Amazon Braket PennyLane Plugin
##############################
.. image:: https://img.shields.io/pypi/v/amazon-braket-pennylane-plugin.svg
:alt: Latest Version
:target: https://pypi.python.org/pypi/amazon-braket-pennylane-plugin
.. image:: https://img.shields.io/pypi/pyversions/amazon-braket-pennylane-plugin.svg
:alt: Supported Python Versions
:target: https://pypi.python.org/pypi/amazon-braket-pennylane-plugin
.. image:: https://img.shields.io/github/actions/workflow/status/amazon-braket/amazon-braket-strawberryfields-plugin-python/python-package.yml?branch=main&logo=github
:alt: Build Status
:target: https://github.com/amazon-braket/amazon-braket-pennylane-plugin-python/actions?query=workflow%3A%22Python+package%22
.. image:: https://codecov.io/gh/amazon-braket/amazon-braket-pennylane-plugin-python/branch/main/graph/badge.svg?token=VPPM8BJKW4
:alt: codecov
:target: https://codecov.io/gh/amazon-braket/amazon-braket-pennylane-plugin-python
.. image:: https://img.shields.io/readthedocs/amazon-braket-pennylane-plugin-python.svg?logo=read-the-docs
:alt: Documentation Status
:target: https://amazon-braket-pennylane-plugin-python.readthedocs.io/en/latest/?badge=latest
The Amazon Braket PennyLane plugin offers four Amazon Braket quantum devices to work with PennyLane:
* ``braket.aws.qubit`` for running with the Amazon Braket service's quantum devices, both QPUs and simulators
* ``braket.local.qubit`` for running the Amazon Braket SDK's local simulator where you can optionally specify the backend ("default", "braket_sv", "braket_dm" etc)
* ``braket.aws.ahs`` for running with the Amazon Braket service's analog Hamiltonian simulation QPUs
* ``braket.local.ahs`` for running analog Hamiltonian simulation on Amazon Braket SDK's local simulator
.. header-start-inclusion-marker-do-not-remove
The `Amazon Braket Python SDK <https://github.com/amazon-braket/amazon-braket-sdk-python>`__ is an open source
library that provides a framework to interact with quantum computing hardware
devices and simulators through Amazon Braket.
`PennyLane <https://pennylane.readthedocs.io>`__ is a machine learning library for optimization and automatic
differentiation of hybrid quantum-classical computations.
.. header-end-inclusion-marker-do-not-remove
The plugin documentation can be found here: `<https://amazon-braket-pennylane-plugin-python.readthedocs.io/en/latest/>`__.
Features
========
Provides four devices to be used with PennyLane:
* Two gate-based devices, ``braket.aws.qubit`` for running on the Amazon Braket service,
and ``braket.local.qubit`` for running on the Amazon Braket SDK's local simulator.
* Two analog Hamiltonian simulation devices, ``braket.aws.ahs`` for running on QPU via the Amazon Braket service,
and ``braket.local.ahs`` for running on the Amazon Braket SDK's local simulator.
* Combines Amazon Braket with PennyLane's automatic differentiation and optimization.
For the gate-based devices:
* Both devices support most core qubit PennyLane operations.
* All PennyLane observables are supported.
* Provides custom PennyLane operations to cover additional Braket operations: ``ISWAP``, ``PSWAP``, and many more.
Every custom operation supports analytic differentiation.
For the analog Hamiltonian simulation devices:
* The devices support ``ParametrizedEvolution`` operators created via the
`PennyLane pulse programming <https://docs.pennylane.ai/en/stable/code/qml_pulse.html>`_ module.
* PennyLane observables in the measurement (Z) basis are supported
* Provides translation of user-defined pulse level control to simulation and hardware implementation
.. installation-start-inclusion-marker-do-not-remove
Installation
============
Before you begin working with the Amazon Braket PennyLane Plugin, make sure
that you installed or configured the following prerequisites:
* Download and install `Python 3.9 <https://www.python.org/downloads/>`__ or greater.
