Code from BasicOptimizer.scala:75 executed in 188.99 seconds (1.671 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: 915687013745900
    Reset training subject: 915690426297600
    Adding measurement cb8a3f0 to history. Total: 0
    LBFGS Accumulation History: 1 points
    Constructing line search parameters: GD+Trust
    th(0)=1.2155659049749374;dx=-6.514923241846194E-8
    Armijo: th(2.154434690031884)=1.2155659049749374; dx=-6.514896819480663E-8 evalInputDelta=0.0
    Armijo: th(1.077217345015942)=1.2155659049749374; dx=-6.514896870440616E-8 evalInputDelta=0.0
    Armijo: th(0.3590724483386473)=1.2155659049749374; dx=-6.514896854405404E-8 evalInputDelta=0.0
    Armijo: th(0.08976811208466183)=1.2155659049749374; dx=-6.514896854405404E-8 evalInputDelta=0.0
    Armijo: th(0.017953622416932366)=1.2155659049749374; dx=-6.514896854405404E-8 evalInputDelta=0.0
    Armijo: th(0.002992270402822061)=1.2155659049749374; dx=-6.514896854405404E-8 evalInputDelta=0.0
    WOLFE (weak): th(4.2746720040315154E-4)=1.2155659049749374; dx=-6.514896854405404E-8 evalInputDelta=0.0
    Armijo: th(0.0017098688016126062)=1.2155659049749374; dx=-6.514896854405404E-8 evalInputDelta=0.0
    WOLFE (weak): th(0.001068668001007879)=1.2155659049749374; dx=-6.514896854405404E-8 evalInputDelta=0.0
    WOLFE (weak): th(0.0013892684013102426)=1.2155659049749374; dx=-6.514896854405404E-8 evalInputDelta=0.0
    WOLFE (weak): th(0.0015495686014614244)=1.2155659049749374; dx=-6.514896854405404E-8 evalInputDelta=0.0
    WOLFE (weak): th(0.0016297187015370152)=1.2155659049749374; dx=-6.514896854405404E-8 evalInputDelta=0.0
    WOLFE (weak): th(0.0016697937515748108)=1.2155659049749374; dx=-6.514896854405404E-8 evalInputDelta=0.0
    WOLFE (weak): th(0.0016898312765937086)=1.2155659049749374; dx=-6.514896854405404E-8 evalInputDelta=0.0
    WOLFE (weak): th(0.0016998500391031575)=1.2155659049749374; dx=-6.514896854405404E-8 evalInputDelta=0.0
    Armijo: th(0.0017048594203578817)=1.2155659049749374; dx=-6.514896854405404E-8 evalInputDelta=0.0
    WOLFE (weak): th(0.0017023547297305196)=1.2155659049749374; dx=-6.514896854405404E-8 evalInputDelta=0.0
    WOLFE (weak): th(0.0017036070750442007)=1.2155659049749374; 

...skipping 1729 bytes...

    8 evalInputDelta=0.0
    Armijo: th(0.009178542054183652)=1.2155659049749374; dx=-6.514896854405404E-8 evalInputDelta=0.0
    WOLFE (weak): th(0.008260687848765286)=1.2155659049749374; dx=-6.514896854405404E-8 evalInputDelta=0.0
    Armijo: th(0.00871961495147447)=1.2155659049749374; dx=-6.514896854405404E-8 evalInputDelta=0.0
    WOLFE (weak): th(0.008490151400119878)=1.2155659049749374; dx=-6.514896854405404E-8 evalInputDelta=0.0
    Armijo: th(0.008604883175797173)=1.2155659049749374; dx=-6.514896854405404E-8 evalInputDelta=0.0
    Armijo: th(0.008547517287958526)=1.2155659049749374; dx=-6.514896854405404E-8 evalInputDelta=0.0
    WOLFE (weak): th(0.008518834344039203)=1.2155659049749374; dx=-6.514896854405404E-8 evalInputDelta=0.0
    Armijo: th(0.008533175815998864)=1.2155659049749374; dx=-6.514896854405404E-8 evalInputDelta=0.0
    Armijo: th(0.008526005080019033)=1.2155659049749374; dx=-6.514896854405404E-8 evalInputDelta=0.0
    Armijo: th(0.008522419712029118)=1.2155659049749374; dx=-6.514896854405404E-8 evalInputDelta=0.0
    Armijo: th(0.008520627028034161)=1.2155659049749374; dx=-6.514896854405404E-8 evalInputDelta=0.0
    WOLFE (weak): th(0.008519730686036682)=1.2155659049749374; dx=-6.514896854405404E-8 evalInputDelta=0.0
    WOLFE (weak): th(0.008520178857035422)=1.2155659049749374; dx=-6.514896854405404E-8 evalInputDelta=0.0
    WOLFE (weak): th(0.008520402942534791)=1.2155659049749374; dx=-6.514896854405404E-8 evalInputDelta=0.0
    WOLFE (weak): th(0.008520514985284475)=1.2155659049749374; dx=-6.514896854405404E-8 evalInputDelta=0.0
    WOLFE (weak): th(0.008520571006659318)=1.2155659049749374; dx=-6.514896854405404E-8 evalInputDelta=0.0
    mu ~= nu (0.008520571006659318): th(0.0)=1.2155659049749374
    Fitness changed from 1.2155659049749374 to 1.2155659049749374
    Static Iteration Total: 85.9828; Orientation: 0.0610; Line Search: 79.3859
    Iteration 2 failed. Error: 1.2155659049749374
    Previous Error: 0.0 -> 1.2155659049749374
    Optimization terminated 2
    Final threshold in iteration 2: 1.2155659049749374 (> -Infinity) after 188.989s (< 720.000s)
    

Returns:

    1.2155659049749374