Deprecating Legacy Devices

pennylane/devices/default_qubit_autograd.py

@@ -14,6 +14,9 @@
 """This module contains an autograd implementation of the :class:`~.DefaultQubitLegacy`
 reference plugin.
 """
+import warnings
+
+from pennylane import PennyLaneDeprecationWarning
 from pennylane import numpy as pnp
 from pennylane.devices import DefaultQubitLegacy
 
@@ -34,6 +37,9 @@ class DefaultQubitAutograd(DefaultQubitLegacy):
 
  pip install autograd
 
+ .. warning::
+ This device is deprecated. Use :class:`~.devices.DefaultQubit` instead; for example through ``qml.device("default.qubit")``.
+
  **Example**
 
  The ``default.qubit.autograd`` is designed to be used with end-to-end classical backpropagation
@@ -104,6 +110,13 @@ def _const_mul(constant, array):
  return constant * array
 
  def __init__(self, wires, *, shots=None, analytic=None):
+ warnings.warn(
+ f"Use of '{self.short_name}' is deprecated. Instead, use 'default.qubit'. "
+ "If you experience issues, reach out to the PennyLane team on "
+ "the discussion forum: https://discuss.pennylane.ai/",
+ PennyLaneDeprecationWarning,
+ )
+
  r_dtype = pnp.float64
  c_dtype = pnp.complex128
  super().__init__(wires, shots=shots, r_dtype=r_dtype, c_dtype=c_dtype, analytic=analytic)

pennylane/devices/default_qubit_jax.py

@@ -14,6 +14,8 @@
 """This module contains a jax implementation of the :class:`~.DefaultQubitLegacy`
 reference plugin.
 """
+import warnings
+
 # pylint: disable=ungrouped-imports
 import numpy as np
 
@@ -49,6 +51,9 @@ class DefaultQubitJax(DefaultQubitLegacy):
 
  pip install jax jaxlib
 
+ .. warning::
+ This device is deprecated. Use :class:`~.devices.DefaultQubit` instead; for example through ``qml.device("default.qubit")``.
+
  **Example**
 
  The ``default.qubit.jax`` device is designed to be used with end-to-end classical backpropagation
@@ -165,6 +170,13 @@ def circuit():
  operations = DefaultQubitLegacy.operations.union({"ParametrizedEvolution"})
 
  def __init__(self, wires, *, shots=None, prng_key=None, analytic=None):
+ warnings.warn(
+ f"Use of '{self.short_name}' is deprecated. Instead, use 'default.qubit'. "
+ "If you experience issues, reach out to the PennyLane team on "
+ "the discussion forum: https://discuss.pennylane.ai/",
+ qml.PennyLaneDeprecationWarning,
+ )
+
  if jax.config.read("jax_enable_x64"):
  c_dtype = jnp.complex128
  r_dtype = jnp.float64

pennylane/devices/default_qubit_legacy.py

@@ -20,6 +20,7 @@
 """
 import functools
 import itertools
+import warnings
 from string import ascii_letters as ABC
 from typing import List
 
@@ -82,8 +83,8 @@ class DefaultQubitLegacy(QubitDevice):
 
  .. warning::
 
- This is the legacy implementation of DefaultQubit. It has been replaced by
- ``qml.devices.DefaultQubit``, which can be accessed with the familiar constructor,
+ This is the legacy implementation of DefaultQubit and is deprecated. It has been replaced by
+ :class:`~.devices.DefaultQubit`, which can be accessed with the familiar constructor,
  ``qml.device("default.qubit")``.
 
