| Name | feedbax JSON |
| Version |
0.1.2
JSON |
| download |
| home_page | |
| Summary | Optimal feedback control + interventions in JAX. |
| upload_time | 2024-03-13 14:44:59 |
| maintainer | |
| docs_url | None |
| author | |
| requires_python | >=3.11 |
| license | Apache License Version 2.0, January 2004 http://www.apache.org/licenses/ TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION 1. Definitions. "License" shall mean the terms and conditions for use, reproduction, and distribution as defined by Sections 1 through 9 of this document. "Licensor" shall mean the copyright owner or entity authorized by the copyright owner that is granting the License. "Legal Entity" shall mean the union of the acting entity and all other entities that control, are controlled by, or are under common control with that entity. For the purposes of this definition, "control" means (i) the power, direct or indirect, to cause the direction or management of such entity, whether by contract or otherwise, or (ii) ownership of fifty percent (50%) or more of the outstanding shares, or (iii) beneficial ownership of such entity. "You" (or "Your") shall mean an individual or Legal Entity exercising permissions granted by this License. "Source" form shall mean the preferred form for making modifications, including but not limited to software source code, documentation source, and configuration files. "Object" form shall mean any form resulting from mechanical transformation or translation of a Source form, including but not limited to compiled object code, generated documentation, and conversions to other media types. "Work" shall mean the work of authorship, whether in Source or Object form, made available under the License, as indicated by a copyright notice that is included in or attached to the work (an example is provided in the Appendix below). "Derivative Works" shall mean any work, whether in Source or Object form, that is based on (or derived from) the Work and for which the editorial revisions, annotations, elaborations, or other modifications represent, as a whole, an original work of authorship. For the purposes of this License, Derivative Works shall not include works that remain separable from, or merely link (or bind by name) to the interfaces of, the Work and Derivative Works thereof. "Contribution" shall mean any work of authorship, including the original version of the Work and any modifications or additions to that Work or Derivative Works thereof, that is intentionally submitted to Licensor for inclusion in the Work by the copyright owner or by an individual or Legal Entity authorized to submit on behalf of the copyright owner. For the purposes of this definition, "submitted" means any form of electronic, verbal, or written communication sent to the Licensor or its representatives, including but not limited to communication on electronic mailing lists, source code control systems, and issue tracking systems that are managed by, or on behalf of, the Licensor for the purpose of discussing and improving the Work, but excluding communication that is conspicuously marked or otherwise designated in writing by the copyright owner as "Not a Contribution." "Contributor" shall mean Licensor and any individual or Legal Entity on behalf of whom a Contribution has been received by Licensor and subsequently incorporated within the Work. 2. Grant of Copyright License. Subject to the terms and conditions of this License, each Contributor hereby grants to You a perpetual, worldwide, non-exclusive, no-charge, royalty-free, irrevocable copyright license to reproduce, prepare Derivative Works of, publicly display, publicly perform, sublicense, and distribute the Work and such Derivative Works in Source or Object form. 3. Grant of Patent License. Subject to the terms and conditions of this License, each Contributor hereby grants to You a perpetual, worldwide, non-exclusive, no-charge, royalty-free, irrevocable (except as stated in this section) patent license to make, have made, use, offer to sell, sell, import, and otherwise transfer the Work, where such license applies only to those patent claims licensable by such Contributor that are necessarily infringed by their Contribution(s) alone or by combination of their Contribution(s) with the Work to which such Contribution(s) was submitted. If You institute patent litigation against any entity (including a cross-claim or counterclaim in a lawsuit) alleging that the Work or a Contribution incorporated within the Work constitutes direct or contributory patent infringement, then any patent licenses granted to You under this License for that Work shall terminate as of the date such litigation is filed. 