Merge pull request #139 from RoboTeamTwente/nova_2

Nova 2

.gitignore

@@ -37,3 +37,14 @@ ENV/
 env.bak/
 venv.bak/
 __pycache__/
+
+# Docker
+docker/runner/ssl-game-controller-config/20*
+docker/runner/ssl-game-controller-config/state-store.json.stream
+
+# RL
+roboteam_ai/src/RL/src/tmp/eval_monitor.monitor.csv
+roboteam_ai/src/RL/src/tmp/monitor.monitor.csv
+roboteam_ai/src/RL/src/ppo_tensorboard_main
+roboteam_ai/src/RL/src/best_model_PPO.zip
+docker/runner/ssl-game-controller-config/state-store.json.stream

.gitmodules

@@ -11,3 +11,6 @@
 [submodule "roboteam_robothub/roboteam_embedded_messages"]
 	path = roboteam_robothub/roboteam_embedded_messages
 	url = https://github.com/RoboTeamTwente/roboteam_embedded_messages.git
+[submodule "tigers_sumatra"]
+	path = tigers_sumatra
+	url = https://github.com/RoboTeamTwente/tigers_sumatra.git

Dockerfile

@@ -0,0 +1,31 @@
+FROM roboteamtwente/roboteam:development
+
+# Create symbolic link from /home/roboteam to /home/roboteamtwente
+USER root
+RUN ln -s /home/roboteamtwente /home/roboteam
+
+# Install Java
+RUN apk add --no-cache openjdk11
+
+# Install Java 21
+RUN wget https://github.com/adoptium/temurin21-binaries/releases/download/jdk-21.0.1%2B12/OpenJDK21U-jdk_x64_alpine-linux_hotspot_21.0.1_12.tar.gz \
+    && tar -xzf OpenJDK21U-jdk_x64_alpine-linux_hotspot_21.0.1_12.tar.gz \
+    && mv jdk-21* /usr/lib/jvm/java-21-openjdk
+
+# Set up Java environment variables to point to Java 21
+ENV JAVA_HOME=/usr/lib/jvm/java-21-openjdk
+ENV PATH="${JAVA_HOME}/bin:${PATH}"
+
+WORKDIR /home/roboteam
+
+# Copy the entire current directory into the container
+COPY --chown=roboteamtwente:roboteamtwente . /home/roboteam/
+
+# Make sure build.sh is executable
+RUN chmod +x build.sh
+
+# Add the lib directory to LD_LIBRARY_PATH
+ENV LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/home/roboteam/build/release/lib
+
+# Switch back to the roboteamtwente user
+USER roboteamtwente

Dockerfile.ray

@@ -0,0 +1,16 @@
+# This dockerfile uses the ray project's official ray image as a base.
+# It also adds the torch and gymnasium libraries to the image.
+# It also adds the roboteam RL code to the image.
+
+FROM rayproject/ray:latest-py310
+
+# Install dependencies in a single layer to keep it cached
+RUN pip install torch==2.5.1 gymnasium numpy==1.24.3 ray[rllib]==2.38.0 pyzmq protobuf websockets
+
+# Copy the entire roboteam root folder (including the roboteam_ai and roboteam_networking folders)
+COPY roboteam_ai /roboteam/roboteam_ai
+COPY roboteam_networking /roboteam/roboteam_networking
+
+# Set working directory and Python path
+WORKDIR /roboteam
+ENV PYTHONPATH="/roboteam:${PYTHONPATH}"

Dockerfile.zmq_server

@@ -0,0 +1,20 @@
+FROM python:3.9-slim
+
+# Install system dependencies
+RUN apt-get update && \
+    apt-get install -y libzmq3-dev build-essential && \
+    apt-get clean && \
+    rm -rf /var/lib/apt/lists/*
+
+# Install Python dependencies
+RUN pip install pyzmq protobuf
+
+# Create working directory
+WORKDIR /app
+
+# Copy the Python script and proto files
+COPY roboteam_ai/src/rl/src/zmq_server.py /app/
+COPY /roboteam_networking/ /app/roboteam_networking/
+
+# Run the script
+CMD ["python", "zmq_server.py"]

README.md

@@ -36,3 +36,15 @@ To enable Tracy
 - Compile Tracy Server and run
   - Information is in the tracy [docs](https://github.com/wolfpld/tracy)
 - Run AI
+
+### Use of Ray
+
+The dockerimage Dockerfile.ray is used to build a docker image with the ray project's official ray image as a base. It also adds the necessary libraries to the image and the roboteam RL code to the image. Only build it if you want to deploy it to a cluster.
+
+Build the docker image using the following command from the root folder:
+
+- docker build -t roboteamtwente/ray:development -f Dockerfile.ray .
+
+Push it using the following command:
+
+- docker push roboteamtwente/ray:development

docker/README.md

@@ -100,6 +100,10 @@ docker run -itd --name rtt-release-env -h rtt-release-env roboteamtwente/robotea
 #### TODO
 https://lemariva.com/blog/2020/10/vscode-c-development-and-debugging-containers
 
+
+### Profile explanation
+If you want to run certain docker containers with a single command, you create a profile. This will run every docker container that has this command.
+
 ### Docker geeks
 We highly discourage executing command under this section unless you know what you are doing and for some reason you need to edit dockerfiles or composes structure.
 

