add pre-commit hook for dotnet-format (#4362)

.circleci/config.yml

             # Need ruby for search-and-replace
             sudo apt-get update
             sudo apt-get install ruby-full
+
+            # install dotnet and the formatter - see https://docs.microsoft.com/en-us/dotnet/core/install/linux-debian#debian-9-
+            pushd ~
+            wget -O - https://packages.microsoft.com/keys/microsoft.asc | gpg --dearmor > microsoft.asc.gpg
+            sudo mv microsoft.asc.gpg /etc/apt/trusted.gpg.d/
+            wget https://packages.microsoft.com/config/debian/9/prod.list
+            sudo mv prod.list /etc/apt/sources.list.d/microsoft-prod.list
+            sudo chown root:root /etc/apt/trusted.gpg.d/microsoft.asc.gpg
+            sudo chown root:root /etc/apt/sources.list.d/microsoft-prod.list
+            popd
+
+            sudo apt-get install -y apt-transport-https && \
+              sudo apt-get update && \
+              sudo apt-get install -y dotnet-sdk-3.1 && \
+              dotnet tool install -g dotnet-format --version 4.1.131201
+
+            echo "Setting up venv"
             python3 -m venv venv
             . venv/bin/activate
             pip install --upgrade pip
           name: Check Code Style using pre-commit
           command: |
             . venv/bin/activate
+            export PATH="$PATH:~/.dotnet/tools"
             pre-commit run --show-diff-on-failure --all-files
 
   markdown_link_check:

.pre-commit-config.yaml

         name: validate release links
         language: script
         entry: utils/validate_release_links.py
-
+    -   id: dotnet-format
+        name: dotnet-format
+        language: script
+        entry: utils/run_dotnet_format.py
+        types: [c#]
 

DevProject/Assets/ML-Agents/Scripts/Tests/Performance/SensorPerformanceTests.cs

         {
             using (Measure.ProfilerMarkers(s_Markers))
             {
-                for(var i=0; i<k_MarkerTestSteps; i++)
+                for (var i = 0; i < k_MarkerTestSteps; i++)
                 {
                     RunAgent<CollectObservationsAgent>(k_NumAgentSteps, 7, ObservableAttributeOptions.Ignore);
                 }

Project/Assets/ML-Agents/Editor/DisableBurstFromMenu.cs

-#if UNITY_CLOUD_BUILD
+#if UNITY_CLOUD_BUILD
 using UnityEditor;
 
 public class DisableBurstFromMenu

Project/Assets/ML-Agents/Examples/Crawler/Scripts/CrawlerAgent.cs

     Vector3 m_WalkDir; //Direction to the target
     Quaternion m_WalkDirLookRot; //Will hold the rotation to our target
 
-    [Header("Target To Walk Towards")] [Space(10)]
+    [Header("Target To Walk Towards")]
+    [Space(10)]
     public TargetController target; //Target the agent will walk towards.
 
     [Header("Body Parts")] [Space(10)] public Transform body;
     public Transform leg3Lower;
 
 
-    [Header("Orientation")] [Space(10)]
+    [Header("Orientation")]
+    [Space(10)]
     //This will be used as a stabilized model space reference point for observations
     //Because ragdolls can move erratically during training, using a stabilized reference transform improves learning
     public OrientationCubeController orientationCube;
-    [Header("Reward Functions To Use")] [Space(10)]
+    [Header("Reward Functions To Use")]
+    [Space(10)]
-    [Header("Foot Grounded Visualization")] [Space(10)]
+    [Header("Foot Grounded Visualization")]
+    [Space(10)]
     public bool useFootGroundedVisualization;
 
     public MeshRenderer foot0;
         {
             throw new ArgumentException(
                 "NaN in movingTowardsDot.\n" +
-                $" orientationCube.transform.forward: {orientationCube.transform.forward}\n"+
-                $" body.velocity: {m_JdController.bodyPartsDict[body].rb.velocity}\n"+
+                $" orientationCube.transform.forward: {orientationCube.transform.forward}\n" +
+                $" body.velocity: {m_JdController.bodyPartsDict[body].rb.velocity}\n" +
                 $" maximumWalkingSpeed: {maximumWalkingSpeed}"
             );
         }
         {
             throw new ArgumentException(
                 "NaN in movingTowardsDot.\n" +
-                $" orientationCube.transform.forward: {orientationCube.transform.forward}\n"+
+                $" orientationCube.transform.forward: {orientationCube.transform.forward}\n" +
                 $" body.forward: {body.forward}"
             );
         }

Project/Assets/ML-Agents/Examples/FoodCollector/Scripts/FoodCollectorSettings.cs

         // Send stats via SideChannel so that they'll appear in TensorBoard.
         // These values get averaged every summary_frequency steps, so we don't
         // need to send every Update() call.
-        if ((Time.frameCount % 100)== 0)
+        if ((Time.frameCount % 100) == 0)
         {
             m_Recorder.Add("TotalScore", totalScore);
         }

Project/Assets/ML-Agents/Examples/GridWorld/Scripts/GridAgent.cs

         // Mask the necessary actions if selected by the user.
         if (maskActions)
         {
-           // Prevents the agent from picking an action that would make it collide with a wall
+            // Prevents the agent from picking an action that would make it collide with a wall
             var positionX = (int)transform.position.x;
             var positionZ = (int)transform.position.z;
             var maxPosition = (int)m_ResetParams.GetWithDefault("gridSize", 5f) - 1;
-                actionMask.WriteMask(0, new []{ k_Left});
+                actionMask.WriteMask(0, new[] { k_Left });
-                actionMask.WriteMask(0, new []{k_Right});
+                actionMask.WriteMask(0, new[] { k_Right });
-                actionMask.WriteMask(0, new []{k_Down});
+                actionMask.WriteMask(0, new[] { k_Down });
-                actionMask.WriteMask(0, new []{k_Up});
+                actionMask.WriteMask(0, new[] { k_Up });
             }
         }
     }

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

 
 using UnityEngine;
 
-namespace  MLAgentsExamples
+namespace MLAgentsExamples
 {
     public class AdjustTrainingTimescale : MonoBehaviour
     {

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

-using UnityEngine;
+using UnityEngine;
-       
+
         public bool updatedByAgent; //should this be updated by the agent? If not, it will use local settings
         public Transform transformToFollow; //ex: hips or body
         public Transform targetToLookAt; //target in the scene the indicator will point to

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

     [System.Serializable]
     public class BodyPart
     {
-        [Header("Body Part Info")][Space(10)] public ConfigurableJoint joint;
+        [Header("Body Part Info")] [Space(10)] public ConfigurableJoint joint;
-        [Header("Ground & Target Contact")][Space(10)]
+        [Header("Ground & Target Contact")]
+        [Space(10)]
         public GroundContact groundContact;
 
         public TargetContact targetContact;
 
-        [Header("Current Joint Settings")][Space(10)]
+        [Header("Current Joint Settings")]
+        [Space(10)]
         public Vector3 currentEularJointRotation;
 
         [HideInInspector] public float currentStrength;
 
-        [Header("Other Debug Info")][Space(10)]
+        [Header("Other Debug Info")]
+        [Space(10)]
         public Vector3 currentJointForce;
 
         public float currentJointForceSqrMag;
 
     public class JointDriveController : MonoBehaviour
     {
-        [Header("Joint Drive Settings")][Space(10)]
+        [Header("Joint Drive Settings")]
+        [Space(10)]
         public float maxJointSpring;
 
         public float jointDampen;

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

     /// </summary>
     public class ModelOverrider : MonoBehaviour
     {
-        HashSet<string> k_SupportedExtensions = new HashSet<string>{"nn", "onnx"};
+        HashSet<string> k_SupportedExtensions = new HashSet<string> { "nn", "onnx" };
         const string k_CommandLineModelOverrideFlag = "--mlagents-override-model";
         const string k_CommandLineModelOverrideDirectoryFlag = "--mlagents-override-model-directory";
         const string k_CommandLineModelOverrideExtensionFlag = "--mlagents-override-model-extension";
 
         int TotalCompletedEpisodes
         {
-            get { return m_PreviousAgentCompletedEpisodes + (m_Agent == null ? 0 : m_Agent.CompletedEpisodes);  }
+            get { return m_PreviousAgentCompletedEpisodes + (m_Agent == null ? 0 : m_Agent.CompletedEpisodes); }
         }
 
         int TotalNumSteps
 
         public bool HasOverrides
         {
-            get { return m_BehaviorNameOverrides.Count > 0 || !string.IsNullOrEmpty(m_BehaviorNameOverrideDirectory);  }
+            get { return m_BehaviorNameOverrides.Count > 0 || !string.IsNullOrEmpty(m_BehaviorNameOverrideDirectory); }
         }
 
         public static string GetOverrideBehaviorName(string originalBehaviorName)
             var args = commandLineArgsOverride ?? Environment.GetCommandLineArgs();
             for (var i = 0; i < args.Length; i++)
             {
-                if (args[i] == k_CommandLineModelOverrideFlag && i < args.Length-2)
+                if (args[i] == k_CommandLineModelOverrideFlag && i < args.Length - 2)
-                else if (args[i] == k_CommandLineModelOverrideDirectoryFlag && i < args.Length-1)
+                else if (args[i] == k_CommandLineModelOverrideDirectoryFlag && i < args.Length - 1)
-                else if (args[i] == k_CommandLineModelOverrideExtensionFlag && i < args.Length-1)
+                else if (args[i] == k_CommandLineModelOverrideExtensionFlag && i < args.Length - 1)
                 {
                     m_OverrideExtension = args[i + 1].Trim().ToLower();
                     var isKnownExtension = k_SupportedExtensions.Contains(m_OverrideExtension);
 #endif
                     }
                 }
-                else if (args[i] == k_CommandLineQuitAfterEpisodesFlag && i < args.Length-1)
+                else if (args[i] == k_CommandLineQuitAfterEpisodesFlag && i < args.Length - 1)
                 {
                     Int32.TryParse(args[i + 1], out maxEpisodes);
                 }
             {
                 assetPath = m_BehaviorNameOverrides[behaviorName];
             }
-            else if(!string.IsNullOrEmpty(m_BehaviorNameOverrideDirectory))
+            else if (!string.IsNullOrEmpty(m_BehaviorNameOverrideDirectory))
             {
                 assetPath = Path.Combine(m_BehaviorNameOverrideDirectory, $"{behaviorName}.{m_OverrideExtension}");
             }
             {
                 model = File.ReadAllBytes(assetPath);
             }
-            catch(IOException)
+            catch (IOException)
             {
                 Debug.Log($"Couldn't load file {assetPath} at full path {Path.GetFullPath(assetPath)}", this);
                 // Cache the null so we don't repeatedly try to load a missing file
 
             if (!overrideOk && m_QuitOnLoadFailure)
             {
-                if(!string.IsNullOrEmpty(overrideError))
+                if (!string.IsNullOrEmpty(overrideError))
                 {
                     Debug.LogWarning(overrideError);
                 }

