VectorSensor and StackedSensor

UnitySDK/Assets/ML-Agents/Editor/Tests/DemonstrationTests.cs

@@ -50,7 +50,7 @@ public void TestStoreInitalize()
                 done = true,
                 id = 5,
                 maxStepReached = true,
-                stackedVectorObservation = new List<float>() { 1f, 1f, 1f },
+                floatObservations = new List<float>() { 1f, 1f, 1f },
                 storedTextActions = "TestAction",
                 storedVectorActions = new[] { 0f, 1f },
                 textObservation = "TestAction",

UnitySDK/Assets/ML-Agents/Editor/Tests/EditModeTestInternalBrainTensorGenerator.cs

@@ -1,36 +1,60 @@
 using System.Collections.Generic;
-using System.Linq;
 using Barracuda;
 using NUnit.Framework;
 using UnityEngine;
 using MLAgents.InferenceBrain;
+using System.Reflection;
+
 
 namespace MLAgents.Tests
 {
     public class EditModeTestInternalBrainTensorGenerator
     {
-        static IEnumerable<Agent> GetFakeAgentInfos()
+        static IEnumerable<Agent> GetFakeAgents()
         {
+            var acaGo = new GameObject("TestAcademy");
+            acaGo.AddComponent<TestAcademy>();
+            var aca = acaGo.GetComponent<TestAcademy>();
+            aca.resetParameters = new ResetParameters();
+
             var goA = new GameObject("goA");
+            var bpA = goA.AddComponent<BehaviorParameters>();
+            bpA.brainParameters.vectorObservationSize = 3;
+            bpA.brainParameters.numStackedVectorObservations = 1;
             var agentA = goA.AddComponent<TestAgent>();
+
+            var goB = new GameObject("goB");
+            var bpB = goA.AddComponent<BehaviorParameters>();
+            bpB.brainParameters.vectorObservationSize = 3;
+            bpB.brainParameters.numStackedVectorObservations = 1;
+            var agentB = goB.AddComponent<TestAgent>();
+
+            var agents = new List<Agent> { agentA, agentB };
+            foreach (var agent in agents)
+            {
+                var agentEnableMethod = typeof(Agent).GetMethod("OnEnableHelper",
+                    BindingFlags.Instance | BindingFlags.NonPublic);
+                agentEnableMethod?.Invoke(agent, new object[] { aca });
+            }
+            agentA.collectObservationsSensor.AddObservation(new Vector3(1, 2, 3));
+            agentB.collectObservationsSensor.AddObservation(new Vector3(4, 5, 6));
+
             var infoA = new AgentInfo
             {
-                stackedVectorObservation = new[] { 1f, 2f, 3f }.ToList(),
                 storedVectorActions = new[] { 1f, 2f },
                 actionMasks = null
             };
-            var goB = new GameObject("goB");
-            var agentB = goB.AddComponent<TestAgent>();
+
             var infoB = new AgentInfo
             {
-                stackedVectorObservation = new[] { 4f, 5f, 6f }.ToList(),
                 storedVectorActions = new[] { 3f, 4f },
                 actionMasks = new[] { true, false, false, false, false },
             };
+
             agentA.Info = infoA;
             agentB.Info = infoB;
 
-            return new List<Agent> { agentA, agentB };
+            return agents;
         }
 
         [Test]
@@ -77,9 +101,12 @@ public void GenerateVectorObservation()
                 shape = new long[] { 2, 3 }
             };
             const int batchSize = 4;
-            var agentInfos = GetFakeAgentInfos();
+            var agentInfos = GetFakeAgents();
             var alloc = new TensorCachingAllocator();
             var generator = new VectorObservationGenerator(alloc);
+            generator.AddSensorIndex(0);
+            generator.AddSensorIndex(1);
+            generator.AddSensorIndex(2);
             generator.Generate(inputTensor, batchSize, agentInfos);
             Assert.IsNotNull(inputTensor.data);
             Assert.AreEqual(inputTensor.data[0, 0], 1);
@@ -98,7 +125,7 @@ public void GeneratePreviousActionInput()
                 valueType = TensorProxy.TensorType.Integer
             };
             const int batchSize = 4;
-            var agentInfos = GetFakeAgentInfos();
+            var agentInfos = GetFakeAgents();
             var alloc = new TensorCachingAllocator();
             var generator = new PreviousActionInputGenerator(alloc);
 
