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Signed-off-by: Raul Sanchez-Mateos <[email protected]>
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amlip_demo_nodes/amlip_collaborative_learning_demo/README.md

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@@ -33,7 +33,7 @@ Create a AML-IP-ws directory and download the repos file that will be used to in
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mkdir ~/AML-IP-ws
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cd ~/AML-IP-ws
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mkdir src
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wget https://raw.githubusercontent.com/eProsima/AML-IP/main/amlip.repos
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wget https://raw.githubusercontent.com/eProsima/AML-IP/v0.1.0/amlip.repos
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vcs import src < amlip.repos
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```
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amlip_demo_nodes/amlip_tensorflow_inference_demo/README.md

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mkdir ~/AML-IP-ws
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cd ~/AML-IP-ws
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mkdir src
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wget https://raw.githubusercontent.com/eProsima/AML-IP/main/amlip.repos
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wget https://raw.githubusercontent.com/eProsima/AML-IP/v0.1.0/amlip.repos
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vcs import src < amlip.repos
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```
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amlip_demo_nodes/amlip_tensorflow_inference_rosbot2r_demo/README.md

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mkdir ~/AML-IP-ws
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cd ~/AML-IP-ws
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mkdir src
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wget https://raw.githubusercontent.com/eProsima/AML-IP/main/amlip.repos
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wget https://raw.githubusercontent.com/eProsima/AML-IP/v0.1.0/amlip.repos
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vcs import src < amlip.repos
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```
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## Docker
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If using Docker instead, build a Docker image from the given [Dockerfile](https://github.com/eProsima/AML-IP/blob/main/amlip_demo_nodes/amlip_tensorflow_inference_demo/Dockerfile) with all required dependencies already installed.
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If using Docker instead, build a Docker image from the given [Dockerfile](https://github.com/eProsima/AML-IP/blob/v0.1.0/amlip_demo_nodes/amlip_tensorflow_inference_demo/Dockerfile) with all required dependencies already installed.
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In order to do so, execute the following to build the docker image:
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```bash

amlip_demo_nodes/amlip_workload_distribution_demo/README.md

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```sh
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mkdir src
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wget https://raw.githubusercontent.com/eProsima/AML-IP/main/amlip.repos
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wget https://raw.githubusercontent.com/eProsima/AML-IP/v0.1.0/amlip.repos
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vcs import src < amlip.repos
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colcon build --packages-up-to amlip_demo_nodes
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source install/setup.bash

amlip_docs/rst/demo/collaborative_learning.rst

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It does not use real *AML Models*, but strings.
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It is implemented in |python| using :code:`amlip_py` API.
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This code can be found `here <https://github.com/eProsima/AML-IP/blob/main/amlip_demo_nodes/amlip_collaborative_learning_demo/amlip_collaborative_learning_demo/model_receiver_custom.py>`__.
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This code can be found `here <https://github.com/eProsima/AML-IP/blob/v0.1.0/amlip_demo_nodes/amlip_collaborative_learning_demo/amlip_collaborative_learning_demo/model_receiver_custom.py>`__.
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The next block includes the Python header files that allow the use of the AML-IP Python API.
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It does not have a real *AML Engine* but instead the calculation is an *upper-case* conversion of the string received.
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It is implemented in |python| using :code:`amlip_py` API.
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This code can be found `here <https://github.com/eProsima/AML-IP/blob/main/amlip_demo_nodes/amlip_collaborative_learning_demo/amlip_collaborative_learning_demo/model_sender_custom.py>`__.
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This code can be found `here <https://github.com/eProsima/AML-IP/blob/v0.1.0/amlip_demo_nodes/amlip_collaborative_learning_demo/amlip_collaborative_learning_demo/model_sender_custom.py>`__.
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The next block includes the Python header files that allow the use of the AML-IP Python API.
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amlip_docs/rst/demo/rosbot2r_inference.rst

