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594 行
22 KiB
594 行
22 KiB
# if UNITY_EDITOR || UNITY_STANDALONE_WIN || UNITY_STANDALONE_OSX || UNITY_STANDALONE_LINUX
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using Grpc.Core;
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#endif
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#if UNITY_EDITOR
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using UnityEditor;
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#endif
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using System;
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using System.Collections.Generic;
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using System.Linq;
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using UnityEngine;
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using Unity.MLAgents.Actuators;
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using Unity.MLAgents.Analytics;
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using Unity.MLAgents.CommunicatorObjects;
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using Unity.MLAgents.Sensors;
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using Unity.MLAgents.SideChannels;
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using Google.Protobuf;
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namespace Unity.MLAgents
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{
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/// Responsible for communication with External using gRPC.
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internal class RpcCommunicator : ICommunicator
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{
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public event QuitCommandHandler QuitCommandReceived;
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public event ResetCommandHandler ResetCommandReceived;
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/// If true, the communication is active.
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bool m_IsOpen;
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List<string> m_BehaviorNames = new List<string>();
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bool m_NeedCommunicateThisStep;
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ObservationWriter m_ObservationWriter = new ObservationWriter();
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Dictionary<string, SensorShapeValidator> m_SensorShapeValidators = new Dictionary<string, SensorShapeValidator>();
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Dictionary<string, List<int>> m_OrderedAgentsRequestingDecisions = new Dictionary<string, List<int>>();
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/// The current UnityRLOutput to be sent when all the brains queried the communicator
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UnityRLOutputProto m_CurrentUnityRlOutput =
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new UnityRLOutputProto();
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Dictionary<string, Dictionary<int, ActionBuffers>> m_LastActionsReceived =
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new Dictionary<string, Dictionary<int, ActionBuffers>>();
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// Brains that we have sent over the communicator with agents.
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HashSet<string> m_SentBrainKeys = new HashSet<string>();
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Dictionary<string, ActionSpec> m_UnsentBrainKeys = new Dictionary<string, ActionSpec>();
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#if UNITY_EDITOR || UNITY_STANDALONE_WIN || UNITY_STANDALONE_OSX || UNITY_STANDALONE_LINUX
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/// The Unity to External client.
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UnityToExternalProto.UnityToExternalProtoClient m_Client;
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#endif
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/// The communicator parameters sent at construction
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CommunicatorInitParameters m_CommunicatorInitParameters;
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/// <summary>
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/// Initializes a new instance of the RPCCommunicator class.
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/// </summary>
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/// <param name="communicatorInitParameters">Communicator parameters.</param>
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public RpcCommunicator(CommunicatorInitParameters communicatorInitParameters)
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{
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m_CommunicatorInitParameters = communicatorInitParameters;
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}
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#region Initialization
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internal static bool CheckCommunicationVersionsAreCompatible(
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string unityCommunicationVersion,
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string pythonApiVersion
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)
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{
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var unityVersion = new Version(unityCommunicationVersion);
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var pythonVersion = new Version(pythonApiVersion);
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if (unityVersion.Major == 0)
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{
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if (unityVersion.Major != pythonVersion.Major || unityVersion.Minor != pythonVersion.Minor)
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{
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return false;
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}
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}
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else if (unityVersion.Major != pythonVersion.Major)
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{
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return false;
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}
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else if (unityVersion.Minor != pythonVersion.Minor)
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{
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// If a feature is used in Unity but not supported in the trainer,
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// we will warn at the point it's used. Don't warn here to avoid noise.
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}
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return true;
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}
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/// <summary>
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/// Sends the initialization parameters through the Communicator.
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/// Is used by the academy to send initialization parameters to the communicator.
