Unverified Commit 1ee7a26d authored by Mayank Mittal's avatar Mayank Mittal Committed by GitHub

Adds information about Orbit and Isaac ecosystem (#24)

* adds info on orbit in isaac ecosystem
* simplifies developer guide
* updates roadmap
* adds isaacsim version note
* fixes the bibtex entry
parent ce8c1c01
......@@ -14,18 +14,21 @@ and efficient simulation.
If you use ``orbit`` in your work, please cite the `paper <https://arxiv.org/abs/2301.04195>`_
using the following BibTeX entry:
:cite:`mittal2023orbit` using the following BibTeX entry:
.. code-block:: bibtex
@misc{mittal2023orbit,
author = {Mayank Mittal and Calvin Yu and Qinxi Yu and Jingzhou Liu and Nikita Rudin and David Hoeller and Jia Lin Yuan and Pooria Poorsarvi Tehrani and Ritvik Singh and Yunrong Guo and Hammad Mazhar and Ajay Mandlekar and Buck Babich and Gavriel State and Marco Hutter and Animesh Garg},
title = {ORBIT: A Unified Simulation Framework for Interactive Robot Learning Environments},
year = {2023},
eprint = {arXiv:2301.04195},
@article{mittal2023orbit,
author={Mittal, Mayank and Yu, Calvin and Yu, Qinxi and Liu, Jingzhou and Rudin, Nikita and Hoeller, David and Yuan, Jia Lin and Singh, Ritvik and Guo, Yunrong and Mazhar, Hammad and Mandlekar, Ajay and Babich, Buck and State, Gavriel and Hutter, Marco and Garg, Animesh},
journal={IEEE Robotics and Automation Letters},
title={Orbit: A Unified Simulation Framework for Interactive Robot Learning Environments},
year={2023},
volume={8},
number={6},
pages={3740-3747},
doi={10.1109/LRA.2023.3270034}
}
.. toctree::
:maxdepth: 2
:caption: Getting Started
......@@ -70,6 +73,7 @@ using the following BibTeX entry:
:maxdepth: 1
:caption: References
source/refs/faq
source/refs/contributing
source/refs/troubleshooting
source/refs/issues
......
......@@ -97,3 +97,45 @@
pages={3019-3026},
doi={10.1109/LRA.2018.2849506}
}
@article{makoviychuk2021isaac,
title={Isaac gym: High performance gpu-based physics simulation for robot learning},
author={Makoviychuk, Viktor and Wawrzyniak, Lukasz and Guo, Yunrong and Lu, Michelle and Storey, Kier and Macklin, Miles and Hoeller, David and Rudin, Nikita and Allshire, Arthur and Handa, Ankur and others},
journal={arXiv preprint arXiv:2108.10470},
year={2021}
}
@article{handa2022dextreme,
title={DeXtreme: Transfer of Agile In-hand Manipulation from Simulation to Reality},
author={Handa, Ankur and Allshire, Arthur and Makoviychuk, Viktor and Petrenko, Aleksei and Singh, Ritvik and Liu, Jingzhou and Makoviichuk, Denys and Van Wyk, Karl and Zhurkevich, Alexander and Sundaralingam, Balakumar and others},
journal={arXiv preprint arXiv:2210.13702},
year={2022}
}
@article{narang2022factory,
title={Factory: Fast contact for robotic assembly},
author={Narang, Yashraj and Storey, Kier and Akinola, Iretiayo and Macklin, Miles and Reist, Philipp and Wawrzyniak, Lukasz and Guo, Yunrong and Moravanszky, Adam and State, Gavriel and Lu, Michelle and others},
journal={arXiv preprint arXiv:2205.03532},
year={2022}
}
@inproceedings{allshire2022transferring,
title={Transferring dexterous manipulation from gpu simulation to a remote real-world trifinger},
author={Allshire, Arthur and MittaI, Mayank and Lodaya, Varun and Makoviychuk, Viktor and Makoviichuk, Denys and Widmaier, Felix and W{\"u}thrich, Manuel and Bauer, Stefan and Handa, Ankur and Garg, Animesh},
booktitle={2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},
pages={11802--11809},
year={2022},
organization={IEEE}
}
@article{mittal2023orbit,
author={Mittal, Mayank and Yu, Calvin and Yu, Qinxi and Liu, Jingzhou and Rudin, Nikita and Hoeller, David and Yuan, Jia Lin and Singh, Ritvik and Guo, Yunrong and Mazhar, Hammad and Mandlekar, Ajay and Babich, Buck and State, Gavriel and Hutter, Marco and Garg, Animesh},
journal={IEEE Robotics and Automation Letters},
title={Orbit: A Unified Simulation Framework for Interactive Robot Learning Environments},
year={2023},
volume={8},
number={6},
pages={3740-3747},
doi={10.1109/LRA.2023.3270034}
}
......@@ -63,6 +63,10 @@ for code comments and layout,
`PEP-585 <https://www.python.org/dev/peps/pep-0585/>`__ for
type-hinting.