  This change will not alter device behaviour for most workflows, but may have implications for
@@ -207,6 +208,13 @@ class DefaultQubitLegacy(QubitDevice):
  def __init__(
  self, wires, *, r_dtype=np.float64, c_dtype=np.complex128, shots=None, analytic=None
  ):
+ warnings.warn(
+ f"Use of '{self.short_name}' is deprecated. Instead, use 'default.qubit'. "
+ "If you experience issues, reach out to the PennyLane team on "
+ "the discussion forum: https://discuss.pennylane.ai/",
+ qml.PennyLaneDeprecationWarning,
+ )
+
  super().__init__(wires, shots, r_dtype=r_dtype, c_dtype=c_dtype, analytic=analytic)
  self._debugger = None
 

pennylane/devices/default_qubit_tf.py

@@ -15,6 +15,7 @@
 reference plugin.
 """
 import itertools
+import warnings
 
 import numpy as np
 from packaging.version import Version
@@ -42,7 +43,7 @@
 
 
 class DefaultQubitTF(DefaultQubitLegacy):
- """Simulator plugin based on ``"default.qubit.legacy"``, written using TensorFlow.
+ r"""Simulator plugin based on ``"default.qubit.legacy"``, written using TensorFlow.
 
  **Short name:** ``default.qubit.tf``
 
@@ -57,6 +58,9 @@ class DefaultQubitTF(DefaultQubitLegacy):
 
  pip install tensorflow>=2.0
 
+ .. warning::
+ This device is deprecated. Use :class:`~.devices.DefaultQubit` instead; for example through ``qml.device("default.qubit")``.
+
  **Example**
 
  The ``default.qubit.tf`` is designed to be used with end-to-end classical backpropagation
@@ -162,6 +166,13 @@ def _asarray(array, dtype=None):
  return res
 
  def __init__(self, wires, *, shots=None, analytic=None):
+ warnings.warn(
+ f"Use of '{self.short_name}' is deprecated. Instead, use 'default.qubit'. "
+ "If you experience issues, reach out to the PennyLane team on "
+ "the discussion forum: https://discuss.pennylane.ai/",
+ qml.PennyLaneDeprecationWarning,
+ )
+
  r_dtype = tf.float64
  c_dtype = tf.complex128
 

pennylane/devices/default_qubit_torch.py

@@ -34,6 +34,7 @@
 
 import numpy as np
 
+from pennylane import PennyLaneDeprecationWarning
 from pennylane.ops.qubit.attributes import diagonal_in_z_basis
 
 from . import DefaultQubitLegacy
@@ -43,7 +44,7 @@
 
 
 class DefaultQubitTorch(DefaultQubitLegacy):
- """Simulator plugin based on ``"default.qubit.legacy"``, written using PyTorch.
+ r"""Simulator plugin based on ``"default.qubit.legacy"``, written using PyTorch.
 
  **Short name:** ``default.qubit.torch``
 
@@ -58,6 +59,10 @@ class DefaultQubitTorch(DefaultQubitLegacy):
 
  pip install torch>=1.8.0
 
+ .. warning::
+ This device is deprecated. Use :class:`~.devices.DefaultQubit` instead; for example through ``qml.device("default.qubit")``.
+
+
  **Example**
 
  The ``default.qubit.torch`` is designed to be used with end-to-end classical backpropagation
@@ -165,6 +170,12 @@ def circuit(x):
  _ndim = staticmethod(lambda tensor: tensor.ndim)
 
  def __init__(self, wires, *, shots=None, analytic=None, torch_device=None):
+ warnings.warn(
+ f"Use of '{self.short_name}' is deprecated. Instead, use 'default.qubit'. "
+ "If you experience issues, reach out to the PennyLane team on "
+ "the discussion forum: https://discuss.pennylane.ai/",
+ PennyLaneDeprecationWarning,
+ )
  # Store if the user specified a Torch device. Otherwise the execute
  # method attempts to infer the Torch device from the gate parameters.
  self._torch_device_specified = torch_device is not None

tests/conftest.py

@@ -49,6 +49,17 @@ def set_numpy_seed():
  yield
 
 
+@pytest.fixture(scope="function", autouse=True)
+def capture_legacy_device_deprecation_warnings(recwarn):
+ yield
+
+ for w in recwarn:
+ if isinstance(w.message, qml.PennyLaneDeprecationWarning):
+ assert "Use of 'default.qubit." in str(w.message)
+ assert "is deprecated" in str(w.message)
+ assert "use 'default.qubit'" in str(w.message)
+
+
 @pytest.fixture(scope="session")
 def tol():
  """Numerical tolerance for equality tests."""

tests/devices/test_default_qubit_legacy.py

@@ -2001,7 +2001,8 @@ class TestApplyOps:
  gates in DefaultQubitLegacy."""
 
  state = np.arange(2**4, dtype=np.complex128).reshape((2, 2, 2, 2))
- dev = qml.device("default.qubit.legacy", wires=4)
+ with pytest.warns(qml.PennyLaneDeprecationWarning):
+ dev = qml.device("default.qubit.legacy", wires=4)
 
  single_qubit_ops = [
  (qml.PauliX, dev._apply_x),

tests/devices/test_default_qubit_legacy_broadcasting.py

@@ -1619,7 +1619,8 @@ class TestApplyOpsBroadcasted:
  gates in DefaultQubitLegacy."""
 
  broadcasted_state = np.arange(2**4 * 3, dtype=np.complex128).reshape((3, 2, 2, 2, 2))
- dev = qml.device("default.qubit.legacy", wires=4)
+ with pytest.warns(qml.PennyLaneDeprecationWarning):
+ dev = qml.device("default.qubit.legacy", wires=4)
 
  single_qubit_ops = [
  (qml.PauliX, dev._apply_x),

tests/drawer/test_draw.py

@@ -878,13 +878,11 @@ def circ():
 
 
 class TestLevelExpansionStrategy:
- @pytest.fixture(
- params=[qml.device("default.qubit.legacy", wires=3), qml.devices.DefaultQubit()],
- )
- def transforms_circuit(self, request):
+ @pytest.fixture
+ def transforms_circuit(self):
  @qml.transforms.merge_rotations
  @qml.transforms.cancel_inverses
- @qml.qnode(request.param, diff_method="parameter-shift")
+ @qml.qnode(qml.device("default.qubit"), diff_method="parameter-shift")
  def circ(weights, order):
  qml.RandomLayers(weights, wires=(0, 1))
  qml.Permute(order, wires=(0, 1, 2))
@@ -1015,11 +1013,7 @@ def circ():
  assert draw(circ)() == expected
 
 
-@pytest.mark.parametrize(
- "device",
- [qml.device("default.qubit.legacy", wires=2), qml.device("default.qubit", wires=2)],
-)
-def test_applied_transforms(device):
+def test_applied_transforms():
  """Test that any transforms applied to the qnode are included in the output."""
 
  @qml.transform
@@ -1028,7 +1022,7 @@ def just_pauli_x(_):
  return (new_tape,), lambda res: res[0]
 
  @just_pauli_x
- @qml.qnode(device)
+ @qml.qnode(qml.device("default.qubit", wires=2))
  def my_circuit(x):
  qml.RX(x, wires=0)
  qml.SWAP(wires=(0, 1))

tests/drawer/test_draw_mpl.py

@@ -81,13 +81,11 @@ def test_fig_argument():
 
 
 class TestLevelExpansionStrategy:
- @pytest.fixture(
- params=[qml.device("default.qubit.legacy", wires=3), qml.devices.DefaultQubit()],
- )
- def transforms_circuit(self, request):
+ @pytest.fixture
+ def transforms_circuit(self):
  @qml.transforms.merge_rotations
  @qml.transforms.cancel_inverses
- @qml.qnode(request.param, diff_method="parameter-shift")
+ @qml.qnode(qml.device("default.qubit"), diff_method="parameter-shift")
  def circ(weights, order):
  qml.RandomLayers(weights, wires=(0, 1))
  qml.Permute(order, wires=(0, 1, 2))
@@ -125,18 +123,14 @@ def test_equivalent_levels(self, transforms_circuit, levels, expected_metadata):
 
  plt.close("all")
 
- @pytest.mark.parametrize(
- "device",
- [qml.device("default.qubit.legacy", wires=3), qml.devices.DefaultQubit(wires=3)],
- )
  @pytest.mark.parametrize(
  "strategy, initial_strategy, n_lines",
  [("gradient", "device", 3), ("device", "gradient", 13)],
  )
- def test_expansion_strategy(self, device, strategy, initial_strategy, n_lines):
+ def test_expansion_strategy(self, strategy, initial_strategy, n_lines):
  """Test that the expansion strategy keyword controls what operations are drawn."""
 
