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71 行
2.2 KiB
71 行
2.2 KiB
using System.Collections.Generic;
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using Unity.MLAgents.Actuators;
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using Unity.MLAgents.Analytics;
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using Unity.MLAgents.Sensors;
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namespace Unity.MLAgents.Policies
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{
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/// <summary>
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/// The Remote Policy only works when training.
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/// When training your Agents, the RemotePolicy will be controlled by Python.
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/// </summary>
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internal class RemotePolicy : IPolicy
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{
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int m_AgentId;
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string m_FullyQualifiedBehaviorName;
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ActionSpec m_ActionSpec;
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ActionBuffers m_LastActionBuffer;
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private bool m_AnalyticsSent = false;
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internal ICommunicator m_Communicator;
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/// <summary>
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/// List of actuators, only used for analytics
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/// </summary>
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private IList<IActuator> m_Actuators;
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/// <inheritdoc />
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public RemotePolicy(
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ActionSpec actionSpec,
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IList<IActuator> actuators,
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string fullyQualifiedBehaviorName)
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{
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m_FullyQualifiedBehaviorName = fullyQualifiedBehaviorName;
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m_Communicator = Academy.Instance.Communicator;
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m_Communicator?.SubscribeBrain(m_FullyQualifiedBehaviorName, actionSpec);
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m_ActionSpec = actionSpec;
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m_Actuators = actuators;
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}
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/// <inheritdoc />
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public void RequestDecision(AgentInfo info, List<ISensor> sensors)
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{
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if (!m_AnalyticsSent)
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{
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m_AnalyticsSent = true;
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TrainingAnalytics.RemotePolicyInitialized(
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m_FullyQualifiedBehaviorName,
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sensors,
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m_ActionSpec,
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m_Actuators
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);
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}
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m_AgentId = info.episodeId;
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m_Communicator?.PutObservations(m_FullyQualifiedBehaviorName, info, sensors);
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}
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/// <inheritdoc />
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public ref readonly ActionBuffers DecideAction()
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{
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m_Communicator?.DecideBatch();
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var actions = m_Communicator?.GetActions(m_FullyQualifiedBehaviorName, m_AgentId);
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m_LastActionBuffer = actions == null ? ActionBuffers.Empty : (ActionBuffers)actions;
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return ref m_LastActionBuffer;
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}
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public void Dispose()
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{
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}
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}
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}
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