diff --git a/README.md b/README.md index b6716c9..a14fee6 100644 --- a/README.md +++ b/README.md @@ -149,9 +149,9 @@ All the following examples can be executed online using Google colab notebooks: - [All Notebooks](https://github.com/Stable-Baselines-Team/rl-colab-notebooks/tree/sb3) - [Getting Started](https://colab.research.google.com/github/Stable-Baselines-Team/rl-colab-notebooks/blob/sb3/stable_baselines_getting_started.ipynb) - [Training, Saving, Loading](https://colab.research.google.com/github/Stable-Baselines-Team/rl-colab-notebooks/blob/sb3/saving_loading_dqn.ipynb) - +- [Atari Games](https://colab.research.google.com/github/Stable-Baselines-Team/rl-colab-notebooks/blob/sb3/atari_games.ipynb) - [RL Baselines Zoo](https://colab.research.google.com/github/Stable-Baselines-Team/rl-colab-notebooks/blob/sb3/rl-baselines-zoo.ipynb) diff --git a/docs/guide/examples.rst b/docs/guide/examples.rst index 4b8d09e..0f98de7 100644 --- a/docs/guide/examples.rst +++ b/docs/guide/examples.rst @@ -13,13 +13,11 @@ notebooks: - `All Notebooks `_ - `Getting Started`_ - `Training, Saving, Loading`_ +- `Multiprocessing`_ +- `Monitor Training and Plotting`_ +- `Atari Games`_ - `RL Baselines zoo`_ - -.. - `Multiprocessing`_ -.. - `Monitor Training and Plotting`_ -.. - `Atari Games`_ -.. - `Breakout`_ (trained agent included) .. - `Hindsight Experience Replay`_ .. _Getting Started: https://colab.research.google.com/github/Stable-Baselines-Team/rl-colab-notebooks/blob/sb3/stable_baselines_getting_started.ipynb @@ -27,7 +25,6 @@ notebooks: .. _Multiprocessing: https://colab.research.google.com/github/Stable-Baselines-Team/rl-colab-notebooks/blob/sb3/multiprocessing_rl.ipynb .. _Monitor Training and Plotting: https://colab.research.google.com/github/Stable-Baselines-Team/rl-colab-notebooks/blob/sb3/monitor_training.ipynb .. _Atari Games: https://colab.research.google.com/github/Stable-Baselines-Team/rl-colab-notebooks/blob/sb3/atari_games.ipynb -.. _Breakout: https://colab.research.google.com/github/Stable-Baselines-Team/rl-colab-notebooks/blob/sb3/breakout.ipynb .. _Hindsight Experience Replay: https://colab.research.google.com/github/Stable-Baselines-Team/rl-colab-notebooks/blob/sb3/stable_baselines_her.ipynb .. _RL Baselines zoo: https://colab.research.google.com/github/Stable-Baselines-Team/rl-colab-notebooks/blob/sb3/rl-baselines-zoo.ipynb @@ -91,9 +88,9 @@ In the following example, we will train, save and load a A2C model on the Lunar Multiprocessing: Unleashing the Power of Vectorized Environments ---------------------------------------------------------------- -.. -.. .. image:: ../_static/img/colab-badge.svg -.. :target: https://colab.research.google.com/github/Stable-Baselines-Team/rl-colab-notebooks/blob/sb3/multiprocessing_rl.ipynb + +.. image:: ../_static/img/colab-badge.svg + :target: https://colab.research.google.com/github/Stable-Baselines-Team/rl-colab-notebooks/blob/sb3/multiprocessing_rl.ipynb .. figure:: https://cdn-images-1.medium.com/max/960/1*h4WTQNVIsvMXJTCpXm_TAw.gif @@ -106,7 +103,6 @@ Multiprocessing: Unleashing the Power of Vectorized Environments import numpy as np from stable_baselines3 import PPO - from stable_baselines3.ppo import MlpPolicy from stable_baselines3.common.vec_env import SubprocVecEnv from stable_baselines3.common.cmd_util import make_vec_env from stable_baselines3.common.utils import set_random_seed @@ -160,12 +156,9 @@ This could be useful when you want to monitor training, for instance display liv learning curves in Tensorboard (or in Visdom) or save the best agent. If your callback returns False, training is aborted early. -.. .. image:: ../_static/img/colab-badge.svg -.. :target: https://colab.research.google.com/github/Stable-Baselines-Team/rl-colab-notebooks/blob/sb3/monitor_training.ipynb -.. -.. .. figure:: ../_static/img/learning_curve.png -.. -.. Learning curve of TD3 on LunarLanderContinuous environment +.. image:: ../_static/img/colab-badge.svg + :target: https://colab.research.google.com/github/Stable-Baselines-Team/rl-colab-notebooks/blob/sb3/monitor_training.ipynb + .. code-block:: python @@ -176,7 +169,6 @@ If your callback returns False, training is aborted early. import matplotlib.pyplot as plt from stable_baselines3 import TD3 - from stable_baselines3.td3 import MlpPolicy from stable_baselines3.common import results_plotter from stable_baselines3.common.monitor import Monitor from stable_baselines3.common.results_plotter import load_results, ts2xy, plot_results @@ -240,7 +232,7 @@ If your callback returns False, training is aborted early. n_actions = env.action_space.shape[-1] action_noise = NormalActionNoise(mean=np.zeros(n_actions), sigma=0.1 * np.ones(n_actions)) # Because we use parameter noise, we should use a MlpPolicy with layer normalization - model = TD3(MlpPolicy, env, action_noise=action_noise, verbose=0) + model = TD3('MlpPolicy', env, action_noise=action_noise, verbose=0) # Create the callback: check every 1000 steps callback = SaveOnBestTrainingRewardCallback(check_freq=1000, log_dir=log_dir) # Train the agent @@ -267,8 +259,8 @@ Training a RL agent on Atari games is straightforward thanks to ``make_atari_env It will do `all the preprocessing `_ and multiprocessing for you. -.. .. image:: ../_static/img/colab-badge.svg -.. :target: https://colab.research.google.com/github/Stable-Baselines-Team/rl-colab-notebooks/blob/sb3/atari_games.ipynb +.. image:: ../_static/img/colab-badge.svg + :target: https://colab.research.google.com/github/Stable-Baselines-Team/rl-colab-notebooks/blob/sb3/atari_games.ipynb .. .. code-block:: python diff --git a/docs/misc/changelog.rst b/docs/misc/changelog.rst index 4f3db8a..5391ad7 100644 --- a/docs/misc/changelog.rst +++ b/docs/misc/changelog.rst @@ -3,6 +3,28 @@ Changelog ========== +Pre-Release 0.8.0a0 (WIP) +------------------------------ + +Breaking Changes: +^^^^^^^^^^^^^^^^^ + +New Features: +^^^^^^^^^^^^^ + +Bug Fixes: +^^^^^^^^^^ + +Deprecations: +^^^^^^^^^^^^^ + +Others: +^^^^^^^ + +Documentation: +^^^^^^^^^^^^^^ +- Updated notebook links + Pre-Release 0.7.0 (2020-06-10) ------------------------------ @@ -61,6 +83,7 @@ Documentation: - Added a paragraph on "MlpPolicy"/"CnnPolicy" and policy naming scheme under "Developer Guide" - Fixed second-level listing in changelog + Pre-Release 0.6.0 (2020-06-01) ------------------------------ diff --git a/stable_baselines3/version.txt b/stable_baselines3/version.txt index faef31a..4c46bdd 100644 --- a/stable_baselines3/version.txt +++ b/stable_baselines3/version.txt @@ -1 +1 @@ -0.7.0 +0.8.0a0