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Update notebooks (#65)
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Antonin RAFFIN
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4 changed files with 38 additions and 23 deletions
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@ -149,9 +149,9 @@ All the following examples can be executed online using Google colab notebooks:
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- [All Notebooks](https://github.com/Stable-Baselines-Team/rl-colab-notebooks/tree/sb3)
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- [Getting Started](https://colab.research.google.com/github/Stable-Baselines-Team/rl-colab-notebooks/blob/sb3/stable_baselines_getting_started.ipynb)
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- [Training, Saving, Loading](https://colab.research.google.com/github/Stable-Baselines-Team/rl-colab-notebooks/blob/sb3/saving_loading_dqn.ipynb)
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<!-- - [Multiprocessing](https://colab.research.google.com/github/Stable-Baselines-Team/rl-colab-notebooks/blob/sb3/multiprocessing_rl.ipynb)
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- [Multiprocessing](https://colab.research.google.com/github/Stable-Baselines-Team/rl-colab-notebooks/blob/sb3/multiprocessing_rl.ipynb)
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- [Monitor Training and Plotting](https://colab.research.google.com/github/Stable-Baselines-Team/rl-colab-notebooks/blob/sb3/monitor_training.ipynb)
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- [Atari Games](https://colab.research.google.com/github/Stable-Baselines-Team/rl-colab-notebooks/blob/sb3/atari_games.ipynb) -->
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- [Atari Games](https://colab.research.google.com/github/Stable-Baselines-Team/rl-colab-notebooks/blob/sb3/atari_games.ipynb)
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- [RL Baselines Zoo](https://colab.research.google.com/github/Stable-Baselines-Team/rl-colab-notebooks/blob/sb3/rl-baselines-zoo.ipynb)
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@ -13,13 +13,11 @@ notebooks:
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- `All Notebooks <https://github.com/Stable-Baselines-Team/rl-colab-notebooks/tree/sb3>`_
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- `Getting Started`_
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- `Training, Saving, Loading`_
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- `Multiprocessing`_
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- `Monitor Training and Plotting`_
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- `Atari Games`_
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- `RL Baselines zoo`_
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.. - `Multiprocessing`_
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.. - `Monitor Training and Plotting`_
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.. - `Atari Games`_
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.. - `Breakout`_ (trained agent included)
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.. - `Hindsight Experience Replay`_
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.. _Getting Started: https://colab.research.google.com/github/Stable-Baselines-Team/rl-colab-notebooks/blob/sb3/stable_baselines_getting_started.ipynb
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@ -27,7 +25,6 @@ notebooks:
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.. _Multiprocessing: https://colab.research.google.com/github/Stable-Baselines-Team/rl-colab-notebooks/blob/sb3/multiprocessing_rl.ipynb
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.. _Monitor Training and Plotting: https://colab.research.google.com/github/Stable-Baselines-Team/rl-colab-notebooks/blob/sb3/monitor_training.ipynb
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.. _Atari Games: https://colab.research.google.com/github/Stable-Baselines-Team/rl-colab-notebooks/blob/sb3/atari_games.ipynb
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.. _Breakout: https://colab.research.google.com/github/Stable-Baselines-Team/rl-colab-notebooks/blob/sb3/breakout.ipynb
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.. _Hindsight Experience Replay: https://colab.research.google.com/github/Stable-Baselines-Team/rl-colab-notebooks/blob/sb3/stable_baselines_her.ipynb
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.. _RL Baselines zoo: https://colab.research.google.com/github/Stable-Baselines-Team/rl-colab-notebooks/blob/sb3/rl-baselines-zoo.ipynb
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@ -91,9 +88,9 @@ In the following example, we will train, save and load a A2C model on the Lunar
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Multiprocessing: Unleashing the Power of Vectorized Environments
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----------------------------------------------------------------
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..
