Deprecate old QNode

doc/code/qml_beta.rst

@@ -6,17 +6,10 @@ and features.
 
 .. currentmodule:: pennylane.beta
 
-.. automodapi:: pennylane.beta.interfaces
-    :include-all-objects:
-    :no-inheritance-diagram:
-
 .. automodapi:: pennylane.beta.plugins
     :include-all-objects:
     :no-inheritance-diagram:
 
-.. automodapi:: pennylane.beta.qnodes
-    :include-all-objects:
-
 .. automodapi:: pennylane.beta.vqe
     :include-all-objects:
     :no-inheritance-diagram:

doc/code/qml_interfaces.rst

@@ -14,3 +14,7 @@ qml.interfaces
 .. rubric:: Modules
 
 .. automodule:: pennylane.interfaces
+
+.. automodapi:: pennylane.interfaces
+    :include-all-objects:
+    :no-inheritance-diagram:

doc/code/qml_qnodes.rst

@@ -0,0 +1,5 @@
+qml.qnodes
+==========
+
+.. automodapi:: pennylane.qnodes
+    :include-all-objects:

pennylane/__init__.py

@@ -36,12 +36,11 @@
 from .measure import expval, var, sample
 from .ops import *
 from .optimize import *
-from .qnode import QNode, QuantumFunctionError
+from .qnodes import qnode, QNode, QuantumFunctionError
 from ._version import __version__
 
-# NOTE: this has to be imported last,
-# otherwise it will clash with the .qnode import.
-from .decorator import qnode
+
+_current_context = None
 
 
 # overwrite module docstrings

pennylane/_device.py

@@ -20,7 +20,7 @@
 import numpy as np
 
 from pennylane.operation import Operation, Observable, Sample, Variance, Expectation, Tensor
-from .qnode import QuantumFunctionError
+from pennylane.qnodes import QuantumFunctionError
 
 
 class DeviceError(Exception):

pennylane/beta/__init__.py

@@ -14,6 +14,4 @@
 """
 This module contains experimental, contributed, and beta code.
 """
-import pennylane.beta.interfaces
-import pennylane.beta.qnodes
 import pennylane.beta.vqe

pennylane/beta/plugins/expt_tensornet_tf.py

@@ -202,14 +202,10 @@ class TensorNetworkTF(TensorNetwork):
 
         pip install tensornetwork>=0.2 tensorflow>=2.0
 
-    In addition, you will need to use the new-style QNode to enable
-    calculation of the quantum gradient using TensorFlow.
-
     **Example:**
 
-    >>> from pennylane.beta.qnodes import qnode
     >>> dev = qml.device("expt.tensornet.tf", wires=1)
-    >>> @qnode(dev, interface="autograd", diff_method="best")
+    >>> @qml.qnode(dev, interface="autograd", diff_method="best")
     >>> def circuit(x):
     ...     qml.RX(x[1], wires=0)
     ...     qml.Rot(x[0], x[1], x[2], wires=0)

pennylane/beta/vqe/vqe.py

@@ -18,7 +18,7 @@
 import numpy as np
 from pennylane.ops import Observable
 from pennylane.measure import expval
-from pennylane.qnode import QNode
+from pennylane.qnodes import QNode
 
 
 class Hamiltonian:
@@ -122,12 +122,7 @@ def circuit(*params, obs=obs):
             ansatz(*params, wires=range(device.num_wires))
             return expval(obs)
 
-        qnode = QNode(circuit, device)
-
-        if interface == "tf":
-            qnode = qnode.to_tf()
-        elif interface == "torch":
-            qnode = qnode.to_torch()
+        qnode = QNode(circuit, device, interface=interface)
 
         qnodes.append(qnode)
 

pennylane/interfaces/tf.py

@@ -12,7 +12,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 """
-This module contains the :func:`TFQNode` function to convert Numpy-interfacing quantum nodes to TensorFlow
+This module contains the :func:`to_tf` function to convert Numpy-interfacing quantum nodes to TensorFlow
 compatible quantum nodes.
 """
 # pylint: disable=redefined-outer-name
@@ -31,7 +31,7 @@
     from tensorflow import Variable # pylint: disable=unused-import,ungrouped-imports
 
 
-def TFQNode(qnode):
+def to_tf(qnode):
     """Function that accepts a :class:`~.QNode`, and returns a TensorFlow eager-execution-compatible QNode.
 
