Update GAE computation docstring (#655)

* Fix typo in buffers.py

* Revert "Fix typo in buffers.py"

This reverts commit ca643d5e3a509ae1b8a65bf0de98f4609ca9d8da.

* Ignore pytype errors

* Update GAE computation docstring

Co-authored-by: Antonin Raffin <antonin.raffin@ensta.org>

docs/misc/changelog.rst

@@ -34,6 +34,7 @@ Documentation:
 - Add highway-env to projects page (@eleurent)
 - Add tactile-gym to projects page (@ac-93)
 - Fix indentation in the RL tips page (@cove9988)
+- Update GAE computation docstring
 
 
 Release 1.3.0 (2021-10-23)

setup.cfg

@@ -16,6 +16,7 @@ filterwarnings =
 
 [pytype]
 inputs = stable_baselines3
+disable = pyi-error
 
 [flake8]
 ignore = W503,W504,E203,E231  # line breaks before and after binary operators

stable_baselines3/common/buffers.py

@@ -352,9 +352,9 @@ class RolloutBuffer(BaseBuffer):
         and GAE(lambda) advantage.
 
         Uses Generalized Advantage Estimation (https://arxiv.org/abs/1506.02438)
-        to compute the advantage. To obtain vanilla advantage (A(s) = R - V(S))
-        where R is the discounted reward with value bootstrap,
-        set ``gae_lambda=1.0`` during initialization.
+        to compute the advantage. To obtain Monte-Carlo advantage estimate (A(s) = R - V(S))
+        where R is the sum of discounted reward with value bootstrap
+        (because we don't always have full episode), set ``gae_lambda=1.0`` during initialization.
 
         The TD(lambda) estimator has also two special cases:
         - TD(1) is Monte-Carlo estimate (sum of discounted rewards)
@@ -364,7 +364,6 @@ class RolloutBuffer(BaseBuffer):
 
         :param last_values: state value estimation for the last step (one for each env)
         :param dones: if the last step was a terminal step (one bool for each env).
-
         """
         # Convert to numpy
         last_values = last_values.clone().cpu().numpy().flatten()
@@ -623,7 +622,7 @@ class DictRolloutBuffer(RolloutBuffer):
     :param action_space: Action space
     :param device:
     :param gae_lambda: Factor for trade-off of bias vs variance for Generalized Advantage Estimator
-        Equivalent to classic advantage when set to 1.
+        Equivalent to Monte-Carlo advantage estimate when set to 1.
     :param gamma: Discount factor
     :param n_envs: Number of parallel environments
     """

stable_baselines3/common/vec_env/stacked_observations.py

@@ -18,6 +18,7 @@ class StackedObservations(object):
 
     :param num_envs: number of environments
     :param n_stack: Number of frames to stack
+    :param observation_space: Environment observation space.
     :param channels_order: If "first", stack on first image dimension. If "last", stack on last dimension.
         If None, automatically detect channel to stack over in case of image observation or default to "last" (default).
     """