@@ -120,7 +147,7 @@ public void GenerateActionMaskInput()
                 valueType = TensorProxy.TensorType.FloatingPoint
             };
             const int batchSize = 4;
-            var agentInfos = GetFakeAgentInfos();
+            var agentInfos = GetFakeAgents();
             var alloc = new TensorCachingAllocator();
             var generator = new ActionMaskInputGenerator(alloc);
             generator.Generate(inputTensor, batchSize, agentInfos);

UnitySDK/Assets/ML-Agents/Editor/Tests/MLAgentsEditModeTest.cs

@@ -2,7 +2,6 @@
 using NUnit.Framework;
 using System.Reflection;
 using MLAgents.Sensor;
-using MLAgents.InferenceBrain;
 
 namespace MLAgents.Tests
 {
@@ -83,10 +82,14 @@ public TestSensor(string n)
 
         public int[] GetFloatObservationShape()
         {
-            return new[] { 1 };
+            return new[] { 0 };
         }
 
-        public void WriteToTensor(TensorProxy tensorProxy, int agentIndex) { }
+        public int Write(WriteAdapter adapter)
+        {
+            // No-op
+            return 0;
+        }
 
         public byte[] GetCompressedObservation()
         {

UnitySDK/Assets/ML-Agents/Editor/Tests/RayPerceptionTests.cs

@@ -15,7 +15,6 @@ public void TestPerception3D()
             var go = new GameObject("MyGameObject");
             var rayPer3D = go.AddComponent<RayPerception3D>();
             var result = rayPer3D.Perceive(1f, angles, tags);
-            Debug.Log(result.Count);
             Assert.IsTrue(result.Count == angles.Length * (tags.Length + 2));
         }
 

UnitySDK/Assets/ML-Agents/Editor/Tests/StandaloneBuildTest.cs

@@ -28,9 +28,9 @@ static void BuildStandalonePlayerOSX()
             }
 #else
             var error = buildResult;
-            var isOK = string.IsNullOrEmpty(error);
+            var isOk = string.IsNullOrEmpty(error);
 #endif
-            if (isOK)
+            if (isOk)
             {
                 EditorApplication.Exit(0);
             }

UnitySDK/Assets/ML-Agents/Scripts/Agent.cs

@@ -12,23 +12,14 @@ namespace MLAgents
     /// </summary>
     public struct AgentInfo
     {
-        /// <summary>
-        /// Most recent agent vector (i.e. numeric) observation.
-        /// </summary>
-        public List<float> vectorObservation;
-
-        /// <summary>
-        /// The previous agent vector observations, stacked. The length of the
-        /// history (i.e. number of vector observations to stack) is specified
-        /// in the Brain parameters.
-        /// </summary>
-        public List<float> stackedVectorObservation;
-
         /// <summary>
         /// Most recent compressed observations.
         /// </summary>
         public List<CompressedObservation> compressedObservations;
 
+        // TODO struct?
+        public List<float> floatObservations;
+
         /// <summary>
         /// Most recent text observation.
         /// </summary>
@@ -261,6 +252,10 @@ public AgentInfo Info
         [FormerlySerializedAs("m_Sensors")]
         public List<ISensor> sensors;
 
