Update docs (#4269)

* Incrementing the version number to `v0.32.0-dev` (#4266) * pre-release for v0.31.0 * Update doc/releases/changelog-0.31.0.md * Incrementing the version number to v0.32.0-dev * Update installation.rst (#4247) Update Python version to 3.8 Co-authored-by: Romain Moyard <[email protected]> * docs typos * don't include updating versioning from master * don't include python requirements from master * update example output for shot_vector * Update pennylane/operation.py Co-authored-by: Matthew Silverman <[email protected]> * fix entirely unrelated rendering issue --------- Co-authored-by: Matthew Silverman <[email protected]> Co-authored-by: Catalina Albornoz <[email protected]> Co-authored-by: Romain Moyard <[email protected]>
PennyLaneAI · Jun 21, 2023 · 975d1e9 · 975d1e9
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diff --git a/pennylane/gradients/__init__.py b/pennylane/gradients/__init__.py
@@ -264,7 +264,6 @@ def circuit(weights):
 
     ops = [
         qml.RX(weights[0], wires=0),
-
         qml.RY(weights[1], wires=1),
         qml.CNOT(wires=[0, 1]),
         qml.RX(weights[2], wires=1)]

diff --git a/pennylane/operation.py b/pennylane/operation.py
@@ -705,7 +705,7 @@ def compute_matrix(*params, **hyperparams):  # pylint:disable=unused-argument
         The canonical matrix is the textbook matrix representation that does not consider wires.
         Implicitly, this assumes that the wires of the operator correspond to the global wire order.
 
-        .. seealso:: :meth:`.Operator.matrix` and :func:`qml.matrix`
+        .. seealso:: :meth:`.Operator.matrix` and :func:`qml.matrix() <pennylane.matrix>`
 
         Args:
             *params (list): trainable parameters of the operator, as stored in the ``parameters`` attribute

diff --git a/pennylane/pulse/convenience_functions.py b/pennylane/pulse/convenience_functions.py
@@ -234,7 +234,7 @@ def wrapped(p, t):
         time = jnp.linspace(0, 10, 1000)
         timespan=(2, 7)
         y = qml.pulse.pwc(timespan)(params, time)
-        plt.plot(time, y, label=f"params={params},\ntimespan={timespan}")
+        plt.plot(time, y, label=f"params={params}, timespan={timespan}")
         plt.legend()
         plt.show()
 

diff --git a/pennylane/tape/qscript.py b/pennylane/tape/qscript.py
@@ -171,7 +171,7 @@ class QuantumScript:
     >>> s_vec = [1, 1, 2, 2, 2]
     >>> qscript = QuantumScript([qml.Hadamard(0)], [qml.expval(qml.PauliZ(0))], shots=s_vec)
     >>> qscript.shots.shot_vector
-    (ShotCopies(shots=1, copies=2), ShotCopies(shots=2, copies=3))
+    (ShotCopies(1 shots x 2), ShotCopies(2 shots x 3))
 
     ``ops``, ``measurements``, and ``prep`` are converted to lists upon initialization,
     so those arguments accept any iterable object:

diff --git a/pennylane/transforms/batch_transform.py b/pennylane/transforms/batch_transform.py
@@ -82,6 +82,9 @@ def my_transform(tape, a, b):
             '''Generates two tapes, one with all RX replaced with RY,
             and the other with all RX replaced with RZ.'''
 
+            ops1 = []
+            ops2 = []
+
             # loop through all operations on the input tape
             for op in tape._ops:
                 if op.name == "RX":
@@ -94,7 +97,7 @@ def my_transform(tape, a, b):
                     ops1.append(op)
                     ops2.append(op)
 
-            tape1 = qml.tape.QuantumTape(ops1, tape.measurments, tape._prep)
+            tape1 = qml.tape.QuantumTape(ops1, tape.measurements, tape._prep)
             tape2 = qml.tape.QuantumTape(ops2, tape.measurements, tape._prep)
 
             def processing_fn(results):