For documentation, we adopt the `Google Style Guide <https://sphinxcontrib-napoleon.readthedocs.io/en/latest/example_google.html>`__
for docstrings. We use `Sphinx <https://www.sphinx-doc.org/en/master/>`__ for generating the documentation.
Please make sure that your code is well-documented and follows the guidelines.
We use the following tools for maintaining code quality:
* `pre-commit <https://pre-commit.com/>`__: Runs a list of formatters and linters over the codebase.
......@@ -78,6 +82,88 @@ following command in the terminal:
./orbit.sh --format # or `./orbit.sh -f`
Contributing Documentation
--------------------------
Contributing to the documentation is as easy as contributing to the codebase. All the source files
for the documentation are located in the ``orbit/docs`` directory. The documentation is written in
`reStructuredText <https://docutils.sourceforge.io/rst.html>`__ format.
We use `Sphinx <https://www.sphinx-doc.org/en/master/>`__ with the
`Book Theme <https://sphinx-book-theme.readthedocs.io/en/stable/>`__
for maintaining the documentation.
Sending a pull request for the documentation is the same as sending a pull request for the codebase.
Please follow the steps mentioned in the `Contributing Code`_ section.
.. caution::
To build the documentation, we recommend creating a `virtual environment <https://docs.python.org/3/library/venv.html>`__
to install the dependencies. This can also be a `conda environment <https://docs.conda.io/projects/conda/en/latest/user-guide/tasks/manage-environments.html>`__.
To build the documentation, run the following command in the terminal which installs the required python packages and
builds the documentation using the ``docs/Makefile``:
.. code:: bash
./orbit.sh --docs # or `./orbit.sh -d`
The documentation is generated in the ``docs/_build`` directory. To view the documentation, open
the ``index.html`` file in the ``html`` directory. This can be done by running the following command
in the terminal:
.. code:: bash
xdg-open docs/_build/html/index.html
.. hint::
The ``xdg-open`` command is used to open the ``index.html`` file in the default browser. If you are
using a different operating system, you can use the appropriate command to open the file in the browser.
To do a clean build, run the following command in the terminal:
.. code:: bash
rm -rf docs/_build && ./orbit.sh --docs
Contributing assets
-------------------
Currently, we host the assets for the extensions on `NVIDIA Nucleus Server <https://docs.omniverse.nvidia.com/prod_nucleus/prod_nucleus/overview.html>`__.
Nucleus is a cloud-based storage service that allows users to store and share large files. It is
integrated with the `NVIDIA Omniverse Platform <https://developer.nvidia.com/omniverse>`__.
Since all assets are hosted on Nucleus, we do not need to include them in the repository. However,
we need to include the links to the assets in the documentation.
The included assets are part of the `Isaac Sim Content <https://docs.omniverse.nvidia.com/app_isaacsim/app_isaacsim/reference_assets.html>`__.
To use this content, you need to download the files to a Nucleus server or create an **Isaac** Mount on
a Nucleus server.
Please check the `Isaac Sim documentation <https://docs.omniverse.nvidia.com/app_isaacsim/app_isaacsim/install_faq.html#assets-and-nucleus>`__
for more information on how to download the assets.
.. attention::
We are currently working on a better way to contribute assets. We will update this section once we
have a solution. In the meantime, please follow the steps mentioned below.
To host your own assets, the current solution is:
1. Create a separate repository for the assets and add it over there
2. Make sure the assets are licensed for use and distribution
3. Include images of the assets in the README file of the repository
4. Send a pull request with a link to the repository
We will then verify the assets, its licensing, and include the assets into the Nucleus server for hosting.
