use bot::burnrl::{dqn_model, environment, utils::demo_model}; use burn::backend::{ndarray::NdArrayDevice, Autodiff, NdArray}; use burn::module::Module; use burn::record::{CompactRecorder, Recorder}; use burn_rl::agent::DQN; use burn_rl::base::{Action, Agent, ElemType, Environment, State}; type Backend = Autodiff>; type Env = environment::TrictracEnvironment; fn main() { println!("> Entraînement"); let num_episodes = 10; let agent = dqn_model::run::(num_episodes, false); //true); let valid_agent = agent.valid(); println!("> Sauvegarde du modèle de validation"); save_model(valid_agent.model().as_ref().unwrap()); println!("> Test avec le modèle entraîné"); demo_model::(valid_agent); println!("> Chargement du modèle pour test"); let loaded_model = load_model(); let loaded_agent = DQN::new(loaded_model); println!("> Test avec le modèle chargé"); demo_model::(loaded_agent); } fn save_model(model: &dqn_model::Net>) { let path = "models/burn_dqn".to_string(); let recorder = CompactRecorder::new(); let model_path = format!("{}_model.mpk", path); println!("Modèle de validation sauvegardé : {}", model_path); recorder .record(model.clone().into_record(), model_path.into()) .unwrap(); } fn load_model() -> dqn_model::Net> { // TODO : reprendre le DENSE_SIZE de dqn_model.rs const DENSE_SIZE: usize = 128; let path = "models/burn_dqn".to_string(); let model_path = format!("{}_model.mpk", path); println!("Chargement du modèle depuis : {}", model_path); let device = NdArrayDevice::default(); let recorder = CompactRecorder::new(); let record = recorder .load(model_path.into(), &device) .expect("Impossible de charger le modèle"); dqn_model::Net::new( ::StateType::size(), DENSE_SIZE, ::ActionType::size(), ) .load_record(record) }