+        public VectorSensor collectObservationsSensor;
+
+        WriteAdapter m_WriteAdapter = new WriteAdapter();
+
         /// MonoBehaviour function that is called when the attached GameObject
         /// becomes enabled or active.
         void OnEnable()
@@ -475,16 +470,12 @@ void ResetData()
             if (m_Info.textObservation == null)
                 m_Info.textObservation = "";
             m_Action.textActions = "";
-            m_Info.vectorObservation =
-                new List<float>(param.vectorObservationSize);
-            m_Info.stackedVectorObservation =
-                new List<float>(param.vectorObservationSize
-                    * param.numStackedVectorObservations);
-            m_Info.stackedVectorObservation.AddRange(
-                new float[param.vectorObservationSize
-                          * param.numStackedVectorObservations]);
 
             m_Info.compressedObservations = new List<CompressedObservation>();
+            m_Info.floatObservations = new List<float>();
+            m_Info.floatObservations.AddRange(
+                new float[param.vectorObservationSize
+                    * param.numStackedVectorObservations]);
             m_Info.customObservation = null;
         }
 
@@ -523,13 +514,30 @@ public virtual float[] Heuristic()
         /// </summary>
         public void InitializeSensors()
         {
+            // Get all attached sensor components
             var attachedSensorComponents = GetComponents<SensorComponent>();
             sensors.Capacity += attachedSensorComponents.Length;
             foreach (var component in attachedSensorComponents)
             {
                 sensors.Add(component.CreateSensor());
             }
 
+            // Support legacy CollectObservations
+            var param = m_PolicyFactory.brainParameters;
+            if (param.vectorObservationSize > 0)
+            {
+                collectObservationsSensor = new VectorSensor(param.vectorObservationSize);
+                if (param.numStackedVectorObservations > 1)
+                {
+                    var stackingSensor = new StackingSensor(collectObservationsSensor, param.numStackedVectorObservations);
+                    sensors.Add(stackingSensor);
+                }
+                else
+                {
+                    sensors.Add(collectObservationsSensor);
+                }
+            }
+
             // Sort the Sensors by name to ensure determinism
             sensors.Sort((x, y) => x.GetName().CompareTo(y.GetName()));
 
@@ -554,7 +562,6 @@ void SendInfoToBrain()
 
             m_Info.storedVectorActions = m_Action.vectorActions;
             m_Info.storedTextActions = m_Action.textActions;
-            m_Info.vectorObservation.Clear();
             m_Info.compressedObservations.Clear();
             m_ActionMasker.ResetMask();
             using (TimerStack.Instance.Scoped("CollectObservations"))
@@ -563,21 +570,7 @@ void SendInfoToBrain()
             }
             m_Info.actionMasks = m_ActionMasker.GetMask();
 
-            var param = m_PolicyFactory.brainParameters;
-            if (m_Info.vectorObservation.Count != param.vectorObservationSize)
-            {
-                throw new UnityAgentsException(string.Format(
-                    "Vector Observation size mismatch in continuous " +
-                    "agent {0}. " +
-                    "Was Expecting {1} but received {2}. ",
-                    gameObject.name,
-                    param.vectorObservationSize,
-                    m_Info.vectorObservation.Count));
-            }
-
-            Utilities.ShiftLeft(m_Info.stackedVectorObservation, param.vectorObservationSize);
-            Utilities.ReplaceRange(m_Info.stackedVectorObservation, m_Info.vectorObservation,
-                m_Info.stackedVectorObservation.Count - m_Info.vectorObservation.Count);
+            // var param = m_PolicyFactory.brainParameters; // look, no brain params!
 
             m_Info.reward = m_Reward;
             m_Info.done = m_Done;
@@ -609,18 +602,27 @@ void SendInfoToBrain()
         /// </summary>
         public void GenerateSensorData()
         {
+
+            int floatsWritten = 0;
             // Generate data for all Sensors
-            // TODO add bool argument indicating when to compress? For now, we always will compress.
             for (var i = 0; i < sensors.Count; i++)
             {
                 var sensor = sensors[i];
-                var compressedObs = new CompressedObservation
+                if (sensor.GetCompressionType() == SensorCompressionType.None)
                 {
-                    Data = sensor.GetCompressedObservation(),
-                    Shape = sensor.GetFloatObservationShape(),
-                    CompressionType = sensor.GetCompressionType()
-                };
-                m_Info.compressedObservations.Add(compressedObs);
+                    m_WriteAdapter.SetTarget(m_Info.floatObservations, floatsWritten);
+                    floatsWritten += sensor.Write(m_WriteAdapter);
+                }
+                else
+                {
+                    var compressedObs = new CompressedObservation
+                    {
+                        Data = sensor.GetCompressedObservation(),
+                        Shape = sensor.GetFloatObservationShape(),
+                        CompressionType = sensor.GetCompressionType()
+                    };
+                    m_Info.compressedObservations.Add(compressedObs);
+                }
             }
         }
 
