BasicOptimizer.scala:89 executed in 313.58 seconds (4.985 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: 641966593500100
Reset training subject: 641972249064600
Adding measurement 64edb1a4 to history. Total: 0
LBFGS Accumulation History: 1 points
Constructing line search parameters: GD+Trust
th(0)=-71.92150203356908;dx=-1.2241391072416216E-6
Armijo: th(2.154434690031884)=-71.92150203356908; dx=-1.1989067580691863E-6 evalInputDelta=0.0
Armijo: th(1.077217345015942)=-71.92150203356908; dx=-1.1986758561973415E-6 evalInputDelta=0.0
Armijo: th(0.3590724483386473)=-71.92150203356908; dx=-1.1984765858662213E-6 evalInputDelta=0.0
Armijo: th(0.08976811208466183)=-71.92150203356908; dx=-1.1989918428001771E-6 evalInputDelta=0.0
Armijo: th(0.017953622416932366)=-71.92150203356908; dx=-1.1991286055067385E-6 evalInputDelta=0.0
WOLFE (weak): th(0.002992270402822061)=-71.92150203356908; dx=-1.1989331861507405E-6 evalInputDelta=0.0
Armijo: th(0.010472946409877214)=-71.92150203356908; dx=-1.1985924881567825E-6 evalInputDelta=0.0
Armijo: th(0.006732608406349637)=-71.92150203356908; dx=-1.1983473476494104E-6 evalInputDelta=0.0
WOLFE (weak): th(0.004862439404585849)=-71.92150203356908; dx=-1.1985951540659723E-6 evalInputDelta=0.0
WOLFE (weak): th(0.005797523905467743)=-71.92150203356908; dx=-1.1988003617547165E-6 evalInputDelta=0.0
Armijo: th(0.00626506615590869)=-71.92150203356908; dx=-1.1985192798976485E-6 evalInputDelta=0.0
Armijo: th(0.006031295030688217)=-71.92150203356908; dx=-1.1987289550838602E-6 evalInputDelta=0.0
Armijo: th(0.00591440946807798)=-71.92150203356908; dx=-1.1985220520603795E-6 evalInputDelta=0.0
Armijo: th(0.0058559666867728614)=-71.92150203356908; dx=-1.198636911853209E-6 evalInputDelta=0.0
Armijo: th(0.005826745296120302)=-71.92150203356908; dx=-1.1989442914415542E-6 evalInputDelta=0.0
Armijo: th(0.005812134600794022)=-71.92150203356908; dx=-1.1988324658866933E-6 evalInputDelta=0.0
Armijo: th(0.005804829253130883)=-71.92150203356908; dx=-1.1990117087040792E-6 evalInputDelta=0.0
WOLFE (weak): th(0.005801176579299313)=-71.92150203356908; dx=-1.198801739434212E-6 evalInputDelta=0.0
WOLFE (weak): th(0.005803002916215098)=-71.92150203356908; dx=-1.199121744529907E-6 evalInputDelta=0.0
WOLFE (weak): th(0.00580391608467299)=-71.92150203356908; dx=-1.1988903175308309E-6 evalInputDelta=0.0
WOLFE (weak): th(0.005804372668901936)=-71.92150203356908; dx=-1.198878285012163E-6 evalInputDelta=0.0
Armijo: th(0.005804600961016409)=-71.92150203356908; dx=-1.198808350722642E-6 evalInputDelta=0.0
Armijo: th(0.005804486814959172)=-71.92150203356908; dx=-1.19913896598685E-6 evalInputDelta=0.0
Armijo: th(0.005804429741930554)=-71.92150203356908; dx=-1.1991201057315515E-6 evalInputDelta=0.0
mu ~= nu (0.005804372668901936): th(0.0)=-71.92150203356908
Fitness changed from -71.92150203356908 to -71.92150203356908
Static Iteration Total: 168.4554; Orientation: 0.1408; Line Search: 151.4129
Iteration 1 failed. Error: -71.92150203356908
Previous Error: 0.0 -> -71.92150203356908
Retrying iteration 1
Reset training subject: 642135049029200
Adding measurement 133c77ca to history. Total: 0
LBFGS Accumulation History: 1 points
th(0)=-71.92150203356908;dx=-1.224503841361427E-6
WOLFE (weak): th(0.012505203311811642)=-71.92150203356908; dx=-1.1990935307084212E-6 evalInputDelta=0.0
WOLFE (weak): th(0.025010406623623284)=-71.92150203356908; dx=-1.1991219553260257E-6 evalInputDelta=0.0
Armijo: th(0.07503121987086986)=-71.92150203356908; dx=-1.1987374545686765E-6 evalInputDelta=0.0
Armijo: th(0.05002081324724657)=-71.92150203356908; dx=-1.1991286633544416E-6 evalInputDelta=0.0
Armijo: th(0.03751560993543493)=-71.92150203356908; dx=-1.1985964067434198E-6 evalInputDelta=0.0
Armijo: th(0.0312630082795291)=-71.92150203356908; dx=-1.1989500728820129E-6 evalInputDelta=0.0
WOLFE (weak): th(0.028136707451576193)=-71.92150203356908; dx=-1.1990121262628053E-6 evalInputDelta=0.0
Armijo: th(0.029699857865552647)=-71.92150203356908; dx=-1.1987998304885926E-6 evalInputDelta=0.0
WOLFE (weak): th(0.028918282658564422)=-71.92150203356908; dx=-1.198737313192594E-6 evalInputDelta=0.0
Armijo: th(0.029309070262058534)=-71.92150203356908; dx=-1.1989300934808592E-6 evalInputDelta=0.0
Armijo: th(0.029113676460311478)=-71.92150203356908; dx=-1.1991362870102662E-6 evalInputDelta=0.0
Armijo: th(0.02901597955943795)=-71.92150203356908; dx=-1.1982310330788838E-6 evalInputDelta=0.0
WOLFE (weak): th(0.028967131109001187)=-71.92150203356908; dx=-1.1989353491706256E-6 evalInputDelta=0.0
WOLFE (weak): th(0.02899155533421957)=-71.92150203356908; dx=-1.1987733395730896E-6 evalInputDelta=0.0
WOLFE (weak): th(0.02900376744682876)=-71.92150203356908; dx=-1.1988641853116671E-6 evalInputDelta=0.0
WOLFE (weak): th(0.029009873503133356)=-71.92150203356908; dx=-1.1986041916613044E-6 evalInputDelta=0.0
WOLFE (weak): th(0.029012926531285656)=-71.92150203356908; dx=-1.1991327251676544E-6 evalInputDelta=0.0
Armijo: th(0.029014453045361804)=-71.92150203356908; dx=-1.1987663026887585E-6 evalInputDelta=0.0
Armijo: th(0.029013689788323728)=-71.92150203356908; dx=-1.1988524125468782E-6 evalInputDelta=0.0
WOLFE (weak): th(0.029013308159804692)=-71.92150203356908; dx=-1.1990352652475507E-6 evalInputDelta=0.0
Armijo: th(0.02901349897406421)=-71.92150203356908; dx=-1.1991305469668931E-6 evalInputDelta=0.0
mu ~= nu (0.029013308159804692): th(0.0)=-71.92150203356908
Fitness changed from -71.92150203356908 to -71.92150203356908
Static Iteration Total: 145.1210; Orientation: 0.1268; Line Search: 132.5756
Iteration 2 failed. Error: -71.92150203356908
Previous Error: 0.0 -> -71.92150203356908
Optimization terminated 2
Final threshold in iteration 2: -71.92150203356908 (> -Infinity) after 313.577s (< 5400.000s)

Returns

    -71.92150203356908