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/// </summary>
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/// <returns>Whether the connection was successful.</returns>
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/// <param name="initParameters">The Unity Initialization Parameters to be sent.</param>
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/// <param name="initParametersOut">The External Initialization Parameters received.</param>
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public bool Initialize(CommunicatorInitParameters initParameters, out UnityRLInitParameters initParametersOut)
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{
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var academyParameters = new UnityRLInitializationOutputProto
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{
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Name = initParameters.name,
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PackageVersion = initParameters.unityPackageVersion,
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CommunicationVersion = initParameters.unityCommunicationVersion,
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Capabilities = initParameters.CSharpCapabilities.ToProto()
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};
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UnityInputProto input;
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UnityInputProto initializationInput;
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try
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{
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initializationInput = Initialize(
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new UnityOutputProto
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{
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RlInitializationOutput = academyParameters
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},
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out input
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);
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}
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catch (Exception ex)
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{
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if (ex is RpcException rpcException)
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{
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switch (rpcException.Status.StatusCode)
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{
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case StatusCode.Unavailable:
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// This is the common case where there's no trainer to connect to.
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break;
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case StatusCode.DeadlineExceeded:
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// We don't currently set a deadline for connection, but likely will in the future.
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break;
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default:
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Debug.Log($"Unexpected gRPC exception when trying to initialize communication: {rpcException}");
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break;
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}
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}
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else
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{
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Debug.Log($"Unexpected exception when trying to initialize communication: {ex}");
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}
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initParametersOut = new UnityRLInitParameters();
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return false;
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}
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var pythonPackageVersion = initializationInput.RlInitializationInput.PackageVersion;
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var pythonCommunicationVersion = initializationInput.RlInitializationInput.CommunicationVersion;
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TrainingAnalytics.SetTrainerInformation(pythonPackageVersion, pythonCommunicationVersion);
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var communicationIsCompatible = CheckCommunicationVersionsAreCompatible(
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initParameters.unityCommunicationVersion,
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pythonCommunicationVersion
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);
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// Initialization succeeded part-way. The most likely cause is a mismatch between the communicator
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// API strings, so log an explicit warning if that's the case.
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if (initializationInput != null && input == null)
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{
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if (!communicationIsCompatible)
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{
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Debug.LogWarningFormat(
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"Communication protocol between python ({0}) and Unity ({1}) have different " +
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"versions which make them incompatible. Python library version: {2}.",
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pythonCommunicationVersion, initParameters.unityCommunicationVersion,
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pythonPackageVersion
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);
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}
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else
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{
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Debug.LogWarningFormat(
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"Unknown communication error between Python. Python communication protocol: {0}, " +
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"Python library version: {1}.",
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pythonCommunicationVersion,
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pythonPackageVersion
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);
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}
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initParametersOut = new UnityRLInitParameters();
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return false;
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}
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UpdateEnvironmentWithInput(input.RlInput);
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initParametersOut = initializationInput.RlInitializationInput.ToUnityRLInitParameters();
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return true;
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}
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/// <summary>
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/// Adds the brain to the list of brains which will be sending information to External.
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/// </summary>
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/// <param name="brainKey">Brain key.</param>
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/// <param name="actionSpec"> Description of the actions for the Agent.</param>
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public void SubscribeBrain(string brainKey, ActionSpec actionSpec)
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{
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if (m_BehaviorNames.Contains(brainKey))
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{
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return;
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}
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m_BehaviorNames.Add(brainKey);
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m_CurrentUnityRlOutput.AgentInfos.Add(
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brainKey,
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new UnityRLOutputProto.Types.ListAgentInfoProto()
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);
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CacheActionSpec(brainKey, actionSpec);
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}
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void UpdateEnvironmentWithInput(UnityRLInputProto rlInput)
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{
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SideChannelManager.ProcessSideChannelData(rlInput.SideChannel.ToArray());
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SendCommandEvent(rlInput.Command);
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}
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UnityInputProto Initialize(UnityOutputProto unityOutput, out UnityInputProto unityInput)
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{
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#if UNITY_EDITOR || UNITY_STANDALONE_WIN || UNITY_STANDALONE_OSX || UNITY_STANDALONE_LINUX
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m_IsOpen = true;
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var channel = new Channel(
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"localhost:" + m_CommunicatorInitParameters.port,
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ChannelCredentials.Insecure);
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m_Client = new UnityToExternalProto.UnityToExternalProtoClient(channel);
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var result = m_Client.Exchange(WrapMessage(unityOutput, 200));
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var inputMessage = m_Client.Exchange(WrapMessage(null, 200));
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unityInput = inputMessage.UnityInput;
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#if UNITY_EDITOR
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EditorApplication.playModeStateChanged += HandleOnPlayModeChanged;
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#endif
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if (result.Header.Status != 200 || inputMessage.Header.Status != 200)
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{
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m_IsOpen = false;
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QuitCommandReceived?.Invoke();
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}
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return result.UnityInput;
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#else
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throw new UnityAgentsException("You cannot perform training on this platform.");
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#endif
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}
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#endregion
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#region Destruction
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/// <summary>
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/// Close the communicator gracefully on both sides of the communication.
