Code from BasicOptimizer.scala:75 executed in 185.69 seconds (2.017 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: 913719426090800
    Reset training subject: 913722753333500
    Adding measurement 33ed4527 to history. Total: 0
    LBFGS Accumulation History: 1 points
    Constructing line search parameters: GD+Trust
    th(0)=1.1555031538009644;dx=-5.781606689035842E-8
    Armijo: th(2.154434690031884)=1.1555031538009644; dx=-5.781484484387835E-8 evalInputDelta=0.0
    Armijo: th(1.077217345015942)=1.1555031538009644; dx=-5.7814845564264556E-8 evalInputDelta=0.0
    Armijo: th(0.3590724483386473)=1.1555031538009644; dx=-5.7814845242405615E-8 evalInputDelta=0.0
    Armijo: th(0.08976811208466183)=1.1555031538009644; dx=-5.7814845242405615E-8 evalInputDelta=0.0
    Armijo: th(0.017953622416932366)=1.1555031538009644; dx=-5.7814845242405615E-8 evalInputDelta=0.0
    Armijo: th(0.002992270402822061)=1.1555031538009644; dx=-5.7814845242405615E-8 evalInputDelta=0.0
    WOLFE (weak): th(4.2746720040315154E-4)=1.1555031538009644; dx=-5.7814845242405615E-8 evalInputDelta=0.0
    WOLFE (weak): th(0.0017098688016126062)=1.1555031538009644; dx=-5.7814845242405615E-8 evalInputDelta=0.0
    Armijo: th(0.0023510696022173336)=1.1555031538009644; dx=-5.7814845242405615E-8 evalInputDelta=0.0
    Armijo: th(0.00203046920191497)=1.1555031538009644; dx=-5.7814845242405615E-8 evalInputDelta=0.0
    WOLFE (weak): th(0.001870169001763788)=1.1555031538009644; dx=-5.7814845242405615E-8 evalInputDelta=0.0
    Armijo: th(0.001950319101839379)=1.1555031538009644; dx=-5.7814845242405615E-8 evalInputDelta=0.0
    WOLFE (weak): th(0.0019102440518015836)=1.1555031538009644; dx=-5.7814845242405615E-8 evalInputDelta=0.0
    Armijo: th(0.0019302815768204814)=1.1555031538009644; dx=-5.7814845242405615E-8 evalInputDelta=0.0
    WOLFE (weak): th(0.0019202628143110325)=1.1555031538009644; dx=-5.7814845242405615E-8 evalInputDelta=0.0
    Armijo: th(0.001925272195565757)=1.1555031538009644; dx=-5.7814845242405615E-8 evalInputDelta=0.0
    Armijo: th(0.0019227675049383946)=1.1555031538009644; dx=-5.7814845242405615E-8 evalInputDelta=0.0
    Armijo: th(0.0019215151596247136)=1.1555031538009644; dx=-5.78148452424

...skipping 1716 bytes...

    ta=0.0
    Armijo: th(0.010342728401420438)=1.1555031538009644; dx=-5.7814845242405615E-8 evalInputDelta=0.0
    WOLFE (weak): th(0.009308455561278394)=1.1555031538009644; dx=-5.7814845242405615E-8 evalInputDelta=0.0
    Armijo: th(0.009825591981349416)=1.1555031538009644; dx=-5.7814845242405615E-8 evalInputDelta=0.0
    WOLFE (weak): th(0.009567023771313906)=1.1555031538009644; dx=-5.7814845242405615E-8 evalInputDelta=0.0
    Armijo: th(0.009696307876331661)=1.1555031538009644; dx=-5.7814845242405615E-8 evalInputDelta=0.0
    Armijo: th(0.009631665823822784)=1.1555031538009644; dx=-5.7814845242405615E-8 evalInputDelta=0.0
    WOLFE (weak): th(0.009599344797568344)=1.1555031538009644; dx=-5.7814845242405615E-8 evalInputDelta=0.0
    Armijo: th(0.009615505310695563)=1.1555031538009644; dx=-5.7814845242405615E-8 evalInputDelta=0.0
    Armijo: th(0.009607425054131953)=1.1555031538009644; dx=-5.7814845242405615E-8 evalInputDelta=0.0
    Armijo: th(0.00960338492585015)=1.1555031538009644; dx=-5.7814845242405615E-8 evalInputDelta=0.0
    Armijo: th(0.009601364861709247)=1.1555031538009644; dx=-5.7814845242405615E-8 evalInputDelta=0.0
    WOLFE (weak): th(0.009600354829638795)=1.1555031538009644; dx=-5.7814845242405615E-8 evalInputDelta=0.0
    WOLFE (weak): th(0.00960085984567402)=1.1555031538009644; dx=-5.7814845242405615E-8 evalInputDelta=0.0
    WOLFE (weak): th(0.009601112353691633)=1.1555031538009644; dx=-5.7814845242405615E-8 evalInputDelta=0.0
    WOLFE (weak): th(0.00960123860770044)=1.1555031538009644; dx=-5.7814845242405615E-8 evalInputDelta=0.0
    WOLFE (weak): th(0.009601301734704843)=1.1555031538009644; dx=-5.7814845242405615E-8 evalInputDelta=0.0
    mu ~= nu (0.009601301734704843): th(0.0)=1.1555031538009644
    Fitness changed from 1.1555031538009644 to 1.1555031538009644
    Static Iteration Total: 84.3046; Orientation: 0.0611; Line Search: 77.9414
    Iteration 2 failed. Error: 1.1555031538009644
    Previous Error: 0.0 -> 1.1555031538009644
    Optimization terminated 2
    Final threshold in iteration 2: 1.1555031538009644 (> -Infinity) after 185.688s (< 720.000s)
    

Returns:

    1.1555031538009644