Merge branch 'master' into device-docs

.github/workflows/docker.yml

@@ -1,8 +1,5 @@
 name: Docker builds
-on:
- push:
- branches:
- - master
+on: workflow_dispatch
 
 jobs:
  base-tests:

.pylintrc

@@ -2,20 +2,20 @@
 # A comma-separated list of package or module names from where C extensions may
 # be loaded. Extensions are loading into the active Python interpreter and may
 # run arbitrary code
-extension-pkg-whitelist=numpy,scipy,autograd,toml,appdir,autograd.numpy,autograd.numpy.linalg,autograd.numpy.builtins,semantic_version,torch,tensorflow,tensorflow.contrib,tensorflow.contrib.eager,LazyLoader,networkx,networkx.dag
+extension-pkg-whitelist=numpy,scipy,autograd,toml,appdir,autograd.numpy,autograd.numpy.linalg,autograd.numpy.builtins,semantic_version,packaging,torch,tensorflow,tensorflow.contrib,tensorflow.contrib.eager,LazyLoader,networkx,networkx.dag
 
 [TYPECHECK]
 
 # List of module names for which member attributes should not be checked
 # (useful for modules/projects where namespaces are manipulated during runtime
 # and thus existing member attributes cannot be deduced by static analysis. It
 # supports qualified module names, as well as Unix pattern matching.
-ignored-modules=numpy,scipy,autograd,toml,appdir,autograd.numpy,autograd.numpy.linalg,autograd.numpy.builtins,semantic_version,torch,tensorflow,tensorflow.contrib,tensorflow.contrib.eager,LazyLoader,networkx,networkx.dag,math,pennylane.numpy
+ignored-modules=numpy,scipy,autograd,toml,appdir,autograd.numpy,autograd.numpy.linalg,autograd.numpy.builtins,semantic_version,packaging,torch,tensorflow,tensorflow.contrib,tensorflow.contrib.eager,LazyLoader,networkx,networkx.dag,math,pennylane.numpy
 
 # List of classes names for which member attributes should not be checked
 # (useful for classes with attributes dynamically set). This supports can work
 # with qualified names.
-ignored-classes=numpy,scipy,autograd,toml,appdir,autograd.numpy,autograd.numpy.linalg,autograd.numpy.builtins,semantic_version,torch,tensorflow,tensorflow.contrib,tensorflow.contrib.eager,LazyLoader,networkx,networkx.dag,math,pennylane.numpy,pennylane.numpy.random,pennylane.numpy.linalg,pennylane.numpy.builtins,pennylane.operation,rustworkx,kahypar
+ignored-classes=numpy,scipy,autograd,toml,appdir,autograd.numpy,autograd.numpy.linalg,autograd.numpy.builtins,semantic_version,packaging,torch,tensorflow,tensorflow.contrib,tensorflow.contrib.eager,LazyLoader,networkx,networkx.dag,math,pennylane.numpy,pennylane.numpy.random,pennylane.numpy.linalg,pennylane.numpy.builtins,pennylane.operation,rustworkx,kahypar
 
 [MESSAGES CONTROL]
 

doc/development/guide/installation.rst

@@ -19,6 +19,7 @@ be installed alongside PennyLane:
 * `appdirs <https://github.com/ActiveState/appdirs>`_
 * `semantic-version <https://github.com/rbarrois/python-semanticversion>`_ >= 2.7
 * `autoray <https://github.com/jcmgray/autoray>`__ >= 0.6.11
+* `packaging <https://github.com/pypa/packaging>`_
 
 The following Python packages are optional:
 

doc/releases/changelog-dev.md

@@ -9,6 +9,9 @@
 
 <h3>Improvements 🛠</h3>
 
+* Added `packaging` in the required list of packages.
+ [(#5769)](https://github.com/PennyLaneAI/pennylane/pull/5769).
+
 * Logging now allows for an easier opt-in across the stack, and also extends control support to `catalyst`.
  [(#5528)](https://github.com/PennyLaneAI/pennylane/pull/5528).
 