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

-using System.Collections.Generic;
+using System.Collections.Generic;
 using System.Linq;
 using UnityEngine;
 
                 var displayValues = s_DisplayTransformValues[target];
 
                 var index = 0;
-                var orderedKeys = displayValues.Keys.OrderBy(x => - displayValues[x].time);
+                var orderedKeys = displayValues.Keys.OrderBy(x => -displayValues[x].time);
                 foreach (var key in orderedKeys)
                 {
                     s_KeyStyle.alignment = TextAnchor.MiddleRight;
             s_RedStyle = s_ColorStyle[5];
         }
     }
-}
+}

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

-using UnityEngine;
+using UnityEngine;
 
 namespace Unity.MLAgentsExamples
 {

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

             m_OriginalMaximumDeltaTime = Time.maximumDeltaTime;
             m_OriginalSolverIterations = Physics.defaultSolverIterations;
             m_OriginalSolverVelocityIterations = Physics.defaultSolverVelocityIterations;
-            m_OriginalReuseCollisionCallbacks = Physics.reuseCollisionCallbacks ;
+            m_OriginalReuseCollisionCallbacks = Physics.reuseCollisionCallbacks;
 
             // Override
             Physics.gravity *= gravityMultiplier;

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

         }
 
         /// <inheritdoc/>
-        public void Update() {}
+        public void Update() { }
 
         /// <inheritdoc/>
         public void Reset() { }

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

-using UnityEngine;
+using UnityEngine;
 using Random = UnityEngine.Random;
 using Unity.MLAgents;
 using UnityEngine.Events;
     /// </summary>
     public class TargetController : MonoBehaviour
     {
-        
+
-        
+
-        
+
         [Header("Target Fell Protection")]
         public bool respawnIfFallsOffPlatform = true; //If the target falls off the platform, reset the position.
         public float fallDistance = 5; //distance below the starting height that will trigger a respawn 

Project/Assets/ML-Agents/Examples/Startup/Scripts/Startup.cs

             // no scene environment variable is found.
             var args = Environment.GetCommandLineArgs();
             Console.WriteLine("Command line arguments passed: " + String.Join(" ", args));
-            for (int i = 0; i < args.Length; i++) {
-                if (args [i] == k_SceneCommandLineFlag && i < args.Length - 1) {
+            for (int i = 0; i < args.Length; i++)
+            {
+                if (args[i] == k_SceneCommandLineFlag && i < args.Length - 1)
+                {
                     sceneName = args[i + 1];
                 }
             }

Project/Assets/ML-Agents/Examples/Tennis/Scripts/HitWall.cs

     public bool net;
 
     public enum FloorHit
-        {
-            Service,
-            FloorHitUnset,
-            FloorAHit,
-            FloorBHit
-        }
+    {
+        Service,
+        FloorHitUnset,
+        FloorAHit,
+        FloorBHit
+    }
 
     public FloorHit lastFloorHit;
 
         lastFloorHit = FloorHit.Service;
         net = false;
     }
-    
+
     void AgentAWins()
     {
         m_AgentA.SetReward(1);

Project/Assets/ML-Agents/Examples/Worm/Scripts/WormAgent.cs

     public bool respawnTargetWhenTouched;
     public float targetSpawnRadius;
 
-    [Header("Body Parts")] [Space(10)]
+    [Header("Body Parts")]
+    [Space(10)]
-    [Header("Joint Settings")] [Space(10)]
+    [Header("Joint Settings")]
+    [Space(10)]
     JointDriveController m_JdController;
     Vector3 m_DirToTarget;
     float m_MovingTowardsDot;
     //We want to collect this info because it is the actual rotation, not the "target rotation"
     public Quaternion GetJointRotation(ConfigurableJoint joint)
     {
-        return(Quaternion.FromToRotation(joint.axis, joint.connectedBody.transform.rotation.eulerAngles));
+        return (Quaternion.FromToRotation(joint.axis, joint.connectedBody.transform.rotation.eulerAngles));
     }
 
     /// <summary>
         float maxDist = 10;
         if (Physics.Raycast(bodySegment0.position, Vector3.down, out hit, maxDist))
         {
-            sensor.AddObservation(hit.distance/maxDist);
+            sensor.AddObservation(hit.distance / maxDist);
         }
         else
             sensor.AddObservation(1);
         bpDict[bodySegment2].SetJointStrength(continuousActions[++i]);
         bpDict[bodySegment3].SetJointStrength(continuousActions[++i]);
 
-        if (bodySegment0.position.y < ground.position.y -2)
+        if (bodySegment0.position.y < ground.position.y - 2)
         {
             EndEpisode();
         }

com.unity.ml-agents.extensions/Runtime/Sensors/ArticulationBodyJointExtractor.cs

         }
     }
 }
-#endif
+#endif

com.unity.ml-agents.extensions/Runtime/Sensors/ArticulationBodyPoseExtractor.cs

         }
     }
 }
-#endif // UNITY_2020_1_OR_NEWER
+#endif // UNITY_2020_1_OR_NEWER

com.unity.ml-agents.extensions/Runtime/Sensors/ArticulationBodySensorComponent.cs

     }
 
 }
-#endif // UNITY_2020_1_OR_NEWER
+#endif // UNITY_2020_1_OR_NEWER

com.unity.ml-agents.extensions/Runtime/Sensors/PhysicsBodySensor.cs

 
             var numJointExtractorObservations = 0;
             m_JointExtractors = new List<IJointExtractor>(poseExtractor.NumEnabledPoses);
-            foreach(var rb in poseExtractor.GetEnabledRigidbodies())
+            foreach (var rb in poseExtractor.GetEnabledRigidbodies())
             {
                 var jointExtractor = new RigidBodyJointExtractor(rb);
                 numJointExtractorObservations += jointExtractor.NumObservations(settings);
         }
 
         /// <inheritdoc/>
-        public void Reset() {}
+        public void Reset() { }
 
         /// <inheritdoc/>
         public SensorCompressionType GetCompressionType()

com.unity.ml-agents.extensions/Runtime/Sensors/PhysicsSensorSettings.cs

                     }
                 }
 
-                foreach(var vel in poseExtractor.GetEnabledModelSpaceVelocities())
+                foreach (var vel in poseExtractor.GetEnabledModelSpaceVelocities())
                 {
                     if (settings.UseModelSpaceLinearVelocity)
                     {
                     }
                 }
 
-                foreach(var vel in poseExtractor.GetEnabledLocalSpaceVelocities())
+                foreach (var vel in poseExtractor.GetEnabledLocalSpaceVelocities())
                 {
                     if (settings.UseLocalSpaceLinearVelocity)
                     {

com.unity.ml-agents.extensions/Runtime/Sensors/PoseExtractor.cs

                 var localUp = localPose[i].rotation * Vector3.up;
                 var localFwd = localPose[i].rotation * Vector3.forward;
                 var localRight = localPose[i].rotation * Vector3.right;
-                Debug.DrawLine(current.position+offset, current.position+offset+.1f*localUp, Color.red);
-                Debug.DrawLine(current.position+offset, current.position+offset+.1f*localFwd, Color.green);
-                Debug.DrawLine(current.position+offset, current.position+offset+.1f*localRight, Color.blue);
+                Debug.DrawLine(current.position + offset, current.position + offset + .1f * localUp, Color.red);
+                Debug.DrawLine(current.position + offset, current.position + offset + .1f * localFwd, Color.green);
+                Debug.DrawLine(current.position + offset, current.position + offset + .1f * localRight, Color.blue);
             }
         }
 
                 {
                     // Push to the stack in reverse order
                     var children = tree[current];
-                    for (var childIdx = children.Count-1; childIdx >= 0; childIdx--)
+                    for (var childIdx = children.Count - 1; childIdx >= 0; childIdx--)
-                        stack.Push((children[childIdx], depth+1));
+                        stack.Push((children[childIdx], depth + 1));
                     }
                 }
 

com.unity.ml-agents.extensions/Runtime/Sensors/RigidBodyJointExtractor.cs

 
         public static int NumObservations(Rigidbody body, Joint joint, PhysicsSensorSettings settings)
         {
-            if(body == null || joint == null)
+            if (body == null || joint == null)
             {
                 return 0;
             }

com.unity.ml-agents.extensions/Runtime/Sensors/RigidBodyPoseExtractor.cs

             if (rootGameObject == null)
             {
                 rbs = rootBody.GetComponentsInChildren<Rigidbody>();
-                joints = rootBody.GetComponentsInChildren <Joint>();
+                joints = rootBody.GetComponentsInChildren<Joint>();
             }
             else
             {
 
             for (var i = 0; i < rbs.Length; i++)
             {
-                if(rbs[i] != null)
+                if (rbs[i] != null)
                 {
                     bodyToIndex[rbs[i]] = i;
                 }

com.unity.ml-agents.extensions/Runtime/Sensors/RigidBodySensorComponent.cs

     /// <summary>
     /// Editor component that creates a PhysicsBodySensor for the Agent.
     /// </summary>
-    public class RigidBodySensorComponent  : SensorComponent
+    public class RigidBodySensorComponent : SensorComponent
     {
         /// <summary>
         /// The root Rigidbody of the system.
             var numPoseObservations = poseExtractor.GetNumPoseObservations(Settings);
 
             var numJointObservations = 0;
-            foreach(var rb in poseExtractor.GetEnabledRigidbodies())
+            foreach (var rb in poseExtractor.GetEnabledRigidbodies())
             {
                 var joint = rb.GetComponent<Joint>();
                 numJointObservations += RigidBodyJointExtractor.NumObservations(rb, joint, Settings);

com.unity.ml-agents.extensions/Tests/Editor/Sensors/ArticulationBodyPoseExtractorTests.cs

