Revert device gradients fix

doc/releases/changelog-dev.md

@@ -178,6 +178,9 @@
   instead of the controlled version of the diagonal unitary.
   [(#2525)](https://github.com/PennyLaneAI/pennylane/pull/2525)
 
+* Reverted device defined gradients fix [(#2485)](https://github.com/PennyLaneAI/pennylane/pull/2485), since
+  code change was breaking some devices. [(#2595)](https://github.com/PennyLaneAI/pennylane/pull/2595)
+
 <h3>Deprecations</h3>
 
 <h3>Documentation</h3>
@@ -197,5 +200,4 @@
 This release contains contributions from (in alphabetical order):
 
 Amintor Dusko, Chae-Yeun Park, Christian Gogolin, Christina Lee, David Wierichs, Edward Jiang, Guillermo Alonso-Linaje,
-Jay Soni, Juan Miguel Arrazola, Maria Schuld, Mikhail Andrenkov, Soran Jahangiri, Utkarsh Azad
-
+Jay Soni, Juan Miguel Arrazola, Maria Schuld, Mikhail Andrenkov, Samuel Banning, Soran Jahangiri, Utkarsh Azad

pennylane/interfaces/autograd.py

@@ -234,10 +234,9 @@ def grad_fn(dy):
         return_vjps = [
             qml.math.to_numpy(v, max_depth=_n) if isinstance(v, ArrayBox) else v for v in vjps
         ]
-        if device.capabilities().get("provides_jacobian", False):
-            # in the case where the device provides the jacobian,
-            # the output of grad_fn must be wrapped in a tuple in
-            # order to match the input parameters to _execute.
+        if device.short_name == "strawberryfields.gbs":
+            # TODO: remove this exceptional case once the source of this issue
+            # https://github.com/PennyLaneAI/pennylane-sf/issues/89 is determined
             return (return_vjps,)
         return return_vjps
 

tests/interfaces/test_autograd.py

@@ -1141,3 +1141,29 @@ def circuit(v):
 
         d_out = d_circuit(params)
         assert np.allclose(d_out, np.array([1.0, 2.0, 3.0, 4.0]))
+
+    def test_custom_jacobians_2(self):
+
+        class MyQubit(DefaultQubit):
+            @classmethod
+            def capabilities(cls):
+                capabilities = super().capabilities().copy()
+                capabilities.update(
+                    provides_jacobian=True,  # with this commented out everything works
+                )
+                return capabilities
+
+            def jacobian(self, *args, **kwargs):
+                raise NotImplementedError()
+
+        dev = MyQubit(wires=2)
+
+        @qml.qnode(dev, diff_method='parameter-shift', mode="backward")
+        def qnode(params):
+            qml.RY(params[0], wires=[0])
+            return qml.expval(qml.PauliZ(0))
+
+        params = np.array([0.2])
+
+        assert np.isclose(qnode(params), 0.9800665778412417)
+        assert np.isclose(qml.jacobian(qnode)(params), -0.19866933)