@@ -24,6 +27,9 @@
 * The sorting order of parameter-shift terms is now guaranteed to resolve ties in the absolute value with the sign of the shifts.
  [(#5582)](https://github.com/PennyLaneAI/pennylane/pull/5582)
 
+* `qml.transforms.split_non_commuting` can now handle circuits containing measurements of multi-term observables.
+ [(#5729)](https://github.com/PennyLaneAI/pennylane/pull/5729)
+
 <h4>Mid-circuit measurements and dynamic circuits</h4>
 
 * The `dynamic_one_shot` transform uses a single auxiliary tape with a shot vector and `default.qubit` implements the loop over shots with `jax.vmap`.
@@ -190,6 +196,9 @@
 
 <h3>Bug fixes 🐛</h3>
 
+* Disable Docker builds on PR merge.
+ [(#5777)](https://github.com/PennyLaneAI/pennylane/pull/5777)
+
 * The validation of the adjoint method in `DefaultQubit` correctly handles device wires now.
  [(#5761)](https://github.com/PennyLaneAI/pennylane/pull/5761)
 

doc/requirements.txt

@@ -10,6 +10,7 @@ m2r2
 numpy
 pygments-github-lexers
 semantic_version==2.10
+packaging
 scipy
 docutils==0.16
 sphinx~=3.5.0; python_version < "3.10"

pennylane/__init__.py

@@ -1,4 +1,4 @@
-# Copyright 2018-2021 Xanadu Quantum Technologies Inc.
+# Copyright 2018-2024 Xanadu Quantum Technologies Inc.
 
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
@@ -20,6 +20,7 @@
 
 
 import numpy as _np
+
 from semantic_version import SimpleSpec, Version
 
 from pennylane.boolean_fn import BooleanFn

pennylane/compiler/compiler.py

@@ -20,7 +20,7 @@
 from sys import version_info
 from typing import List, Optional
 
-from semantic_version import Version
+from packaging.version import Version
 
 PL_CATALYST_MIN_VERSION = Version("0.6.0")
 

pennylane/devices/default_qubit_tf.py

@@ -1,4 +1,4 @@
-# Copyright 2018-2021 Xanadu Quantum Technologies Inc.
+# Copyright 2018-2024 Xanadu Quantum Technologies Inc.
 
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
@@ -17,7 +17,7 @@
 import itertools
 
 import numpy as np
-import semantic_version
+from packaging.version import Version
 
 import pennylane as qml
 
@@ -29,7 +29,7 @@
 
  from tensorflow.python.framework.errors_impl import InvalidArgumentError
 
- SUPPORTS_APPLY_OPS = semantic_version.match(">=2.3.0", tf.__version__)
+ SUPPORTS_APPLY_OPS = Version(tf.__version__) >= Version("2.3.0")
 
 except ImportError as e: # pragma: no cover
  raise ImportError("default.qubit.tf device requires TensorFlow>=2.0") from e

pennylane/devices/default_qubit_torch.py

@@ -1,4 +1,4 @@
-# Copyright 2018-2021 Xanadu Quantum Technologies Inc.
+# Copyright 2018-2024 Xanadu Quantum Technologies Inc.
 
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
@@ -18,12 +18,14 @@
 import logging
 import warnings
 
-import semantic_version
+from packaging.version import Version
 
 try:
  import torch
 
- VERSION_SUPPORT = semantic_version.match(">=1.8.1", torch.__version__)
+ VERSION_SUPPORT = Version(torch.__version__) >= Version(
+ "1.8.1",
+ )
  if not VERSION_SUPPORT: # pragma: no cover
  raise ImportError("default.qubit.torch device requires Torch>=1.8.1")
 

pennylane/ops/qubit/hamiltonian.py

@@ -775,8 +775,9 @@ def __rmatmul__(self, H):
  ops1 = self.ops.copy()
 
  if isinstance(H, (Tensor, Observable)):
+ qml.QueuingManager.remove(H)
+ qml.QueuingManager.remove(self)
  terms = [copy(H) @ op for op in ops1]
-
  return qml.simplify(Hamiltonian(coeffs1, terms))
 
  return NotImplemented
@@ -790,11 +791,15 @@ def __add__(self, H):
  return self
 
  if isinstance(H, Hamiltonian):
+ qml.QueuingManager.remove(H)
+ qml.QueuingManager.remove(self)
  coeffs = qml.math.concatenate([self_coeffs, copy(H.coeffs)], axis=0)
  ops.extend(H.ops.copy())
  return qml.simplify(Hamiltonian(coeffs, ops))
 
  if isinstance(H, (Tensor, Observable)):
+ qml.QueuingManager.remove(H)
+ qml.QueuingManager.remove(self)
  coeffs = qml.math.concatenate(
  [self_coeffs, qml.math.cast_like([1.0], self_coeffs)], axis=0
  )

pennylane/qnn/keras.py

@@ -1,4 +1,4 @@
-# Copyright 2018-2021 Xanadu Quantum Technologies Inc.
+# Copyright 2018-2024 Xanadu Quantum Technologies Inc.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
@@ -17,7 +17,7 @@
 from collections.abc import Iterable
 from typing import Optional, Text
 
-from semantic_version import Version
+from packaging.version import Version
 
 try:
  import tensorflow as tf