         }
     }
 }
-#endif
+#endif

com.unity.ml-agents.extensions/Tests/Editor/Sensors/ArticulationBodySensorTests.cs

         }
     }
 }
-#endif // #if UNITY_2020_1_OR_NEWER
+#endif // #if UNITY_2020_1_OR_NEWER

com.unity.ml-agents.extensions/Tests/Editor/Sensors/PoseExtractorTests.cs

                 return Pose.identity;
             }
 
-            protected  internal override Vector3 GetLinearVelocityAt(int index)
+            protected internal override Vector3 GetLinearVelocityAt(int index)
             {
                 return Vector3.zero;
             }
             }
 
             // Getting a parent index should throw an index exception
-            Assert.Throws <NullReferenceException>(
+            Assert.Throws<NullReferenceException>(
                 () => poseExtractor.GetParentIndex(0)
             );
 
                 };
             }
 
-            protected  internal override Vector3 GetLinearVelocityAt(int index)
+            protected internal override Vector3 GetLinearVelocityAt(int index)
             {
                 return Vector3.zero;
             }
         {
             // Degenerate case with a loop
             var poseExtractor = new UselessPoseExtractor();
-            poseExtractor.Init(new[] {-1, 2, 1});
+            poseExtractor.Init(new[] { -1, 2, 1 });
-            poseExtractor.Init(new[] {-1, 1});
+            poseExtractor.Init(new[] { -1, 1 });
 
             // This just shouldn't blow up
             poseExtractor.GetDisplayNodes();

com.unity.ml-agents.extensions/Tests/Editor/Sensors/RigidBodyPoseExtractorTests.cs

             // body 1 has parent 0
             Assert.AreEqual(0, poseExtractor.GetParentIndex(1));
 
-            var virtualRootPos = new Vector3(0,2,0);
+            var virtualRootPos = new Vector3(0, 2, 0);
             var virtualRootRot = Quaternion.Euler(0, 42, 0);
             virtualRoot.transform.position = virtualRootPos;
             virtualRoot.transform.rotation = virtualRootRot;

com.unity.ml-agents.extensions/Tests/Runtime/RuntimeExampleTest.cs

 namespace Unity.MLAgents.Extensions.Tests
 {
 
-    internal class RuntimeExampleTest {
+    internal class RuntimeExampleTest
+    {
 
         [Test]
         public void RuntimeTestMath()

com.unity.ml-agents/CHANGELOG.md

 ### Minor Changes
 #### com.unity.ml-agents (C#)
 - Update Barracuda to 1.0.2.
+- Enabled C# formatting using `dotnet-format`.
 #### ml-agents / ml-agents-envs / gym-unity (Python)
 
 ### Bug Fixes

com.unity.ml-agents/CONTRIBUTING.md

 ### Code style
 
 All python code should be formatted with
-[`black`](https://github.com/ambv/black). Style and formatting for C# may be
-enforced later.
+[`black`](https://github.com/ambv/black).
+
+C# code is formatted using [`dotnet-format`](https://github.com/dotnet/format).
+You must have [dotnet](https://dotnet.microsoft.com/download) and
+`dotnet-format` installed first.
 
 ### Python type annotations
 

com.unity.ml-agents/Editor/DemonstrationImporter.cs

     /// <summary>
     /// Asset Importer used to parse demonstration files.
     /// </summary>
-    [ScriptedImporter(1, new[] {"demo"})]
+    [ScriptedImporter(1, new[] { "demo" })]
     internal class DemonstrationImporter : ScriptedImporter
     {
         const string k_IconPath = "Packages/com.unity.ml-agents/Editor/Icons/DemoIcon.png";

com.unity.ml-agents/Runtime/Academy.cs

                 // This try-catch is because DontDestroyOnLoad cannot be used in Editor Tests
                 GameObject.DontDestroyOnLoad(m_StepperObject);
             }
-            catch {}
+            catch { }
         }
 
         /// <summary>
 
         void ResetActions()
         {
-            DecideAction = () => {};
-            DestroyAction = () => {};
-            AgentPreStep = i => {};
-            AgentSendState = () => {};
-            AgentAct = () => {};
-            AgentForceReset = () => {};
-            OnEnvironmentReset = () => {};
+            DecideAction = () => { };
+            DestroyAction = () => { };
+            AgentPreStep = i => { };
+            AgentSendState = () => { };
+            AgentAct = () => { };
+            AgentForceReset = () => { };
+            OnEnvironmentReset = () => { };
         }
 
         static void OnQuitCommandReceived()

com.unity.ml-agents/Runtime/Actuators/ActionSegment.cs

         /// </summary>
         /// <param name="actionArray">The action array to use for the this segment.</param>
         public ActionSegment(T[] actionArray)
-            : this(actionArray ?? System.Array.Empty<T>(), 0, actionArray?.Length ?? 0) {}
+            : this(actionArray ?? System.Array.Empty<T>(), 0, actionArray?.Length ?? 0) { }
 
         /// <summary>
         /// Construct an <see cref="ActionSegment{T}"/> with an underlying array

com.unity.ml-agents/Runtime/Actuators/ActionSpec.cs

         {
             NumContinuousActions = numContinuousActions;
             NumDiscreteActions = numDiscreteActions;
-            BranchSizes =  branchSizes;
+            BranchSizes = branchSizes;
             SumOfDiscreteBranchSizes = branchSizes?.Sum() ?? 0;
         }
     }

com.unity.ml-agents/Runtime/Actuators/IActionReceiver.cs

         /// <see cref="ActionSegment{T}"/> initialized from a float array.</returns>
         public static ActionBuffers FromDiscreteActions(float[] discreteActions)
         {
-           return new ActionBuffers(ActionSegment<float>.Empty, discreteActions == null ? ActionSegment<int>.Empty
-                               : new ActionSegment<int>(Array.ConvertAll(discreteActions,
-                                   x => (int)x)));
+            return new ActionBuffers(ActionSegment<float>.Empty, discreteActions == null ? ActionSegment<int>.Empty
+                                : new ActionSegment<int>(Array.ConvertAll(discreteActions,
+                                    x => (int)x)));
         }
 
         public ActionBuffers(float[] continuousActions, int[] discreteActions)

com.unity.ml-agents/Runtime/Actuators/VectorActuator.cs

 
         public void WriteDiscreteActionMask(IDiscreteActionMask actionMask)
         {
-                m_ActionReceiver.WriteDiscreteActionMask(actionMask);
+            m_ActionReceiver.WriteDiscreteActionMask(actionMask);
         }
 
         /// <summary>

com.unity.ml-agents/Runtime/Agent.cs

             public int maxStep;
         }
 
-        [SerializeField][HideInInspector]
+        [SerializeField]
+        [HideInInspector]
-        [SerializeField][HideInInspector]
+        [SerializeField]
+        [HideInInspector]
         internal bool hasUpgradedFromAgentParameters;
 
         /// <summary>
         ///
         /// [GameObject]: https://docs.unity3d.com/Manual/GameObjects.html
         /// </remarks>
-        public virtual void Initialize() {}
+        public virtual void Initialize() { }
 
         /// <summary>
         /// Implement `Heuristic()` to choose an action for this agent using a custom heuristic.
         /// </summary>
         /// <seealso cref="Initialize"/>
         /// <seealso cref="EndEpisode"/>
-        public virtual void OnEpisodeBegin() {}
+        public virtual void OnEpisodeBegin() { }
 
         /// <summary>
         /// Gets the last ActionBuffer for this agent.

com.unity.ml-agents/Runtime/Agent.deprecated.cs

             Array.Clear(actionsOut, 0, actionsOut.Length);
         }
 
-        public virtual void OnActionReceived(float[] vectorAction) {}
+        public virtual void OnActionReceived(float[] vectorAction) { }
 
         /// <summary>
         /// Returns the last action that was decided on by the Agent.

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

             var agentInfoProto = ai.ToAgentInfoProto();
 
             var agentActionProto = new AgentActionProto();
-            if(ai.storedVectorActions != null)
+            if (ai.storedVectorActions != null)
             {
                 agentActionProto.VectorActions.AddRange(ai.storedVectorActions);
             }
             var brainParametersProto = new BrainParametersProto
             {
                 VectorActionSize = { bp.VectorActionSize },
-                VectorActionSpaceType = (SpaceTypeProto) bp.VectorActionSpaceType,
+                VectorActionSpaceType = (SpaceTypeProto)bp.VectorActionSpaceType,
-            if(bp.VectorActionDescriptions != null)
+            if (bp.VectorActionDescriptions != null)
             {
                 brainParametersProto.VectorActionDescriptions.AddRange(bp.VectorActionDescriptions);
             }

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

         Dictionary<string, BrainParameters> m_UnsentBrainKeys = new Dictionary<string, BrainParameters>();
 
