DRL_HF

PPO Agent playing LunarLander-v3

This is a trained model of a PPO agent playing LunarLander-v3 using the stable-baselines3 library.

To use it type something like:

from huggingface_sb3 import load_from_hub repo_id = "Classroom-workshop/assignment2-omar" # The repo_id filename = "ppo-LunarLander-v3.zip" # The model filename.zip

When the model was trained on Python 3.8 the pickle protocol is 5

But Python 3.6, 3.7 use protocol 4

In order to get compatibility we need to:

1. Install pickle5 (we done it at the beginning of the colab)

2. Create a custom empty object we pass as parameter to PPO.load()

custom_objects = { "learning_rate": 0.0, "lr_schedule": lambda _: 0.0, "clip_range": lambda _: 0.0, }

checkpoint = load_from_hub(repo_id, filename) model = PPO.load(checkpoint, custom_objects=custom_objects, print_system_info=True)

Evaluate the model in the environment

eval_env = Monitor(gym.make("LunarLander-v3")) mean_reward, std_reward = evaluate_policy(model, eval_env, n_eval_episodes=10, deterministic=True) print(f"mean_reward={mean_reward:.2f} +/- {std_reward}")