Low hanging fruit tests for coverage.

Author: surfnerd

com.unity.ml-agents/Runtime/Policies/HeuristicPolicy.cs

@@ -60,7 +60,7 @@ public void Dispose()
         /// Trivial implementation of the IList interface that does nothing.
         /// This is only used for "writing" observations that we will discard.
         /// </summary>
-        class NullList : IList<float>
+        internal class NullList : IList<float>
         {
             public IEnumerator<float> GetEnumerator()
             {

com.unity.ml-agents/Runtime/Policies/RemotePolicy.cs

@@ -1,5 +1,5 @@
-
 using System.Collections.Generic;
+using System.Diagnostics;
 using Unity.MLAgents.Actuators;
 using Unity.MLAgents.Sensors;
 using Unity.MLAgents.Analytics;
@@ -17,7 +17,9 @@ internal class RemotePolicy : IPolicy
         string m_FullyQualifiedBehaviorName;
         ActionSpec m_ActionSpec;
         ActionBuffers m_LastActionBuffer;
+#if MLA_UNITY_ANALYTICS_MODULE
         private bool m_AnalyticsSent = false;
+#endif
 
         internal ICommunicator m_Communicator;
 
@@ -41,6 +43,14 @@ public RemotePolicy(
 
         /// <inheritdoc />
         public void RequestDecision(AgentInfo info, List<ISensor> sensors)
+        {
+            SendAnalytics(sensors);
+            m_AgentId = info.episodeId;
+            m_Communicator?.PutObservations(m_FullyQualifiedBehaviorName, info, sensors);
+        }
+
+        [Conditional("MLA_UNITY_ANALYTICS_MODULE")]
+        void SendAnalytics(IList<ISensor> sensors)
         {
             if (!m_AnalyticsSent)
             {
@@ -52,8 +62,6 @@ public void RequestDecision(AgentInfo info, List<ISensor> sensors)
                     m_Actuators
                 );
             }
-            m_AgentId = info.episodeId;
-            m_Communicator?.PutObservations(m_FullyQualifiedBehaviorName, info, sensors);
         }
 
         /// <inheritdoc />

com.unity.ml-agents/Tests/Editor/Communicator/GrpcExtensionsTests.cs

@@ -1,4 +1,7 @@
 using System;
+using System.Text.RegularExpressions;
+using Google.Protobuf;
+using Google.Protobuf.Collections;
 using NUnit.Framework;
 using Unity.MLAgents.Actuators;
 using Unity.MLAgents.Demonstrations;
@@ -7,18 +10,33 @@
 
 using Unity.MLAgents.Analytics;
 using Unity.MLAgents.CommunicatorObjects;
+using UnityEditor.VersionControl;
+using UnityEngine;
+using UnityEngine.TestTools;
 
 namespace Unity.MLAgents.Tests
 {
     [TestFixture]
     public class GrpcExtensionsTests
     {
+        [SetUp]
+        public void SetUp()
+        {
+            Academy.Instance.TrainerCapabilities = new UnityRLCapabilities();
+        }
+
         [Test]
         public void TestDefaultBrainParametersToProto()
         {
             // Should be able to convert a default instance to proto.
             var brain = new BrainParameters();
             brain.ToProto("foo", false);
+            Academy.Instance.TrainerCapabilities = new UnityRLCapabilities
+            {
+                BaseRLCapabilities = true,
+                HybridActions = false
+            };
+            brain.ToProto("foo", false);
         }
 
         [Test]
@@ -27,22 +45,104 @@ public void TestDefaultActionSpecToProto()
             // Should be able to convert a default instance to proto.
             var actionSpec = new ActionSpec();
             actionSpec.ToBrainParametersProto("foo", false);
+            Academy.Instance.TrainerCapabilities = new UnityRLCapabilities
+            {
+                BaseRLCapabilities = true,
+                HybridActions = false
+            };
+            actionSpec.ToBrainParametersProto("foo", false);
 