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/// </summary>
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public void Dispose()
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{
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#if UNITY_EDITOR || UNITY_STANDALONE_WIN || UNITY_STANDALONE_OSX || UNITY_STANDALONE_LINUX
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if (!m_IsOpen)
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{
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return;
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}
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try
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{
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m_Client.Exchange(WrapMessage(null, 400));
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m_IsOpen = false;
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}
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catch
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{
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// ignored
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}
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#else
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throw new UnityAgentsException(
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"You cannot perform training on this platform.");
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#endif
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}
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#endregion
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#region Sending Events
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void SendCommandEvent(CommandProto command)
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{
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switch (command)
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{
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case CommandProto.Quit:
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{
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QuitCommandReceived?.Invoke();
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return;
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}
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case CommandProto.Reset:
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{
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foreach (var brainName in m_OrderedAgentsRequestingDecisions.Keys)
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{
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m_OrderedAgentsRequestingDecisions[brainName].Clear();
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}
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ResetCommandReceived?.Invoke();
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return;
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}
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default:
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{
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return;
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}
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}
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}
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#endregion
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#region Sending and retreiving data
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public void DecideBatch()
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{
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if (!m_NeedCommunicateThisStep)
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{
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return;
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}
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m_NeedCommunicateThisStep = false;
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SendBatchedMessageHelper();
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}
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/// <summary>
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/// Sends the observations of one Agent.
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/// </summary>
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/// <param name="behaviorName">Batch Key.</param>
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/// <param name="info">Agent info.</param>
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/// <param name="sensors">Sensors that will produce the observations</param>
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public void PutObservations(string behaviorName, AgentInfo info, List<ISensor> sensors)
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{
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#if DEBUG
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if (!m_SensorShapeValidators.ContainsKey(behaviorName))
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{
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m_SensorShapeValidators[behaviorName] = new SensorShapeValidator();
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}
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m_SensorShapeValidators[behaviorName].ValidateSensors(sensors);
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#endif
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using (TimerStack.Instance.Scoped("AgentInfo.ToProto"))
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{
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var agentInfoProto = info.ToAgentInfoProto();
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using (TimerStack.Instance.Scoped("GenerateSensorData"))
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{
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foreach (var sensor in sensors)
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{
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var obsProto = sensor.GetObservationProto(m_ObservationWriter);
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agentInfoProto.Observations.Add(obsProto);
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}
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}
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m_CurrentUnityRlOutput.AgentInfos[behaviorName].Value.Add(agentInfoProto);
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}
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m_NeedCommunicateThisStep = true;
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if (!m_OrderedAgentsRequestingDecisions.ContainsKey(behaviorName))
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{
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m_OrderedAgentsRequestingDecisions[behaviorName] = new List<int>();
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}
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if (!info.done)
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{
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m_OrderedAgentsRequestingDecisions[behaviorName].Add(info.episodeId);
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}
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if (!m_LastActionsReceived.ContainsKey(behaviorName))
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{
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m_LastActionsReceived[behaviorName] = new Dictionary<int, ActionBuffers>();
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}
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m_LastActionsReceived[behaviorName][info.episodeId] = ActionBuffers.Empty;
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if (info.done)
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{
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m_LastActionsReceived[behaviorName].Remove(info.episodeId);
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}
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}
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/// <summary>
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/// Helper method that sends the current UnityRLOutput, receives the next UnityInput and
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/// Applies the appropriate AgentAction to the agents.
