BasicOptimizer.scala:89 executed in 3335.20 seconds (21.342 gc):

    val lineSearchInstance: LineSearchStrategy = lineSearchFactory
    val trainer = new IterativeTrainer(trainable)
    trainer.setOrientation(orientation())
    trainer.setMonitor(new TrainingMonitor() {
      override def clear(): Unit = trainingMonitor.clear()
  
      override def log(msg: String): Unit = {
        trainingMonitor.log(msg)
        BasicOptimizer.this.log(msg)
      }
  
      override def onStepFail(currentPoint: Step): Boolean = {
        BasicOptimizer.this.onStepFail(trainable.addRef().asInstanceOf[Trainable], currentPoint)
      }
  
      override def onStepComplete(currentPoint: Step): Unit = {
        if (0 < logEvery && (0 == currentPoint.iteration % logEvery || currentPoint.iteration < logEvery)) {
          val image = currentImage()
          timelineAnimation += image
          val caption = "Iteration " + currentPoint.iteration
          out.p(caption + "\n" + out.jpg(image, caption))
        }
        BasicOptimizer.this.onStepComplete(trainable.addRef().asInstanceOf[Trainable], currentPoint)
        trainingMonitor.onStepComplete(currentPoint)
        super.onStepComplete(currentPoint)
      }
    })
    trainer.setTimeout(trainingMinutes, TimeUnit.MINUTES)
    trainer.setMaxIterations(trainingIterations)
    trainer.setLineSearchFactory((_: CharSequence) => lineSearchInstance)
    trainer.setTerminateThreshold(java.lang.Double.NEGATIVE_INFINITY)
    val result = trainer.run.asInstanceOf[lang.Double]
    trainer.freeRef()
    result
Logging 
Reset training subject: 4833066322208
Reset training subject: 4891427378037
Adding measurement 2012bc17 to history. Total: 0
LBFGS Accumulation History: 1 points
Constructing line search parameters: GD+Trust
th(0)=-1.9174160957336426;dx=-1.777641284457772E-7
Armijo: th(2.154434690031884)=-1.9174160659313202; dx=-1.7399993196855969E-7 evalInputDelta=-2.9802322387695312E-8
Armijo: th(1.077217345015942)=-1.9174160957336426; dx=-1.7401358758698295E-7 evalInputDelta=0.0
Armijo: th(0.3590724483386473)=-1.9174160957336426; dx=-1.740582245185589E-7 evalInputDelta=0.0
Armijo: th(0.08976811208466183)=-1.9174160957336426; dx=-1.7416870265288022E-7 evalInputDelta=0.0
Armijo: th(0.017953622416932366)=-1.9174160957336426; dx=-1.739885852940794E-7 evalInputDelta=0.0
Armijo: th(0.002992270402822061)=-1.9174160957336426; dx=-1.7396553540619843E-7 evalInputDelta=0.0
WOLFE (weak): th(4.2746720040315154E-4)=-1.9174160957336426; dx=-1.7402301685193743E-7 evalInputDelta=0.0
Armijo: th(0.0017098688016126062)=-1.9174160957336426; dx=-1.741989367831113E-7 evalInputDelta=0.0
Armijo: th(0.001068668001007879)=-1.9174160957336426; dx=-1.7406034125400544E-7 evalInputDelta=0.0
Armijo: th(7.480676007055152E-4)=-1.9174160957336426; dx=-1.740402231669649E-7 evalInputDelta=0.0
WOLFE (weak): th(5.877674005543334E-4)=-1.9174160957336426; dx=-1.7387415499805865E-7 evalInputDelta=0.0
Armijo: th(6.679175006299243E-4)=-1.9174160957336426; dx=-1.741804994871963E-7 evalInputDelta=0.0
Armijo: th(6.278424505921289E-4)=-1.9174160957336426; dx=-1.7418174830565182E-7 evalInputDelta=0.0
WOLFE (weak): th(6.078049255732311E-4)=-1.9174160957336426; dx=-1.739332253409575E-7 evalInputDelta=0.0
WOLFE (weak): th(6.1782368808268E-4)=-1.9174160957336426; dx=-1.7399548951048176E-7 evalInputDelta=0.0
WOLFE (weak): th(6.228330693374045E-4)=-1.9174160957336426; dx=-1.74064273103209E-7 evalInputDelta=0.0
Armijo: th(6.253377599647667E-4)=-1.9174160957336426; dx=-1.7418718394405837E-7 evalInputDelta=0.0
WOLFE (weak): th(6.240854146510855E-4)=-1.9174160957336426; dx=-1.7390183218090841E-7 evalInputDelta=0.0
Armijo: th(6.24711587307926E-4)=-1.9174160957336426; dx=-1.7410797955653637E-7 evalInputDelta=0.0