+            Academy.Instance.TrainerCapabilities = new UnityRLCapabilities();
             // Continuous
             actionSpec = ActionSpec.MakeContinuous(3);
             actionSpec.ToBrainParametersProto("foo", false);
+            Academy.Instance.TrainerCapabilities = new UnityRLCapabilities
+            {
+                BaseRLCapabilities = true,
+                HybridActions = false
+            };
+            actionSpec.ToBrainParametersProto("foo", false);
+
+            Academy.Instance.TrainerCapabilities = new UnityRLCapabilities();
 
             // Discrete
             actionSpec = ActionSpec.MakeDiscrete(1, 2, 3);
             actionSpec.ToBrainParametersProto("foo", false);
+            Academy.Instance.TrainerCapabilities = new UnityRLCapabilities
+            {
+                BaseRLCapabilities = true,
+                HybridActions = false
+            };
+            actionSpec.ToBrainParametersProto("foo", false);
+        }
+
+        [Test]
+        public void ToBrainParameters()
+        {
+            // Should be able to convert a default instance to proto.
+            var actionSpec = new ActionSpec();
+            actionSpec.ToBrainParametersProto("foo", false).ToBrainParameters();
+            Academy.Instance.TrainerCapabilities = new UnityRLCapabilities
+            {
+                BaseRLCapabilities = true,
+                HybridActions = false
+            };
+            actionSpec.ToBrainParametersProto("foo", false).ToBrainParameters();
+
+            Academy.Instance.TrainerCapabilities = new UnityRLCapabilities();
+            // Continuous
+            actionSpec = ActionSpec.MakeContinuous(3);
+            actionSpec.ToBrainParametersProto("foo", false).ToBrainParameters();
+            Academy.Instance.TrainerCapabilities = new UnityRLCapabilities
+            {
+                BaseRLCapabilities = true,
+                HybridActions = false
+            };
+            actionSpec.ToBrainParametersProto("foo", false).ToBrainParameters();
+
+            Academy.Instance.TrainerCapabilities = new UnityRLCapabilities();
+
+            // Discrete
+            actionSpec = ActionSpec.MakeDiscrete(1, 2, 3);
+            actionSpec.ToBrainParametersProto("foo", false).ToBrainParameters();
+            Academy.Instance.TrainerCapabilities = new UnityRLCapabilities
+            {
+                BaseRLCapabilities = true,
+                HybridActions = false
+            };
+            actionSpec.ToBrainParametersProto("foo", false).ToBrainParameters();
         }
 
         [Test]
         public void TestDefaultAgentInfoToProto()
         {
             // Should be able to convert a default instance to proto.
             var agentInfo = new AgentInfo();
-            agentInfo.ToInfoActionPairProto();
+            var pairProto = agentInfo.ToInfoActionPairProto();
+            pairProto.AgentInfo.Observations.Add(new ObservationProto
+            {
+                CompressedData = ByteString.Empty,
+                CompressionType = CompressionTypeProto.None,
+                FloatData = new ObservationProto.Types.FloatData(),
+                ObservationType = ObservationTypeProto.Default,
+                Name = "Sensor"
+            });
+            pairProto.AgentInfo.Observations[0].Shape.Add(0);
+            pairProto.GetObservationSummaries();
+            agentInfo.ToAgentInfoProto();
+            agentInfo.groupId = 1;
+            Academy.Instance.TrainerCapabilities = new UnityRLCapabilities
+            {
+                BaseRLCapabilities = true,
+                MultiAgentGroups = false
+            };
+            agentInfo.ToAgentInfoProto();
+            LogAssert.Expect(LogType.Warning, new Regex(".+"));
+            Academy.Instance.TrainerCapabilities = new UnityRLCapabilities
+            {
+                BaseRLCapabilities = true,
+                MultiAgentGroups = true
+            };
             agentInfo.ToAgentInfoProto();
         }
 
@@ -164,8 +264,6 @@ public void TestGetObservationProtoCapabilities()
                     Assert.AreEqual(obsProto.CompressedData.Length, 0);
                 }
             }
-
-
         }
 
         [Test]
@@ -185,6 +283,7 @@ public void TestIsTrivialMapping()
             sparseChannelSensor.Mapping = new[] { 0, 0, 0, 1, 1, 1 };
             Assert.AreEqual(GrpcExtensions.IsTrivialMapping(sparseChannelSensor), false);
         }
+
         [Test]
         public void TestDefaultTrainingEvents()
         {