Unity 机器学习代理工具包 (ML-Agents) 是一个开源项目,它使游戏和模拟能够作为训练智能代理的环境。
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using System;
using System.Collections.Generic;
using Unity.MLAgents.Actuators;
using Unity.MLAgents.Sensors;
using UnityEngine;
using UnityEngine.Analytics;
#if UNITY_EDITOR
using UnityEditor;
using UnityEditor.Analytics;
#endif
namespace Unity.MLAgents.Analytics
{
internal class TrainingAnalytics
{
const string k_VendorKey = "unity.ml-agents";
const string k_TrainingEnvironmentInitializedEventName = "ml_agents_training_environment_initialized";
const string k_TrainingBehaviorInitializedEventName = "ml_agents_training_behavior_initialized";
const string k_RemotePolicyInitializedEventName = "ml_agents_remote_policy_initialized";
private static readonly string[] s_EventNames =
{
k_TrainingEnvironmentInitializedEventName,
k_TrainingBehaviorInitializedEventName,
k_RemotePolicyInitializedEventName
};
/// <summary>
/// Whether or not we've registered this particular event yet
/// </summary>
static bool s_EventsRegistered = false;
/// <summary>
/// Hourly limit for this event name
/// </summary>
const int k_MaxEventsPerHour = 1000;
/// <summary>
/// Maximum number of items in this event.
/// </summary>
const int k_MaxNumberOfElements = 1000;
private static bool s_SentEnvironmentInitialized;
/// <summary>
/// Behaviors that we've already sent events for.
/// </summary>
private static HashSet<string> s_SentRemotePolicyInitialized;
private static HashSet<string> s_SentTrainingBehaviorInitialized;
private static Guid s_TrainingSessionGuid;
// These are set when the RpcCommunicator connects
private static string s_TrainerPackageVersion = "";
private static string s_TrainerCommunicationVersion = "";
static bool EnableAnalytics()
{
if (s_EventsRegistered)
{
return true;
}
foreach (var eventName in s_EventNames)
{
#if UNITY_EDITOR
AnalyticsResult result = EditorAnalytics.RegisterEventWithLimit(eventName, k_MaxEventsPerHour, k_MaxNumberOfElements, k_VendorKey);
#else
AnalyticsResult result = AnalyticsResult.UnsupportedPlatform;
#endif
if (result != AnalyticsResult.Ok)
{
return false;
}
}
s_EventsRegistered = true;
if (s_SentRemotePolicyInitialized == null)
{
s_SentRemotePolicyInitialized = new HashSet<string>();
s_SentTrainingBehaviorInitialized = new HashSet<string>();
s_TrainingSessionGuid = Guid.NewGuid();
}
return s_EventsRegistered;
}
/// <summary>
/// Cache information about the trainer when it becomes available in the RpcCommunicator.
/// </summary>
/// <param name="communicationVersion"></param>
/// <param name="packageVersion"></param>
public static void SetTrainerInformation(string packageVersion, string communicationVersion)
{
s_TrainerPackageVersion = packageVersion;
s_TrainerCommunicationVersion = communicationVersion;
}
public static bool IsAnalyticsEnabled()
{
#if UNITY_EDITOR
return EditorAnalytics.enabled;
#else
return false;
#endif
}
public static void TrainingEnvironmentInitialized(TrainingEnvironmentInitializedEvent tbiEvent)
{
if (!IsAnalyticsEnabled())
return;
if (!EnableAnalytics())
return;
if (s_SentEnvironmentInitialized)
{
// We already sent an TrainingEnvironmentInitializedEvent. Exit so we don't resend.
return;
}
s_SentEnvironmentInitialized = true;
tbiEvent.TrainingSessionGuid = s_TrainingSessionGuid.ToString();
// Note - to debug, use JsonUtility.ToJson on the event.