@@ -719,7 +721,7 @@ protected void SetActionMask(int branch, IEnumerable<int> actionIndices)
         /// <param name="observation">Observation.</param>
         protected void AddVectorObs(float observation)
         {
-            m_Info.vectorObservation.Add(observation);
+            collectObservationsSensor.AddObservation(observation);
         }
 
         /// <summary>
@@ -729,7 +731,7 @@ protected void AddVectorObs(float observation)
         /// <param name="observation">Observation.</param>
         protected void AddVectorObs(int observation)
         {
-            m_Info.vectorObservation.Add(observation);
+            collectObservationsSensor.AddObservation(observation);
         }
 
         /// <summary>
@@ -739,9 +741,7 @@ protected void AddVectorObs(int observation)
         /// <param name="observation">Observation.</param>
         protected void AddVectorObs(Vector3 observation)
         {
-            m_Info.vectorObservation.Add(observation.x);
-            m_Info.vectorObservation.Add(observation.y);
-            m_Info.vectorObservation.Add(observation.z);
+            collectObservationsSensor.AddObservation(observation);
         }
 
         /// <summary>
@@ -751,8 +751,7 @@ protected void AddVectorObs(Vector3 observation)
         /// <param name="observation">Observation.</param>
         protected void AddVectorObs(Vector2 observation)
         {
-            m_Info.vectorObservation.Add(observation.x);
-            m_Info.vectorObservation.Add(observation.y);
+            collectObservationsSensor.AddObservation(observation);
         }
 
         /// <summary>
@@ -762,7 +761,7 @@ protected void AddVectorObs(Vector2 observation)
         /// <param name="observation">Observation.</param>
         protected void AddVectorObs(IEnumerable<float> observation)
         {
-            m_Info.vectorObservation.AddRange(observation);
+            collectObservationsSensor.AddObservation(observation);
         }
 
         /// <summary>
@@ -772,10 +771,7 @@ protected void AddVectorObs(IEnumerable<float> observation)
         /// <param name="observation">Observation.</param>
         protected void AddVectorObs(Quaternion observation)
         {
-            m_Info.vectorObservation.Add(observation.x);
-            m_Info.vectorObservation.Add(observation.y);
-            m_Info.vectorObservation.Add(observation.z);
-            m_Info.vectorObservation.Add(observation.w);
+            collectObservationsSensor.AddObservation(observation);
         }
 
         /// <summary>
@@ -785,14 +781,12 @@ protected void AddVectorObs(Quaternion observation)
         /// <param name="observation"></param>
         protected void AddVectorObs(bool observation)
         {
-            m_Info.vectorObservation.Add(observation ? 1f : 0f);
+            collectObservationsSensor.AddObservation(observation);
         }
 
         protected void AddVectorObs(int observation, int range)
         {
-            var oneHotVector = new float[range];
-            oneHotVector[observation] = 1;
-            m_Info.vectorObservation.AddRange(oneHotVector);
+            collectObservationsSensor.AddOneHotObservation(observation, range);
         }
 
         /// <summary>

UnitySDK/Assets/ML-Agents/Scripts/Grpc/GrpcExtensions.cs

@@ -19,7 +19,7 @@ public static AgentInfoProto ToProto(this AgentInfo ai)
         {
             var agentInfoProto = new AgentInfoProto
             {
-                StackedVectorObservation = { ai.stackedVectorObservation },
+                StackedVectorObservation = { ai.floatObservations },
                 StoredVectorActions = { ai.storedVectorActions },
                 StoredTextActions = ai.storedTextActions,
                 TextObservation = ai.textObservation,