AgentInfoConvertor(AgentInfo info)
{
var agentInfoProto = new CommunicatorObjects.AgentInfoProto
{
StackedVectorObservation = { info.stackedVectorObservation },
StoredVectorActions = { info.storedVectorActions },
StoredTextActions = info.storedTextActions,
TextObservation = info.textObservation,
Reward = info.reward,
MaxStepReached = info.maxStepReached,
Done = info.done,
Id = info.id,
};
if (info.memories != null)
{
agentInfoProto.Memories.Add(info.memories);
}
if (info.actionMasks != null)
{
agentInfoProto.ActionMask.AddRange(info.actionMasks);
}
foreach (Texture2D obs in info.visualObservations)
{
agentInfoProto.VisualObservations.Add(
ByteString.CopyFrom(obs.EncodeToPNG())
);
}
return(agentInfoProto);
}
/// <summary>
/// Converts a AgentInfo to a protobuffer generated AgentInfoProto
/// </summary>
/// <returns>The protobuf verison of the AgentInfo.</returns>
/// <param name="info">The AgentInfo to convert.</param>
public CommunicatorObjects.AgentInfoProto ToProto()
{
var agentInfoProto = new CommunicatorObjects.AgentInfoProto
{
StackedVectorObservation = { stackedVectorObservation },
StoredVectorActions = { storedVectorActions },
StoredTextActions = storedTextActions,
TextObservation = textObservation,
Reward = reward,
MaxStepReached = maxStepReached,
Done = done,
Id = id,
CustomObservation = customObservation
};
if (memories != null)
{
agentInfoProto.Memories.Add(memories);
}
if (actionMasks != null)
{
agentInfoProto.ActionMask.AddRange(actionMasks);
}
foreach (Texture2D obs in visualObservations)
{
agentInfoProto.VisualObservations.Add(
ByteString.CopyFrom(obs.EncodeToPNG())
);
}
return(agentInfoProto);
}
/// <summary>
/// Sends the brain info. If at least one brain has an agent in need of
/// a decision or if the academy is done, the data is sent via
/// Communicator. Else, a new step is realized. The data can only be
/// sent once all the brains that subscribed to the batcher have tried
/// to send information.
/// </summary>
/// <param name="brainKey">Brain key.</param>
/// <param name="agentInfo">Agent info.</param>
public void SendBrainInfo(
string brainKey, Dictionary <Agent, AgentInfo> agentInfo)
{
// If no communicator is initialized, the Batcher will not transmit
// BrainInfo
if (m_communicator == null)
{
return;
}
// The brain tried called GiveBrainInfo, update m_hasQueried
m_hasQueried[brainKey] = true;
// Populate the currentAgents dictionary
m_currentAgents[brainKey].Clear();
foreach (Agent agent in agentInfo.Keys)
{
m_currentAgents[brainKey].Add(agent);
}
// If at least one agent has data to send, then append data to
// the message and update hasSentState
if (m_currentAgents[brainKey].Count > 0)
{
foreach (Agent agent in m_currentAgents[brainKey])
{
CommunicatorObjects.AgentInfoProto agentInfoProto = agentInfo[agent].ToProto();
m_currentUnityRLOutput.AgentInfos[brainKey].Value.Add(agentInfoProto);
// Avoid visual obs memory leak. This should be called AFTER we are done with the visual obs.
// e.g. after recording them to demo and using them for inference.
agentInfo[agent].ClearVisualObs();
}
m_hasData[brainKey] = true;
}
// If any agent needs to send data, then the whole message
// must be sent
if (m_hasQueried.Values.All(x => x))
{
if (m_hasData.Values.Any(x => x) || m_academyDone)
{
m_currentUnityRLOutput.GlobalDone = m_academyDone;
SendBatchedMessageHelper();
}
// The message was just sent so we must reset hasSentState and
// triedSendState
foreach (string k in m_currentAgents.Keys)
{
m_hasData[k] = false;
m_hasQueried[k] = false;
}
}
}