4. Redistribution. You may reproduce and distribute copies of the Work or Derivative Works thereof in any medium, with or without modifications, and in Source or Object form, provided that You meet the following conditions: (a) You must give any other recipients of the Work or Derivative Works a copy of this License; and (b) You must cause any modified files to carry prominent notices stating that You changed the files; and (c) You must retain, in the Source form of any Derivative Works that You distribute, all copyright, patent, trademark, and attribution notices from the Source form of the Work, excluding those notices that do not pertain to any part of the Derivative Works; and (d) If the Work includes a "NOTICE" text file as part of its distribution, then any Derivative Works that You distribute must include a readable copy of the attribution notices contained within such NOTICE file, excluding those notices that do not pertain to any part of the Derivative Works, in at least one of the following places: within a NOTICE text file distributed as part of the Derivative Works; within the Source form or documentation, if provided along with the Derivative Works; or, within a display generated by the Derivative Works, if and wherever such third-party notices normally appear. The contents of the NOTICE file are for informational purposes only and do not modify the License. You may add Your own attribution notices within Derivative Works that You distribute, alongside or as an addendum to the NOTICE text from the Work, provided that such additional attribution notices cannot be construed as modifying the License. You may add Your own copyright statement to Your modifications and may provide additional or different license terms and conditions for use, reproduction, or distribution of Your modifications, or for any such Derivative Works as a whole, provided Your use, reproduction, and distribution of the Work otherwise complies with the conditions stated in this License. 5. Submission of Contributions. Unless You explicitly state otherwise, any Contribution intentionally submitted for inclusion in the Work by You to the Licensor shall be under the terms and conditions of this License, without any additional terms or conditions. Notwithstanding the above, nothing herein shall supersede or modify the terms of any separate license agreement you may have executed with Licensor regarding such Contributions. 6. Trademarks. This License does not grant permission to use the trade names, trademarks, service marks, or product names of the Licensor, except as required for reasonable and customary use in describing the origin of the Work and reproducing the content of the NOTICE file. 7. Disclaimer of Warranty. Unless required by applicable law or agreed to in writing, Licensor provides the Work (and each Contributor provides its Contributions) on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied, including, without limitation, any warranties or conditions of TITLE, NON-INFRINGEMENT, MERCHANTABILITY, or FITNESS FOR A PARTICULAR PURPOSE. You are solely responsible for determining the appropriateness of using or redistributing the Work and assume any risks associated with Your exercise of permissions under this License. 8. Limitation of Liability. In no event and under no legal theory, whether in tort (including negligence), contract, or otherwise, unless required by applicable law (such as deliberate and grossly negligent acts) or agreed to in writing, shall any Contributor be liable to You for damages, including any direct, indirect, special, incidental, or consequential damages of any character arising as a result of this License or out of the use or inability to use the Work (including but not limited to damages for loss of goodwill, work stoppage, computer failure or malfunction, or any and all other commercial damages or losses), even if such Contributor has been advised of the possibility of such damages. 9. Accepting Warranty or Additional Liability. While redistributing the Work or Derivative Works thereof, You may choose to offer, and charge a fee for, acceptance of support, warranty, indemnity, or other liability obligations and/or rights consistent with this License. However, in accepting such obligations, You may act only on Your own behalf and on Your sole responsibility, not on behalf of any other Contributor, and only if You agree to indemnify, defend, and hold each Contributor harmless for any liability incurred by, or claims asserted against, such Contributor by reason of your accepting any such warranty or additional liability. |
| keywords |
jax
neural-networks
optimal-control
optimal-feedback-control
pytorch
biomechanics
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
# Getting started
Feedbax is a [JAX](https://jax.readthedocs.io/en/latest/beginner_guide.html#beginner-guide) library for optimal feedback control with neural networks.
Feedbax makes it easy to:
- [train](https://docs.lprt.ca/feedbax/examples/0_train_simple) a neural network to control a simulated limb (biomechanical model) to perform movement tasks;
- [intervene](https://docs.lprt.ca/feedbax/examples/3_intervening) on existing models and tasks—for example, to:
- add force fields that disturb a limb;
- alter the activity of a single unit in a neural network;
- perturb the sensory feedback received by a network;
- add any kind of noise to any part of a model's state;
- schedule an intervention to occur on only a subset of task trials or time steps;
- specify which parts of the model are [trainable](https://docs.lprt.ca/feedbax/examples/1_train/#selecting-part-of-the-model-to-train), and which states are available as sensory feedback;
- train [multiple replicates](https://docs.lprt.ca/feedbax/examples/4_vmap) of a model at once;
- swap out components of models, and write new components.