// Debug.Log(
// $"Would send event {k_TrainingEnvironmentInitializedEventName} with body {JsonUtility.ToJson(tbiEvent, true)}"
// );
#if UNITY_EDITOR
if (AnalyticsUtils.s_SendEditorAnalytics)
{
EditorAnalytics.SendEventWithLimit(k_TrainingEnvironmentInitializedEventName, tbiEvent);
}
#else
return;
#endif
}
public static void RemotePolicyInitialized(
string fullyQualifiedBehaviorName,
IList<ISensor> sensors,
ActionSpec actionSpec
)
{
if (!IsAnalyticsEnabled())
return;
if (!EnableAnalytics())
return;
// Extract base behavior name (no team ID)
var behaviorName = ParseBehaviorName(fullyQualifiedBehaviorName);
var added = s_SentRemotePolicyInitialized.Add(behaviorName);
if (!added)
{
// We previously added this model. Exit so we don't resend.
return;
}
var data = GetEventForRemotePolicy(behaviorName, sensors, actionSpec);
// Note - to debug, use JsonUtility.ToJson on the event.
// Debug.Log(
// $"Would send event {k_RemotePolicyInitializedEventName} with body {JsonUtility.ToJson(data, true)}"
// );
#if UNITY_EDITOR
if (AnalyticsUtils.s_SendEditorAnalytics)
{
EditorAnalytics.SendEventWithLimit(k_RemotePolicyInitializedEventName, data);
}
#else
return;
#endif
}
internal static string ParseBehaviorName(string fullyQualifiedBehaviorName)
{
var lastQuestionIndex = fullyQualifiedBehaviorName.LastIndexOf("?");
if (lastQuestionIndex < 0)
{
// Nothing to remove
return fullyQualifiedBehaviorName;
}
return fullyQualifiedBehaviorName.Substring(0, lastQuestionIndex);
}
public static void TrainingBehaviorInitialized(TrainingBehaviorInitializedEvent tbiEvent)
{
if (!IsAnalyticsEnabled())
return;
if (!EnableAnalytics())
return;
var behaviorName = tbiEvent.BehaviorName;
var added = s_SentTrainingBehaviorInitialized.Add(behaviorName);
if (!added)
{
// We previously added this model. Exit so we don't resend.
return;
}
// Hash the behavior name so that there's no concern about PII or "secret" data being leaked.
tbiEvent.TrainingSessionGuid = s_TrainingSessionGuid.ToString();
tbiEvent.BehaviorName = AnalyticsUtils.Hash(tbiEvent.BehaviorName);
// Note - to debug, use JsonUtility.ToJson on the event.
// Debug.Log(
// $"Would send event {k_TrainingBehaviorInitializedEventName} with body {JsonUtility.ToJson(tbiEvent, true)}"
// );
#if UNITY_EDITOR
if (AnalyticsUtils.s_SendEditorAnalytics)
{
EditorAnalytics.SendEventWithLimit(k_TrainingBehaviorInitializedEventName, tbiEvent);
}
#else
return;
#endif
}
static RemotePolicyInitializedEvent GetEventForRemotePolicy(
string behaviorName,
IList<ISensor> sensors,
ActionSpec actionSpec)
{
var remotePolicyEvent = new RemotePolicyInitializedEvent();
// Hash the behavior name so that there's no concern about PII or "secret" data being leaked.
remotePolicyEvent.BehaviorName = AnalyticsUtils.Hash(behaviorName);
remotePolicyEvent.TrainingSessionGuid = s_TrainingSessionGuid.ToString();
remotePolicyEvent.ActionSpec = EventActionSpec.FromActionSpec(actionSpec);
remotePolicyEvent.ObservationSpecs = new List<EventObservationSpec>(sensors.Count);
foreach (var sensor in sensors)
{
remotePolicyEvent.ObservationSpecs.Add(EventObservationSpec.FromSensor(sensor));
}
remotePolicyEvent.MLAgentsEnvsVersion = s_TrainerPackageVersion;
remotePolicyEvent.TrainerCommunicationVersion = s_TrainerCommunicationVersion;
return remotePolicyEvent;
}
}
}