 
-# if UNITY_EDITOR || UNITY_STANDALONE_WIN || UNITY_STANDALONE_OSX || UNITY_STANDALONE_LINUX
+#if UNITY_EDITOR || UNITY_STANDALONE_WIN || UNITY_STANDALONE_OSX || UNITY_STANDALONE_LINUX
         /// The Unity to External client.
         UnityToExternalProto.UnityToExternalProtoClient m_Client;
 #endif
         UnityInputProto Initialize(UnityOutputProto unityOutput,
             out UnityInputProto unityInput)
         {
-# if UNITY_EDITOR || UNITY_STANDALONE_WIN || UNITY_STANDALONE_OSX || UNITY_STANDALONE_LINUX
+#if UNITY_EDITOR || UNITY_STANDALONE_WIN || UNITY_STANDALONE_OSX || UNITY_STANDALONE_LINUX
             m_IsOpen = true;
             var channel = new Channel(
                 "localhost:" + m_CommunicatorInitParameters.port,
         /// </summary>
         public void Dispose()
         {
-# if UNITY_EDITOR || UNITY_STANDALONE_WIN || UNITY_STANDALONE_OSX || UNITY_STANDALONE_LINUX
+#if UNITY_EDITOR || UNITY_STANDALONE_WIN || UNITY_STANDALONE_OSX || UNITY_STANDALONE_LINUX
             if (!m_IsOpen)
             {
                 return;
             switch (command)
             {
                 case CommandProto.Quit:
-                {
-                    QuitCommandReceived?.Invoke();
-                    return;
-                }
+                    {
+                        QuitCommandReceived?.Invoke();
+                        return;
+                    }
-                {
-                    foreach (var brainName in m_OrderedAgentsRequestingDecisions.Keys)
-                        m_OrderedAgentsRequestingDecisions[brainName].Clear();
+                        foreach (var brainName in m_OrderedAgentsRequestingDecisions.Keys)
+                        {
+                            m_OrderedAgentsRequestingDecisions[brainName].Clear();
+                        }
+                        ResetCommandReceived?.Invoke();
+                        return;
-                    ResetCommandReceived?.Invoke();
-                    return;
-                }
-                {
-                    return;
-                }
+                    {
+                        return;
+                    }
             }
         }
 
         /// <param name="sensors">Sensors that will produce the observations</param>
         public void PutObservations(string behaviorName, AgentInfo info, List<ISensor> sensors)
         {
-# if DEBUG
+#if DEBUG
             if (!m_SensorShapeValidators.ContainsKey(behaviorName))
             {
                 m_SensorShapeValidators[behaviorName] = new SensorShapeValidator();
         /// <param name="unityOutput">The UnityOutput to be sent.</param>
         UnityInputProto Exchange(UnityOutputProto unityOutput)
         {
-# if UNITY_EDITOR || UNITY_STANDALONE_WIN || UNITY_STANDALONE_OSX || UNITY_STANDALONE_LINUX
+#if UNITY_EDITOR || UNITY_STANDALONE_WIN || UNITY_STANDALONE_OSX || UNITY_STANDALONE_LINUX
             if (!m_IsOpen)
             {
                 return null;

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

         /// A class holding the capabilities flags for Reinforcement Learning across C# and the Trainer codebase.  This
         /// struct will be used to inform users if and when they are using C# / Trainer features that are mismatched.
         /// </summary>
-        public UnityRLCapabilities(bool baseRlCapabilities=true)
+        public UnityRLCapabilities(bool baseRlCapabilities = true)
         {
             m_BaseRLCapabilities = baseRlCapabilities;
         }

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

         public InferenceDevice InferenceDevice
         {
             get { return m_InferenceDevice; }
-            set { m_InferenceDevice = value; UpdateAgentPolicy();}
+            set { m_InferenceDevice = value; UpdateAgentPolicy(); }
         }
 
         [HideInInspector, SerializeField]
                 case BehaviorType.HeuristicOnly:
                     return GenerateHeuristicPolicy(heuristic);
                 case BehaviorType.InferenceOnly:
-                {
-                    if (m_Model == null)
-                        var behaviorType = BehaviorType.InferenceOnly.ToString();
-                        throw new UnityAgentsException(
-                            $"Can't use Behavior Type {behaviorType} without a model. " +
-                            "Either assign a model, or change to a different Behavior Type."
-                        );
+                        if (m_Model == null)
+                        {
+                            var behaviorType = BehaviorType.InferenceOnly.ToString();
+                            throw new UnityAgentsException(
+                                $"Can't use Behavior Type {behaviorType} without a model. " +
+                                "Either assign a model, or change to a different Behavior Type."
+                            );
+                        }
+                        return new BarracudaPolicy(m_BrainParameters, m_Model, m_InferenceDevice);
-                    return new BarracudaPolicy(m_BrainParameters, m_Model, m_InferenceDevice);
-                }
                 case BehaviorType.Default:
                     if (Academy.Instance.IsCommunicatorOn)
                     {

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

         /// For the discrete action space: the number of branches in the action space.
         /// </value>
         [FormerlySerializedAs("vectorActionSize")]
-        public int[] VectorActionSize = new[] {1};
+        public int[] VectorActionSize = new[] { 1 };
 
         /// <summary>
         /// The list of strings describing what the actions correspond to.

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

             public float this[int index]
             {
                 get { return 0.0f; }
-                set {}
+                set { }
             }
         }
 

com.unity.ml-agents/Runtime/Sampler.cs

 using System.Collections.Generic;
 using Unity.MLAgents.Inference.Utils;
 using UnityEngine;
-using Random=System.Random;
+using Random = System.Random;
 
 namespace Unity.MLAgents
 {
             // Will be used to normalize intervalFuncs
             float sumIntervalSizes = 0;
             //The number of intervals
-            int numIntervals = (int)(intervals.Count/2);
+            int numIntervals = (int)(intervals.Count / 2);
             // List that will store interval lengths
             float[] intervalSizes = new float[numIntervals];
             // List that will store uniform distributions
-            for(int i = 0; i < numIntervals; i++)
+            for (int i = 0; i < numIntervals; i++)
             {
                 var min = intervals[2 * i];
                 var max = intervals[2 * i + 1];
                 intervalFuncs[i] = () => min + (float)distr.NextDouble() * intervalSize;
             }
             // Normalize interval lengths
-            for(int i = 0; i < numIntervals; i++)
+            for (int i = 0; i < numIntervals; i++)
-            } 
+            }
-            for(int i = 1; i < numIntervals; i++)
+            for (int i = 1; i < numIntervals; i++)
-            } 
+            }
             Multinomial intervalDistr = new Multinomial(seed + 1);
             float MultiRange()
             {

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

         /// </summary>
         public SensorCompressionType CompressionType
         {
-            get { return m_CompressionType;  }
+            get { return m_CompressionType; }
             set { m_CompressionType = value; }
         }
 
         }
 
         /// <inheritdoc/>
-        public void Update() {}
+        public void Update() { }
 
         /// <inheritdoc/>
         public void Reset() { }

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

         /// </summary>
         public Camera Camera
         {
-            get { return m_Camera;  }
+            get { return m_Camera; }
             set { m_Camera = value; UpdateSensor(); }
         }
 
         /// </summary>
         public string SensorName
         {
-            get { return m_SensorName;  }
+            get { return m_SensorName; }
             set { m_SensorName = value; }
         }
 
         /// </summary>
         public int Width
         {
-            get { return m_Width;  }
+            get { return m_Width; }
             set { m_Width = value; }
         }
 
         /// </summary>
         public int Height
         {
-            get { return m_Height;  }
-            set { m_Height = value;  }
+            get { return m_Height; }
+            set { m_Height = value; }
         }
 
         [HideInInspector, SerializeField, FormerlySerializedAs("grayscale")]
         /// </summary>
         public bool Grayscale
         {
-            get { return m_Grayscale;  }
+            get { return m_Grayscale; }
             set { m_Grayscale = value; }
         }
 
         /// </summary>
         public SensorCompressionType CompressionType
         {
-            get { return m_Compression;  }
+            get { return m_Compression; }
             set { m_Compression = value; UpdateSensor(); }
         }
 

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

 
         TensorShape m_TensorShape;
 
-        internal ObservationWriter() {}
+        internal ObservationWriter() { }
 
         /// <summary>
         /// Set the writer to write to an IList at the given channelOffset.

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

             var startPositionWorld = Transform.TransformPoint(startPositionLocal);
             var endPositionWorld = Transform.TransformPoint(endPositionLocal);
 
-            return (StartPositionWorld : startPositionWorld, EndPositionWorld : endPositionWorld);
+            return (StartPositionWorld: startPositionWorld, EndPositionWorld: endPositionWorld);
         }
 
         /// <summary>
         }
 
         /// <inheritdoc/>
-        public void Reset() {}
+        public void Reset() { }
 
         /// <inheritdoc/>
         public int[] GetObservationShape()

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

         {
             get { return m_RaysPerDirection; }
             // Note: can't change at runtime
-            set { m_RaysPerDirection = value;}
+            set { m_RaysPerDirection = value; }
         }
 
         [HideInInspector, SerializeField, FormerlySerializedAs("maxRayDegrees")]

com.unity.ml-agents/Runtime/Sensors/Reflection/BoolReflectionSensor.cs

     {
         public BoolReflectionSensor(ReflectionSensorInfo reflectionSensorInfo)
             : base(reflectionSensorInfo, 1)
-        {}
+        { }
 
         internal override void WriteReflectedField(ObservationWriter writer)
         {

com.unity.ml-agents/Runtime/Sensors/Reflection/FloatReflectionSensor.cs

     {
         public FloatReflectionSensor(ReflectionSensorInfo reflectionSensorInfo)
             : base(reflectionSensorInfo, 1)
-        {}
+        { }
 
         internal override void WriteReflectedField(ObservationWriter writer)
         {

com.unity.ml-agents/Runtime/Sensors/Reflection/IntReflectionSensor.cs

     {
         public IntReflectionSensor(ReflectionSensorInfo reflectionSensorInfo)
             : base(reflectionSensorInfo, 1)
-        {}
+        { }
 
         internal override void WriteReflectedField(ObservationWriter writer)
         {

com.unity.ml-agents/Runtime/Sensors/Reflection/ObservableAttribute.cs

         internal static List<ISensor> CreateObservableSensors(object o, bool excludeInherited)
         {
             var sensorsOut = new List<ISensor>();
-            foreach (var(field, attr) in GetObservableFields(o, excludeInherited))
+            foreach (var (field, attr) in GetObservableFields(o, excludeInherited))
             {
                 var sensor = CreateReflectionSensor(o, field, null, attr);
                 if (sensor != null)
             }
 
-            foreach (var(prop, attr) in GetObservableProperties(o, excludeInherited))
+            foreach (var (prop, attr) in GetObservableProperties(o, excludeInherited))
             {
                 if (!prop.CanRead)
                 {
             else
             {
                 var (_, sensorType) = s_TypeToSensorInfo[memberType];
-                sensor = (ISensor) Activator.CreateInstance(sensorType, reflectionSensorInfo);
+                sensor = (ISensor)Activator.CreateInstance(sensorType, reflectionSensorInfo);
             }
 
