remove IDimensionPropertiesSensor.cs

com.unity.ml-agents/Runtime/Analytics/Events.cs

 
         public static EventObservationSpec FromSensor(ISensor sensor)
         {
-            var shape = sensor.GetObservationSpec().Shape;
-            var dimProps = (sensor as IDimensionPropertiesSensor)?.GetDimensionProperties();
+            var obsSpec = sensor.GetObservationSpec();
+            var shape = obsSpec.Shape;
+            var dimProps = obsSpec.DimensionProperties;
-                dimInfos[i].Flags = dimProps != null ? (int)dimProps[i] : 0;
+                dimInfos[i].Flags = (int)dimProps[i];
             }
 
             var builtInSensorType =

com.unity.ml-agents/Runtime/Communicator/GrpcExtensions.cs

         /// <returns></returns>
         public static ObservationProto GetObservationProto(this ISensor sensor, ObservationWriter observationWriter)
         {
-            var shape = sensor.GetObservationSpec().Shape;
+            var obsSpec = sensor.GetObservationSpec();
+            var shape = obsSpec.Shape;
             ObservationProto observationProto = null;
             var compressionType = sensor.GetCompressionType();
             // Check capabilities if we need to concatenate PNGs
                     observationProto.CompressedChannelMapping.AddRange(compressibleSensor.GetCompressedChannelMapping());
                 }
             }
-            // Add the dimension properties if any to the observationProto
-            var dimensionPropertySensor = sensor as IDimensionPropertiesSensor;
-            if (dimensionPropertySensor != null)
+
+            // Add the dimension properties to the observationProto
+            var dimensionProperties = obsSpec.DimensionProperties;
+            for (int i = 0; i < dimensionProperties.Length; i++)
-                var dimensionProperties = dimensionPropertySensor.GetDimensionProperties();
-                int[] intDimensionProperties = new int[dimensionProperties.Length];
-                for (int i = 0; i < dimensionProperties.Length; i++)
-                {
-                    observationProto.DimensionProperties.Add((int)dimensionProperties[i]);
-                }
-                // Checking trainer compatibility with variable length observations
-                if (dimensionProperties.Length == 2)
+                observationProto.DimensionProperties.Add((int)dimensionProperties[i]);
+            }
+
+            // Checking trainer compatibility with variable length observations
+            if (dimensionProperties == new InplaceArray<DimensionProperty>(DimensionProperty.VariableSize, DimensionProperty.None))
+            {
+                var trainerCanHandleVarLenObs = Academy.Instance.TrainerCapabilities == null || Academy.Instance.TrainerCapabilities.VariableLengthObservation;
+                if (!trainerCanHandleVarLenObs)
-                    if (dimensionProperties[0] == DimensionProperty.VariableSize &&
-                    dimensionProperties[1] == DimensionProperty.None)
-                    {
-                        var trainerCanHandleVarLenObs = Academy.Instance.TrainerCapabilities == null || Academy.Instance.TrainerCapabilities.VariableLengthObservation;
-                        if (!trainerCanHandleVarLenObs)
-                        {
-                            throw new UnityAgentsException("Variable Length Observations are not supported by the trainer");
-                        }
-                    }
+                    throw new UnityAgentsException("Variable Length Observations are not supported by the trainer");
+
             // Implement IEnumerable or IList?
             for (var i = 0; i < shape.Length; i++)
             {

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

     /// <summary>
     /// A Sensor that allows to observe a variable number of entities.
     /// </summary>
-    public class BufferSensor : ISensor, IDimensionPropertiesSensor, IBuiltInSensor
+    public class BufferSensor : ISensor, IBuiltInSensor
     {
         private string m_Name;
         private int m_MaxNumObs;
         ObservationSpec m_ObservationSpec;
 
-        static DimensionProperty[] s_DimensionProperties = new DimensionProperty[]{
-                DimensionProperty.VariableSize,
-                DimensionProperty.None
-            };
         public BufferSensor(int maxNumberObs, int obsSize, string name)
         {
             m_Name = name;
         public ObservationSpec GetObservationSpec()
         {
             return m_ObservationSpec;
-        }
-
-        /// <inheritdoc/>
-        public DimensionProperty[] GetDimensionProperties()
-        {
-            return s_DimensionProperties;
         }
 