In case you have any questions, please feel free to reach out to us through e-mail or by opening an issue
in the repository.
Maintaining a changelog
-----------------------
......@@ -146,85 +232,3 @@ For example, the following is a sample changelog:
^^^^^
* Added a new feature.
Contributing Documentation
--------------------------
Contributing to the documentation is as easy as contributing to the codebase. All the source files
for the documentation are located in the ``orbit/docs`` directory. The documentation is written in
`reStructuredText <https://docutils.sourceforge.io/rst.html>`__ format.
We use `Sphinx <https://www.sphinx-doc.org/en/master/>`__ with the
`Book Theme <https://sphinx-book-theme.readthedocs.io/en/stable/>`__
for maintaining the documentation.
Sending a pull request for the documentation is the same as sending a pull request for the codebase.
Please follow the steps mentioned in the `Contributing Code`_ section.
To build the documentation, we recommend creating a `virtual environment <https://docs.python.org/3/library/venv.html>`__
to install the dependencies. This can also be a `conda environment <https://docs.conda.io/projects/conda/en/latest/user-guide/tasks/manage-environments.html>`__.
Execute the following commands in the terminal:
1. Enter the ``orbit/docs`` directory.
.. code:: bash
# enter the location of the docs directory (relative to the root of the repository)
cd docs
2. Install the dependencies (preferably in a virtual/conda environment).
.. code:: bash
# install the dependencies
pip install -r requirements.txt
3. Build the documentation.
.. code:: bash
# build the documentation
make html
4. Open the documentation in a browser.
.. code:: bash
# open the documentation in a browser
xdg-open _build/html/index.html
Contributing assets
-------------------
Currently, we host the assets for the extensions on `NVIDIA Nucleus Server <https://docs.omniverse.nvidia.com/prod_nucleus/prod_nucleus/overview.html>`__.
Nucleus is a cloud-based storage service that allows users to store and share large files. It is
integrated with the `NVIDIA Omniverse Platform <https://developer.nvidia.com/omniverse>`__.
Since all assets are hosted on Nucleus, we do not need to include them in the repository. However,
we need to include the links to the assets in the documentation.
The included assets are part of the `Isaac Sim Content <https://docs.omniverse.nvidia.com/app_isaacsim/app_isaacsim/reference_assets.html>`__.
To use this content, you need to download the files to a Nucleus server or create an **Isaac** Mount on
a Nucleus server.
Please check the `Isaac Sim documentation <https://docs.omniverse.nvidia.com/app_isaacsim/app_isaacsim/install_faq.html#assets-and-nucleus>`__
for more information on how to download the assets.
.. attention::
We are currently working on a better way to contribute assets. We will update this section once we
have a solution. In the meantime, please follow the steps mentioned below.
To host your own assets, the current solution is:
1. Create a separate repository for the assets and add it over there
2. Make sure the assets are licensed for use and distribution
3. Include images of the assets in the README file of the repository
4. Send a pull request with a link to the repository
We will then verify the assets, its licensing, and include the assets into the Nucleus server for hosting.
In case you have any questions, please feel free to reach out to us through e-mail or by opening an issue
in the repository.
Frequently Asked Questions
==========================
Where does Orbit fit in the Isaac ecosystem?
--------------------------------------------
.. attention::
This section is based on the author's understanding of the Isaac ecosystem and is not an official
statement from NVIDIA.
Over the years, NVIDIA has developed a number of tools for robotics and AI. These tools leverage
the power of GPUs to accelerate the simulation both in terms of speed and realism. They show great
promise in the field of simulation technology and are being used by many researchers and companies
worldwide.
`Isaac Gym`_ :cite:`makoviychuk2021isaac` provides a high performance GPU-based physics simulation
for robot learning. It is built on top of `PhysX`_ which supports GPU-accelerated simulation of rigid bodies
and a Python API to directly access physics simulation data. Through an end-to-end GPU pipeline, it is possible
to achieve high frame rates compared to CPU-based physics engines. The tool has been used successfully in a
number of research projects, including legged locomotion :cite:`rudin2022learning` :cite:`rudin2022advanced`,
in-hand manipulation :cite:`handa2022dextreme` :cite:`allshire2022transferring`, and industrial assembly
:cite:`narang2022factory`.
