From b1794ebc528b0c0a68238f294e6d51000e4ccdf5 Mon Sep 17 00:00:00 2001 From: Antonin RAFFIN Date: Mon, 11 May 2020 15:32:01 +0200 Subject: [PATCH] [ci skip] Simplify quickstart example --- README.md | 1 - docs/guide/quickstart.rst | 3 +-- setup.py | 3 +-- 3 files changed, 2 insertions(+), 5 deletions(-) diff --git a/README.md b/README.md index c3e9850..db8feff 100644 --- a/README.md +++ b/README.md @@ -116,7 +116,6 @@ Here is a quick example of how to train and run PPO on a cartpole environment: import gym from stable_baselines3 import PPO -from stable_baselines3.ppo import MlpPolicy env = gym.make('CartPole-v1') diff --git a/docs/guide/quickstart.rst b/docs/guide/quickstart.rst index 54a967c..88545b4 100644 --- a/docs/guide/quickstart.rst +++ b/docs/guide/quickstart.rst @@ -13,11 +13,10 @@ Here is a quick example of how to train and run A2C on a CartPole environment: import gym from stable_baselines3 import A2C - from stable_baselines3.a2c import MlpPolicy env = gym.make('CartPole-v1') - model = A2C(MlpPolicy, env, verbose=1) + model = A2C('MlpPolicy', env, verbose=1) model.learn(total_timesteps=10000) obs = env.reset() diff --git a/setup.py b/setup.py index e9a892f..9a596db 100644 --- a/setup.py +++ b/setup.py @@ -40,11 +40,10 @@ Here is a quick example of how to train and run PPO on a cartpole environment: import gym from stable_baselines3 import PPO -from stable_baselines3.ppo import MlpPolicy env = gym.make('CartPole-v1') -model = PPO(MlpPolicy, env, verbose=1) +model = PPO('MlpPolicy', env, verbose=1) model.learn(total_timesteps=10000) obs = env.reset()