Code from BasicOptimizer.scala:75 executed in 168.94 seconds (2.025 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: 917742784013400
    Reset training subject: 917745795010000
    Adding measurement 614805a5 to history. Total: 0
    LBFGS Accumulation History: 1 points
    Constructing line search parameters: GD+Trust
    th(0)=0.6058425903320312;dx=-3.563971343993236E-8
    Armijo: th(2.154434690031884)=0.6058425903320312; dx=-3.553117266117685E-8 evalInputDelta=0.0
    Armijo: th(1.077217345015942)=0.6058425903320312; dx=-3.553117304793405E-8 evalInputDelta=0.0
    Armijo: th(0.3590724483386473)=0.6058425903320312; dx=-3.553117286469476E-8 evalInputDelta=0.0
    Armijo: th(0.08976811208466183)=0.6058425903320312; dx=-3.553117286469476E-8 evalInputDelta=0.0
    Armijo: th(0.017953622416932366)=0.6058425903320312; dx=-3.553117286469476E-8 evalInputDelta=0.0
    Armijo: th(0.002992270402822061)=0.6058425903320312; dx=-3.553117286469476E-8 evalInputDelta=0.0
    WOLFE (weak): th(4.2746720040315154E-4)=0.6058425903320312; dx=-3.553117286469476E-8 evalInputDelta=0.0
    Armijo: th(0.0017098688016126062)=0.6058425903320312; dx=-3.553117286469476E-8 evalInputDelta=0.0
    WOLFE (weak): th(0.001068668001007879)=0.6058425903320312; dx=-3.553117286469476E-8 evalInputDelta=0.0
    WOLFE (weak): th(0.0013892684013102426)=0.6058425903320312; dx=-3.553117286469476E-8 evalInputDelta=0.0
    WOLFE (weak): th(0.0015495686014614244)=0.6058425903320312; dx=-3.553117286469476E-8 evalInputDelta=0.0
    Armijo: th(0.0016297187015370152)=0.6058425903320312; dx=-3.553117286469476E-8 evalInputDelta=0.0
    Armijo: th(0.0015896436514992198)=0.6058425903320312; dx=-3.553117286469476E-8 evalInputDelta=0.0
    Armijo: th(0.0015696061264803222)=0.6058425903320312; dx=-3.553117286469476E-8 evalInputDelta=0.0
    Armijo: th(0.0015595873639708733)=0.6058425903320312; dx=-3.553117286469476E-8 evalInputDelta=0.0
    WOLFE (weak): th(0.0015545779827161488)=0.6058425903320312; dx=-3.553117286469476E-8 evalInputDelta=0.0
    WOLFE (weak): th(0.0015570826733435112)=0.6058425903320312; dx=-3.553117286469476E-8 evalInputDelta=0.0
    Armijo: th(0.0015583350186571922)=0.6058425903320312; dx=-3.553117286469476E-

...skipping 1704 bytes...

    8 evalInputDelta=0.0
    Armijo: th(0.008389190827709822)=0.6058425903320312; dx=-3.553117286469476E-8 evalInputDelta=0.0
    WOLFE (weak): th(0.00755027174493884)=0.6058425903320312; dx=-3.553117286469476E-8 evalInputDelta=0.0
    Armijo: th(0.007969731286324331)=0.6058425903320312; dx=-3.553117286469476E-8 evalInputDelta=0.0
    WOLFE (weak): th(0.007760001515631585)=0.6058425903320312; dx=-3.553117286469476E-8 evalInputDelta=0.0
    Armijo: th(0.007864866400977957)=0.6058425903320312; dx=-3.553117286469476E-8 evalInputDelta=0.0
    Armijo: th(0.007812433958304771)=0.6058425903320312; dx=-3.553117286469476E-8 evalInputDelta=0.0
    WOLFE (weak): th(0.007786217736968178)=0.6058425903320312; dx=-3.553117286469476E-8 evalInputDelta=0.0
    Armijo: th(0.007799325847636474)=0.6058425903320312; dx=-3.553117286469476E-8 evalInputDelta=0.0
    Armijo: th(0.007792771792302327)=0.6058425903320312; dx=-3.553117286469476E-8 evalInputDelta=0.0
    Armijo: th(0.007789494764635252)=0.6058425903320312; dx=-3.553117286469476E-8 evalInputDelta=0.0
    Armijo: th(0.0077878562508017155)=0.6058425903320312; dx=-3.553117286469476E-8 evalInputDelta=0.0
    WOLFE (weak): th(0.007787036993884947)=0.6058425903320312; dx=-3.553117286469476E-8 evalInputDelta=0.0
    WOLFE (weak): th(0.007787446622343331)=0.6058425903320312; dx=-3.553117286469476E-8 evalInputDelta=0.0
    WOLFE (weak): th(0.007787651436572523)=0.6058425903320312; dx=-3.553117286469476E-8 evalInputDelta=0.0
    WOLFE (weak): th(0.00778775384368712)=0.6058425903320312; dx=-3.553117286469476E-8 evalInputDelta=0.0
    WOLFE (weak): th(0.007787805047244418)=0.6058425903320312; dx=-3.553117286469476E-8 evalInputDelta=0.0
    mu ~= nu (0.007787805047244418): th(0.0)=0.6058425903320312
    Fitness changed from 0.6058425903320312 to 0.6058425903320312
    Static Iteration Total: 76.2853; Orientation: 0.0625; Line Search: 70.4053
    Iteration 2 failed. Error: 0.6058425903320312
    Previous Error: 0.0 -> 0.6058425903320312
    Optimization terminated 2
    Final threshold in iteration 2: 0.6058425903320312 (> -Infinity) after 168.938s (< 720.000s)
    

Returns:

    0.6058425903320312