Code from BasicOptimizer.scala:75 executed in 7381.25 seconds (128.533 gc):

    val lineSearchInstance: LineSearchStrategy = lineSearchFactory
    IterativeTrainer.wrap(trainable)
      .setOrientation(orientation())
      .setMonitor(new TrainingMonitor() {
        override def clear(): Unit = trainingMonitor.clear()
  
        override def log(msg: String): Unit = trainingMonitor.log(msg)
  
        override def onStepFail(currentPoint: Step): Boolean = {
          BasicOptimizer.this.onStepFail(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, currentPoint)
          trainingMonitor.onStepComplete(currentPoint)
          super.onStepComplete(currentPoint)
        }
      })
      .setTimeout(trainingMinutes, TimeUnit.MINUTES)
      .setMaxIterations(trainingIterations)
      .setLineSearchFactory((_: CharSequence) => lineSearchInstance)
      .setTerminateThreshold(java.lang.Double.NEGATIVE_INFINITY)
      .runAndFree
      .asInstanceOf[lang.Double]

Logging:

    Reset training subject: 1518881916186200
    Reset training subject: 1519013816811800
    Adding measurement 5afd2f4e to history. Total: 0
    LBFGS Accumulation History: 1 points
    Constructing line search parameters: GD+Trust
    th(0)=14.61162660785282;dx=-2.157690298292462E-7
    Armijo: th(2.154434690031884)=14.61162660785282; dx=-2.1574348427560711E-7 evalInputDelta=0.0
    Armijo: th(1.077217345015942)=14.61162660785282; dx=-2.1574348427591488E-7 evalInputDelta=0.0
    Armijo: th(0.3590724483386473)=14.61162660785282; dx=-2.1574348427591488E-7 evalInputDelta=0.0
    Armijo: th(0.08976811208466183)=14.61162660785282; dx=-2.1574348427591488E-7 evalInputDelta=0.0
    Armijo: th(0.017953622416932366)=14.61162660785282; dx=-2.1574348427591488E-7 evalInputDelta=0.0
    WOLFE (weak): th(0.002992270402822061)=14.61162660785282; dx=-2.1574348427591488E-7 evalInputDelta=0.0
    Armijo: th(0.010472946409877214)=14.61162660785282; dx=-2.1574348427591488E-7 evalInputDelta=0.0
    Armijo: th(0.006732608406349637)=14.61162660785282; dx=-2.1574348427591488E-7 evalInputDelta=0.0
    Armijo: th(0.004862439404585849)=14.61162660785282; dx=-2.1574348427591488E-7 evalInputDelta=0.0
    WOLFE (weak): th(0.003927354903703955)=14.61162660785282; dx=-2.1574348427591488E-7 evalInputDelta=0.0
    Armijo: th(0.004394897154144902)=14.61162660785282; dx=-2.1574348427591488E-7 evalInputDelta=0.0
    Armijo: th(0.004161126028924428)=14.61162660785282; dx=-2.1574348427591488E-7 evalInputDelta=0.0
    WOLFE (weak): th(0.004044240466314191)=14.61162660785282; dx=-2.1574348427591488E-7 evalInputDelta=0.0
    WOLFE (weak): th(0.00410268324761931)=14.61162660785282; dx=-2.1574348427591488E-7 evalInputDelta=0.0
    Armijo: th(0.004131904638271869)=14.61162660785282; dx=-2.1574348427591488E-7 evalInputDelta=0.0
    Armijo: th(0.004117293942945589)=14.61162660785282; dx=-2.1574348427591488E-7 evalInputDelta=0.0
    WOLFE (weak): th(0.004109988595282449)=14.61162660785282; dx=-2.1574348427591488E-7 evalInputDelta=0.0
    WOLFE (weak): th(0.004113641269114019)=14.61162660785282; dx=-2.1574348427591488E-7 evalInput

...skipping 1688 bytes...

    1488E-7 evalInputDelta=0.0
    Armijo: th(0.022170953294630164)=14.61162660785282; dx=-2.1574348427591488E-7 evalInputDelta=0.0
    WOLFE (weak): th(0.019953857965167146)=14.61162660785282; dx=-2.1574348427591488E-7 evalInputDelta=0.0
    Armijo: th(0.021062405629898653)=14.61162660785282; dx=-2.1574348427591488E-7 evalInputDelta=0.0
    WOLFE (weak): th(0.0205081317975329)=14.61162660785282; dx=-2.1574348427591488E-7 evalInputDelta=0.0
    Armijo: th(0.020785268713715777)=14.61162660785282; dx=-2.1574348427591488E-7 evalInputDelta=0.0
    Armijo: th(0.020646700255624338)=14.61162660785282; dx=-2.1574348427591488E-7 evalInputDelta=0.0
    WOLFE (weak): th(0.02057741602657862)=14.61162660785282; dx=-2.1574348427591488E-7 evalInputDelta=0.0
    Armijo: th(0.02061205814110148)=14.61162660785282; dx=-2.1574348427591488E-7 evalInputDelta=0.0
    Armijo: th(0.020594737083840048)=14.61162660785282; dx=-2.1574348427591488E-7 evalInputDelta=0.0
    Armijo: th(0.02058607655520933)=14.61162660785282; dx=-2.1574348427591488E-7 evalInputDelta=0.0
    Armijo: th(0.020581746290893974)=14.61162660785282; dx=-2.1574348427591488E-7 evalInputDelta=0.0
    WOLFE (weak): th(0.020579581158736295)=14.61162660785282; dx=-2.1574348427591488E-7 evalInputDelta=0.0
    WOLFE (weak): th(0.020580663724815134)=14.61162660785282; dx=-2.1574348427591488E-7 evalInputDelta=0.0
    WOLFE (weak): th(0.020581205007854556)=14.61162660785282; dx=-2.1574348427591488E-7 evalInputDelta=0.0
    WOLFE (weak): th(0.020581475649374265)=14.61162660785282; dx=-2.1574348427591488E-7 evalInputDelta=0.0
    WOLFE (weak): th(0.02058161097013412)=14.61162660785282; dx=-2.1574348427591488E-7 evalInputDelta=0.0
    mu ~= nu (0.02058161097013412): th(0.0)=14.61162660785282
    Fitness changed from 14.61162660785282 to 14.61162660785282
    Static Iteration Total: 3344.5404; Orientation: 0.6351; Line Search: 3078.4417
    Iteration 2 failed. Error: 14.61162660785282
    Previous Error: 0.0 -> 14.61162660785282
    Optimization terminated 2
    Final threshold in iteration 2: 14.61162660785282 (> -Infinity) after 7381.250s (< 7200.000s)
    

Returns:

    14.61162660785282