Some edits to the documentation

docs/Python-API-Documentation.md

     * [UNSPECIFIED](#mlagents_envs.base_env.DimensionProperty.UNSPECIFIED)
     * [NONE](#mlagents_envs.base_env.DimensionProperty.NONE)
     * [TRANSLATIONAL\_EQUIVARIANCE](#mlagents_envs.base_env.DimensionProperty.TRANSLATIONAL_EQUIVARIANCE)
+    * [VARIABLE\_SIZE](#mlagents_envs.base_env.DimensionProperty.VARIABLE_SIZE)
   * [ObservationType](#mlagents_envs.base_env.ObservationType)
   * [ObservationSpec](#mlagents_envs.base_env.ObservationSpec)
   * [BehaviorSpec](#mlagents_envs.base_env.BehaviorSpec)
 class DimensionProperty(IntFlag)
 ```
 
-No properties specified.
+The dimension property of a dimension of an observation.
-No Property of the observation in that dimension. Observation can be processed with
-Fully connected networks.
+No properties specified.
-Means it is suitable to do a convolution in this dimension.
+No Property of the observation in that dimension. Observation can be processed with
+Fully connected networks.
+
+Means it is suitable to do a convolution in this dimension.
+
+<a name="mlagents_envs.base_env.DimensionProperty.VARIABLE_SIZE"></a>
+#### VARIABLE\_SIZE
 
 Means that there can be a variable number of observations in this dimension.
 The observations are unordered.

ml-agents-envs/mlagents_envs/base_env.py

 
 class DimensionProperty(IntFlag):
     """
+    The dimension property of a dimension of an observation.
+    """
+
+    UNSPECIFIED = 0
+    """
-    UNSPECIFIED = 0
+    NONE = 1
-    NONE = 1
+
+    TRANSLATIONAL_EQUIVARIANCE = 2
-    TRANSLATIONAL_EQUIVARIANCE = 2
+
+    VARIABLE_SIZE = 4
-    VARIABLE_SIZE = 4
 
 
 class ObservationType(Enum):
     """
 
-    # Observation information is generic.
+
-    # Observation contains goal information for current task.
-    GOAL_SIGNAL = 1
+    """
+    Observation information is generic.
+    """
+    GOAL_SIGNAL = 1
+    """
+    Observation contains goal information for current task
+    """
 
 class ObservationSpec(NamedTuple):
     """