     Args:
@@ -85,12 +85,7 @@ def grad(grad_output, **tfkwargs):
             # evaluate the Jacobian matrix of the QNode
             variables = tfkwargs.get('variables', None)
 
-            if hasattr(qnode, "to_autograd"):
-                # new style QNode.jacobian has a different signature
-                jacobian = qnode.jacobian(args, kwargs)
-            else:
-                jacobian = qnode.jacobian(args, **kwargs)
-
+            jacobian = qnode.jacobian(args, kwargs)
             grad_output_np = grad_output.numpy()
 
             # perform the vector-Jacobian product

pennylane/interfaces/torch.py

@@ -12,7 +12,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 """
-This module contains the :func:`TorchQNode` function to convert Numpy-interfacing quantum nodes to PyTorch
+This module contains the :func:`to_torch` function to convert Numpy-interfacing quantum nodes to PyTorch
 compatible quantum nodes.
 """
 # pylint: disable=redefined-outer-name,arguments-differ
@@ -95,7 +95,7 @@ def kwargs_to_numpy(kwargs):
     return res
 
 
-def TorchQNode(qnode):
+def to_torch(qnode):
     """Function that accepts a :class:`~.QNode`, and returns a PyTorch-compatible QNode.
 
     Args:
@@ -140,11 +140,7 @@ def backward(ctx, grad_output): #pragma: no cover
             # the way in which the backward class is created on the fly
 
             # evaluate the Jacobian matrix of the QNode
-            if hasattr(qnode, "to_autograd"):
-                # new style QNode.jacobian has a different signature
-                jacobian = qnode.jacobian(ctx.args, ctx.kwargs)
-            else:
-                jacobian = qnode.jacobian(ctx.args, **ctx.kwargs)
+            jacobian = qnode.jacobian(ctx.args, ctx.kwargs)
 
             if grad_output.is_cuda: # pragma: no cover
                 grad_output_np = grad_output.cpu().detach().numpy()

pennylane/measure.py

@@ -17,14 +17,15 @@
 outcomes from quantum observables - expectation values, variances of expectations,
 and measurement samples.
 """
-from .qnode import QNode, QuantumFunctionError
+import pennylane as qml
 from .operation import Observable, Sample, Variance, Expectation, Tensor
+from .qnodes import QuantumFunctionError
 
 
 def _remove_if_in_queue(op):
     r"""Helper function to handle removing ops from the QNode queue"""
-    if op in QNode._current_context.queue:
-        QNode._current_context.queue.remove(op)
+    if op in qml._current_context.queue:
+        qml._current_context.queue.remove(op)
 
 
 def expval(op):
@@ -41,7 +42,7 @@ def expval(op):
             "{} is not an observable: cannot be used with expval".format(op.name)
         )
 
-    if QNode._current_context is not None:
+    if qml._current_context is not None:
         # delete observables from QNode operation queue if needed
         if isinstance(op, Tensor):
             for o in op.obs:
@@ -52,9 +53,9 @@ def expval(op):
     # set return type to be an expectation value
     op.return_type = Expectation
 
-    if QNode._current_context is not None:
+    if qml._current_context is not None:
         # add observable to QNode observable queue
-        QNode._current_context._append_op(op)
+        qml._current_context._append_op(op)
 
     return op
 
@@ -73,20 +74,20 @@ def var(op):
             "{} is not an observable: cannot be used with var".format(op.name)
         )
 
-    if QNode._current_context is not None:
+    if qml._current_context is not None:
         # delete operations from QNode queue
         if isinstance(op, Tensor):
             for o in op.obs:
-                QNode._current_context.queue.remove(o)
+                qml._current_context.queue.remove(o)
         else:
-            QNode._current_context.queue.remove(op)
+            qml._current_context.queue.remove(op)
 
     # set return type to be a variance
     op.return_type = Variance
 
-    if QNode._current_context is not None:
+    if qml._current_context is not None:
         # add observable to QNode observable queue
-        QNode._current_context._append_op(op)
+        qml._current_context._append_op(op)
 
     return op
 
@@ -106,19 +107,19 @@ def sample(op):
             "{} is not an observable: cannot be used with sample".format(op.name)
         )
 
-    if QNode._current_context is not None:
+    if qml._current_context is not None:
         # delete operations from QNode queue
         if isinstance(op, Tensor):
             for o in op.obs:
-                QNode._current_context.queue.remove(o)
+                qml._current_context.queue.remove(o)
         else:
-            QNode._current_context.queue.remove(op)
+            qml._current_context.queue.remove(op)
 
     # set return type to be a sample
     op.return_type = Sample
 
-    if QNode._current_context is not None:
+    if qml._current_context is not None:
         # add observable to QNode observable queue
-        QNode._current_context._append_op(op)
+        qml._current_context._append_op(op)
 
     return op