<!-- - track the progress of a training run in Tensorboard. -->
Feedbax is currently in active [development](#development). Expect some changes in the near future!
## Feedbax is a JAX library
Feedbax uses JAX and [Equinox](https://docs.kidger.site/equinox/).
[Never used JAX before](https://docs.lprt.ca/feedbax/examples/pytrees/)?
Please also check out [MotorNet](https://github.com/OlivierCodol/MotorNet), a PyTorch library with many similarities to Feedbax.
## Installation
`pip install feedbax`
Currently requires Python>=3.11.
For best performance, [install JAX](https://jax.readthedocs.io/en/latest/installation.html) with GPU support.
## Documentation
Documentation is available [here](https://docs.lprt.ca/feedbax).
## Development
I've developed Feedbax over the last few months, while learning JAX. My short-term objective has been to support my own use cases—graduate research in the neuroscience of motor control—but I've also tried to design something reusable and general.
I've added GitHub [issues](https://github.com/mlprt/feedbax/issues) to document some of my choices and uncertainties. For an overview of major issues in different categories, check out [this GitHub conversation](https://github.com/mlprt/feedbax/discussions/27). Refer also to [this page](https://docs.lprt.ca/feedbax/structure) of the docs, for an informal overview of how Feedbax objects relate to each other.
There are many features, especially pre-built models and tasks, that could still be implemented. Some of the models and tasks that *are* implemented, have yet to be fully optimized. So far I've focused more on the overall structure, than on coverage of all the common use cases I can imagine. If there's a particular model, task, or feature you'd like Feedbax to support, [let us know](https://github.com/mlprt/feedbax/issues), or contribute some code!
## Acknowledgments
- Thanks to my PhD supervisor Gunnar Blohm and to the rest of our [lab](http://compneurosci.com/), as well as to Dominik Endres and Stephen H. Scott for discussions that have directly influenced this project
- Special thanks to [Patrick Kidger](https://github.com/patrick-kidger), whose JAX libraries and their documentation often serve as examples to me
Raw data
{
"_id": null,
"home_page": "",
"name": "feedbax",
"maintainer": "",
"docs_url": null,
"requires_python": ">=3.11",
"maintainer_email": "",
"keywords": "jax,neural-networks,optimal-control,optimal-feedback-control,pytorch,biomechanics",
"author": "",
"author_email": "Matt L Laporte <matt.l.laporte@gmail.com>",
"download_url": "https://files.pythonhosted.org/packages/b0/da/a0a502f599bc609966ce005dcc8abad88feb2fcfc528d661f766533b0175/feedbax-0.1.2.tar.gz",
"platform": null,
"description": "# Getting started\n\nFeedbax is a [JAX](https://jax.readthedocs.io/en/latest/beginner_guide.html#beginner-guide) library for optimal feedback control with neural networks.\n\nFeedbax makes it easy to:\n\n- [train](https://docs.lprt.ca/feedbax/examples/0_train_simple) a neural network to control a simulated limb (biomechanical model) to perform movement tasks;\n- [intervene](https://docs.lprt.ca/feedbax/examples/3_intervening) on existing models and tasks\u2014for example, to:\n - add force fields that disturb a limb;\n - alter the activity of a single unit in a neural network;\n - perturb the sensory feedback received by a network;\n - add any kind of noise to any part of a model's state;\n- schedule an intervention to occur on only a subset of task trials or time steps;\n- specify which parts of the model are [trainable](https://docs.lprt.ca/feedbax/examples/1_train/#selecting-part-of-the-model-to-train), and which states are available as sensory feedback;\n- train [multiple replicates](https://docs.lprt.ca/feedbax/examples/4_vmap) of a model at once;\n- swap out components of models, and write new components.\n<!-- - track the progress of a training run in Tensorboard. -->\n\nFeedbax is currently in active [development](#development). Expect some changes in the near future!\n\n## Feedbax is a JAX library\n\nFeedbax uses JAX and [Equinox](https://docs.kidger.site/equinox/).\n\n[Never used JAX before](https://docs.lprt.ca/feedbax/examples/pytrees/)?\n\nPlease also check out [MotorNet](https://github.com/OlivierCodol/MotorNet), a PyTorch library with many similarities to Feedbax.