Added script demonstrating how to restore a policy

scripts/restore_and_watch_policy.py

@@ -0,0 +1,32 @@
+from pathlib import Path
+from typing import cast
+
+from armscan_env.wrapper import ArmscanEnvFactory
+
+from tianshou.highlevel.env import EnvMode
+from tianshou.highlevel.experiment import Experiment
+
+# Place your path here
+saved_experiment_dir = Path("log/random-actions/42/20240814-150513")
+
+if __name__ == "__main__":
+    restored_experiment = Experiment.from_directory(str(saved_experiment_dir), restore_policy=True)
+
+    restored_policy = restored_experiment.create_experiment_world().policy
+    # this can be now used to perform actions, you can also use a notebook
+
+    env_factory: ArmscanEnvFactory = cast(ArmscanEnvFactory, restored_experiment.env_factory)
+    # TODO @Carlo: modify here to set different volumes
+    env_factory.name2volume = env_factory.name2volume
+
+    # Create env manually and run policy on it
+    restored_env = env_factory.create_env(mode=EnvMode.WATCH)
+    obs, info = restored_env.reset()
+    for _ in range(5):
+        obs, *_ = restored_env.step(restored_policy.compute_action(obs))
+
+    # Or use the restored experiment to run the policy
+    restored_experiment.config.train = False
+    restored_experiment.config.watch = True
+    restored_experiment.config.persistence_enabled = False
+    restored_experiment.run()