Despite the success of Isaac Gym, it is not designed to be a general purpose simulator for
robotics. For example, it does not include interaction between deformable and rigid objects, high-fidelity
rendering, and support for ROS. The tool has been primarily designed as a preview release to showcase the
capabilities of the underlying physics engine. With the release of `Isaac Sim`_, NVIDIA is building
a general purpose simulator for robotics and has integrated the functionalities of Isaac Gym into
Isaac Sim.
`Isaac Sim`_ is a robot simulation toolkit built on top of Omniverse, which is a general purpose platform
that aims to unite complex 3D workflows. Isaac Sim leverages the latest advances in graphics and
physics simulation to provide a high-fidelity simulation environment for robotics. It supports
ROS/ROS2, various sensor simulation, tools for domain randomization and synthetic data creation.
Overall, it is a powerful tool for roboticists and is a huge step forward in the field of robotics
simulation.
With the release of above two tools, NVIDIA also released an open-sourced set of environments called
`IsaacGymEnvs`_ and `OmniIsaacGymEnvs`_, that have been built on top of Isaac Gym and Isaac Sim respectively.
These environments have been designed to display the capabilities of the underlying simulators and provide
a starting point to understand what is possible with the simulators for robot learning. These environments
can be used for benchmarking but are not designed for developing and testing custom environments and algorithms.
This is where ``orbit`` comes in.
Orbit :cite:`mittal2023orbit` is built on top of Isaac Sim to provide a unified and flexible framework
for robot learning that exploits latest simulation technologies. It is designed to be modular and extensible,
and aims to simplify common workflows in robotics research (such as RL, learning from demonstrations, and
motion planning). The main goals of the framework are summarized as follows:
- **Modularity**: It is possible to easily add new environments, sensors, and tasks. It is also possible
to easily swap out different components to suit the needs of the user.
- **Agility**: While still dependant on Isaac Sim, the framework includes pre-release features that
are not yet available in Isaac Sim. This allows the framework to be more agile and adapt to the
changing needs of the community.
- **Openness**: The framework is designed to be open-sourced. This makes it possible to easily
integrate with other tools and environments from the robotics community with long-term support and
maintenance.
- **Battery-included**: The framework includes a number of environments, sensors, and tasks that are
ready to use. This allows researchers to get started quickly and focus on their research. It also
includes a number of examples to showcase the capabilities of the framework.
While it includes some pre-built environments, sensors, and tasks, its main goal is to provide an open-sourced,
unified and easy-to-use interface for developing and testing custom environments and robot learning algorithms.
While it inherits the capabilities of Isaac Sim, it also adds a number of new features that pertain to robot
learning research. For example, including actuator dynamics in the simulation and support to collect data from
human demonstrations.
Where does the name come from?
------------------------------
"Orbit" suggests a sense of movement circling around a central point. For us, this symbolizes bringing
together the different components and paradigms centered around robot learning, and making a unified
ecosystem for it.
The name further connotes modularity and flexibility. Similar to planets in a solar system at different speeds
and positions, the framework is designed to not be rigid or inflexible. Rather, it aims to provide the users
the ability to adjust and move around the different components to suit their needs.
Finally, the name "orbit" also suggests a sense of exploration and discovery. We hope that the framework will
provide a platform for researchers to explore and discover new ideas and paradigms in robot learning.
Why should I use Orbit?
-----------------------
Since Isaac Sim remains closed-sourced, it is difficult for users to contribute to the simulator and build a
common framework for research. On its current path, we see the community using the simulator will simply
develop their own frameworks that will result in scattered efforts with a lot of duplication of work.
This has happened in the past with other simulators, and we believe that it is not the best way to move
forward as a community.
Orbit provides an open-sourced platform for the community to drive progress with consolidated efforts
toward designing benchmarks and robot learning systems as a joint initiative. This allows us to reuse
existing components and algorithms, and to build on top of each other's work. Doing so not only saves
time and effort, but also allows us to focus on the more important aspects of research. Our hope with
Orbit is that it becomes the de-facto platform for robot learning research and an environment *zoo*
that leverages Isaac Sim. As the framework matures, we foresee it benefitting hugely from the latest
simulation developments (as part of internal developments at NVIDIA and collaborating partners)
and research in robotics.
