Added Action masking for Space.sample() (#2906)

* Allows a new RNG to be generated with seed=-1 and updated env_checker to fix bug if environment doesn't use np_random in reset

* Revert "fixed `gym.vector.make` where the checker was being applied in the opposite case than was intended to (#2871)"

This reverts commit 519dfd9117.

* Remove bad pushed commits

* Fixed spelling in core.py

* Pins pytest to the last py 3.6 version

* Add support for action masking in Space.sample(mask=...)

* Fix action mask

* Fix action_mask

* Fix action_mask

* Added docstrings, fixed bugs and added taxi examples

* Fixed bugs

* Add tests for sample

* Add docstrings and test space sample mask Discrete and MultiBinary

* Add MultiDiscrete sampling and tests

* Remove sample mask from graph

* Update gym/spaces/multi_discrete.py

Co-authored-by: Markus Krimmel <montcyril@gmail.com>

* Updates based on Marcus28 and jjshoots for Graph.py

* Updates based on Marcus28 and jjshoots for Graph.py

* jjshoot review

* jjshoot review

* Update assert check

* Update type hints

Co-authored-by: Markus Krimmel <montcyril@gmail.com>

gym/spaces/space.py

@@ -1,6 +1,7 @@
 """Implementation of the `Space` metaclass."""
 
 from typing import (
+    Any,
     Generic,
     Iterable,
     List,
@@ -81,8 +82,17 @@ class Space(Generic[T_cov]):
         """Return the shape of the space as an immutable property."""
         return self._shape
 
-    def sample(self) -> T_cov:
-        """Randomly sample an element of this space. Can be uniform or non-uniform sampling based on boundedness of space."""
+    def sample(self, mask: Optional[Any] = None) -> T_cov:
+        """Randomly sample an element of this space.
+
+        Can be uniform or non-uniform sampling based on boundedness of space.
+
+        Args:
+            mask: A mask used for sampling, expected ``dtype=np.int8`` and see sample implementation for expected shape.
+
+        Returns:
+            A sampled actions from the space
+        """
         raise NotImplementedError
 
     def seed(self, seed: Optional[int] = None) -> list: