Code from BasicOptimizer.scala:75 executed in 58.42 seconds (1.212 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: 915252505873700
    Reset training subject: 915253590511700
    Adding measurement 711e4256 to history. Total: 0
    LBFGS Accumulation History: 1 points
    Constructing line search parameters: GD+Trust
    th(0)=0.7908048182725906;dx=-1.7473066935536184E-7
    Armijo: th(2.154434690031884)=0.7908048182725906; dx=-1.7472848415059945E-7 evalInputDelta=0.0
    Armijo: th(1.077217345015942)=0.7908048778772354; dx=-1.7472832140208564E-7 evalInputDelta=-5.9604644775390625E-8
    Armijo: th(0.3590724483386473)=0.7908048182725906; dx=-1.7472828676309673E-7 evalInputDelta=0.0
    Armijo: th(0.08976811208466183)=0.7908048182725906; dx=-1.7472828671736446E-7 evalInputDelta=0.0
    Armijo: th(0.017953622416932366)=0.7908048182725906; dx=-1.7472828671736446E-7 evalInputDelta=0.0
    Armijo: th(0.002992270402822061)=0.7908048182725906; dx=-1.7472828671736446E-7 evalInputDelta=0.0
    Armijo: th(4.2746720040315154E-4)=0.7908048182725906; dx=-1.7472828671736446E-7 evalInputDelta=0.0
    WOLFE (weak): th(5.343340005039394E-5)=0.7908048182725906; dx=-1.7472828671736446E-7 evalInputDelta=0.0
    WOLFE (weak): th(2.4045030022677274E-4)=0.7908048182725906; dx=-1.7472828671736446E-7 evalInputDelta=0.0
    Armijo: th(3.3395875031496216E-4)=0.7908048182725906; dx=-1.7472828671736446E-7 evalInputDelta=0.0
    WOLFE (weak): th(2.8720452527086743E-4)=0.7908048182725906; dx=-1.7472828671736446E-7 evalInputDelta=0.0
    WOLFE (weak): th(3.105816377929148E-4)=0.7908048182725906; dx=-1.7472828671736446E-7 evalInputDelta=0.0
    Armijo: th(3.222701940539385E-4)=0.7908048182725906; dx=-1.7472828671736446E-7 evalInputDelta=0.0
    WOLFE (weak): th(3.164259159234267E-4)=0.7908048182725906; dx=-1.7472828671736446E-7 evalInputDelta=0.0
    Armijo: th(3.1934805498868256E-4)=0.7908048182725906; dx=-1.7472828671736446E-7 evalInputDelta=0.0
    Armijo: th(3.178869854560546E-4)=0.7908048182725906; dx=-1.7472828671736446E-7 evalInputDelta=0.0
    WOLFE (weak): th(3.1715645068974065E-4)=0.7908048182725906; dx=-1.7472828671736446E-7 evalInputDelta=0.0
    WOLFE (weak): th(3.1752171807289766E-4)=0.79

...skipping 1768 bytes...

    alInputDelta=0.0
    Armijo: th(0.0017111293964893841)=0.7908048182725906; dx=-1.7472828671736446E-7 evalInputDelta=0.0
    WOLFE (weak): th(0.0015400164568404456)=0.7908048182725906; dx=-1.7472828671736446E-7 evalInputDelta=0.0
    Armijo: th(0.001625572926664915)=0.7908048182725906; dx=-1.7472828671736446E-7 evalInputDelta=0.0
    WOLFE (weak): th(0.0015827946917526803)=0.7908048182725906; dx=-1.7472828671736446E-7 evalInputDelta=0.0
    Armijo: th(0.0016041838092087975)=0.7908048182725906; dx=-1.7472828671736446E-7 evalInputDelta=0.0
    Armijo: th(0.001593489250480739)=0.7908048182725906; dx=-1.7472828671736446E-7 evalInputDelta=0.0
    WOLFE (weak): th(0.0015881419711167096)=0.7908048182725906; dx=-1.7472828671736446E-7 evalInputDelta=0.0
    Armijo: th(0.0015908156107987243)=0.7908048182725906; dx=-1.7472828671736446E-7 evalInputDelta=0.0
    Armijo: th(0.001589478790957717)=0.7908048182725906; dx=-1.7472828671736446E-7 evalInputDelta=0.0
    Armijo: th(0.0015888103810372132)=0.7908048182725906; dx=-1.7472828671736446E-7 evalInputDelta=0.0
    WOLFE (weak): th(0.0015884761760769613)=0.7908048182725906; dx=-1.7472828671736446E-7 evalInputDelta=0.0
    Armijo: th(0.0015886432785570874)=0.7908048182725906; dx=-1.7472828671736446E-7 evalInputDelta=0.0
    Armijo: th(0.0015885597273170243)=0.7908048182725906; dx=-1.7472828671736446E-7 evalInputDelta=0.0
    Armijo: th(0.0015885179516969927)=0.7908048182725906; dx=-1.7472828671736446E-7 evalInputDelta=0.0
    Armijo: th(0.001588497063886977)=0.7908048182725906; dx=-1.7472828671736446E-7 evalInputDelta=0.0
    Armijo: th(0.001588486619981969)=0.7908048182725906; dx=-1.7472828671736446E-7 evalInputDelta=0.0
    mu ~= nu (0.0015884761760769613): th(0.0)=0.7908048182725906
    Fitness changed from 0.7908048182725906 to 0.7908048182725906
    Static Iteration Total: 26.6818; Orientation: 0.0199; Line Search: 24.2582
    Iteration 2 failed. Error: 0.7908048182725906
    Previous Error: 0.0 -> 0.7908048182725906
    Optimization terminated 2
    Final threshold in iteration 2: 0.7908048182725906 (> -Infinity) after 58.416s (< 720.000s)
    

Returns:

    0.7908048182725906