.total_wires[:-1].tolist()
+        )
+        + is_state_batched
+    )
+    # transpose_axes =  + is_state_batched for w in transpose_axes]
     state = math.transpose(state, transpose_axes)
 
     # Reshape the state into 3-dimensional array with axes [batch+other, target, controls]
-    state = state.reshape((-1, 2, 2**(len(op.wires)-1)))
+    state = state.reshape((-1, 2, 2 ** (len(op.wires) - 1)))
 
     # The part of the state to which we want to apply PauliX is now in the last entry along
     # the third axis. Extract it, apply the PauliX along the target axis, and append a dummy axis
     state_x = math.roll(state[:, :, -1], 1, 1)[:, :, np.newaxis]
-    
+
     # Stack the transformed part of the state with the unmodified rest of the state
     state = math.concatenate([state[:, :, :-1], state_x], axis=2)
 
@@ -297,6 +308,7 @@ def apply_multicontrolledx(op: qml.MultiControlledX, state, is_state_batched: bo
     # revert x on all "wrong" controls
     return math.roll(state, 1, roll_axes)
 
+
 @apply_operation.register
 def apply_grover(op: qml.GroverOperator, state, is_state_batched: bool = False, debugger=None):
     r"""Apply GroverOperator to state. This method uses that this operator

tests/devices/qubit/test_apply_operation.py

@@ -831,6 +831,7 @@ def test_double_excitation(self, method):
 
         assert qml.math.allclose(state_v1, state_v2)
 
+
 @pytest.mark.parametrize("num_wires, einsum_called", [(3, True), (8, False)])
 def test_multicontrolledx_dispatching(num_wires, einsum_called, mocker):
     """Test that apply_multicontrolledx dispatches to einsum for small numbers of wires."""