public void StartTensorboard()
{
var args = new List <string>();
args.Add("--logdir=" + tensorFlowCOnfig.SummariesDirectory);
CommandLineRunner.StartCommandLine(tensorFlowCOnfig.TensorboardDirectory, "tensorboard", args.ToArray());
}
IEnumerator DoTrainingCo()
{
Process currentProcess = null;
configIncrement = StartingConfigIncrement;
while (configIncrement <= MaxConfigIncrement)
{
if (OnStartIncrement != null)
{
OnStartIncrement.Invoke();
}
for (currentRun = 0; currentRun < RunsPerConfiguration; currentRun++)
{
yield return(new WaitForSeconds(PauseBeforeRun));
UnityEngine.Debug.Log("Starting run " + currentRun + " in config increment " + configIncrement);
var myArguments = new List <string>(); // Make a copy of the args
var runId = RunSetName + "-inc" + configIncrement + "-run" + currentRun;
myArguments.Add(UnityOutputExeName);
myArguments.Add("--run-id=" + runId); // Add our own arg
myArguments.Add("--train");
if (ContinueFromSaved == true)
{
myArguments.Add("--load");
var sourcePath = Path.Combine(tensorFlowConfig.ModelsDirectory, ContinueFromModel);
var targetPath = Path.Combine(tensorFlowConfig.ModelsDirectory, runId);
Directory.CreateDirectory(targetPath);
CopyDirectory(sourcePath, targetPath);
}
CommandLineRunner.WorkingDirectory = tensorFlowConfig.MlAgentsRootDirectory;
currentProcess = CommandLineRunner.StartCommandLine(tensorFlowConfig.MlAgentsRootDirectory, "learn.py", myArguments.ToArray());
// Coroutine hold until process is complete
while (currentProcess.HasExited == false)
{
yield return(null);
}
if (TbManager != null)
{
yield return(StartCoroutine(TbManager.GetRunStats(runId, currentRun, configIncrement, new Action <RunStatistics>(AddToStats))));
}
}
currentRun = 0;
if (OnNextIncrement != null)
{
OnNextIncrement.Invoke();
}
}
if (OnAllIncrementsComplete != null)
{
OnAllIncrementsComplete.Invoke();
}
}