We are already working with labs in universities and research institutions to integrate their work into Orbit
and hope that others in the community will join us too in this effort. If you are interested in contributing
to Orbit, please reach out to us at `email <mailto:mittalma@ethz.ch>`_.
.. _PhysX: https://developer.nvidia.com/physx-sdk
.. _Isaac Sim: https://developer.nvidia.com/isaac-sim
.. _Isaac Gym: https://developer.nvidia.com/isaac-gym
.. _IsaacGymEnvs: https://github.com/NVIDIA-Omniverse/IsaacGymEnvs
.. _OmniIsaacGymEnvs: https://github.com/NVIDIA-Omniverse/OmniIsaacGymEnvs
Known issues
============
Regression in Isaac Sim 2022.2.1
--------------------------------
In Isaac Sim 2022.2.1, we have noticed the following regression and issues that should be fixed in the
next release:
* The RTX-Lidar sensor does not work properly and returns empty data.
* The :class:`ArticulationView` class leads to issues when using GPU-physics pipeline.
* The :class:`UrdfImporter` does not load the off-diagonal elements of the inertia matrix properly. This
leads to incorrect physics simulation of the robot.
Due to this regression, we recommend using Isaac Sim 2022.2.0 for now. We will update this section once
the issues are fixed in a future release.
Blank initial frames from the camera
------------------------------------
......
......@@ -48,10 +48,17 @@ If you have any questions or suggestions, let us know on
* |check_| Support for conda virtual environment
* |check_| Example of using warp-based state machine for task-space manipulation
* |uncheck| Example on using the APIs in an Omniverse extension
**April or May 2023**
.. attention::
Unfortunately, due to various deadlines, the development of Orbit has been paused for the months of
April and May. One of the many reasons for this is that we are working on a new version of Isaac Sim
(2023.1.0) which brings in a lot of new features and improvements. We will resume the development of
Orbit in June.
**June 2023**
* |uncheck| Example on using the APIs in an Omniverse extension
* |uncheck| Add APIs for rough terrain generation
* |uncheck| Extend MDP manager classes to use sensor observations
......@@ -68,30 +75,28 @@ If you have any questions or suggestions, let us know on
* |uncheck| Quardupeds: Unitree B1, Unitree Go1
* |uncheck| Arms: Kinova Jaco2, Kinova Gen3, Sawyer, UR10e
* |uncheck| Mobile manipulators: Fetch
* |uncheck| Mobile manipulators: Fetch, PR2
* Included environments
* |uncheck| locomotion: rough terrain for legged robots
* |uncheck| rigid-object manipulation: in-hand manipulation, hockey puck pushing, peg-in-hole, stacking
* |uncheck| deformable-object manipulation: cloth folding, cloth lifting
**May 2023**
**July 2023**
* Update environments to use `gym.Env` interface from `Gymnasium <https://github.com/Farama-Foundation/Gymnasium>`_
* Supported sensors
* |uncheck| Stabilize APIs and release 1.0
* Supported sensors (depends on Isaac Sim 2023.1.0 release)
* |uncheck| Cameras (parallelized)
**August 2023**
* Included environments
* |uncheck| deformable-object manipulation: cloth folding, cloth lifting
* |uncheck| deformable-object manipulation: fluid transfer, fluid pouring, soft object lifting
**June 2023**
* |uncheck| Stabilize APIs and release 1.0
.. |check| raw:: html
<input checked="" type="checkbox">
......
......@@ -231,66 +231,3 @@ provided by ``orbit``. These applications are written in python and are structur
These include a random policy, zero-action policy, teleoperation or scripted state machines.
* **workflows**: Contains applications for using environments with various learning-based frameworks. These include different
reinforcement learning or imitation learning libraries.
Building the documentation locally
----------------------------------
The documentation for ``orbit`` is generated using `Sphinx <https://www.sphinx-doc.org/en/master/>`__.
It is written in `reStructuredText <https://docutils.sourceforge.io/rst.html>`__ format and
is located in the ``docs`` directory. We use the `sphinx-book-theme <https://sphinx-book-theme.readthedocs.io/en/stable/>`__
for the documentation theme.
.. caution::
To build the documentation, we recommend creating a virtual environment to avoid any conflicts
with the python packages installed in the system.