\n\n## Installation\n\n`pip install feedbax`\n\nCurrently requires Python>=3.11.\n\nFor best performance, [install JAX](https://jax.readthedocs.io/en/latest/installation.html) with GPU support.\n\n## Documentation\n\nDocumentation is available [here](https://docs.lprt.ca/feedbax).\n\n## Development\n\nI've developed Feedbax over the last few months, while learning JAX. My short-term objective has been to support my own use cases\u2014graduate research in the neuroscience of motor control\u2014but I've also tried to design something reusable and general.\n\nI've added GitHub [issues](https://github.com/mlprt/feedbax/issues) to document some of my choices and uncertainties. For an overview of major issues in different categories, check out [this GitHub conversation](https://github.com/mlprt/feedbax/discussions/27). Refer also to [this page](https://docs.lprt.ca/feedbax/structure) of the docs, for an informal overview of how Feedbax objects relate to each other.\n\nThere are many features, especially pre-built models and tasks, that could still be implemented. Some of the models and tasks that *are* implemented, have yet to be fully optimized. So far I've focused more on the overall structure, than on coverage of all the common use cases I can imagine. If there's a particular model, task, or feature you'd like Feedbax to support, [let us know](https://github.com/mlprt/feedbax/issues), or contribute some code!\n\n## Acknowledgments\n\n- Thanks to my PhD supervisor Gunnar Blohm and to the rest of our [lab](http://compneurosci.com/), as well as to Dominik Endres and Stephen H. Scott for discussions that have directly influenced this project\n- Special thanks to [Patrick Kidger](https://github.com/patrick-kidger), whose JAX libraries and their documentation often serve as examples to me\n\n",
"bugtrack_url": null,
"license": "Apache License Version 2.0, January 2004 http://www.apache.org/licenses/ TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION 1. Definitions. \"License\" shall mean the terms and conditions for use, reproduction, and distribution as defined by Sections 1 through 9 of this document. \"Licensor\" shall mean the copyright owner or entity authorized by the copyright owner that is granting the License. \"Legal Entity\" shall mean the union of the acting entity and all other entities that control, are controlled by, or are under common control with that entity. For the purposes of this definition, \"control\" means (i) the power, direct or indirect, to cause the direction or management of such entity, whether by contract or otherwise, or (ii) ownership of fifty percent (50%) or more of the outstanding shares, or (iii) beneficial ownership of such entity. \"You\" (or \"Your\") shall mean an individual or Legal Entity exercising permissions granted by this License. \"Source\" form shall mean the preferred form for making modifications, including but not limited to software source code, documentation source, and configuration files. \"Object\" form shall mean any form resulting from mechanical transformation or translation of a Source form, including but not limited to compiled object code, generated documentation, and conversions to other media types. \"Work\" shall mean the work of authorship, whether in Source or Object form, made available under the License, as indicated by a copyright notice that is included in or attached to the work (an example is provided in the Appendix below). \"Derivative Works\" shall mean any work, whether in Source or Object form, that is based on (or derived from) the Work and for which the editorial revisions, annotations, elaborations, or other modifications represent, as a whole, an original work of authorship. For the purposes of this License, Derivative Works shall not include works that remain separable from, or merely link (or bind by name) to the interfaces of, the Work and Derivative Works thereof. \"Contribution\" shall mean any work of authorship, including the original version of the Work and any modifications or additions to that Work or Derivative Works thereof, that is intentionally submitted to Licensor for inclusion in the Work by the copyright owner or by an individual or Legal Entity authorized to submit on behalf of the copyright owner. For the purposes of this definition, \"submitted\" means any form of electronic, verbal, or written communication sent to the Licensor or its representatives, including but not limited to communication on electronic mailing lists, source code control systems, and issue tracking systems that are managed by, or on behalf of, the Licensor for the purpose of discussing and improving the Work, but excluding communication that is conspicuously marked or otherwise designated in writing by the copyright owner as \"Not a Contribution.