cleanup

com.unity.ml-agents/Runtime/Sensors/CameraSensor.cs

         int m_Height;
         bool m_Grayscale;
         string m_Name;
-        //int[] m_Shape;
         private ObservationSpec m_ObservationSpec;
         SensorCompressionType m_CompressionType;
 

com.unity.ml-agents/Runtime/Sensors/ObservationSpec.cs

         /// </remarks>
         public InplaceArray<DimensionProperty> DimensionProperties;
 
-
         /// <summary>
         /// The type of the observation, e.g. whether they are generic or
         /// help determine the goal for the Agent.
         /// <returns></returns>
         public static ObservationSpec Vector(int length)
         {
-            InplaceArray<int> shape = new InplaceArray<int>(length);
-            InplaceArray<DimensionProperty> dimProps = new InplaceArray<DimensionProperty>(DimensionProperty.None);
-            return new ObservationSpec(shape, dimProps);
+            return new ObservationSpec(
+                new InplaceArray<int>(length),
+                new InplaceArray<DimensionProperty>(DimensionProperty.None)
+            );
         }
 
         /// <summary>
         /// <returns></returns>
         public static ObservationSpec VariableLength(int obsSize, int maxNumObs)
         {
-            InplaceArray<int> shape = new InplaceArray<int>(obsSize, maxNumObs);
-            InplaceArray<DimensionProperty> dimProps = new InplaceArray<DimensionProperty>(DimensionProperty.VariableSize, DimensionProperty.None);
-            return new ObservationSpec(shape, dimProps);
+            var dimProps = new InplaceArray<DimensionProperty>(
+                DimensionProperty.VariableSize,
+                DimensionProperty.None
+            );
+            return new ObservationSpec(
+                new InplaceArray<int>(obsSize, maxNumObs),
+                dimProps
+            );
         }
 
         /// <summary>
         /// <returns></returns>
         public static ObservationSpec Visual(int height, int width, int channels)
         {
-            InplaceArray<int> shape = new InplaceArray<int>(height, width, channels);
-            InplaceArray<DimensionProperty> dimProps = new InplaceArray<DimensionProperty>(
-                DimensionProperty.TranslationalEquivariance, DimensionProperty.TranslationalEquivariance, DimensionProperty.None
+            var dimProps = new InplaceArray<DimensionProperty>(
+                DimensionProperty.TranslationalEquivariance,
+                DimensionProperty.TranslationalEquivariance,
+                DimensionProperty.None
-            return new ObservationSpec(shape, dimProps);
+            return new ObservationSpec(
+                new InplaceArray<int>(height, width, channels),
+                dimProps
+            );
+        /// <remarks>
+        /// Note that not all combinations of DimensionProperty may be supported by the trainer.
+        /// shape and dimensionProperties must have the same size.
+        /// </remarks>
-        internal ObservationSpec(
+        public ObservationSpec(
             InplaceArray<int> shape,
             InplaceArray<DimensionProperty> dimensionProperties,
             ObservationType observationType = ObservationType.Default

com.unity.ml-agents/Runtime/Sensors/ObservationWriter.cs

         /// <param name="offset">Offset from the start of the float data to write to.</param>
         internal void SetTarget(IList<float> data, ObservationSpec observationSpec, int offset)
         {
-            // TODO remove int[] version
             SetTarget(data, observationSpec.Shape, offset);
         }
 

com.unity.ml-agents/Runtime/Sensors/VectorSensor.cs

         // TODO use float[] instead
         // TODO allow setting float[]
         List<float> m_Observations;
-        private ObservationSpec m_ObservationSpec;
+        ObservationSpec m_ObservationSpec;
         string m_Name;
 
         /// <summary>