             // Wrap the base sensor in a StackingSensor if we're using stacking.
         internal static int GetTotalObservationSize(object o, bool excludeInherited, List<string> errorsOut)
         {
             int sizeOut = 0;
-            foreach (var(field, attr) in GetObservableFields(o, excludeInherited))
+            foreach (var (field, attr) in GetObservableFields(o, excludeInherited))
             {
                 if (s_TypeToSensorInfo.ContainsKey(field.FieldType))
                 {
                 }
             }
 
-            foreach (var(prop, attr) in GetObservableProperties(o, excludeInherited))
+            foreach (var (prop, attr) in GetObservableProperties(o, excludeInherited))
             {
                 if (!prop.CanRead)
                 {

com.unity.ml-agents/Runtime/Sensors/Reflection/QuaternionReflectionSensor.cs

     {
         public QuaternionReflectionSensor(ReflectionSensorInfo reflectionSensorInfo)
             : base(reflectionSensorInfo, 4)
-        {}
+        { }
 
         internal override void WriteReflectedField(ObservationWriter writer)
         {

com.unity.ml-agents/Runtime/Sensors/Reflection/ReflectionSensorBase.cs

             m_PropertyInfo = reflectionSensorInfo.PropertyInfo;
             m_ObservableAttribute = reflectionSensorInfo.ObservableAttribute;
             m_SensorName = reflectionSensorInfo.SensorName;
-            m_Shape = new[] {size};
+            m_Shape = new[] { size };
         }
 
         /// <inheritdoc/>
         }
 
         /// <inheritdoc/>
-        public void Update() {}
+        public void Update() { }
-        public void Reset() {}
+        public void Reset() { }
 
         /// <inheritdoc/>
         public SensorCompressionType GetCompressionType()

com.unity.ml-agents/Runtime/Sensors/Reflection/Vector2ReflectionSensor.cs

     {
         public Vector2ReflectionSensor(ReflectionSensorInfo reflectionSensorInfo)
             : base(reflectionSensorInfo, 2)
-        {}
+        { }
 
         internal override void WriteReflectedField(ObservationWriter writer)
         {

com.unity.ml-agents/Runtime/Sensors/Reflection/Vector3ReflectionSensor.cs

     {
         public Vector3ReflectionSensor(ReflectionSensorInfo reflectionSensorInfo)
             : base(reflectionSensorInfo, 3)
-        {}
+        { }
 
         internal override void WriteReflectedField(ObservationWriter writer)
         {

com.unity.ml-agents/Runtime/Sensors/Reflection/Vector4ReflectionSensor.cs

     {
         public Vector4ReflectionSensor(ReflectionSensorInfo reflectionSensorInfo)
             : base(reflectionSensorInfo, 4)
-        {}
+        { }
 
         internal override void WriteReflectedField(ObservationWriter writer)
         {

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

         /// </summary>
         public SensorCompressionType CompressionType
         {
-            get { return m_CompressionType;  }
+            get { return m_CompressionType; }
             set { m_CompressionType = value; }
         }
 
         }
 
         /// <inheritdoc/>
-        public void Update() {}
+        public void Update() { }
-        public void Reset() {}
+        public void Reset() { }
 
         /// <inheritdoc/>
         public SensorCompressionType GetCompressionType()

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

         /// </summary>
         public RenderTexture RenderTexture
         {
-            get { return m_RenderTexture;  }
-            set { m_RenderTexture = value;  }
+            get { return m_RenderTexture; }
+            set { m_RenderTexture = value; }
         }
 
         [HideInInspector, SerializeField, FormerlySerializedAs("sensorName")]
         /// </summary>
         public string SensorName
         {
-            get { return m_SensorName;  }
+            get { return m_SensorName; }
             set { m_SensorName = value; }
         }
 
         /// </summary>
         public bool Grayscale
         {
-            get { return m_Grayscale;  }
+            get { return m_Grayscale; }
             set { m_Grayscale = value; }
         }
 
         /// </summary>
         public SensorCompressionType CompressionType
         {
-            get { return m_Compression;  }
+            get { return m_Compression; }
             set { m_Compression = value; UpdateSensor(); }
         }
 

com.unity.ml-agents/Runtime/SideChannels/EnvironmentParametersChannel.cs

                     IList<float> intervals = msg.ReadFloatList();
                     sampler = SamplerFactory.CreateMultiRangeUniformSampler(intervals, seed);
                 }
-                else{
+                else
+                {
                     Debug.LogWarning("EnvironmentParametersChannel received an unknown data type.");
                 }
                 m_Parameters[key] = sampler;

com.unity.ml-agents/Runtime/Timer.cs

         public double TotalSeconds
         {
             get { return CurrentTicks * s_TicksToSeconds; }
-            set {}  // Serialization needs this, but unused.
+            set { }  // Serialization needs this, but unused.
         }
 
         /// <summary>
                 var selfTicks = Mathf.Max(0, CurrentTicks - totalChildTicks);
                 return selfTicks * s_TicksToSeconds;
             }
-            set {}  // Serialization needs this, but unused.
+            set { }  // Serialization needs this, but unused.
         }
 
         public IReadOnlyDictionary<string, TimerNode> Children
         [DataMember(Name = "gauges", EmitDefaultValue = false)]
         Dictionary<string, GaugeNode> m_Gauges = new Dictionary<string, GaugeNode>();
 
-        public RootNode(string name="root") : base(name, true)
+        public RootNode(string name = "root") : base(name, true)
         {
             m_Metadata.Add("timer_format_version", k_TimerFormatVersion);
             m_Metadata.Add("start_time_seconds", $"{DateTimeOffset.Now.ToUnixTimeSeconds()}");
         /// <param name="filename"></param>
         public void SaveJsonTimers(string filename = null)
         {
-# if UNITY_EDITOR || UNITY_STANDALONE_WIN || UNITY_STANDALONE_OSX || UNITY_STANDALONE_LINUX
+#if UNITY_EDITOR || UNITY_STANDALONE_WIN || UNITY_STANDALONE_OSX || UNITY_STANDALONE_LINUX
             try
             {
                 if (filename == null)

com.unity.ml-agents/Tests/Editor/Actuators/ActuatorDiscreteActionMaskTests.cs

         [Test]
         public void FirstBranchMask()
         {
-            var actuator1 = new TestActuator(ActionSpec.MakeDiscrete(new[] {4, 5, 6}), "actuator1");
-            var masker = new ActuatorDiscreteActionMask(new IActuator[] {actuator1}, 15, 3);
+            var actuator1 = new TestActuator(ActionSpec.MakeDiscrete(new[] { 4, 5, 6 }), "actuator1");
+            var masker = new ActuatorDiscreteActionMask(new IActuator[] { actuator1 }, 15, 3);
-            masker.WriteMask(0, new[] {1, 2, 3});
+            masker.WriteMask(0, new[] { 1, 2, 3 });
             mask = masker.GetMask();
             Assert.IsFalse(mask[0]);
             Assert.IsTrue(mask[1]);
         [Test]
         public void SecondBranchMask()
         {
-            var actuator1 = new TestActuator(ActionSpec.MakeDiscrete(new[] {4, 5, 6}), "actuator1");
-            var masker = new ActuatorDiscreteActionMask(new[] {actuator1}, 15, 3);
-            masker.WriteMask(1, new[] {1, 2, 3});
+            var actuator1 = new TestActuator(ActionSpec.MakeDiscrete(new[] { 4, 5, 6 }), "actuator1");
+            var masker = new ActuatorDiscreteActionMask(new[] { actuator1 }, 15, 3);
+            masker.WriteMask(1, new[] { 1, 2, 3 });
             var mask = masker.GetMask();
             Assert.IsFalse(mask[0]);
             Assert.IsFalse(mask[4]);
         [Test]
         public void MaskReset()
         {
-            var actuator1 = new TestActuator(ActionSpec.MakeDiscrete(new[] {4, 5, 6}), "actuator1");
-            var masker = new ActuatorDiscreteActionMask(new IActuator[] {actuator1}, 15, 3);
-            masker.WriteMask(1, new[] {1, 2, 3});
+            var actuator1 = new TestActuator(ActionSpec.MakeDiscrete(new[] { 4, 5, 6 }), "actuator1");
+            var masker = new ActuatorDiscreteActionMask(new IActuator[] { actuator1 }, 15, 3);
+            masker.WriteMask(1, new[] { 1, 2, 3 });
             masker.ResetMask();
             var mask = masker.GetMask();
             for (var i = 0; i < 15; i++)
         [Test]
         public void ThrowsError()
         {
-            var actuator1 = new TestActuator(ActionSpec.MakeDiscrete(new[] {4, 5, 6}), "actuator1");
-            var masker = new ActuatorDiscreteActionMask(new IActuator[] {actuator1}, 15, 3);
+            var actuator1 = new TestActuator(ActionSpec.MakeDiscrete(new[] { 4, 5, 6 }), "actuator1");
+            var masker = new ActuatorDiscreteActionMask(new IActuator[] { actuator1 }, 15, 3);
-                () => masker.WriteMask(0, new[] {5}));
+                () => masker.WriteMask(0, new[] { 5 }));
-                () => masker.WriteMask(1, new[] {5}));
-            masker.WriteMask(2, new[] {5});
+                () => masker.WriteMask(1, new[] { 5 }));
+            masker.WriteMask(2, new[] { 5 });
-                () => masker.WriteMask(3, new[] {1}));
+                () => masker.WriteMask(3, new[] { 1 }));
-            masker.WriteMask(0, new[] {0, 1, 2, 3});
+            masker.WriteMask(0, new[] { 0, 1, 2, 3 });
             Assert.Catch<UnityAgentsException>(
                 () => masker.GetMask());
         }
         {
-            var actuator1 = new TestActuator(ActionSpec.MakeDiscrete(new[] {4, 5, 6}), "actuator1");
-            var masker = new ActuatorDiscreteActionMask(new IActuator[] {actuator1}, 15, 3);
-            masker.WriteMask(0, new[] {0, 1});
-            masker.WriteMask(0, new[] {3});
-            masker.WriteMask(2, new[] {1});
+            var actuator1 = new TestActuator(ActionSpec.MakeDiscrete(new[] { 4, 5, 6 }), "actuator1");
+            var masker = new ActuatorDiscreteActionMask(new IActuator[] { actuator1 }, 15, 3);
+            masker.WriteMask(0, new[] { 0, 1 });
+            masker.WriteMask(0, new[] { 3 });
+            masker.WriteMask(2, new[] { 1 });
             var mask = masker.GetMask();
             for (var i = 0; i < 15; i++)
             {

