Few docstring updates in prep for v0.22.0

pennylane/operation.py

@@ -169,7 +169,7 @@ def expand_matrix(base_matrix, wires, wire_order):
     ...                                   [3., 4.]], requires_grad=True)
     >>> res = expand_matrix(base_matrix_torch, wires=["b"], wire_order=["a", "b"])
     >>> type(res)
-    <class 'torch.Tensor'>
+    torch.Tensor
     >>> res.requires_grad
     True
     """

pennylane/transforms/batch_input.py

@@ -66,13 +66,12 @@ def circuit(inputs, weights):
             qml.RY(weights[1], wires=1)
             return qml.expval(qml.PauliZ(1))
 
-    >>> x = np.random.uniform(0,1,(10,2))
-    >>> x.requires_grad = False
-    >>> w = np.random.uniform(0,1,2)
+    >>> x = tf.random.uniform((10, 2), 0, 1)
+    >>> w = tf.random.uniform((2,), 0, 1)
     >>> circuit(x, w)
     <tf.Tensor: shape=(10,), dtype=float64, numpy=
-    array([0.17926078, 0.7480163 , 0.47816999, 0.50381628, 0.349178  ,
-           0.17511444, 0.03769436, 0.19180259, 0.75867188, 0.55335748])>
+    array([0.46230079, 0.73971315, 0.95666004, 0.5355225 , 0.66180948,
+            0.44519553, 0.93874261, 0.9483197 , 0.78737918, 0.90866411])>
     """
     parameters = tape.get_parameters(trainable_only=False)
 

pennylane/transforms/commutation_dag.py

@@ -65,7 +65,8 @@ def circuit(x, y, z):
     the  form ``(ID, CommutationDAGNode)``:
 
     >>> nodes = dag.get_nodes()
-    [(0, <pennylane.transforms.commutation_dag.CommutationDAGNode object at 0x132b03b20>), ...]
+    >>> nodes
+    NodeDataView({0: <pennylane.transforms.commutation_dag.CommutationDAGNode object at 0x7f461c4bb580>, ...}, data='node')
 
     You can also access specific nodes (of type :class:`~.CommutationDAGNode`) by using the :meth:`~.get_node`
     method. See :class:`~.CommutationDAGNode` for a list of available
@@ -205,7 +206,8 @@ def simplify_rotation(rot):
 
 
 def simplify_controlled_rotation(crot):
-    r"""Simplify a general one qubit controlled rotation into CRX, CRY, CRZ and CH.
+    r"""Simplify a general one qubit controlled rotation into CRX, CRY, CRZ and
+    controlled-Hadamard.
 
     Args:
         crot (pennylane.CRot): One qubit controlled rotation.
@@ -286,8 +288,8 @@ def simplify_u3(u3):
 def simplify(operation):
     r"""Simplify the (controlled) rotation operations :class:`~.Rot`,
     :class:`~.U2`, :class:`~.U3`, and :class:`~.CRot` into one of
-    :class:`~.RX`, :class:`~.CRX`, :class:`~.RY`, :class:`~.CRY`, :class:`~.`RZ`,
-    :class:`~.CZ`, :class:`~.H` and :class:`~.CH` where possible.
+    :class:`~.RX`, :class:`~.CRX`, :class:`~.RY`, :class:`~.CRY`, :class:`~.RZ`,
+    :class:`~.CZ`, :class:`~.Hadamard` and controlled-Hadamard where possible.
 
     Args:
         operation (.Operation): Rotation or controlled rotation.
@@ -755,10 +757,10 @@ def _merge_no_duplicates(*iterables):
     """Merge K list without duplicate using python heapq ordered merging.
 
     Args:
-        *iterables: A list of k sorted lists
+        *iterables: A list of k sorted lists.
 
     Yields:
-        Iterator: List from the merging of the k ones (without duplicates)
+        Iterator: List from the merging of the k ones (without duplicates).
     """
     last = object()
     for val in heapq.merge(*iterables):
@@ -897,7 +899,7 @@ def get_node(self, node_id):
         return self._multi_graph.nodes(data="node")[node_id]
 
     def get_nodes(self):
-        """Return iterable to loop through all the nodes in the DAG
+        """Return iterable to loop through all the nodes in the DAG.
 
         Returns:
             networkx.classes.reportviews.NodeDataView: Iterable nodes.

pennylane/transforms/qcut.py

@@ -714,7 +714,7 @@ def contract_tensors(
 
     The network can then be contracted using:
 
-    >>> qml.transforms.contract_tensors(tensors, graph, prep, meas)
+    >>> qml.transforms.qcut.contract_tensors(tensors, graph, prep, meas)
     38
     """
     # pylint: disable=import-outside-toplevel