Making some fields and properties internal (#3342)

* Making some fields and properties internal

* Fixing the formating

* Making more things internal

* Adressing the comments

* reverting the changes made to the recorder

* WriteAdapter public

* Have to make AgentInfo and TensorProxy public because of changes to write adapter and the demorecorder

Author: vincentpierre

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

@@ -25,7 +25,7 @@ namespace MLAgents
     /// <summary>
     /// Helper class to step the Academy during FixedUpdate phase.
     /// </summary>
-    public class AcademyFixedUpdateStepper : MonoBehaviour
+    internal class AcademyFixedUpdateStepper : MonoBehaviour
     {
         void FixedUpdate()
         {
@@ -92,7 +92,7 @@ public bool IsCommunicatorOn
         int m_TotalStepCount;
 
         /// Pointer to the communicator currently in use by the Academy.
-        public ICommunicator Communicator;
+        internal ICommunicator Communicator;
 
         bool m_Initialized;
         List<ModelRunner> m_ModelRunners = new List<ModelRunner>();
@@ -108,27 +108,27 @@ public bool IsCommunicatorOn
 
         // Signals to all the Agents at each environment step so they can use
         // their Policy to decide on their next action.
-        public event System.Action DecideAction;
+        internal event System.Action DecideAction;
 
         // Signals to all the listeners that the academy is being destroyed
-        public event System.Action DestroyAction;
+        internal event System.Action DestroyAction;
 
         // Signals to all the agents at each environment step along with the
         // Academy's maxStepReached, done and stepCount values. The agents rely
         // on this event to update their own values of max step reached and done
         // in addition to aligning on the step count of the global episode.
-        public event System.Action<int> AgentSetStatus;
+        internal event System.Action<int> AgentSetStatus;
 
         // Signals to all the agents at each environment step so they can send
         // their state to their Policy if they have requested a decision.
-        public event System.Action AgentSendState;
+        internal event System.Action AgentSendState;
 
         // Signals to all the agents at each environment step so they can act if
         // they have requested a decision.
-        public event System.Action AgentAct;
+        internal event System.Action AgentAct;
 
         // Signals to all the agents each time the Academy force resets.
-        public event System.Action AgentForceReset;
+        internal event System.Action AgentForceReset;
 
         // Signals that the Academy has been reset by the training process
         public event System.Action OnEnvironmentReset;
@@ -154,7 +154,7 @@ public bool IsCommunicatorOn
         /// Initialize the Academy if it hasn't already been initialized.
         /// This method is always safe to call; it will have no effect if the Academy is already initialized.
         /// </summary>
-        public void LazyInitialization()
+        internal void LazyInitialization()
         {
             if (!m_Initialized)
             {
@@ -426,7 +426,7 @@ void EnvironmentReset()
         /// <param name="inferenceDevice"> The inference device (CPU or GPU)
         /// the ModelRunner will use </param>
         /// <returns> The ModelRunner compatible with the input settings</returns>
-        public ModelRunner GetOrCreateModelRunner(
+        internal ModelRunner GetOrCreateModelRunner(
             NNModel model, BrainParameters brainParameters, InferenceDevice inferenceDevice)
         {
             var modelRunner = m_ModelRunners.Find(x => x.HasModel(model, inferenceDevice));

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

@@ -4,7 +4,7 @@
 
 namespace MLAgents
 {
-    public class ActionMasker
+    internal class ActionMasker
     {
         /// When using discrete control, is the starting indices of the actions
         /// when all the branches are concatenated with each other.

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

@@ -50,7 +50,7 @@ public struct AgentInfo
     /// Struct that contains the action information sent from the Brain to the
     /// Agent.
     /// </summary>
-    public struct AgentAction
+    internal struct AgentAction
     {
         public float[] vectorActions;
     }
@@ -174,12 +174,12 @@ public abstract class Agent : MonoBehaviour
         /// Currently generated from attached SensorComponents, and a legacy VectorSensor
         /// </summary>
         [FormerlySerializedAs("m_Sensors")]
-        public List<ISensor> sensors;
+        internal List<ISensor> sensors;
 
         /// <summary>
         /// VectorSensor which is written to by AddVectorObs
         /// </summary>
-        public VectorSensor collectObservationsSensor;
+        internal VectorSensor collectObservationsSensor;
 
         /// MonoBehaviour function that is called when the attached GameObject
         /// becomes enabled or active.
@@ -420,7 +420,7 @@ public virtual float[] Heuristic()
         /// Set up the list of ISensors on the Agent. By default, this will select any
         /// SensorBase's attached to the Agent.
         /// </summary>
-        public void InitializeSensors()
+        internal void InitializeSensors()
         {
             // Get all attached sensor components
             SensorComponent[] attachedSensorComponents;
@@ -710,20 +710,11 @@ void _AgentReset()
             AgentReset();
         }
 