WOLFE (weak): th(6.243985009795058E-4)=-1.9174160957336426; dx=-1.7400287895544695E-7 evalInputDelta=0.0
Armijo: th(6.24555044143716E-4)=-1.9174160957336426; dx=-1.7388056501894443E-7 evalInputDelta=0.0
WOLFE (weak): th(6.244767725616109E-4)=-1.9174160957336426; dx=-1.7386710574979122E-7 evalInputDelta=0.0
WOLFE (weak): th(6.245159083526635E-4)=-1.9174160957336426; dx=-1.7396697773797058E-7 evalInputDelta=0.0
WOLFE (weak): th(6.245354762481897E-4)=-1.9174160957336426; dx=-1.7402004603382518E-7 evalInputDelta=0.0
WOLFE (weak): th(6.245452601959529E-4)=-1.9174160957336426; dx=-1.7388947297063874E-7 evalInputDelta=0.0
Armijo: th(6.245501521698344E-4)=-1.9174160957336426; dx=-1.7402119005775539E-7 evalInputDelta=0.0
mu ~= nu (6.245452601959529E-4): th(0.0)=-1.9174160957336426
Fitness changed from -1.9174160957336426 to -1.9174160957336426
Static Iteration Total: 1853.4116; Orientation: 0.3487; Line Search: 1678.6954
Iteration 1 failed. Error: -1.9174160957336426
Previous Error: 0.0 -> -1.9174160957336426
Retrying iteration 1
Reset training subject: 6686478253968
Adding measurement 8a170c5 to history. Total: 0
LBFGS Accumulation History: 1 points
th(0)=-1.9174160957336426;dx=-1.7769661019904702E-7
WOLFE (weak): th(0.0013455472437802665)=-1.9174160957336426; dx=-1.7383818575017005E-7 evalInputDelta=0.0
WOLFE (weak): th(0.002691094487560533)=-1.9174160957336426; dx=-1.738601830280194E-7 evalInputDelta=0.0
Armijo: th(0.008073283462681598)=-1.9174160957336426; dx=-1.7371007301940607E-7 evalInputDelta=0.0
Armijo: th(0.005382188975121066)=-1.9174160957336426; dx=-1.7390098710765426E-7 evalInputDelta=0.0
Armijo: th(0.004036641731340799)=-1.9174160957336426; dx=-1.7389233890407346E-7 evalInputDelta=0.0
Armijo: th(0.0033638681094506663)=-1.9174160957336426; dx=-1.7378444298465106E-7 evalInputDelta=0.0
WOLFE (weak): th(0.0030274812985056)=-1.9174160957336426; dx=-1.7386668883526275E-7 evalInputDelta=0.0
Armijo: th(0.003195674703978133)=-1.9174160957336426; dx=-1.7389286749831361E-7 evalInputDelta=0.0
WOLFE (weak): th(0.0031115780012418662)=-1.9174160957336426; dx=-1.7386977714486052E-7 evalInputDelta=0.0
Armijo: th(0.00315362635261)=-1.9174160957336426; dx=-1.7375262812214184E-7 evalInputDelta=0.0
Armijo: th(0.003132602176925933)=-1.9174160957336426; dx=-1.738816379365133E-7 evalInputDelta=0.0
WOLFE (weak): th(0.0031220900890838997)=-1.9174160957336426; dx=-1.7392455522048958E-7 evalInputDelta=0.0
Armijo: th(0.0031273461330049166)=-1.9174160957336426; dx=-1.7377182285164964E-7 evalInputDelta=0.0
Armijo: th(0.0031247181110444083)=-1.9174160957336426; dx=-1.7389448137753262E-7 evalInputDelta=0.0
WOLFE (weak): th(0.0031234041000641538)=-1.9174160957336426; dx=-1.7392746719294348E-7 evalInputDelta=0.0
Armijo: th(0.003124061105554281)=-1.9174160957336426; dx=-1.7383786944079232E-7 evalInputDelta=0.0
WOLFE (weak): th(0.003123732602809217)=-1.9174160957336426; dx=-1.7401164810282348E-7 evalInputDelta=0.0
WOLFE (weak): th(0.003123896854181749)=-1.9174160957336426; dx=-1.7399284200403553E-7 evalInputDelta=0.0
Armijo: th(0.003123978979868015)=-1.9174160957336426; dx=-1.737973051096427E-7 evalInputDelta=0.0
Armijo: th(0.003123937917024882)=-1.9174160957336426; dx=-1.7372678500659057E-7 evalInputDelta=0.0
WOLFE (weak): th(0.0031239173856033153)=-1.9174160957336426; dx=-1.7392444519135373E-7 evalInputDelta=0.0
mu ~= nu (0.0031239173856033153): th(0.0)=-1.9174160957336426
Fitness changed from -1.9174160957336426 to -1.9174160957336426
Static Iteration Total: 1481.7833; Orientation: 0.3429; Line Search: 1365.6963
Iteration 2 failed. Error: -1.9174160957336426
Previous Error: 0.0 -> -1.9174160957336426
Optimization terminated 2
Final threshold in iteration 2: -1.9174160957336426 (> -Infinity) after 3335.196s (< 5400.000s)

Returns

    -1.9174160957336426