[Example] Made available premade example script

Signed-off-by: Matteo Bettini <[email protected]>

benchmarl/run.py

@@ -9,19 +9,15 @@
 def hydra_experiment(cfg: DictConfig) -> None:
     hydra_choices = HydraConfig.get().runtime.choices
     task_name = hydra_choices.task
-    print(f"\nAlgorithm: {hydra_choices.algorithm}, Task: {task_name}")
+    algorithm_name = hydra_choices.algorithm
+
+    print(f"\nAlgorithm: {algorithm_name}, Task: {task_name}")
     print("\nLoaded config:\n")
     print(OmegaConf.to_yaml(cfg))
 
-    experiment = load_experiment_from_hydra(
-        cfg,
-        task_name=task_name,
-    )
+    experiment = load_experiment_from_hydra(cfg, task_name=task_name)
     experiment.run()
 
 
 if __name__ == "__main__":
     hydra_experiment()
-
-    # You can run multiple experiments like so
-    # python simple_hydra_run.py --multirun algorithm=mappo,qmix,maddpg,masac task=vmas/balance

premade_scripts/vmas/config.yaml

@@ -0,0 +1,22 @@
+defaults:
+  - experiment: base_experiment
+  - algorithm: mappo
+  - task: vmas/balance
+  - model: layers/mlp
+  - model@critic_model: layers/mlp
+  - _self_
+
+seed: 0
+
+hydra:
+  searchpath:
+   # Tells hydra to add the default benchmarl configuration to its path
+    - pkg://benchmarl/conf
+
+experiment:
+    sampling_device: "cuda"
+    train_device: "cuda"
+    collected_frames_per_batch: 60_000
+    n_envs_per_worker: 600
+    on_policy_minibatch_size: 4096
+    evaluation_episodes: 200

premade_scripts/vmas/vmas_run.py

@@ -0,0 +1,24 @@
+import hydra
+from benchmarl.experiment import Experiment
+
+from benchmarl.hydra_config import load_experiment_from_hydra
+from hydra.core.hydra_config import HydraConfig
+from omegaconf import DictConfig, OmegaConf
+
+
+@hydra.main(version_base=None, config_path=".", config_name="config")
+def hydra_experiment(cfg: DictConfig) -> None:
+    hydra_choices = HydraConfig.get().runtime.choices
+    task_name = hydra_choices.task
+    algorithm_name = hydra_choices.algorithm
+
+    print(f"\nAlgorithm: {algorithm_name}, Task: {task_name}")
+    print("\nLoaded config:\n")
+    print(OmegaConf.to_yaml(cfg))
+
+    experiment: Experiment = load_experiment_from_hydra(cfg, task_name=task_name)
+    experiment.run()
+
+
+if __name__ == "__main__":
+    hydra_experiment()