If you are using Windows, choose the option *Add Python to environment variables* before you begin the installation.
* Make sure that your AWS account is onboarded to Amazon Braket, as per the instructions
`here <https://github.com/amazon-braket/amazon-braket-sdk-python#prerequisites>`__.
* Download and install `PennyLane <https://pennylane.ai/install.html>`__:
.. code-block:: bash
pip install pennylane
You can then install the latest release of the PennyLane-Braket plugin as follows:
.. code-block:: bash
pip install amazon-braket-pennylane-plugin
You can also install the development version from source by cloning this repository and running a
pip install command in the root directory of the repository:
.. code-block:: bash
git clone https://github.com/amazon-braket/amazon-braket-pennylane-plugin-python.git
cd amazon-braket-pennylane-plugin-python
pip install .
You can check your currently installed version of ``amazon-braket-pennylane-plugin`` with ``pip show``:
.. code-block:: bash
pip show amazon-braket-pennylane-plugin
or alternatively from within Python:
.. code-block:: python
from braket import pennylane_plugin
pennylane_plugin.__version__
Tests
~~~~~
Make sure to install test dependencies first:
.. code-block:: bash
pip install -e "amazon-braket-pennylane-plugin-python[test]"
Unit tests
**********
Run the unit tests using:
.. code-block:: bash
tox -e unit-tests
To run an individual test:
.. code-block:: bash
tox -e unit-tests -- -k 'your_test'
To run linters, doc, and unit tests:
.. code-block:: bash
tox
Integration tests
*****************
To run the integration tests, set the ``AWS_PROFILE`` as explained in the amazon-braket-sdk-python
`README <https://github.com/amazon-braket/amazon-braket-sdk-python/blob/main/README.md>`__:
.. code-block:: bash
export AWS_PROFILE=Your_Profile_Name
Running the integration tests creates an S3 bucket in the same account as the ``AWS_PROFILE``
with the following naming convention ``amazon-braket-pennylane-plugin-integ-tests-{account_id}``.
Run the integration tests with:
.. code-block:: bash
tox -e integ-tests
To run an individual integration test:
.. code-block:: bash
tox -e integ-tests -- -k 'your_test'
Documentation
~~~~~~~~~~~~~
To build the HTML documentation, run:
.. code-block:: bash
tox -e docs
The documentation can then be found in the ``doc/build/documentation/html/`` directory.
.. installation-end-inclusion-marker-do-not-remove
Contributing
============
We welcome contributions - simply fork the repository of this plugin, and then make a
`pull request <https://help.github.com/articles/about-pull-requests/>`__ containing your contribution.
All contributers to this plugin will be listed as authors on the releases.
We also encourage bug reports, suggestions for new features and enhancements, and even links to cool projects
or applications built with the plugin.
.. support-start-inclusion-marker-do-not-remove
Support
=======
- **Source Code:** https://github.com/amazon-braket/amazon-braket-pennylane-plugin-python
- **Issue Tracker:** https://github.com/amazon-braket/amazon-braket-pennylane-plugin-python/issues
- **General Questions:** https://quantumcomputing.stackexchange.com/questions/ask (add the tag amazon-braket)
- **PennyLane Forum:** https://discuss.pennylane.ai
If you are having issues, please let us know by posting the issue on our Github issue tracker, or
by asking a question in the forum.
.. support-end-inclusion-marker-do-not-remove
.. license-start-inclusion-marker-do-not-remove
License
=======
This project is licensed under the Apache-2.0 License.