         /// <summary>

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

     /// <summary>
     /// A sensor that wraps a Camera object to generate visual observations for an agent.
     /// </summary>
-    public class CameraSensor : ISensor, IBuiltInSensor, IDimensionPropertiesSensor
+    public class CameraSensor : ISensor, IBuiltInSensor
     {
         Camera m_Camera;
         int m_Width;
         //int[] m_Shape;
         private ObservationSpec m_ObservationSpec;
         SensorCompressionType m_CompressionType;
-        static DimensionProperty[] s_DimensionProperties = new DimensionProperty[] {
-            DimensionProperty.TranslationalEquivariance,
-            DimensionProperty.TranslationalEquivariance,
-            DimensionProperty.None };
 
         /// <summary>
         /// The Camera used for rendering the sensor observations.
         public ObservationSpec GetObservationSpec()
         {
             return m_ObservationSpec;
-        }
-
-        /// <summary>
-        /// Accessor for the dimension properties of a camera sensor. A camera sensor
-        /// Has translational equivariance along width and hight and no property along
-        /// the channels dimension.
-        /// </summary>
-        /// <returns></returns>
-        public DimensionProperty[] GetDimensionProperties()
-        {
-            return s_DimensionProperties;
         }
 
         /// <summary>

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

     }
 
     /// <summary>
+    /// The Dimension property flags of the observations
+    /// </summary>
+    [System.Flags]
+    public enum DimensionProperty
+    {
+        /// <summary>
+        /// No properties specified.
+        /// </summary>
+        Unspecified = 0,
+
+        /// <summary>
+        /// No Property of the observation in that dimension. Observation can be processed with
+        /// fully connected networks.
+        /// </summary>
+        None = 1,
+
+        /// <summary>
+        /// Means it is suitable to do a convolution in this dimension.
+        /// </summary>
+        TranslationalEquivariance = 2,
+
+        /// <summary>
+        /// Means that there can be a variable number of observations in this dimension.
+        /// The observations are unordered.
+        /// </summary>
+        VariableSize = 4,
+    }
+
+    /// <summary>
     /// Sensor interface for generating observations.
     /// </summary>
     public interface ISensor

com.unity.ml-agents/Tests/Editor/ParameterLoaderTest.cs

             return new int[] { shape[0], shape[1], shape[2] };
         }
     }
-    public class Test3DSensor : ISensor, IBuiltInSensor, IDimensionPropertiesSensor
+    public class Test3DSensor : ISensor, IBuiltInSensor
     {
         int m_Width;
         int m_Height;
         public BuiltInSensorType GetBuiltInSensorType()
         {
             return (BuiltInSensorType)k_BuiltInSensorType;
-        }
-
-        public DimensionProperty[] GetDimensionProperties()
-        {
-            return new[]
-            {
-                DimensionProperty.TranslationalEquivariance,
-                DimensionProperty.TranslationalEquivariance,
-                DimensionProperty.None
-            };
         }
     }
 

com.unity.ml-agents/Tests/Editor/Sensor/BufferSensorTest.cs

 
             var bufferSensor = new BufferSensor(20, 4, "testName");
             var shape = bufferSensor.GetObservationSpec().Shape;
-            var dimProp = bufferSensor.GetDimensionProperties();
+            var dimProp = bufferSensor.GetObservationSpec().DimensionProperties;
             Assert.AreEqual(shape[0], 20);
             Assert.AreEqual(shape[1], 4);
             Assert.AreEqual(shape.Length, 2);

com.unity.ml-agents/Runtime/Sensors/IDimensionPropertiesSensor.cs.meta

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

-namespace Unity.MLAgents.Sensors
-{
-
-    /// <summary>
-    /// The Dimension property flags of the observations
-    /// </summary>
-    [System.Flags]
-    public enum DimensionProperty
-    {
-        /// <summary>
-        /// No properties specified.
-        /// </summary>
-        Unspecified = 0,
-
-        /// <summary>
-        /// No Property of the observation in that dimension. Observation can be processed with
-        /// fully connected networks.
-        /// </summary>
-        None = 1,
-
-        /// <summary>
-        /// Means it is suitable to do a convolution in this dimension.
-        /// </summary>
-        TranslationalEquivariance = 2,
-
-        /// <summary>
-        /// Means that there can be a variable number of observations in this dimension.
-        /// The observations are unordered.
-        /// </summary>
-        VariableSize = 4,
-    }
-
-
-    /// <summary>
-    /// Sensor interface for sensors with special dimension properties.
-    /// </summary>
-    internal interface IDimensionPropertiesSensor
-    {
-        /// <summary>
-        /// Returns the array containing the properties of each dimensions of the
-        /// observation. The length of the array must be equal to the rank of the
-        /// observation tensor.
-        /// </summary>
-        /// <returns>The array of DimensionProperty</returns>
-        DimensionProperty[] GetDimensionProperties();
-    }
-}