Code from BasicOptimizer.scala:75 executed in 180.13 seconds (2.063 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: 919924086401900
    Reset training subject: 919927268304500
    Adding measurement 59cf45b7 to history. Total: 0
    LBFGS Accumulation History: 1 points
    Constructing line search parameters: GD+Trust
    th(0)=0.1958877146244049;dx=-2.268472305271014E-8
    Armijo: th(2.154434690031884)=0.1958877146244049; dx=-2.2487283511784065E-8 evalInputDelta=0.0
    Armijo: th(1.077217345015942)=0.1958877146244049; dx=-2.2487283986635424E-8 evalInputDelta=0.0
    Armijo: th(0.3590724483386473)=0.1958877146244049; dx=-2.248728384941055E-8 evalInputDelta=0.0
    Armijo: th(0.08976811208466183)=0.1958877146244049; dx=-2.248728384941055E-8 evalInputDelta=0.0
    Armijo: th(0.017953622416932366)=0.1958877146244049; dx=-2.248728384941055E-8 evalInputDelta=0.0
    Armijo: th(0.002992270402822061)=0.1958877146244049; dx=-2.248728384941055E-8 evalInputDelta=0.0
    WOLFE (weak): th(4.2746720040315154E-4)=0.1958877146244049; dx=-2.248728384941055E-8 evalInputDelta=0.0
    Armijo: th(0.0017098688016126062)=0.1958877146244049; dx=-2.248728384941055E-8 evalInputDelta=0.0
    Armijo: th(0.001068668001007879)=0.1958877146244049; dx=-2.248728384941055E-8 evalInputDelta=0.0
    Armijo: th(7.480676007055152E-4)=0.1958877146244049; dx=-2.248728384941055E-8 evalInputDelta=0.0
    WOLFE (weak): th(5.877674005543334E-4)=0.1958877146244049; dx=-2.248728384941055E-8 evalInputDelta=0.0
    Armijo: th(6.679175006299243E-4)=0.1958877146244049; dx=-2.248728384941055E-8 evalInputDelta=0.0
    Armijo: th(6.278424505921289E-4)=0.1958877146244049; dx=-2.248728384941055E-8 evalInputDelta=0.0
    WOLFE (weak): th(6.078049255732311E-4)=0.1958877146244049; dx=-2.248728384941055E-8 evalInputDelta=0.0
    Armijo: th(6.1782368808268E-4)=0.1958877146244049; dx=-2.248728384941055E-8 evalInputDelta=0.0
    Armijo: th(6.128143068279556E-4)=0.1958877146244049; dx=-2.248728384941055E-8 evalInputDelta=0.0
    WOLFE (weak): th(6.103096162005933E-4)=0.1958877146244049; dx=-2.248728384941055E-8 evalInputDelta=0.0
    WOLFE (weak): th(6.115619615142745E-4)=0.1958877146244049; dx=-2.248728384941055E-8 evalInputDelt

...skipping 1797 bytes...

    a=0.0
    Armijo: th(0.0032950455777880166)=0.1958877146244049; dx=-2.248728384941055E-8 evalInputDelta=0.0
    WOLFE (weak): th(0.002965541020009215)=0.1958877146244049; dx=-2.248728384941055E-8 evalInputDelta=0.0
    Armijo: th(0.003130293298898616)=0.1958877146244049; dx=-2.248728384941055E-8 evalInputDelta=0.0
    WOLFE (weak): th(0.0030479171594539156)=0.1958877146244049; dx=-2.248728384941055E-8 evalInputDelta=0.0
    Armijo: th(0.0030891052291762656)=0.1958877146244049; dx=-2.248728384941055E-8 evalInputDelta=0.0
    Armijo: th(0.0030685111943150904)=0.1958877146244049; dx=-2.248728384941055E-8 evalInputDelta=0.0
    WOLFE (weak): th(0.0030582141768845028)=0.1958877146244049; dx=-2.248728384941055E-8 evalInputDelta=0.0
    Armijo: th(0.0030633626855997966)=0.1958877146244049; dx=-2.248728384941055E-8 evalInputDelta=0.0
    Armijo: th(0.0030607884312421497)=0.1958877146244049; dx=-2.248728384941055E-8 evalInputDelta=0.0
    Armijo: th(0.0030595013040633262)=0.1958877146244049; dx=-2.248728384941055E-8 evalInputDelta=0.0
    Armijo: th(0.0030588577404739147)=0.1958877146244049; dx=-2.248728384941055E-8 evalInputDelta=0.0
    WOLFE (weak): th(0.0030585359586792087)=0.1958877146244049; dx=-2.248728384941055E-8 evalInputDelta=0.0
    WOLFE (weak): th(0.0030586968495765615)=0.1958877146244049; dx=-2.248728384941055E-8 evalInputDelta=0.0
    WOLFE (weak): th(0.003058777295025238)=0.1958877146244049; dx=-2.248728384941055E-8 evalInputDelta=0.0
    WOLFE (weak): th(0.0030588175177495764)=0.1958877146244049; dx=-2.248728384941055E-8 evalInputDelta=0.0
    WOLFE (weak): th(0.0030588376291117454)=0.1958877146244049; dx=-2.248728384941055E-8 evalInputDelta=0.0
    mu ~= nu (0.0030588376291117454): th(0.0)=0.1958877146244049
    Fitness changed from 0.1958877146244049 to 0.1958877146244049
    Static Iteration Total: 80.0259; Orientation: 0.0681; Line Search: 73.7450
    Iteration 2 failed. Error: 0.1958877146244049
    Previous Error: 0.0 -> 0.1958877146244049
    Optimization terminated 2
    Final threshold in iteration 2: 0.1958877146244049 (> -Infinity) after 180.128s (< 720.000s)
    

Returns:

    0.1958877146244049