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====================
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The Docker Compose used for the demo is ``compose.yaml``.
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You can find it `here <https://github.com/eProsima/AML-IP/blob/main/amlip_demo_nodes/amlip_tensorflow_inference_rosbot2r_demo/compose.yaml>`__.
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You can find it `here <https://github.com/eProsima/AML-IP/blob/v0.1.0/amlip_demo_nodes/amlip_tensorflow_inference_rosbot2r_demo/compose.yaml>`__.
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The Docker Compose launches the following containers:
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In this specific scenario, the data source is the camera of the robot.
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The Python code for the Edge Node is explained in the :ref:`previous tutorial <demo_inference>`, so here we will focus on the additional features added to this demo.
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You can find the complete code `here <https://github.com/eProsima/AML-IP/blob/main/amlip_demo_nodes/amlip_tensorflow_inference_rosbot2r_demo/amlip_tensorflow_inference_rosbot2r_demo/edge_node_async.py>`__.
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You can find the complete code `here <https://github.com/eProsima/AML-IP/blob/v0.1.0/amlip_demo_nodes/amlip_tensorflow_inference_rosbot2r_demo/amlip_tensorflow_inference_rosbot2r_demo/edge_node_async.py>`__.
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The next block includes the Python header files that allow the use of the AML-IP Python API and ROS 2.
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The Inference Node is responsible for making the inferences or predictions on the data it receives using a TensorFlow model.
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The Inference Node is typically a server or a computing resource equipped with high-performance hardware optimized for executing machine learning models efficiently.
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The Python code for the Inference Node is explained in the previous tutorial and can be found `here <https://github.com/eProsima/AML-IP/blob/main/amlip_demo_nodes/amlip_tensorflow_inference_rosbot2r_demo/amlip_tensorflow_inference_rosbot2r_demo/inference_node_async.py>`__.
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The Python code for the Inference Node is explained in the previous tutorial and can be found `here <https://github.com/eProsima/AML-IP/blob/v0.1.0/amlip_demo_nodes/amlip_tensorflow_inference_rosbot2r_demo/amlip_tensorflow_inference_rosbot2r_demo/inference_node_async.py>`__.
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Run demo
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========

amlip_docs/rst/demo/tensor_inference.rst

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The Edge Node is typically located at the edge of a network or closer to the data source, such as a sensor or a device generating the data.
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This is the Python code for the Edge Node application.
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This code can be found `here <https://github.com/eProsima/AML-IP/blob/main/amlip_demo_nodes/amlip_tensorflow_inference_demo/amlip_tensorflow_inference_demo/edge_node_async.py>`__.
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This code can be found `here <https://github.com/eProsima/AML-IP/blob/v0.1.0/amlip_demo_nodes/amlip_tensorflow_inference_demo/amlip_tensorflow_inference_demo/edge_node_async.py>`__.
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The next block includes the Python header files that allow the use of the AML-IP Python API.
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amlip_docs/rst/developer_manual/installation/sources/linux/linux_cmake.rst

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wget https://raw.githubusercontent.com/eProsima/AML-IP/main/amlip.repos
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wget https://raw.githubusercontent.com/eProsima/AML-IP/v0.1.0/amlip.repos
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vcs import src < amlip.repos
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#. Compile all dependencies using CMake_.

amlip_docs/rst/developer_manual/installation/sources/linux/linux_colcon.rst

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wget https://raw.githubusercontent.com/eProsima/AML-IP/v0.1.0/amlip.repos
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vcs import src < amlip.repos
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.. note::

amlip_docs/rst/developer_manual/installation/sources/windows/windows_cmake.rst

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wget https://raw.githubusercontent.com/eProsima/AML-IP/v0.1.0/amlip.repos
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vcs import src < amlip.repos
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#. Compile all dependencies using CMake_.

amlip_docs/rst/developer_manual/installation/sources/windows/windows_colcon.rst

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wget https://raw.githubusercontent.com/eProsima/AML-IP/main/amlip.repos
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wget https://raw.githubusercontent.com/eProsima/AML-IP/v0.1.0/amlip.repos
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.. note::

tools/agent_tool/README.md

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```sh
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mkdir -p ~/AML-IP/src
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wget https://raw.githubusercontent.com/eProsima/AML-IP/main/amlip.repos
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wget https://raw.githubusercontent.com/eProsima/AML-IP/v0.1.0/amlip.repos
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vcs import src < amlip.repos
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colcon build
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```

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