docker/runner/README.md

@@ -0,0 +1,39 @@
+
+In a ray or distributed computing cluster, the terms "head node" and "worker nodes" refer to different roles that containers play in the cluster. The head node is the master node in a Ray cluster. You typically have one head node. Worker nodes are the containers that execute the jobs, in parallel. You can have as many worker nodes as you want.
+
+-----------------------------------------------------------
+
+## Installing Kuberay
+
+curl <https://raw.githubusercontent.com/helm/helm/main/scripts/get-helm-3> | bash
+helm repo add kuberay <https://ray-project.github.io/kuberay-helm/>
+helm repo update
+helm install kuberay-operator kuberay/kuberay-operator --namespace ray-system --create-namespace
+
+<https://docs.ray.io/en/latest/cluster/kubernetes/user-guides/config.html>
+The above source was used for creating the ray-cluster.yaml
+
+Installing kubernetes and minikubernetes, you can follow this guide to check out how to install and run them: <https://medium.com/@areesmoon/installing-minikube-on-ubuntu-20-04-lts-focal-fossa-b10fad9d0511>
+
+Use 'pip install ray' and then 'pip show ray' to get your version of ray.
+
+-----------------------------------------------------------
+
+After you have both kubernetes and ray, use the following command to create a cluster: kubectl apply -f ray-cluster.yaml
+This cluster launches a ray head node and one worker node. Launch the external simulator using kubectl apply -f simulator.yaml
+
+'kubectl get pods'-> this is will give you the cluster name
+
+Use to forward the needed port to the ray service: kubectl port-forward svc/<cluster name> 8265:8265
+This is the port that will be used inside ray_jobs.py, where we submit the jobs to ray.
+
+-----------------------------------------------------------
+
+## Useful commands
+
+kubectl apply -f ray-cluster.yaml
+kubectl delete -f ray-cluster.yaml
+helm install kuberay-operator ray/kuberay-operator
+helm uninstall kuberay-operator
+kubectl port-forward svc/roboteam-ray-cluster-head-nodeport 8265:8265 6379:6379 10001:10001 8000:8000 &
+minikube start -p ray --nodes 2 --memory 4000 --cpus 3

docker/runner/docker-compose.yml

@@ -1,5 +1,3 @@
-version: '3'
-
 services:
 
   roboteam_primary_ai:
@@ -18,7 +16,7 @@ services:
       - LD_LIBRARY_PATH=/home/roboteamtwente/lib/
     volumes:
       - ../../build/release/:/home/roboteamtwente/
-    profiles: ["simulator","diff","game", "robocup"]
+    profiles: ["simulator","diff","game", "robocup", "RL"]
 
   roboteam_secondary_ai:
     image: roboteamtwente/roboteam:development
@@ -61,7 +59,7 @@ services:
     container_name: RTT_roboteam_observer_sim
     restart: always
     working_dir: "/home/roboteamtwente/"
-    command: sh -c "./bin/roboteam_observer --vision-ip 224.5.23.2 --referee-ip 224.5.23.1 --vision-port 10020 --referee-port 10003 --log"
+    command: sh -c "./bin/roboteam_observer --vision-ip 224.5.23.2 --referee-ip 224.5.23.1 --vision-port 10020 --referee-port 10003"
     network_mode: "host" # Workaround to connect from interface on host to AI websocket, please fix
     expose:
       - 1-65535:1-65535 # For zeromq ports
@@ -72,7 +70,7 @@ services:
       - LD_LIBRARY_PATH=/home/roboteamtwente/lib/
     volumes:
       - ../../build/release/:/home/roboteamtwente/
-    profiles: ["simulator","diff"]
+    profiles: ["simulator","diff", "RL"]
 
   roboteam_observer_game:
     image: roboteamtwente/roboteam:development
@@ -111,7 +109,7 @@ services:
       - LD_LIBRARY_PATH=/home/roboteamtwente/lib/
     volumes:
       - ../../build/release/:/home/roboteamtwente/
-    profiles: ["simulator","diff"]
+    profiles: ["simulator","diff", "RL"]
 
   roboteam_robothub_game:
     image: roboteamtwente/roboteam:development
@@ -147,7 +145,7 @@ services:
       - 8080:8080
     volumes:
       - ../../roboteam_interface/:/home/roboteamtwente/
-    profiles: ["simulator","diff","game", "robocup"]
+    profiles: ["simulator","diff","game", "robocup", "RL"]
 
   roboteam_autoref:
     image: gradle:8.4.0-jdk17
@@ -164,7 +162,7 @@ services:
       - GRADLE_USER_HOME=/home/roboteamtwente/.cache # Cache gradle dependencies
     volumes:
       - ../../roboteam_autoref/:/home/roboteamtwente/
-    profiles: ["simulator","diff","game","autoref"]
+    profiles: ["simulator","diff","game","autoref", "RL"]
 
   erforce_autoref_sim:
     image: roboteamtwente/roboteam:development
@@ -179,7 +177,7 @@ services:
       - 10010:10010 # Tracker port
     volumes:
       - ../../:/home/roboteamtwente/
-    profiles: ["simulator","diff"]
+    profiles: ["simulator","diff", "RL"]
 
   erforce_autoref_game:
     image: roboteamtwente/roboteam:development
@@ -212,13 +210,17 @@ services:
       - 30013:30013 #Simulation Feedback Port
     volumes:
       - ../../:/home/roboteamtwente/
-    profiles: ["simulator","diff"]
+    profiles: ["simulator","diff", "RL"]
 
   ssl-game-controller:
     image: robocupssl/ssl-game-controller:latest
     container_name: RTT_ssl-game-controller
     restart: always
-    network_mode: "host" # Workaround to connect from interface on host to AI websocket, please fix
+    network_mode: "host"
     ports:
-      - "8081:8081/tcp" # UI port
-    profiles: ["simulator","diff","game"]
+      - "8081:8081/tcp"
+    volumes:
+      - ./ssl-game-controller-config:/config
+      - ./ssl-game-controller-data:/data
+    command: -address :8081
+    profiles: ["simulator","diff","game", "RL"]