Docs examples warning - issue #526 (#530)

* Update a2c.rst

* Update ddpg.rst

* Update dqn.rst

* Update her.rst

* Update ppo.rst

* Update sac.rst

* Update td3.rst

* Update changelog.rst

* modified message

* Update examples.rst

Co-authored-by: Anssi <kaneran21@hotmail.com>

docs/guide/examples.rst

@@ -3,6 +3,11 @@
 Examples
 ========
 
+.. note::
+
+        These examples are only to demonstrate the use of the library and its functions, and the trained agents may not solve the environments. Optimized               hyperparameters can be found in the RL Zoo `repository <https://github.com/DLR-RM/rl-baselines3-zoo>`_.
+
+
 Try it online with Colab Notebooks!
 -----------------------------------
 

docs/misc/changelog.rst

@@ -30,6 +30,7 @@ Documentation:
 - Updated multiprocessing example
 - Added example of ``VecEnvWrapper``
 - Added a note about logging to tensorboard more often
+- Added warning about simplicity of examples and link to RL zoo (@MihaiAnca13)
 
 
 Release 1.1.0 (2021-07-01)
@@ -736,4 +737,4 @@ And all the contributors:
 @diditforlulz273 @liorcohen5 @ManifoldFR @mloo3 @SwamyDev @wmmc88 @megan-klaiber @thisray
 @tfederico @hn2 @LucasAlegre @AptX395 @zampanteymedio @JadenTravnik @decodyng @ardabbour @lorenz-h @mschweizer @lorepieri8 @vwxyzjn
 @ShangqunYu @PierreExeter @JacopoPan @ltbd78 @tom-doerr @Atlis @liusida @09tangriro @amy12xx @juancroldan @benblack769 @bstee615
-@c-rizz @skandermoalla
+@c-rizz @skandermoalla @MihaiAnca13

docs/modules/a2c.rst

@@ -47,6 +47,8 @@ Dict          ❌     ✔️
 Example
 -------
 
+This example is only to demonstrate the use of the library and its functions, and the trained agents may not solve the environments. Optimized hyperparameters can be found in RL Zoo `repository <https://github.com/DLR-RM/rl-baselines3-zoo>`_.
+
 Train a A2C agent on ``CartPole-v1`` using 4 environments.
 
 .. code-block:: python

docs/modules/ddpg.rst

@@ -57,6 +57,8 @@ Dict          ❌     ✔️
 Example
 -------
 
+This example is only to demonstrate the use of the library and its functions, and the trained agents may not solve the environments. Optimized hyperparameters can be found in RL Zoo `repository <https://github.com/DLR-RM/rl-baselines3-zoo>`_.
+
 .. code-block:: python
 
   import gym

docs/modules/dqn.rst

@@ -52,6 +52,8 @@ Dict          ❌      ✔️️
 Example
 -------
 
+This example is only to demonstrate the use of the library and its functions, and the trained agents may not solve the environments. Optimized hyperparameters can be found in RL Zoo `repository <https://github.com/DLR-RM/rl-baselines3-zoo>`_.
+
 .. code-block:: python
 
   import gym

docs/modules/her.rst

@@ -58,6 +58,8 @@ Please refer to the used model (DQN, QR-DQN, SAC, TQC, TD3, or DDPG) for that se
 Example
 -------
 
+This example is only to demonstrate the use of the library and its functions, and the trained agents may not solve the environments. Optimized hyperparameters can be found in RL Zoo `repository <https://github.com/DLR-RM/rl-baselines3-zoo>`_.
+
 .. code-block:: python
 
     from stable_baselines3 import HerReplayBuffer, DDPG, DQN, SAC, TD3

docs/modules/ppo.rst

@@ -48,6 +48,8 @@ Dict          ❌     ✔️
 Example
 -------
 
+This example is only to demonstrate the use of the library and its functions, and the trained agents may not solve the environments. Optimized hyperparameters can be found in RL Zoo `repository <https://github.com/DLR-RM/rl-baselines3-zoo>`_.
+
 Train a PPO agent on ``Pendulum-v0`` using 4 environments.
 
 .. code-block:: python

docs/modules/sac.rst

@@ -64,6 +64,8 @@ Dict          ❌     ✔️
 Example
 -------
 
+This example is only to demonstrate the use of the library and its functions, and the trained agents may not solve the environments. Optimized hyperparameters can be found in RL Zoo `repository <https://github.com/DLR-RM/rl-baselines3-zoo>`_.
+
 .. code-block:: python
 
   import gym

docs/modules/td3.rst

@@ -57,6 +57,8 @@ Dict          ❌     ✔️
 Example
 -------
 
+This example is only to demonstrate the use of the library and its functions, and the trained agents may not solve the environments. Optimized hyperparameters can be found in RL Zoo `repository <https://github.com/DLR-RM/rl-baselines3-zoo>`_.
+
 .. code-block:: python
 
   import gym