com.unity.ml-agents/Tests/Editor/Actuators/ActuatorManagerTests.cs

         public void TestEnsureBufferDiscrete()
         {
             var manager = new ActuatorManager();
-            var actuator1 = new TestActuator(ActionSpec.MakeDiscrete(new[] {1 , 2, 3, 4}), "actuator1");
-            var actuator2 = new TestActuator(ActionSpec.MakeDiscrete(new[] {1, 1, 1}), "actuator2");
+            var actuator1 = new TestActuator(ActionSpec.MakeDiscrete(new[] { 1, 2, 3, 4 }), "actuator1");
+            var actuator2 = new TestActuator(ActionSpec.MakeDiscrete(new[] { 1, 1, 1 }), "actuator2");
             manager.Add(actuator1);
             manager.Add(actuator2);
             var actuator1ActionSpaceDef = actuator1.ActionSpec;
                 actuator1ActionSpaceDef.NumDiscreteActions + actuator2ActionSpaceDef.NumDiscreteActions);
 
             manager.UpdateActions(new ActionBuffers(Array.Empty<float>(),
-                new[] { 0, 1, 2, 3, 4, 5, 6}));
+                new[] { 0, 1, 2, 3, 4, 5, 6 }));
 
             Assert.IsTrue(0 == manager.NumContinuousActions);
             Assert.IsTrue(7 == manager.NumDiscreteActions);
         public void TestFailOnMixedActionSpace()
         {
             var manager = new ActuatorManager();
-            var actuator1 = new TestActuator(ActionSpec.MakeDiscrete(new[] {1 , 2, 3, 4}), "actuator1");
+            var actuator1 = new TestActuator(ActionSpec.MakeDiscrete(new[] { 1, 2, 3, 4 }), "actuator1");
             var actuator2 = new TestActuator(ActionSpec.MakeContinuous(3), "actuator2");
             manager.Add(actuator1);
             manager.Add(actuator2);
         public void TestExecuteActionsDiscrete()
         {
             var manager = new ActuatorManager();
-            var actuator1 = new TestActuator(ActionSpec.MakeDiscrete(new[] {1 , 2, 3, 4}), "actuator1");
-            var actuator2 = new TestActuator(ActionSpec.MakeDiscrete(new[] {1, 1, 1}), "actuator2");
+            var actuator1 = new TestActuator(ActionSpec.MakeDiscrete(new[] { 1, 2, 3, 4 }), "actuator1");
+            var actuator2 = new TestActuator(ActionSpec.MakeDiscrete(new[] { 1, 1, 1 }), "actuator2");
-            var discreteActionBuffer = new[] { 0, 1, 2, 3, 4, 5, 6};
+            var discreteActionBuffer = new[] { 0, 1, 2, 3, 4, 5, 6 };
             manager.UpdateActions(new ActionBuffers(Array.Empty<float>(),
                 discreteActionBuffer));
 
             manager.Add(actuator1);
             manager.Add(actuator2);
 
-            var continuousActionBuffer = new[] { 0f, 1f, 2f, 3f, 4f, 5f};
+            var continuousActionBuffer = new[] { 0f, 1f, 2f, 3f, 4f, 5f };
             manager.UpdateActions(new ActionBuffers(continuousActionBuffer,
                 Array.Empty<int>()));
 
             var actuator2 = new TestActuator(ActionSpec.MakeContinuous(3), "actuator2");
             manager.Add(actuator1);
             manager.Add(actuator2);
-            var continuousActionBuffer = new[] { 0f, 1f, 2f, 3f, 4f, 5f};
+            var continuousActionBuffer = new[] { 0f, 1f, 2f, 3f, 4f, 5f };
             manager.UpdateActions(new ActionBuffers(continuousActionBuffer,
                 Array.Empty<int>()));
 
             var manager = new ActuatorManager();
             var actuator1 = new TestActuator(ActionSpec.MakeDiscrete(new[] { 1, 2, 3 }),
                 "actuator1");
-            var actuator2 = new TestActuator(ActionSpec.MakeDiscrete(new[] {1, 2, 3}), "actuator2");
+            var actuator2 = new TestActuator(ActionSpec.MakeDiscrete(new[] { 1, 2, 3 }), "actuator2");
-            var discreteActionBuffer = new[] { 0, 1, 2, 3, 4, 5};
+            var discreteActionBuffer = new[] { 0, 1, 2, 3, 4, 5 };
             manager.UpdateActions(new ActionBuffers(Array.Empty<float>(),
                 discreteActionBuffer));
 
             var manager = new ActuatorManager();
             var actuator1 = new TestActuator(ActionSpec.MakeDiscrete(new[] { 1, 2, 3 }),
                 "actuator1");
-            var actuator2 = new TestActuator(ActionSpec.MakeDiscrete(new[] {1, 2, 3}), "actuator2");
+            var actuator2 = new TestActuator(ActionSpec.MakeDiscrete(new[] { 1, 2, 3 }), "actuator2");
 
             manager.Add(actuator1);
             manager.Add(actuator2);
             var manager = new ActuatorManager();
             var actuator1 = new TestActuator(ActionSpec.MakeDiscrete(new[] { 1, 2, 3 }),
                 "actuator1");
-            var actuator2 = new TestActuator(ActionSpec.MakeDiscrete(new[] {1, 2, 3}), "actuator2");
+            var actuator2 = new TestActuator(ActionSpec.MakeDiscrete(new[] { 1, 2, 3 }), "actuator2");
             manager.Add(actuator1);
             manager.Add(actuator2);
 
         public void TestIndexSet()
         {
             var manager = new ActuatorManager();
-            var actuator1 = new TestActuator(ActionSpec.MakeDiscrete(new[] { 1, 2, 3, 4}),
+            var actuator1 = new TestActuator(ActionSpec.MakeDiscrete(new[] { 1, 2, 3, 4 }),
-            var actuator2 = new TestActuator(ActionSpec.MakeDiscrete(new[] {1, 2, 3}), "actuator2");
+            var actuator2 = new TestActuator(ActionSpec.MakeDiscrete(new[] { 1, 2, 3 }), "actuator2");
             manager.Add(actuator1);
             Assert.IsTrue(manager.NumDiscreteActions == 4);
             Assert.IsTrue(manager.SumOfDiscreteBranchSizes == 10);
         public void TestInsert()
         {
             var manager = new ActuatorManager();
-            var actuator1 = new TestActuator(ActionSpec.MakeDiscrete(new[] { 1, 2, 3, 4}),
+            var actuator1 = new TestActuator(ActionSpec.MakeDiscrete(new[] { 1, 2, 3, 4 }),
-            var actuator2 = new TestActuator(ActionSpec.MakeDiscrete(new[] {1, 2, 3}), "actuator2");
+            var actuator2 = new TestActuator(ActionSpec.MakeDiscrete(new[] { 1, 2, 3 }), "actuator2");
             manager.Add(actuator1);
             Assert.IsTrue(manager.NumDiscreteActions == 4);
             Assert.IsTrue(manager.SumOfDiscreteBranchSizes == 10);
             var actuator2 = new TestActuator(ActionSpec.MakeContinuous(3), "actuator2");
             manager.Add(actuator1);
             manager.Add(actuator2);
-            var continuousActionBuffer = new[] { 0f, 1f, 2f, 3f, 4f, 5f};
+            var continuousActionBuffer = new[] { 0f, 1f, 2f, 3f, 4f, 5f };
             manager.UpdateActions(new ActionBuffers(continuousActionBuffer,
                 Array.Empty<int>()));
 
 
-            Assert.IsTrue(manager.StoredActions.ContinuousActions.SequenceEqual(new[] { 0f, 0f, 0f, 0f, 0f, 0f}));
+            Assert.IsTrue(manager.StoredActions.ContinuousActions.SequenceEqual(new[] { 0f, 0f, 0f, 0f, 0f, 0f }));
         }
 
         [Test]
-            var va1 = new TestActuator(ActionSpec.MakeDiscrete(new[] {1, 2, 3}), "name");
-            var va2 = new TestActuator(ActionSpec.MakeDiscrete(new[] {3, 2, 1}), "name1");
+            var va1 = new TestActuator(ActionSpec.MakeDiscrete(new[] { 1, 2, 3 }), "name");
+            var va2 = new TestActuator(ActionSpec.MakeDiscrete(new[] { 3, 2, 1 }), "name1");
             manager.Add(va1);
             manager.Add(va2);
 

com.unity.ml-agents/Tests/Editor/Actuators/VectorActuatorTests.cs

         public void TestConstruct()
         {
             var ar = new TestActionReceiver();
-            var va = new VectorActuator(ar, new[] {1, 2, 3}, SpaceType.Discrete, "name");
+            var va = new VectorActuator(ar, new[] { 1, 2, 3 }, SpaceType.Discrete, "name");
-            var va1 = new VectorActuator(ar, new[] {4}, SpaceType.Continuous, "name");
+            var va1 = new VectorActuator(ar, new[] { 4 }, SpaceType.Continuous, "name");
 