\" \"Contributor\" shall mean Licensor and any individual or Legal Entity on behalf of whom a Contribution has been received by Licensor and subsequently incorporated within the Work. 2. Grant of Copyright License. Subject to the terms and conditions of this License, each Contributor hereby grants to You a perpetual, worldwide, non-exclusive, no-charge, royalty-free, irrevocable copyright license to reproduce, prepare Derivative Works of, publicly display, publicly perform, sublicense, and distribute the Work and such Derivative Works in Source or Object form. 3. Grant of Patent License. Subject to the terms and conditions of this License, each Contributor hereby grants to You a perpetual, worldwide, non-exclusive, no-charge, royalty-free, irrevocable (except as stated in this section) patent license to make, have made, use, offer to sell, sell, import, and otherwise transfer the Work, where such license applies only to those patent claims licensable by such Contributor that are necessarily infringed by their Contribution(s) alone or by combination of their Contribution(s) with the Work to which such Contribution(s) was submitted. If You institute patent litigation against any entity (including a cross-claim or counterclaim in a lawsuit) alleging that the Work or a Contribution incorporated within the Work constitutes direct or contributory patent infringement, then any patent licenses granted to You under this License for that Work shall terminate as of the date such litigation is filed. 4. Redistribution. You may reproduce and distribute copies of the Work or Derivative Works thereof in any medium, with or without modifications, and in Source or Object form, provided that You meet the following conditions: (a) You must give any other recipients of the Work or Derivative Works a copy of this License; and (b) You must cause any modified files to carry prominent notices stating that You changed the files; and (c) You must retain, in the Source form of any Derivative Works that You distribute, all copyright, patent, trademark, and attribution notices from the Source form of the Work, excluding those notices that do not pertain to any part of the Derivative Works; and (d) If the Work includes a \"NOTICE\" text file as part of its distribution, then any Derivative Works that You distribute must include a readable copy of the attribution notices contained within such NOTICE file, excluding those notices that do not pertain to any part of the Derivative Works, in at least one of the following places: within a NOTICE text file distributed as part of the Derivative Works; within the Source form or documentation, if provided along with the Derivative Works; or, within a display generated by the Derivative Works, if and wherever such third-party notices normally appear. The contents of the NOTICE file are for informational purposes only and do not modify the License. You may add Your own attribution notices within Derivative Works that You distribute, alongside or as an addendum to the NOTICE text from the Work, provided that such additional attribution notices cannot be construed as modifying the License. You may add Your own copyright statement to Your modifications and may provide additional or different license terms and conditions for use, reproduction, or distribution of Your modifications, or for any such Derivative Works as a whole, provided Your use, reproduction, and distribution of the Work otherwise complies with the conditions stated in this License. 5. Submission of Contributions. Unless You explicitly state otherwise, any Contribution intentionally submitted for inclusion in the Work by You to the Licensor shall be under the terms and conditions of this License, without any additional terms or conditions. Notwithstanding the above, nothing herein shall supersede or modify the terms of any separate license agreement you may have executed with Licensor regarding such Contributions. 