/// <summary>
/// Sends the academy parameters through the Communicator.
/// Is used by the academy to send the AcademyParameters to the communicator.
/// </summary>
/// <returns>The External Initialization Parameters received.</returns>
/// <param name="academyParameters">The Unity Initialization Parameters to be sent.</param>
public CommunicatorObjects.UnityRLInitializationInput SendAcademyParameters(
CommunicatorObjects.UnityRLInitializationOutput academyParameters)
{
CommunicatorObjects.UnityInput input;
var initializationInput = new CommunicatorObjects.UnityInput();
try
{
initializationInput = m_communicator.Initialize(
new CommunicatorObjects.UnityOutput
{
RlInitializationOutput = academyParameters
},
out input);
}
catch
{
throw new UnityAgentsException(
"The Communicator was unable to connect. Please make sure the External " +
"process is ready to accept communication with Unity.");
}
var firstRlInput = input.RlInput;
m_command = firstRlInput.Command;
m_arenasParameters = input.RlResetInput;
m_isTraining = firstRlInput.IsTraining;
return(initializationInput.RlInitializationInput);
}
/// <summary>
/// Helper method that sends the curent UnityRLOutput, receives the next UnityInput and
/// Applies the appropriate AgentAction to the agents.
/// </summary>
void SendBatchedMessageHelper()
{
var input = m_communicator.Exchange(
new CommunicatorObjects.UnityOutput
{
RlOutput = m_currentUnityRLOutput
});
m_messagesReceived += 1;
foreach (string k in m_currentUnityRLOutput.AgentInfos.Keys)
{
m_currentUnityRLOutput.AgentInfos[k].Value.Clear();
}
if (input == null)
{
m_command = CommunicatorObjects.CommandProto.Quit;
return;
}
CommunicatorObjects.UnityRLInput rlInput = input.RlInput;
if (rlInput == null)
{
m_command = CommunicatorObjects.CommandProto.Quit;
return;
}
m_command = rlInput.Command;
m_arenasParameters = input.RlResetInput;
m_isTraining = rlInput.IsTraining;
if (rlInput.AgentActions == null)
{
return;
}
foreach (var brainName in rlInput.AgentActions.Keys)
{
if (!m_currentAgents[brainName].Any())
{
continue;
}
if (!rlInput.AgentActions[brainName].Value.Any())
{
continue;
}
for (var i = 0; i < m_currentAgents[brainName].Count; i++)
{
var agent = m_currentAgents[brainName][i];
var action = rlInput.AgentActions[brainName].Value[i];
agent.UpdateVectorAction(action.VectorActions.ToArray());
agent.UpdateMemoriesAction(action.Memories.ToList());
agent.UpdateTextAction(action.TextActions);
agent.UpdateValueAction(action.Value);
}
}
}