-        public void UpdateAgentAction(AgentAction action)
+        internal void UpdateAgentAction(AgentAction action)
         {
             m_Action = action;
         }
 
-        /// <summary>
-        /// Updates the vector action.
-        /// </summary>
-        /// <param name="vectorActions">Vector actions.</param>
-        public void UpdateVectorAction(float[] vectorActions)
-        {
-            m_Action.vectorActions = vectorActions;
-        }
-
         /// <summary>
         /// Scales continuous action from [-1, 1] to arbitrary range.
         /// </summary>

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

@@ -0,0 +1,4 @@
+using System.Runtime.CompilerServices;
+
+[assembly: InternalsVisibleTo("Unity.ML-Agents.Editor.Tests")]
+[assembly: InternalsVisibleTo("Unity.ML-Agents.Editor")]

com.unity.ml-agents/Runtime/AssemblyInfo.cs.meta

@@ -3,7 +3,7 @@ namespace MLAgents
     /// <summary>
     /// Grouping for use in AddComponentMenu (instead of nesting the menus).
     /// </summary>
-    public enum MenuGroup
+    internal enum MenuGroup
     {
         Default = 0,
         Sensors = 50

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

@@ -1,6 +1,6 @@
 namespace MLAgents
 {
-    public static class EpisodeIdCounter
+    internal static class EpisodeIdCounter
     {
         private static int Counter;
         public static int GetEpisodeId()

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

@@ -13,13 +13,13 @@
 
 namespace MLAgents
 {
-    public static class GrpcExtensions
+    internal static class GrpcExtensions
     {
         /// <summary>
         /// Converts a AgentInfo to a protobuf generated AgentInfoActionPairProto
         /// </summary>
         /// <returns>The protobuf version of the AgentInfoActionPairProto.</returns>
-        internal static AgentInfoActionPairProto ToInfoActionPairProto(this AgentInfo ai)
+        public static AgentInfoActionPairProto ToInfoActionPairProto(this AgentInfo ai)
         {
             var agentInfoProto = ai.ToAgentInfoProto();
 
@@ -39,7 +39,7 @@ internal static AgentInfoActionPairProto ToInfoActionPairProto(this AgentInfo ai
         /// Converts a AgentInfo to a protobuf generated AgentInfoProto
         /// </summary>
         /// <returns>The protobuf version of the AgentInfo.</returns>
-        internal static AgentInfoProto ToAgentInfoProto(this AgentInfo ai)
+        public static AgentInfoProto ToAgentInfoProto(this AgentInfo ai)
         {
             var agentInfoProto = new AgentInfoProto
             {
@@ -64,7 +64,7 @@ internal static AgentInfoProto ToAgentInfoProto(this AgentInfo ai)
         /// <param name="bp">The instance of BrainParameter to extend.</param>
         /// <param name="name">The name of the brain.</param>
         /// <param name="isTraining">Whether or not the Brain is training.</param>
-        internal static BrainParametersProto ToProto(this BrainParameters bp, string name, bool isTraining)
+        public static BrainParametersProto ToProto(this BrainParameters bp, string name, bool isTraining)
         {
             var brainParametersProto = new BrainParametersProto
             {
@@ -81,7 +81,7 @@ internal static BrainParametersProto ToProto(this BrainParameters bp, string nam
         /// <summary>
         /// Convert metadata object to proto object.
         /// </summary>
-        internal static DemonstrationMetaProto ToProto(this DemonstrationMetaData dm)
+        public static DemonstrationMetaProto ToProto(this DemonstrationMetaData dm)
         {
             var demoProto = new DemonstrationMetaProto
             {
@@ -97,7 +97,7 @@ internal static DemonstrationMetaProto ToProto(this DemonstrationMetaData dm)
         /// <summary>
         /// Initialize metadata values based on proto object.
         /// </summary>
-        internal static DemonstrationMetaData ToDemonstrationMetaData(this DemonstrationMetaProto demoProto)
+        public static DemonstrationMetaData ToDemonstrationMetaData(this DemonstrationMetaProto demoProto)
         {
             var dm = new DemonstrationMetaData
             {
@@ -118,7 +118,7 @@ internal static DemonstrationMetaData ToDemonstrationMetaData(this Demonstration
         /// </summary>
         /// <param name="bpp">An instance of a brain parameters protobuf object.</param>
         /// <returns>A BrainParameters struct.</returns>
-        internal static BrainParameters ToBrainParameters(this BrainParametersProto bpp)
+        public static BrainParameters ToBrainParameters(this BrainParametersProto bpp)
         {
             var bp = new BrainParameters
             {
@@ -129,23 +129,23 @@ internal static BrainParameters ToBrainParameters(this BrainParametersProto bpp)
             return bp;
         }
 