6. Trademarks. This License does not grant permission to use the trade names, trademarks, service marks, or product names of the Licensor, except as required for reasonable and customary use in describing the origin of the Work and reproducing the content of the NOTICE file. 7. Disclaimer of Warranty. Unless required by applicable law or agreed to in writing, Licensor provides the Work (and each Contributor provides its Contributions) on an \"AS IS\" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied, including, without limitation, any warranties or conditions of TITLE, NON-INFRINGEMENT, MERCHANTABILITY, or FITNESS FOR A PARTICULAR PURPOSE. You are solely responsible for determining the appropriateness of using or redistributing the Work and assume any risks associated with Your exercise of permissions under this License. 8. Limitation of Liability. In no event and under no legal theory, whether in tort (including negligence), contract, or otherwise, unless required by applicable law (such as deliberate and grossly negligent acts) or agreed to in writing, shall any Contributor be liable to You for damages, including any direct, indirect, special, incidental, or consequential damages of any character arising as a result of this License or out of the use or inability to use the Work (including but not limited to damages for loss of goodwill, work stoppage, computer failure or malfunction, or any and all other commercial damages or losses), even if such Contributor has been advised of the possibility of such damages. 9. Accepting Warranty or Additional Liability. While redistributing the Work or Derivative Works thereof, You may choose to offer, and charge a fee for, acceptance of support, warranty, indemnity, or other liability obligations and/or rights consistent with this License. However, in accepting such obligations, You may act only on Your own behalf and on Your sole responsibility, not on behalf of any other Contributor, and only if You agree to indemnify, defend, and hold each Contributor harmless for any liability incurred by, or claims asserted against, such Contributor by reason of your accepting any such warranty or additional liability. ",
"summary": "Optimal feedback control + interventions in JAX.",
"version": "0.1.2",
"project_urls": {
"repository": "https://github.com/mlprt/feedbax"
},
"split_keywords": [
"jax",
"neural-networks",
"optimal-control",
"optimal-feedback-control",
"pytorch",
"biomechanics"
],
"urls": [
{
"comment_text": "",
"digests": {
"blake2b_256": "19643eea7106ffa6cb359ebc528d682dc226bb35b3c33b10fbe40d805de835e1",
"md5": "7d1eb72a34e86f2a50a96251d97ee8ad",
"sha256": "af785aadab5e86c20bec4176d859fc19d47587453cfe0c2fbcf46d137c6036a0"
},
"downloads": -1,
"filename": "feedbax-0.1.2-py3-none-any.whl",
"has_sig": false,
"md5_digest": "7d1eb72a34e86f2a50a96251d97ee8ad",
"packagetype": "bdist_wheel",
"python_version": "py3",
"requires_python": ">=3.11",
"size": 84425,
"upload_time": "2024-03-13T14:44:57",
"upload_time_iso_8601": "2024-03-13T14:44:57.975911Z",
"url": "https://files.pythonhosted.org/packages/19/64/3eea7106ffa6cb359ebc528d682dc226bb35b3c33b10fbe40d805de835e1/feedbax-0.1.2-py3-none-any.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": "",
"digests": {
"blake2b_256": "b0daa0a502f599bc609966ce005dcc8abad88feb2fcfc528d661f766533b0175",
"md5": "ad9be5a8e11a382dd4089e4ef69c11dc",
"sha256": "470a7dd6332e5f53ba3974c45d678d2a85c21f998f625d3243f71fae64d633cd"
},
"downloads": -1,
"filename": "feedbax-0.1.2.tar.gz",
"has_sig": false,
"md5_digest": "ad9be5a8e11a382dd4089e4ef69c11dc",
"packagetype": "sdist",
"python_version": "source",
"requires_python": ">=3.11",
"size": 77753,
"upload_time": "2024-03-13T14:44:59",
"upload_time_iso_8601": "2024-03-13T14:44:59.241967Z",
"url": "https://files.pythonhosted.org/packages/b0/da/a0a502f599bc609966ce005dcc8abad88feb2fcfc528d661f766533b0175/feedbax-0.1.2.tar.gz",
"yanked": false,
"yanked_reason": null
}
],
"upload_time": "2024-03-13 14:44:59",
"github": true,
"gitlab": false,
"bitbucket": false,
"codeberg": false,
"github_user": "mlprt",
"github_project": "feedbax",
"travis_ci": false,
"coveralls": false,
"github_actions": true,
"lcname": "feedbax"
}
