Address comments

Project/Assets/ML-Agents/Examples/SharedAssets/Scripts/VectorSensorComponent.cs

 
 public class VectorSensorComponent : SensorComponent
 {
-    public int observationSize;
+    int m_observationSize;
+    ObservationType m_ObservationType;
+
+    public int ObservationSize
+    {
+        get { return m_observationSize; }
+        set { m_observationSize = value; }
+    }
+
-    public ObservationType observationType;
+    public ObservationType ObservationType
+    {
+        get { return m_ObservationType; }
+        set { m_ObservationType = value; }
+    }
+
 
     /// <summary>
     /// Creates a VectorSensor.
     {
-        sensor = new VectorSensor(observationSize, observationType: observationType);
+        sensor = new VectorSensor(m_observationSize, observationType: m_ObservationType);
         return sensor;
     }
 
-        return new[] { observationSize };
+        return new[] { m_observationSize };
     }
 }

ml-agents/mlagents/trainers/torch/networks.py

         for idx, processor in enumerate(self.processors):
             obs_input = inputs[idx]
             processed_obs = processor(obs_input)
-            if (
-                self.obs_types[idx] == ObservationType.DEFAULT
-                or self.conditioning_type == ConditioningType.DEFAULT
-            ):
+
+            if self.obs_types[idx] == ObservationType.DEFAULT:
-            elif (
-                self.obs_types[idx] == ObservationType.GOAL
-                and self.conditioning_type != ConditioningType.DEFAULT
-            ):
+            elif self.obs_types[idx] == ObservationType.GOAL:
+
+        if self.conditioning_type == ConditioningType.DEFAULT:
+            obs_encodes = obs_encodes + goal_encodes
+            goal_encodes = []
 
         if len(obs_encodes) == 0:
             raise Exception("No valid inputs to network.")