.. license-end-inclusion-marker-do-not-remove
Raw data
{
"_id": null,
"home_page": "https://github.com/amazon-braket/amazon-braket-pennylane-plugin-python",
"name": "amazon-braket-pennylane-plugin",
"maintainer": null,
"docs_url": null,
"requires_python": ">=3.8.2",
"maintainer_email": null,
"keywords": "Amazon AWS Quantum",
"author": "Amazon Web Services",
"author_email": null,
"download_url": "https://files.pythonhosted.org/packages/59/90/ec8be07b9cb708a689844cc6cd900ab85c0dd948e13fcc4045dd0fc559c2/amazon_braket_pennylane_plugin-1.25.0.tar.gz",
"platform": null,
"description": "Amazon Braket PennyLane Plugin\n##############################\n\n.. image:: https://img.shields.io/pypi/v/amazon-braket-pennylane-plugin.svg\n :alt: Latest Version\n :target: https://pypi.python.org/pypi/amazon-braket-pennylane-plugin\n.. image:: https://img.shields.io/pypi/pyversions/amazon-braket-pennylane-plugin.svg\n :alt: Supported Python Versions\n :target: https://pypi.python.org/pypi/amazon-braket-pennylane-plugin\n.. image:: https://img.shields.io/github/actions/workflow/status/amazon-braket/amazon-braket-strawberryfields-plugin-python/python-package.yml?branch=main&logo=github \n :alt: Build Status\n :target: https://github.com/amazon-braket/amazon-braket-pennylane-plugin-python/actions?query=workflow%3A%22Python+package%22\n.. image:: https://codecov.io/gh/amazon-braket/amazon-braket-pennylane-plugin-python/branch/main/graph/badge.svg?token=VPPM8BJKW4\n :alt: codecov\n :target: https://codecov.io/gh/amazon-braket/amazon-braket-pennylane-plugin-python\n.. image:: https://img.shields.io/readthedocs/amazon-braket-pennylane-plugin-python.svg?logo=read-the-docs\n :alt: Documentation Status\n :target: https://amazon-braket-pennylane-plugin-python.readthedocs.io/en/latest/?badge=latest\n\nThe Amazon Braket PennyLane plugin offers four Amazon Braket quantum devices to work with PennyLane:\n\n* ``braket.aws.qubit`` for running with the Amazon Braket service's quantum devices, both QPUs and simulators\n* ``braket.local.qubit`` for running the Amazon Braket SDK's local simulator where you can optionally specify the backend (\"default\", \"braket_sv\", \"braket_dm\" etc)\n* ``braket.aws.ahs`` for running with the Amazon Braket service's analog Hamiltonian simulation QPUs\n* ``braket.local.ahs`` for running analog Hamiltonian simulation on Amazon Braket SDK's local simulator\n\n.. header-start-inclusion-marker-do-not-remove\n\nThe `Amazon Braket Python SDK <https://github.com/amazon-braket/amazon-braket-sdk-python>`__ is an open source\nlibrary that provides a framework to interact with quantum computing hardware\ndevices and simulators through Amazon Braket.\n\n`PennyLane <https://pennylane.readthedocs.io>`__ is a machine learning library for optimization and automatic\ndifferentiation of hybrid quantum-classical computations.\n\n.. header-end-inclusion-marker-do-not-remove\n\nThe plugin documentation can be found here: `<https://amazon-braket-pennylane-plugin-python.readthedocs.io/en/latest/>`__.\n\nFeatures\n========\n\nProvides four devices to be used with PennyLane:\n\n* Two gate-based devices, ``braket.aws.qubit`` for running on the Amazon Braket service,\n and ``braket.local.qubit`` for running on the Amazon Braket SDK's local simulator.\n* Two analog Hamiltonian simulation devices, ``braket.aws.ahs`` for running on QPU via the Amazon Braket service,\n and ``braket.local.ahs`` for running on the Amazon Braket SDK's local simulator.\n* Combines Amazon Braket with PennyLane's automatic differentiation and optimization.