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.. .. image:: ../_static/img/colab-badge.svg
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.. :target: https://colab.research.google.com/github/Stable-Baselines-Team/rl-colab-notebooks/blob/sb3/multiprocessing_rl.ipynb
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.. image:: ../_static/img/colab-badge.svg
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:target: https://colab.research.google.com/github/Stable-Baselines-Team/rl-colab-notebooks/blob/sb3/multiprocessing_rl.ipynb
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.. figure:: https://cdn-images-1.medium.com/max/960/1*h4WTQNVIsvMXJTCpXm_TAw.gif
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@ -106,7 +103,6 @@ Multiprocessing: Unleashing the Power of Vectorized Environments
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import numpy as np
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from stable_baselines3 import PPO
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from stable_baselines3.ppo import MlpPolicy
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from stable_baselines3.common.vec_env import SubprocVecEnv
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from stable_baselines3.common.cmd_util import make_vec_env
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from stable_baselines3.common.utils import set_random_seed
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@ -160,12 +156,9 @@ This could be useful when you want to monitor training, for instance display liv
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learning curves in Tensorboard (or in Visdom) or save the best agent.
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If your callback returns False, training is aborted early.
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.. .. image:: ../_static/img/colab-badge.svg
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.. :target: https://colab.research.google.com/github/Stable-Baselines-Team/rl-colab-notebooks/blob/sb3/monitor_training.ipynb
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..
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.. .. figure:: ../_static/img/learning_curve.png
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..
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.. Learning curve of TD3 on LunarLanderContinuous environment
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.. image:: ../_static/img/colab-badge.svg
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:target: https://colab.research.google.com/github/Stable-Baselines-Team/rl-colab-notebooks/blob/sb3/monitor_training.ipynb
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.. code-block:: python
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@ -176,7 +169,6 @@ If your callback returns False, training is aborted early.
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import matplotlib.pyplot as plt
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from stable_baselines3 import TD3
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from stable_baselines3.td3 import MlpPolicy
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from stable_baselines3.common import results_plotter
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from stable_baselines3.common.monitor import Monitor
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from stable_baselines3.common.results_plotter import load_results, ts2xy, plot_results
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@ -240,7 +232,7 @@ If your callback returns False, training is aborted early.
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n_actions = env.action_space.shape[-1]
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action_noise = NormalActionNoise(mean=np.zeros(n_actions), sigma=0.1 * np.ones(n_actions))
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# Because we use parameter noise, we should use a MlpPolicy with layer normalization
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model = TD3(MlpPolicy, env, action_noise=action_noise, verbose=0)
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model = TD3('MlpPolicy', env, action_noise=action_noise, verbose=0)
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# Create the callback: check every 1000 steps
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callback = SaveOnBestTrainingRewardCallback(check_freq=1000, log_dir=log_dir)
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# Train the agent
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@ -267,8 +259,8 @@ Training a RL agent on Atari games is straightforward thanks to ``make_atari_env
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It will do `all the preprocessing <https://danieltakeshi.github.io/2016/11/25/frame-skipping-and-preprocessing-for-deep-q-networks-on-atari-2600-games/>`_
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and multiprocessing for you.
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.. .. image:: ../_static/img/colab-badge.svg
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.. :target: https://colab.research.google.com/github/Stable-Baselines-Team/rl-colab-notebooks/blob/sb3/atari_games.ipynb
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.. image:: ../_static/img/colab-badge.svg
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:target: https://colab.research.google.com/github/Stable-Baselines-Team/rl-colab-notebooks/blob/sb3/atari_games.ipynb
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..
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.. code-block:: python
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@ -3,6 +3,28 @@
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Changelog
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==========
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Pre-Release 0.8.0a0 (WIP)
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------------------------------
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Breaking Changes:
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^^^^^^^^^^^^^^^^^
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New Features:
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^^^^^^^^^^^^^
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Bug Fixes:
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^^^^^^^^^^
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Deprecations:
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^^^^^^^^^^^^^
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Others:
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^^^^^^^
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Documentation:
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^^^^^^^^^^^^^^
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- Updated notebook links
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Pre-Release 0.7.0 (2020-06-10)
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------------------------------
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@ -61,6 +83,7 @@ Documentation:
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- Added a paragraph on "MlpPolicy"/"CnnPolicy" and policy naming scheme under "Developer Guide"
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- Fixed second-level listing in changelog
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Pre-Release 0.6.0 (2020-06-01)
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------------------------------
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@ -1 +1 @@
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0.7.0
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0.8.0a0
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