-        internal static UnityRLInitParameters ToUnityRLInitParameters(this UnityRLInitializationInputProto inputProto)
+        public static UnityRLInitParameters ToUnityRLInitParameters(this UnityRLInitializationInputProto inputProto)
         {
             return new UnityRLInitParameters
             {
                 seed = inputProto.Seed
             };
         }
 
-        internal static AgentAction ToAgentAction(this AgentActionProto aap)
+        public static AgentAction ToAgentAction(this AgentActionProto aap)
         {
             return new AgentAction
             {
                 vectorActions = aap.VectorActions.ToArray()
             };
         }
 
-        internal static List<AgentAction> ToAgentActionList(this UnityRLInputProto.Types.ListAgentActionProto proto)
+        public static List<AgentAction> ToAgentActionList(this UnityRLInputProto.Types.ListAgentActionProto proto)
         {
             var agentActions = new List<AgentAction>(proto.Value.Count);
             foreach (var ap in proto.Value)
@@ -155,7 +155,7 @@ internal static List<AgentAction> ToAgentActionList(this UnityRLInputProto.Types
             return agentActions;
         }
 
-        internal static ObservationProto ToProto(this Observation obs)
+        public static ObservationProto ToProto(this Observation obs)
         {
             ObservationProto obsProto = null;
 
@@ -199,7 +199,7 @@ internal static ObservationProto ToProto(this Observation obs)
         /// <param name="sensor"></param>
         /// <param name="writeAdapter"></param>
         /// <returns></returns>
-        internal static ObservationProto GetObservationProto(this ISensor sensor, WriteAdapter writeAdapter)
+        public static ObservationProto GetObservationProto(this ISensor sensor, WriteAdapter writeAdapter)
         {
             var shape = sensor.GetObservationShape();
             ObservationProto observationProto = null;

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

@@ -16,7 +16,7 @@
 namespace MLAgents
 {
     /// Responsible for communication with External using gRPC.
-    public class RpcCommunicator : ICommunicator
+    internal class RpcCommunicator : ICommunicator
     {
         public event QuitCommandHandler QuitCommandReceived;
         public event ResetCommandHandler ResetCommandReceived;

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

@@ -89,7 +89,7 @@ Since the messages are sent back and forth with exchange and simultaneously when
     UnityOutput and UnityInput can be extended to provide functionalities beyond RL
     UnityRLOutput and UnityRLInput can be extended to provide new RL functionalities
      */
-    public interface ICommunicator : IDisposable
+    internal interface ICommunicator : IDisposable
     {
         /// <summary>
         /// Quit was received by the communicator.

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

@@ -11,7 +11,7 @@ namespace MLAgents.InferenceBrain
     /// The Applier for the Continuous Action output tensor. Tensor is assumed to contain the
     /// continuous action data of the agents in the batch.
     /// </summary>
-    public class ContinuousActionOutputApplier : TensorApplier.IApplier
+    internal class ContinuousActionOutputApplier : TensorApplier.IApplier
     {
         public void Apply(TensorProxy tensorProxy, IEnumerable<int> actionIds, Dictionary<int, float[]> lastActions)
         {
@@ -42,7 +42,7 @@ public void Apply(TensorProxy tensorProxy, IEnumerable<int> actionIds, Dictionar
     /// The Applier for the Discrete Action output tensor. Uses multinomial to sample discrete
     /// actions from the logits contained in the tensor.
     /// </summary>
-    public class DiscreteActionOutputApplier : TensorApplier.IApplier
+    internal class DiscreteActionOutputApplier : TensorApplier.IApplier
     {
         readonly int[] m_ActionSize;
         readonly Multinomial m_Multinomial;
@@ -189,7 +189,7 @@ public static void Eval(TensorProxy src, TensorProxy dst, Multinomial multinomia
     /// The Applier for the Memory output tensor. Tensor is assumed to contain the new
     /// memory data of the agents in the batch.
     /// </summary>
-    public class MemoryOutputApplier : TensorApplier.IApplier
+    internal class MemoryOutputApplier : TensorApplier.IApplier
     {
         Dictionary<int, List<float>> m_Memories;
 
@@ -219,7 +219,7 @@ public void Apply(TensorProxy tensorProxy, IEnumerable<int> actionIds, Dictionar
         }
     }
 
-    public class BarracudaMemoryOutputApplier : TensorApplier.IApplier
+    internal class BarracudaMemoryOutputApplier : TensorApplier.IApplier
     {
         readonly int m_MemoriesCount;
         readonly int m_MemoryIndex;

com.unity.ml-agents/Runtime/InferenceBrain/ApplierImpl.cs

@@ -11,7 +11,7 @@ namespace MLAgents.InferenceBrain
     /// Prepares the Tensors for the Learning Brain and exposes a list of failed checks if Model
     /// and BrainParameters are incompatible.
     /// </summary>
-    public class BarracudaModelParamLoader
+    internal class BarracudaModelParamLoader
     {
         enum ModelActionType
         {