\n\n\nFor the gate-based devices:\n\n* Both devices support most core qubit PennyLane operations.\n* All PennyLane observables are supported.\n* Provides custom PennyLane operations to cover additional Braket operations: ``ISWAP``, ``PSWAP``, and many more.\n Every custom operation supports analytic differentiation.\n\n\nFor the analog Hamiltonian simulation devices:\n\n* The devices support ``ParametrizedEvolution`` operators created via the\n `PennyLane pulse programming <https://docs.pennylane.ai/en/stable/code/qml_pulse.html>`_ module.\n* PennyLane observables in the measurement (Z) basis are supported\n* Provides translation of user-defined pulse level control to simulation and hardware implementation\n\n\n.. installation-start-inclusion-marker-do-not-remove\n\nInstallation\n============\n\nBefore you begin working with the Amazon Braket PennyLane Plugin, make sure\nthat you installed or configured the following prerequisites:\n\n\n* Download and install `Python 3.9 <https://www.python.org/downloads/>`__ or greater.\n If you are using Windows, choose the option *Add Python to environment variables* before you begin the installation.\n* Make sure that your AWS account is onboarded to Amazon Braket, as per the instructions\n `here <https://github.com/amazon-braket/amazon-braket-sdk-python#prerequisites>`__.\n* Download and install `PennyLane <https://pennylane.ai/install.html>`__:\n\n .. code-block:: bash\n\n pip install pennylane\n\n\nYou can then install the latest release of the PennyLane-Braket plugin as follows:\n\n.. code-block:: bash\n\n pip install amazon-braket-pennylane-plugin\n\n\nYou can also install the development version from source by cloning this repository and running a\npip install command in the root directory of the repository:\n\n.. code-block:: bash\n\n git clone https://github.com/amazon-braket/amazon-braket-pennylane-plugin-python.git\n cd amazon-braket-pennylane-plugin-python\n pip install .\n\n\nYou can check your currently installed version of ``amazon-braket-pennylane-plugin`` with ``pip show``:\n\n.. code-block:: bash\n\n pip show amazon-braket-pennylane-plugin\n\n\nor alternatively from within Python:\n\n.. code-block:: python\n\n from braket import pennylane_plugin\n pennylane_plugin.__version__\n\nTests\n~~~~~\n\nMake sure to install test dependencies first:\n\n.. code-block:: bash\n\n pip install -e \"amazon-braket-pennylane-plugin-python[test]\"\n\nUnit tests\n**********\n\nRun the unit tests using:\n\n.. code-block:: bash\n\n tox -e unit-tests\n\n\nTo run an individual test:\n\n.. code-block:: bash\n\n tox -e unit-tests -- -k 'your_test'\n\n\nTo run linters, doc, and unit tests:\n\n.. code-block:: bash\n\n tox\n\nIntegration tests\n*****************\n\nTo run the integration tests, set the ``AWS_PROFILE`` as explained in the amazon-braket-sdk-python\n`README <https://github.com/amazon-braket/amazon-braket-sdk-python/blob/main/README.md>`__:\n\n.. code-block:: bash\n\n export AWS_PROFILE=Your_Profile_Name\n\n\nRunning the integration tests creates an S3 bucket in the same account as the ``AWS_PROFILE``\nwith the following naming convention ``amazon-braket-pennylane-plugin-integ-tests-{account_id}``.\n\nRun the integration tests with:\n\n.. code-block:: bash\n\n tox -e integ-tests\n\nTo run an individual integration test:\n\n.. code-block:: bash\n\n tox -e integ-tests -- -k 'your_test'\n\nDocumentation\n~~~~~~~~~~~~~\n\nTo build the HTML documentation, run:\n\n.. code-block:: bash\n\n tox -e docs\n\nThe documentation can then be found in the ``doc/build/documentation/html/`` directory.