The duckietown-RL-transformer repository provides solution for lane following in the Duckietown environment. It includes train, evaluation and test script for a hybrid CNN - Transformer (GTrXL) machine learning model, which is supposed to control duckiebot. The solution builds upon the Ray RLlib framework for reinforcement learning (RL) and Weights & Biases framework for logging.
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Simulation | Real world |
Steps for Native (or in virtual env) setup
0.1 (Optional) Make your venv.
sudo apt update
sudo apt install python3.8-venv
cd to/your/project/path
python -m venv .venv_duckietown/ #create venv
source .venv_duckietown/bin/activate #activate it
0.2. Get the repository and step into it.
git clone https://github.com/TothAron/duckietown-RL-transformer-thesis.git
cd duckietown-RL-transformer-thesis/
0.3. Install dependecies
pip install -r requirements.txt
1.0. (Optional) Make sure you activate venv and got to the right path, if not:
cd to/your/project/path
source .venv_duckietown/bin/activate #activate it
cd duckietown-RL-transformer-thesis
1.1. Login to your Weights and Biases account (if do not have one, create at: https://wandb.ai)
wandb login # paste your token from wandb.ai/authorize
1.2. Set your settings and hyperparameters in train config file at:
dev_and_test/config/default.py
1.3. Start training.
CUDA_VISIBLE_DEVICES=<gpu_idx> xvfb-run -a -s "-screen 0 1400x900x24" taskset --cpu-list <start_cpu_idx>-<end_cpu_idx> python dev_and_test/run_train.py
NOTE: <gpu_idx>
and <start_cpu_idx>
can be selected with the help of nvidia-smi
and htop
unix commands relatively.
1.4. The only thing is left to check your training logs live at wandb.ai
2.1. Setup your testing configuration at:
dev_and_test/config/test_config.py
2.2. Start testing 👓
CUDA_VISIBLE_DEVICES=<gpu_idx> xvfb-run -a -s "-screen 0 1400x900x24" taskset --cpu-list <start_cpu_idx>-<end_cpu_idx> python dev_and_test/run_test.py
2.3. Check evaluation results at:
evaluation_results/
The used environment wrapper modules and the evaluator for testing are the modified versions of:
https://github.com/kaland313/Duckietown-RL
MIT License Copyright (c) 2019 András Kalapos