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/// </summary>
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void SendBatchedMessageHelper()
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{
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var message = new UnityOutputProto
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{
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RlOutput = m_CurrentUnityRlOutput,
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};
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var tempUnityRlInitializationOutput = GetTempUnityRlInitializationOutput();
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if (tempUnityRlInitializationOutput != null)
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{
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message.RlInitializationOutput = tempUnityRlInitializationOutput;
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}
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byte[] messageAggregated = SideChannelManager.GetSideChannelMessage();
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message.RlOutput.SideChannel = ByteString.CopyFrom(messageAggregated);
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var input = Exchange(message);
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UpdateSentActionSpec(tempUnityRlInitializationOutput);
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foreach (var k in m_CurrentUnityRlOutput.AgentInfos.Keys)
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{
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m_CurrentUnityRlOutput.AgentInfos[k].Value.Clear();
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}
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var rlInput = input?.RlInput;
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if (rlInput?.AgentActions == null)
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{
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return;
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}
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UpdateEnvironmentWithInput(rlInput);
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foreach (var brainName in rlInput.AgentActions.Keys)
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{
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if (!m_OrderedAgentsRequestingDecisions[brainName].Any())
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{
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continue;
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}
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if (!rlInput.AgentActions[brainName].Value.Any())
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{
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continue;
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}
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var agentActions = rlInput.AgentActions[brainName].ToAgentActionList();
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var numAgents = m_OrderedAgentsRequestingDecisions[brainName].Count;
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for (var i = 0; i < numAgents; i++)
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{
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var agentAction = agentActions[i];
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var agentId = m_OrderedAgentsRequestingDecisions[brainName][i];
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if (m_LastActionsReceived[brainName].ContainsKey(agentId))
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{
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m_LastActionsReceived[brainName][agentId] = agentAction;
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}
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}
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}
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foreach (var brainName in m_OrderedAgentsRequestingDecisions.Keys)
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{
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m_OrderedAgentsRequestingDecisions[brainName].Clear();
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}
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}
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public ActionBuffers GetActions(string behaviorName, int agentId)
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{
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if (m_LastActionsReceived.ContainsKey(behaviorName))
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{
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if (m_LastActionsReceived[behaviorName].ContainsKey(agentId))
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{
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return m_LastActionsReceived[behaviorName][agentId];
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}
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}
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return ActionBuffers.Empty;
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}
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/// <summary>
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/// Send a UnityOutput and receives a UnityInput.
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/// </summary>
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/// <returns>The next UnityInput.</returns>
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/// <param name="unityOutput">The UnityOutput to be sent.</param>
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UnityInputProto Exchange(UnityOutputProto unityOutput)
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{
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#if UNITY_EDITOR || UNITY_STANDALONE_WIN || UNITY_STANDALONE_OSX || UNITY_STANDALONE_LINUX
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if (!m_IsOpen)
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{
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return null;
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}
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try
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{
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var message = m_Client.Exchange(WrapMessage(unityOutput, 200));
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if (message.Header.Status == 200)
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{
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return message.UnityInput;
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}
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m_IsOpen = false;
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// Not sure if the quit command is actually sent when a
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// non 200 message is received. Notify that we are indeed
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// quitting.
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QuitCommandReceived?.Invoke();
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return message.UnityInput;
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}
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catch (Exception ex)
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{
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if (ex is RpcException rpcException)
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{
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// Log more verbose errors if they're something the user can possibly do something about.
