Fix TF tests.

pennylane/devices/qubit/apply_operation.py

@@ -403,14 +403,9 @@ def apply_pauliz(op: qml.Z, state, is_state_batched: bool = False, debugger=None
 def apply_phaseshift(op: qml.PhaseShift, state, is_state_batched: bool = False, debugger=None, **_):
  """Apply PhaseShift to state."""
 
- axis = op.wires[0] + is_state_batched
- n_dim = math.ndim(state)
-
- if n_dim >= 9 and math.get_interface(state) == "tensorflow":
- return apply_operation_tensordot(op, state, is_state_batched=is_state_batched)
-
- params = qml.math.atleast_1d(op.parameters[0])
+ params = op.parameters[0]
  if is_state_batched or (op.batch_size is not None and len(params) > 1):
+ params = math.atleast_1d(params)
  slices = []
  for i, p in enumerate(params):
  slices.append(
@@ -422,11 +417,17 @@ def apply_phaseshift(op: qml.PhaseShift, state, is_state_batched: bool = False,
  )
  return math.stack(slices, axis=0)
 
+ axis = op.wires[0] + is_state_batched
+ n_dim = math.ndim(state)
+
+ if n_dim >= 9 and math.get_interface(state) == "tensorflow":
+ return apply_operation_tensordot(op, state, is_state_batched=is_state_batched)
+
  sl_0 = _get_slice(0, axis, n_dim)
  sl_1 = _get_slice(1, axis, n_dim)
 
  # must be first state and then -1 because it breaks otherwise
- state1 = math.cast(state[sl_1], dtype=complex) * math.exp(1.0j * params)
+ state1 = math.multiply(state[sl_1], math.exp(1j * params))
  state = math.stack([state[sl_0], state1], axis=axis)
  if op.batch_size == 1:
  state = math.stack([state], axis=0)

tests/devices/qubit/test_apply_operation.py

@@ -802,7 +802,7 @@ def test_broadcasted_op(self, op, method, ml_framework):
  @pytest.mark.parametrize("op", unbroadcasted_ops)
  def test_broadcasted_state(self, op, method, ml_framework):
  """Tests that unbatched operations are applied correctly to a batched state."""
- state = np.ones((3, 2, 2, 2)) / np.sqrt(8)
+ state = np.ones((3, 2, 2, 2), dtype=complex) / np.sqrt(8)
 
  res = method(op, qml.math.asarray(state, like=ml_framework), is_state_batched=True)
  missing_wires = 3 - len(op.wires)
@@ -819,7 +819,7 @@ def test_broadcasted_op_broadcasted_state(self, op, method, ml_framework):
  if method is apply_operation_tensordot:
  pytest.skip("Tensordot doesn't support batched operator and batched state.")
 
- state = np.ones((3, 2, 2, 2)) / np.sqrt(8)
+ state = np.ones((3, 2, 2, 2), dtype=complex) / np.sqrt(8)
 
  res = method(op, qml.math.asarray(state, like=ml_framework), is_state_batched=True)
  missing_wires = 3 - len(op.wires)