\n\n.. installation-end-inclusion-marker-do-not-remove\n\nContributing\n============\n\nWe welcome contributions - simply fork the repository of this plugin, and then make a\n`pull request <https://help.github.com/articles/about-pull-requests/>`__ containing your contribution.\nAll contributers to this plugin will be listed as authors on the releases.\n\nWe also encourage bug reports, suggestions for new features and enhancements, and even links to cool projects\nor applications built with the plugin.\n\n.. support-start-inclusion-marker-do-not-remove\n\nSupport\n=======\n\n- **Source Code:** https://github.com/amazon-braket/amazon-braket-pennylane-plugin-python\n- **Issue Tracker:** https://github.com/amazon-braket/amazon-braket-pennylane-plugin-python/issues\n- **General Questions:** https://quantumcomputing.stackexchange.com/questions/ask (add the tag amazon-braket)\n- **PennyLane Forum:** https://discuss.pennylane.ai\n\nIf you are having issues, please let us know by posting the issue on our Github issue tracker, or\nby asking a question in the forum.\n\n.. support-end-inclusion-marker-do-not-remove\n\n.. license-start-inclusion-marker-do-not-remove\n\nLicense\n=======\n\nThis project is licensed under the Apache-2.0 License.\n\n.. license-end-inclusion-marker-do-not-remove\n",
"bugtrack_url": null,
"license": "Apache License 2.0",
"summary": "An open source framework for using Amazon Braket devices with the PennyLane quantum machine learning library",
"version": "1.25.0",
"project_urls": {
"Homepage": "https://github.com/amazon-braket/amazon-braket-pennylane-plugin-python"
},
"split_keywords": [
"amazon",
"aws",
"quantum"
],
"urls": [
{
"comment_text": "",
"digests": {
"blake2b_256": "64a36b2204ec50aeba01d041bf155c01256064d80f5087c3005d4420cca205f9",
"md5": "0479f5f011f8685de7477dc33a8c732e",
"sha256": "4770db5ad1d0837c6d5c49f3edd2ffb494a5a5f698776b4db90ba61b0a22b3e8"
},
"downloads": -1,
"filename": "amazon_braket_pennylane_plugin-1.25.0-py3-none-any.whl",
"has_sig": false,
"md5_digest": "0479f5f011f8685de7477dc33a8c732e",
"packagetype": "bdist_wheel",
"python_version": "py3",
"requires_python": ">=3.8.2",
"size": 40314,
"upload_time": "2024-04-22T16:18:48",
"upload_time_iso_8601": "2024-04-22T16:18:48.109227Z",
"url": "https://files.pythonhosted.org/packages/64/a3/6b2204ec50aeba01d041bf155c01256064d80f5087c3005d4420cca205f9/amazon_braket_pennylane_plugin-1.25.0-py3-none-any.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": "",
"digests": {
"blake2b_256": "5990ec8be07b9cb708a689844cc6cd900ab85c0dd948e13fcc4045dd0fc559c2",
"md5": "91817b432eb226940916d45c2de2a6d1",
"sha256": "ac5cf9bc324eba1f9409eab821ca29a25cf242f12256f48e7274c6ab93569f96"
},
"downloads": -1,
"filename": "amazon_braket_pennylane_plugin-1.25.0.tar.gz",
"has_sig": false,
"md5_digest": "91817b432eb226940916d45c2de2a6d1",
"packagetype": "sdist",
"python_version": "source",
"requires_python": ">=3.8.2",
"size": 36427,
"upload_time": "2024-04-22T16:18:50",
"upload_time_iso_8601": "2024-04-22T16:18:50.658027Z",
"url": "https://files.pythonhosted.org/packages/59/90/ec8be07b9cb708a689844cc6cd900ab85c0dd948e13fcc4045dd0fc559c2/amazon_braket_pennylane_plugin-1.25.0.tar.gz",
"yanked": false,
"yanked_reason": null
}
],
"upload_time": "2024-04-22 16:18:50",
"github": true,
"gitlab": false,
"bitbucket": false,
"codeberg": false,
"github_user": "amazon-braket",
"github_project": "amazon-braket-pennylane-plugin-python",
"travis_ci": false,
"coveralls": true,
"github_actions": true,
"tox": true,
"lcname": "amazon-braket-pennylane-plugin"
}
JSON
