internal static RemotePolicyInitializedEvent GetEventForRemotePolicy(
string behaviorName,
IList <ISensor> sensors,
ActionSpec actionSpec,
IList <IActuator> actuators
)
{
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.ActuatorInfos = new List <EventActuatorInfo>(actuators.Count);
foreach (var actuator in actuators)
{
remotePolicyEvent.ActuatorInfos.Add(EventActuatorInfo.FromActuator(actuator));
}
remotePolicyEvent.MLAgentsEnvsVersion = s_TrainerPackageVersion;
remotePolicyEvent.TrainerCommunicationVersion = s_TrainerCommunicationVersion;
return(remotePolicyEvent);
}
internal static TrainingBehaviorInitializedEvent SanitizeTrainingBehaviorInitializedEvent(TrainingBehaviorInitializedEvent tbiEvent)
{
// Hash the behavior name if the message version is from an older version of ml-agents that doesn't do trainer-side hashing.
// We'll also, for extra safety, verify that the BehaviorName is the size of the expected SHA256 hash.
// Context: The config field was added at the same time as trainer side hashing, so messages including it should already be hashed.
if (tbiEvent.Config.Length == 0 || tbiEvent.BehaviorName.Length != 64)
{
tbiEvent.BehaviorName = AnalyticsUtils.Hash(k_VendorKey, tbiEvent.BehaviorName);
}
return(tbiEvent);
}
/// <summary>
/// Generate an InferenceEvent for the model.
/// </summary>
/// <param name="nnModel"></param>
/// <param name="behaviorName"></param>
/// <param name="inferenceDevice"></param>
/// <param name="sensors"></param>
/// <param name="actionSpec"></param>
/// <param name="actuators"></param>
/// <returns></returns>
internal static InferenceEvent GetEventForModel(
NNModel nnModel,
string behaviorName,
InferenceDevice inferenceDevice,
IList <ISensor> sensors,
ActionSpec actionSpec,
IList <IActuator> actuators
)
{
var barracudaModel = ModelLoader.Load(nnModel);
var inferenceEvent = new InferenceEvent();
// Hash the behavior name so that there's no concern about PII or "secret" data being leaked.
inferenceEvent.BehaviorName = AnalyticsUtils.Hash(behaviorName);
inferenceEvent.BarracudaModelSource = barracudaModel.IrSource;
inferenceEvent.BarracudaModelVersion = barracudaModel.IrVersion;
inferenceEvent.BarracudaModelProducer = barracudaModel.ProducerName;
inferenceEvent.MemorySize = (int)barracudaModel.GetTensorByName(TensorNames.MemorySize)[0];
inferenceEvent.InferenceDevice = (int)inferenceDevice;
if (barracudaModel.ProducerName == "Script")
{
// .nn files don't have these fields set correctly. Assign some placeholder values.
inferenceEvent.BarracudaModelSource = "NN";
inferenceEvent.BarracudaModelProducer = "tensorflow_to_barracuda.py";
}
#if UNITY_EDITOR
var barracudaPackageInfo = UnityEditor.PackageManager.PackageInfo.FindForAssembly(typeof(Tensor).Assembly);
inferenceEvent.BarracudaPackageVersion = barracudaPackageInfo.version;
#else
inferenceEvent.BarracudaPackageVersion = null;
#endif
inferenceEvent.ActionSpec = EventActionSpec.FromActionSpec(actionSpec);
inferenceEvent.ObservationSpecs = new List <EventObservationSpec>(sensors.Count);
foreach (var sensor in sensors)
{
inferenceEvent.ObservationSpecs.Add(EventObservationSpec.FromSensor(sensor));
}
inferenceEvent.ActuatorInfos = new List <EventActuatorInfo>(actuators.Count);
foreach (var actuator in actuators)
{
inferenceEvent.ActuatorInfos.Add(EventActuatorInfo.FromActuator(actuator));
}
inferenceEvent.TotalWeightSizeBytes = GetModelWeightSize(barracudaModel);
inferenceEvent.ModelHash = GetModelHash(barracudaModel);
return(inferenceEvent);
}
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 && MLA_UNITY_ANALYTICS_MODULE_ENABLED
if (AnalyticsUtils.s_SendEditorAnalytics)
{
EditorAnalytics.SendEventWithLimit(k_TrainingBehaviorInitializedEventName, tbiEvent);
}
#else
return;
#endif
}
