Update version in docs

Signed-off-by: Raul Sanchez-Mateos <[email protected]>

Author: rsanchez15

amlip_demo_nodes/amlip_collaborative_learning_demo/README.md

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

amlip_demo_nodes/amlip_tensorflow_inference_demo/README.md

@@ -37,7 +37,7 @@ Create a AML-IP-ws directory and download the repos file that will be used to in
 mkdir ~/AML-IP-ws
 cd ~/AML-IP-ws
 mkdir src
-wget https://raw.githubusercontent.com/eProsima/AML-IP/main/amlip.repos
+wget https://raw.githubusercontent.com/eProsima/AML-IP/v0.1.0/amlip.repos
 vcs import src < amlip.repos
 ```
 

amlip_demo_nodes/amlip_tensorflow_inference_rosbot2r_demo/README.md

@@ -37,7 +37,7 @@ Create a AML-IP-ws directory and download the repos file that will be used to in
 mkdir ~/AML-IP-ws
 cd ~/AML-IP-ws
 mkdir src
-wget https://raw.githubusercontent.com/eProsima/AML-IP/main/amlip.repos
+wget https://raw.githubusercontent.com/eProsima/AML-IP/v0.1.0/amlip.repos
 vcs import src < amlip.repos
 ```
 
@@ -139,7 +139,7 @@ Inference sent to client AMLEdgeNode.fb.d4.38.13.
 
 ## Docker
 
-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.
+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.
 In order to do so, execute the following to build the docker image:
 
 ```bash

amlip_demo_nodes/amlip_workload_distribution_demo/README.md

@@ -92,7 +92,7 @@ In order to build the following project and be able to operate with this demo No
 
 ```sh
 mkdir src
-wget https://raw.githubusercontent.com/eProsima/AML-IP/main/amlip.repos
+wget https://raw.githubusercontent.com/eProsima/AML-IP/v0.1.0/amlip.repos
 vcs import src < amlip.repos
 colcon build --packages-up-to amlip_demo_nodes
 source install/setup.bash

amlip_docs/rst/demo/collaborative_learning.rst

@@ -62,7 +62,7 @@ This is the Python code for the :ref:`user_manual_nodes_model_receiver` applicat
 It does not use real *AML Models*, but strings.
 It is implemented in |python| using :code:`amlip_py` API.
 
-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>`__.
+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>`__.
 
 The next block includes the Python header files that allow the use of the AML-IP Python API.
 
@@ -134,7 +134,7 @@ It does not use real *AML Models*, but strings.
 It does not have a real *AML Engine* but instead the calculation is an *upper-case* conversion of the string received.
 It is implemented in |python| using :code:`amlip_py` API.
 
-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>`__.
+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>`__.
 
 The next block includes the Python header files that allow the use of the AML-IP Python API.
 

amlip_docs/rst/demo/rosbot2r_inference.rst

@@ -53,7 +53,7 @@ ROSbot 2R Deployment
 ====================
 
 The Docker Compose used for the demo is ``compose.yaml``.
-You can find it `here <https://github.com/eProsima/AML-IP/blob/main/amlip_demo_nodes/amlip_tensorflow_inference_rosbot2r_demo/compose.yaml>`__.
+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>`__.
 
 The Docker Compose launches the following containers:
 
@@ -126,7 +126,7 @@ The Edge Node is typically located at the edge of a network or closer to the dat
 In this specific scenario, the data source is the camera of the robot.
 
 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.
-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>`__.
+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>`__.
 
 The next block includes the Python header files that allow the use of the AML-IP Python API and ROS 2.
 
@@ -177,7 +177,7 @@ Inference Node
 The Inference Node is responsible for making the inferences or predictions on the data it receives using a TensorFlow model.
 The Inference Node is typically a server or a computing resource equipped with high-performance hardware optimized for executing machine learning models efficiently.
 
-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>`__.
+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>`__.
 
 Run demo
 ========

amlip_docs/rst/demo/tensor_inference.rst

@@ -97,7 +97,7 @@ Edge Node serves as the entity responsible for sending the data to be inferred t
 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.
 
 This is the Python code for the Edge Node application.
-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>`__.
+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>`__.
 
 The next block includes the Python header files that allow the use of the AML-IP Python API.
 

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

@@ -24,7 +24,7 @@ Local installation
         mkdir -p ~/AML-IP/src
         mkdir -p ~/AML-IP/build
         cd ~/AML-IP
-        wget https://raw.githubusercontent.com/eProsima/AML-IP/main/amlip.repos
+        wget https://raw.githubusercontent.com/eProsima/AML-IP/v0.1.0/amlip.repos
         vcs import src < amlip.repos
 
 #.  Compile all dependencies using CMake_.

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

@@ -27,7 +27,7 @@ Download eProsima dependencies
 
         mkdir -p ~/AML-IP/src
         cd ~/AML-IP
-        wget https://raw.githubusercontent.com/eProsima/AML-IP/main/amlip.repos
+        wget https://raw.githubusercontent.com/eProsima/AML-IP/v0.1.0/amlip.repos
         vcs import src < amlip.repos
 
     .. note::

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

@@ -26,7 +26,7 @@ Local installation
         mkdir <path\to\user\workspace>\AML-IP\src
         mkdir <path\to\user\workspace>\AML-IP\build
         cd <path\to\user\workspace>\AML-IP
-        wget https://raw.githubusercontent.com/eProsima/AML-IP/main/amlip.repos
+        wget https://raw.githubusercontent.com/eProsima/AML-IP/v0.1.0/amlip.repos
         vcs import src < amlip.repos
 
 #.  Compile all dependencies using CMake_.