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switch (rpcException.Status.StatusCode)
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{
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case StatusCode.Unavailable:
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// This can happen when python disconnects. Ignore it to avoid noisy logs.
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break;
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case StatusCode.ResourceExhausted:
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// This happens is the message body is too large. There's no way to
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// gracefully handle this, but at least we can show the message and the
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// user can try to reduce the number of agents or observation sizes.
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Debug.LogError($"GRPC Exception: {rpcException.Message}. Disconnecting from trainer.");
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break;
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default:
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// Other unknown errors. Log at INFO level.
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Debug.Log($"GRPC Exception: {rpcException.Message}. Disconnecting from trainer.");
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break;
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}
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}
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else
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{
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// Fall-through for other error types
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Debug.LogError($"Communication Exception: {ex.Message}. Disconnecting from trainer.");
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}
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m_IsOpen = false;
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QuitCommandReceived?.Invoke();
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return null;
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}
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#else
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throw new UnityAgentsException(
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"You cannot perform training on this platform.");
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#endif
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}
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/// <summary>
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/// Wraps the UnityOutput into a message with the appropriate status.
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/// </summary>
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/// <returns>The UnityMessage corresponding.</returns>
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/// <param name="content">The UnityOutput to be wrapped.</param>
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/// <param name="status">The status of the message.</param>
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static UnityMessageProto WrapMessage(UnityOutputProto content, int status)
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{
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return new UnityMessageProto
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{
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Header = new HeaderProto { Status = status },
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UnityOutput = content
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};
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}
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void CacheActionSpec(string behaviorName, ActionSpec actionSpec)
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{
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if (m_SentBrainKeys.Contains(behaviorName))
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{
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return;
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}
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// TODO We should check that if m_unsentBrainKeys has brainKey, it equals actionSpec
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m_UnsentBrainKeys[behaviorName] = actionSpec;
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}
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UnityRLInitializationOutputProto GetTempUnityRlInitializationOutput()
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{
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UnityRLInitializationOutputProto output = null;
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foreach (var behaviorName in m_UnsentBrainKeys.Keys)
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{
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if (m_CurrentUnityRlOutput.AgentInfos.ContainsKey(behaviorName))
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{
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if (m_CurrentUnityRlOutput.AgentInfos[behaviorName].CalculateSize() > 0)
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{
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// Only send the actionSpec if there is a non empty list of
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// AgentInfos ready to be sent.
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// This is to ensure that The Python side will always have a first
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// observation when receiving the ActionSpec
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if (output == null)
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{
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output = new UnityRLInitializationOutputProto();
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}
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var actionSpec = m_UnsentBrainKeys[behaviorName];
|
|
output.BrainParameters.Add(actionSpec.ToBrainParametersProto(behaviorName, true));
|
|
}
|
|
}
|
|
}
|
|
|
|
return output;
|
|
}
|
|
|
|
void UpdateSentActionSpec(UnityRLInitializationOutputProto output)
|
|
{
|
|
if (output == null)
|
|
{
|
|
return;
|
|
}
|
|
|
|
foreach (var brainProto in output.BrainParameters)
|
|
{
|
|
m_SentBrainKeys.Add(brainProto.BrainName);
|
|
m_UnsentBrainKeys.Remove(brainProto.BrainName);
|
|
}
|
|
}
|
|
|
|
#endregion
|
|
|
|
#if UNITY_EDITOR
|
|
/// <summary>
|
|
/// When the editor exits, the communicator must be closed
|
|
/// </summary>
|
|
/// <param name="state">State.</param>
|
|
void HandleOnPlayModeChanged(PlayModeStateChange state)
|
|
{
|
|
// This method is run whenever the playmode state is changed.
|
|
if (state == PlayModeStateChange.ExitingPlayMode)
|
|
{
|
|
Dispose();
|
|
}
|
|
}
|
|
|
|
#endif
|
|
}
|
|
}
|