- @qml.qnode(device, expansion_strategy=initial_strategy)
+ @qml.qnode(qml.device("default.qubit"), expansion_strategy=initial_strategy)
  def circuit():
  qml.Permute([2, 0, 1], wires=(0, 1, 2))
  return qml.expval(qml.PauliZ(0))
@@ -499,11 +493,7 @@ def circuit():
  assert ax.texts[-1].get_text() == "X†"
 
 
-@pytest.mark.parametrize(
- "device",
- [qml.device("default.qubit.legacy", wires=2), qml.device("default.qubit", wires=2)],
-)
-def test_applied_transforms(device):
+def test_applied_transforms():
  """Test that any transforms applied to the qnode are included in the output."""
 
  @qml.transform
@@ -512,7 +502,7 @@ def just_pauli_x(_):
  return (new_tape,), lambda res: res[0]
 
  @just_pauli_x
- @qml.qnode(device)
+ @qml.qnode(qml.device("default.qubit", wires=2))
  def my_circuit():
  qml.SWAP(wires=(0, 1))
  qml.CNOT(wires=(0, 1))

tests/interfaces/test_jacobian_products.py

@@ -31,7 +31,8 @@
 )
 
 dev = qml.device("default.qubit")
-dev_old = qml.device("default.qubit.legacy", wires=5)
+with pytest.warns(qml.PennyLaneDeprecationWarning):
+ dev_old = qml.device("default.qubit.legacy", wires=5)
 dev_lightning = qml.device("lightning.qubit", wires=5)
 adjoint_config = qml.devices.ExecutionConfig(gradient_method="adjoint")
 dev_ps = ParamShiftDerivativesDevice()

tests/interfaces/test_transform_program_integration.py

@@ -24,11 +24,12 @@
 
 import pennylane as qml
 
-device_suite = (
- qml.device("default.qubit.legacy", wires=5),
- qml.devices.DefaultQubit(),
- qml.device("lightning.qubit", wires=5),
-)
+with pytest.warns(qml.PennyLaneDeprecationWarning):
+ device_suite = (
+ qml.device("default.qubit.legacy", wires=5),
+ qml.devices.DefaultQubit(),
+ qml.device("lightning.qubit", wires=5),
+ )
 
 
 @pytest.mark.all_interfaces

tests/ops/qubit/test_observables.py

@@ -676,10 +676,10 @@ def test_matrix_representation(self, basis_state, expected, n_wires, tol):
  assert np.allclose(res_dynamic, expected, atol=tol)
  assert np.allclose(res_static, expected, atol=tol)
 
- @pytest.mark.parametrize(
-  "dev", (qml.device("default.qubit"), qml.device("default.qubit.legacy", wires=1))
- )
- def test_integration_batched_state(self, dev):
+ @pytest.mark.parametrize("dev_name", ("default.qubit", "default.qubit.legacy"))
+ def test_integration_batched_state(self, dev_name):
+  dev = qml.device(dev_name, wires=1)
+
  @qml.qnode(dev)
  def circuit(x):
  qml.RX(x, wires=0)

tests/resource/test_specs.py

@@ -21,6 +21,13 @@
 import pennylane as qml
 from pennylane import numpy as pnp
 
+with pytest.warns(qml.PennyLaneDeprecationWarning):
+ devices_list = [
+ (qml.device("default.qubit"), 1),
+ (qml.device("default.qubit", wires=2), 2),
+ (qml.device("default.qubit.legacy", wires=2), 2),
+ ]
+
 
 class TestSpecsTransform:
  """Tests for the transform specs using the QNode"""
@@ -317,11 +324,7 @@ def circuit():
 
  @pytest.mark.parametrize(
  "device,num_wires",
- [
- (qml.device("default.qubit"), 1),
- (qml.device("default.qubit", wires=2), 2),
- (qml.device("default.qubit.legacy", wires=2), 2),
- ],
+ devices_list,
  )
  def test_num_wires_source_of_truth(self, device, num_wires):
  """Tests that num_wires behaves differently on old and new devices."""