             Assert.IsTrue(va1.ActionSpec.NumContinuousActions == 4);
             Assert.IsTrue(va1.ActionSpec.SumOfDiscreteBranchSizes == 0);
         public void TestOnActionReceived()
         {
             var ar = new TestActionReceiver();
-            var va = new VectorActuator(ar, new[] {1, 2, 3}, SpaceType.Discrete, "name");
+            var va = new VectorActuator(ar, new[] { 1, 2, 3 }, SpaceType.Discrete, "name");
 
             var discreteActions = new[] { 0, 1, 1 };
             var ab = new ActionBuffers(ActionSegment<float>.Empty,
         public void TestResetData()
         {
             var ar = new TestActionReceiver();
-            var va = new VectorActuator(ar, new[] {1, 2, 3}, SpaceType.Discrete, "name");
+            var va = new VectorActuator(ar, new[] { 1, 2, 3 }, SpaceType.Discrete, "name");
 
             var discreteActions = new[] { 0, 1, 1 };
             var ab = new ActionBuffers(ActionSegment<float>.Empty,
         public void TestWriteDiscreteActionMask()
         {
             var ar = new TestActionReceiver();
-            var va = new VectorActuator(ar, new[] {1, 2, 3}, SpaceType.Discrete, "name");
-            var bdam = new ActuatorDiscreteActionMask(new[] {va}, 6, 3);
+            var va = new VectorActuator(ar, new[] { 1, 2, 3 }, SpaceType.Discrete, "name");
+            var bdam = new ActuatorDiscreteActionMask(new[] { va }, 6, 3);
 
             var groundTruthMask = new[] { false, true, false, false, true, true };
 

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

             var agentSendInfo = typeof(Agent).GetMethod("SendInfo",
                 BindingFlags.Instance | BindingFlags.NonPublic);
 
-            agentEnableMethod?.Invoke(agent1, new object[] {});
+            agentEnableMethod?.Invoke(agent1, new object[] { });
-            agentSendInfo?.Invoke(agent1, new object[] {});
+            agentSendInfo?.Invoke(agent1, new object[] { });
 
             demoRecorder.Close();
 

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

 
             var src = new TensorProxy
             {
-                data = new Tensor(1, 3, new[] {0.1f, 0.2f, 0.7f}),
+                data = new Tensor(1, 3, new[] { 0.1f, 0.2f, 0.7f }),
                 valueType = TensorProxy.TensorType.FloatingPoint
             };
 
 
             DiscreteActionOutputApplier.Eval(src, dst, m);
 
-            float[] reference = {2, 2, 1};
+            float[] reference = { 2, 2, 1 };
             for (var i = 0; i < dst.data.length; i++)
             {
                 Assert.AreEqual(reference[i], dst.data[i]);
 
             DiscreteActionOutputApplier.Eval(src, dst, m);
 
-            float[] reference = {2, 2, 2};
+            float[] reference = { 2, 2, 2 };
             for (var i = 0; i < dst.data.length; i++)
             {
                 Assert.AreEqual(reference[i], dst.data[i]);
 
             DiscreteActionOutputApplier.Eval(src, dst, m);
 
-            float[] reference = {2, 2, 2, 0, 1, 0};
+            float[] reference = { 2, 2, 2, 0, 1, 0 };
             for (var i = 0; i < dst.data.length; i++)
             {
                 Assert.AreEqual(reference[i], dst.data[i]);

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

 
         public ref readonly ActionBuffers DecideAction() { return ref s_EmptyActionBuffers; }
 
-        public void Dispose() {}
+        public void Dispose() { }
     }
 
     public class TestAgent : Agent
             return sensorName;
         }
 
-        public void Update() {}
+        public void Update() { }
 
         public void Reset()
         {
             StackingSensor sensor = null;
             foreach (ISensor s in agent1.sensors)
             {
-                if (s is  StackingSensor)
+                if (s is StackingSensor)
                 {
                     sensor = s as StackingSensor;
                 }
                 aca.EnvironmentStep();
             }
 
-            policy.OnRequestDecision = () =>  SensorTestHelper.CompareObservation(sensor, new[] {18f, 19f, 21f});
+            policy.OnRequestDecision = () => SensorTestHelper.CompareObservation(sensor, new[] { 18f, 19f, 21f });
-            SensorTestHelper.CompareObservation(sensor, new[] {0f, 0f, 0f});
+            SensorTestHelper.CompareObservation(sensor, new[] { 0f, 0f, 0f });
         }
     }
 
                 (ObservableAttributeOptions.ExamineAll, 2)
             };
 
-            foreach (var(behavior, expectedNumSensors) in variants)
+            foreach (var (behavior, expectedNumSensors) in variants)
             {
                 var go = new GameObject();
                 var agent = go.AddComponent<DerivedObservableAgent>();

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

         {
             var validBrainParameters = new BrainParameters();
             validBrainParameters.VectorObservationSize = 8;
-            validBrainParameters.VectorActionSize = new [] { 2 };
+            validBrainParameters.VectorActionSize = new[] { 2 };
             validBrainParameters.NumStackedVectorObservations = 1;
             validBrainParameters.VectorActionSpaceType = SpaceType.Continuous;
             return validBrainParameters;
         {
             var validBrainParameters = new BrainParameters();
             validBrainParameters.VectorObservationSize = 0;
-            validBrainParameters.VectorActionSize = new [] { 2, 3 };
+            validBrainParameters.VectorActionSize = new[] { 2, 3 };
             validBrainParameters.NumStackedVectorObservations = 1;
             validBrainParameters.VectorActionSpaceType = SpaceType.Discrete;
             return validBrainParameters;
             var modelRunner = new ModelRunner(discrete1vis0vec_2_3action_recurrModel, brainParameters);
             var info1 = new AgentInfo();
             info1.episodeId = 1;
-            modelRunner.PutObservations(info1, new [] { sensor_21_20_3.CreateSensor() }.ToList());
+            modelRunner.PutObservations(info1, new[] { sensor_21_20_3.CreateSensor() }.ToList());
-            modelRunner.PutObservations(info2, new [] { sensor_21_20_3.CreateSensor() }.ToList());
+            modelRunner.PutObservations(info2, new[] { sensor_21_20_3.CreateSensor() }.ToList());
 
             modelRunner.DecideBatch();
 

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

         public void TestDim1()
         {
             var m = new Multinomial(2018);
-            var cdf = new[] {1f};
+            var cdf = new[] { 1f };
 
             Assert.AreEqual(0, m.Sample(cdf));
             Assert.AreEqual(0, m.Sample(cdf));
         public void TestDim1Unscaled()
         {
             var m = new Multinomial(2018);
-            var cdf = new[] {0.1f};
+            var cdf = new[] { 0.1f };
 
             Assert.AreEqual(0, m.Sample(cdf));
             Assert.AreEqual(0, m.Sample(cdf));
         public void TestDim3()
         {
             var m = new Multinomial(2018);
-            var cdf = new[] {0.1f, 0.3f, 1.0f};
+            var cdf = new[] { 0.1f, 0.3f, 1.0f };
 
             Assert.AreEqual(2, m.Sample(cdf));
             Assert.AreEqual(2, m.Sample(cdf));
         public void TestDim3Unscaled()
         {
             var m = new Multinomial(2018);
-            var cdf = new[] {0.05f, 0.15f, 0.5f};
+            var cdf = new[] { 0.05f, 0.15f, 0.5f };
 
             Assert.AreEqual(2, m.Sample(cdf));
             Assert.AreEqual(2, m.Sample(cdf));

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

 
         public int[] GetObservationShape()
         {
-            return new [] {m_Height, m_Width, m_Channels };
+            return new[] { m_Height, m_Width, m_Channels };
         }
 
         public int Write(ObservationWriter writer)
             return new byte[0];
         }
 
-        public void Update() {}
+        public void Update() { }
         public void Reset() { }
 
         public SensorCompressionType GetCompressionType()
         {
             var validBrainParameters = new BrainParameters();
             validBrainParameters.VectorObservationSize = 8;
-            validBrainParameters.VectorActionSize = new [] { 2 };
+            validBrainParameters.VectorActionSize = new[] { 2 };
             validBrainParameters.NumStackedVectorObservations = 1;
             validBrainParameters.VectorActionSpaceType = SpaceType.Continuous;
             return validBrainParameters;
         {
             var validBrainParameters = new BrainParameters();
             validBrainParameters.VectorObservationSize = 0;
-            validBrainParameters.VectorActionSize = new [] { 2, 3 };
+            validBrainParameters.VectorActionSize = new[] { 2, 3 };
             validBrainParameters.NumStackedVectorObservations = 1;
             validBrainParameters.VectorActionSpaceType = SpaceType.Discrete;
             return validBrainParameters;
             var model = ModelLoader.Load(continuous2vis8vec2actionModel);
 
             var brainParameters = GetContinuous2vis8vec2actionBrainParameters();
-            brainParameters.VectorActionSize = new [] { 3 }; // Invalid action
+            brainParameters.VectorActionSize = new[] { 3 }; // Invalid action
             var errors = BarracudaModelParamLoader.CheckModel(model, brainParameters, new SensorComponent[] { sensor_21_20_3, sensor_20_22_3 });
             Assert.Greater(errors.Count(), 0);
 
             var model = ModelLoader.Load(discrete1vis0vec_2_3action_recurrModel);
 
             var brainParameters = GetDiscrete1vis0vec_2_3action_recurrModelBrainParameters();
-            brainParameters.VectorActionSize = new [] { 3, 3 }; // Invalid action
+            brainParameters.VectorActionSize = new[] { 3, 3 }; // Invalid action
             var errors = BarracudaModelParamLoader.CheckModel(model, brainParameters, new SensorComponent[] { sensor_21_20_3 });
             Assert.Greater(errors.Count(), 0);
 

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

         const int k_Seed = 1337;
         const double k_Epsilon = 0.0001;
         EnvironmentParametersChannel m_Channel;
-    
+
         public SamplerTests()
         {
             m_Channel = SideChannelManager.GetSideChannel<EnvironmentParametersChannel>();
                     binaryWriter.Write(message.Length);
                     binaryWriter.Write(message);
                 }
-            return memStream.ToArray();
+                return memStream.ToArray();
             }
         }
     }

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

- using System;
- using NUnit.Framework;
- using UnityEngine;
- using Unity.MLAgents.Sensors;
+using System;
+using NUnit.Framework;
+using UnityEngine;
+using Unity.MLAgents.Sensors;
 
 namespace Unity.MLAgents.Tests
 {
                     var obsWriter = new ObservationWriter();
                     var obs = sensor.GetObservationProto(obsWriter);
 