To build the documentation, run the following command in the terminal which installs the required python packages and
builds the documentation using the ``docs/Makefile``:
.. code:: bash
./orbit.sh --docs # or `./orbit.sh -d`
The documentation is generated in the ``docs/_build`` directory. To view the documentation, open
the ``index.html`` file in the ``html`` directory. This can be done by running the following command
in the terminal:
.. code:: bash
xdg-open docs/_build/html/index.html
.. hint::
The ``xdg-open`` command is used to open the ``index.html`` file in the default browser. If you are
using a different operating system, you can use the appropriate command to open the file in the browser.
To do a clean build, run the following command in the terminal:
.. code:: bash
rm -rf docs/_build && ./orbit.sh --docs
Code style
----------
The code style used in ``orbit`` is based on the `Google Python Style Guide <https://google.github.io/styleguide/pyguide.html>`__.
For Python code, the PEP guidelines are followed. Most important ones are `PEP-8 <https://www.python.org/dev/peps/pep-0008/>`__
for code comments and layout, `PEP-484 <http://www.python.org/dev/peps/pep-0484>`__ and
`PEP-585 <https://www.python.org/dev/peps/pep-0585/>`__ for type-hinting.
We use `pre-commit <https://pre-commit.com/>`__ checks, that runs
the `black <https://black.readthedocs.io/en/stable/>`__ formatter and
`flake8 <https://flake8.pycqa.org/en/latest/>`__ to check the code.
Please check `here <https://pre-commit.com/#install>`__ for instructions
to set this up.
To run over the entire repository, please execute the following command in the terminal:
.. code:: bash
./orbit.sh --format # or `./orbit.sh -f`
......@@ -17,6 +17,12 @@ Installation Guide
Installing Isaac Sim
--------------------
.. caution::
We have observed a few issues with the Isaac Sim 2022.2.1 release. We recommend using the
Isaac Sim 2022.2.0 release. For more information, please check the :doc:`/source/refs/issues` page.
Downloading pre-built binaries
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
......@@ -28,7 +34,7 @@ To check the minimum system requirements,refer to the documentation
`here <https://docs.omniverse.nvidia.com/app_isaacsim/app_isaacsim/requirements.html>`__.
.. note::
We have tested ORBIT with Isaac Sim 2022.2 release on Ubuntu
We have tested ORBIT with Isaac Sim 2022.2.0 release on Ubuntu
20.04LTS with NVIDIA driver 515.76.
Configuring the environment variables
......@@ -109,6 +115,16 @@ Installing Orbit
Organizing the workspace
~~~~~~~~~~~~~~~~~~~~~~~~
.. note::
We recommend making a `fork <https://github.com/NVIDIA-Omniverse/Orbit/fork>`_ of the ``orbit`` repository to contribute
to the project. This is not mandatory to use the framework. If you
make a fork, please replace ``NVIDIA-Omniverse`` with your username
in the following instructions.
If you are not familiar with git, we recommend following the `git
tutorial <https://git-scm.com/book/en/v2/Getting-Started-Git-Basics>`__.
- Clone the ``orbit`` repository into your workspace:
.. code:: bash
......@@ -179,21 +195,27 @@ use the following command:
.. code:: bash
# Option 1: Default name for conda environment is 'orbit'
./orbit.sh --conda # or `./orbit.sh -c`
# Option 2: Custom name for conda environment
./orbit.sh --conda my_env # or `./orbit.sh -c my_env`
If you are using ``conda`` to create a virtual environment, make sure to
activate the environment before running any scripts. For example:
.. note::
.. code:: bash
If you are using ``conda`` to create a virtual environment, make sure to
activate the environment before running any scripts. For example:
conda activate orbit # or `conda activate my_env`
.. code:: bash
Once you are in the virtual environment, you do not need to use ``./orbit.sh -p``
to run python scripts. You can use the default python executable in your environment.
conda activate orbit
As an example, you can run the following command to check if the virtual environment is
set up correctly:
Once you are in the virtual environment, you do not need to use ``./orbit.sh -p``
to run python scripts. You can use the default python executable in your environment.
.. code:: bash
python -c "import omni.isaac.orbit; print('Orbit configuration is now complete.')"
Building extensions
~~~~~~~~~~~~~~~~~~~
......
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