-                    Assert.AreEqual((int) compression, (int) obs.CompressionType);
+                    Assert.AreEqual((int)compression, (int)obs.CompressionType);
                     var expectedShape = new[] { height, width, grayscale ? 1 : 3 };
                     Assert.AreEqual(expectedShape, obs.Shape);
                 }

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

             }
         }
 
-        public void Update() {}
+        public void Update() { }
         public void Reset() { }
 
         public SensorCompressionType GetCompressionType()

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

             Assert.AreEqual("derived", sensorsDerivedOnly[0].GetName());
 
             var b = new BaseClass();
-            var baseSensors =  ObservableAttribute.CreateObservableSensors(b, false);
+            var baseSensors = ObservableAttribute.CreateObservableSensors(b, false);
             Assert.AreEqual(2, baseSensors.Count);
         }
     }

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

 
             // AddRange
             writer.SetTarget(buffer, shape, 0);
-            writer.AddRange(new[] {4f, 5f});
+            writer.AddRange(new[] { 4f, 5f });
-            writer.AddRange(new[] {6f, 7f});
+            writer.AddRange(new[] { 6f, 7f });
             Assert.AreEqual(new[] { 4f, 6f, 7f }, buffer);
         }
 
             };
 
             writer.SetTarget(t, 1, 1);
-            writer.AddRange(new[] {-1f, -2f});
+            writer.AddRange(new[] { -1f, -2f });
             Assert.AreEqual(0f, t.data[0, 0]);
             Assert.AreEqual(0f, t.data[0, 1]);
             Assert.AreEqual(0f, t.data[0, 2]);

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

 
         public DummySensor(int dim1, int dim2, int dim3)
         {
-            m_Shape = new[] { dim1, dim2, dim3};
+            m_Shape = new[] { dim1, dim2, dim3 };
         }
 
         public string GetName()

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

             ISensor wrapped = new VectorSensor(4);
             ISensor sensor = new StackingSensor(wrapped, 4);
             Assert.AreEqual("StackingSensor_size4_VectorSensor_size4", sensor.GetName());
-            Assert.AreEqual(sensor.GetObservationShape(), new[] {16});
+            Assert.AreEqual(sensor.GetObservationShape(), new[] { 16 });
         }
 
         [Test]
             ISensor sensor = new StackingSensor(wrapped, 3);
 
-            wrapped.AddObservation(new[] {1f, 2f});
-            SensorTestHelper.CompareObservation(sensor, new[] {0f, 0f, 0f, 0f, 1f, 2f});
+            wrapped.AddObservation(new[] { 1f, 2f });
+            SensorTestHelper.CompareObservation(sensor, new[] { 0f, 0f, 0f, 0f, 1f, 2f });
-            wrapped.AddObservation(new[] {3f, 4f});
-            SensorTestHelper.CompareObservation(sensor, new[] {0f, 0f, 1f, 2f, 3f, 4f});
+            wrapped.AddObservation(new[] { 3f, 4f });
+            SensorTestHelper.CompareObservation(sensor, new[] { 0f, 0f, 1f, 2f, 3f, 4f });
-            wrapped.AddObservation(new[] {5f, 6f});
-            SensorTestHelper.CompareObservation(sensor, new[] {1f, 2f, 3f, 4f, 5f, 6f});
+            wrapped.AddObservation(new[] { 5f, 6f });
+            SensorTestHelper.CompareObservation(sensor, new[] { 1f, 2f, 3f, 4f, 5f, 6f });
-            wrapped.AddObservation(new[] {7f, 8f});
-            SensorTestHelper.CompareObservation(sensor, new[] {3f, 4f, 5f, 6f, 7f, 8f});
+            wrapped.AddObservation(new[] { 7f, 8f });
+            SensorTestHelper.CompareObservation(sensor, new[] { 3f, 4f, 5f, 6f, 7f, 8f });
-            wrapped.AddObservation(new[] {9f, 10f});
-            SensorTestHelper.CompareObservation(sensor, new[] {5f, 6f, 7f, 8f, 9f, 10f});
+            wrapped.AddObservation(new[] { 9f, 10f });
+            SensorTestHelper.CompareObservation(sensor, new[] { 5f, 6f, 7f, 8f, 9f, 10f });
-            SensorTestHelper.CompareObservation(sensor, new[] {5f, 6f, 7f, 8f, 9f, 10f});
+            SensorTestHelper.CompareObservation(sensor, new[] { 5f, 6f, 7f, 8f, 9f, 10f });
         }
 
         [Test]
             ISensor sensor = new StackingSensor(wrapped, 3);
 
-            wrapped.AddObservation(new[] {1f, 2f});
-            SensorTestHelper.CompareObservation(sensor, new[] {0f, 0f, 0f, 0f, 1f, 2f});
+            wrapped.AddObservation(new[] { 1f, 2f });
+            SensorTestHelper.CompareObservation(sensor, new[] { 0f, 0f, 0f, 0f, 1f, 2f });
-            wrapped.AddObservation(new[] {3f, 4f});
-            SensorTestHelper.CompareObservation(sensor, new[] {0f, 0f, 1f, 2f, 3f, 4f});
+            wrapped.AddObservation(new[] { 3f, 4f });
+            SensorTestHelper.CompareObservation(sensor, new[] { 0f, 0f, 1f, 2f, 3f, 4f });
-            wrapped.AddObservation(new[] {5f, 6f});
-            SensorTestHelper.CompareObservation(sensor, new[] {0f, 0f, 0f, 0f, 5f, 6f});
+            wrapped.AddObservation(new[] { 5f, 6f });
+            SensorTestHelper.CompareObservation(sensor, new[] { 0f, 0f, 0f, 0f, 5f, 6f });
         }
     }
 }

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

         {
             var sensor = new VectorSensor(1);
             sensor.AddObservation(1.2f);
-            SensorTestHelper.CompareObservation(sensor, new[] {1.2f});
+            SensorTestHelper.CompareObservation(sensor, new[] { 1.2f });
         }
 
         [Test]
             sensor.AddObservation(42);
-            SensorTestHelper.CompareObservation(sensor, new[] {42f});
+            SensorTestHelper.CompareObservation(sensor, new[] { 42f });
         }
 
         [Test]
             sensor.AddObservation(new Vector3(1, 2, 3));
-            SensorTestHelper.CompareObservation(sensor, new[] {1f, 2f, 3f});
+            SensorTestHelper.CompareObservation(sensor, new[] { 1f, 2f, 3f });
 
             sensor = new VectorSensor(2);
             sensor.AddObservation(new Vector2(4, 5));
         {
             var sensor = new VectorSensor(4);
             sensor.AddObservation(Quaternion.identity);
-            SensorTestHelper.CompareObservation(sensor, new[] {0f, 0f, 0f, 1f});
+            SensorTestHelper.CompareObservation(sensor, new[] { 0f, 0f, 0f, 1f });
         }
 
         [Test]
-            sensor.AddObservation(new[] {1f, 2f, 3f, 4f});
+            sensor.AddObservation(new[] { 1f, 2f, 3f, 4f });
 
             SensorTestHelper.CompareObservation(sensor, new[] { 1f, 2f, 3f, 4f });
         }
         {
             var sensor = new VectorSensor(1);
             sensor.AddObservation(true);
-            SensorTestHelper.CompareObservation(sensor, new[] {1f});
+            SensorTestHelper.CompareObservation(sensor, new[] { 1f });
         }
 
         [Test]
             sensor.AddOneHotObservation(2, 4);
-            SensorTestHelper.CompareObservation(sensor, new[] {0f, 0f, 1f, 0f});
+            SensorTestHelper.CompareObservation(sensor, new[] { 0f, 0f, 1f, 0f });
         }
 
         [Test]
-            sensor.AddObservation(new[] {1f, 2f, 3f, 4f});
+            sensor.AddObservation(new[] { 1f, 2f, 3f, 4f });
-            SensorTestHelper.CompareObservation(sensor, new[] { 1f, 2f});
+            SensorTestHelper.CompareObservation(sensor, new[] { 1f, 2f });
         }
 
         [Test]
-            sensor.AddObservation(new[] {1f, 2f});
+            sensor.AddObservation(new[] { 1f, 2f });
-            SensorTestHelper.CompareObservation(sensor, new[] { 1f, 2f, 0f, 0f});
+            SensorTestHelper.CompareObservation(sensor, new[] { 1f, 2f, 0f, 0f });
         }
     }
 }

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

         [Test]
         public void TestCumSum()
         {
-            var output = Utilities.CumSum(new[] {1, 2, 3, 10});
-            CollectionAssert.AreEqual(output, new[] {0, 1, 3, 6, 16});
+            var output = Utilities.CumSum(new[] { 1, 2, 3, 10 });
+            CollectionAssert.AreEqual(output, new[] { 0, 1, 3, 6, 16 });
-            CollectionAssert.AreEqual(output, new[] {0});
+            CollectionAssert.AreEqual(output, new[] { 0 });
-            output = Utilities.CumSum(new[] {100});
-            CollectionAssert.AreEqual(output, new[] {0, 100});
+            output = Utilities.CumSum(new[] { 100 });
+            CollectionAssert.AreEqual(output, new[] { 0, 100 });
-            output = Utilities.CumSum(new[] {-1, 10});
-            CollectionAssert.AreEqual(output, new[] {0, -1, 9});
+            output = Utilities.CumSum(new[] { -1, 10 });
+            CollectionAssert.AreEqual(output, new[] { 0, -1, 9 });
         }
     }
 }

utils/run_dotnet_format.py

+#!/usr/bin/env python3
+
+import argparse
+import os
+import subprocess
+import tempfile
+
+
+if __name__ == "__main__":
+
+    parser = argparse.ArgumentParser()
+    parser.add_argument("files", nargs="*")
+    args = parser.parse_args()
+
+    with tempfile.TemporaryDirectory() as tempdir:
+        # Could potentially hit the commandline limit, so write files to a response file
+        # See https://github.com/dotnet/format/issues/699
+        resp_file = os.path.join(tempdir, "response.txt")
+        with open(resp_file, "w") as fp:
+            for f in args.files:
+                fp.write(f + "\n")
+
+        subprocess_args = ["dotnet", "format", "--folder", "--include", f"@{resp_file}"]
+        subprocess.check_call(subprocess_args)