Code from BasicOptimizer.scala:75 executed in 10532.69 seconds (155.457 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: 1452608112554300
    Reset training subject: 1452811591104500
    Adding measurement 7a725c89 to history. Total: 0
    LBFGS Accumulation History: 1 points
    Constructing line search parameters: GD+Trust
    th(0)=14.44688205420971;dx=-2.952460276967692E-7
    Armijo: th(2.154434690031884)=14.44688205420971; dx=-2.952436390281194E-7 evalInputDelta=0.0
    Armijo: th(1.077217345015942)=14.44688205420971; dx=-2.952436390371273E-7 evalInputDelta=0.0
    Armijo: th(0.3590724483386473)=14.44688205420971; dx=-2.952436390371273E-7 evalInputDelta=0.0
    Armijo: th(0.08976811208466183)=14.44688205420971; dx=-2.952436390371273E-7 evalInputDelta=0.0
    Armijo: th(0.017953622416932366)=14.44688205420971; dx=-2.952436390371273E-7 evalInputDelta=0.0
    WOLFE (weak): th(0.002992270402822061)=14.44688205420971; dx=-2.952436390371273E-7 evalInputDelta=0.0
    Armijo: th(0.010472946409877214)=14.44688205420971; dx=-2.952436390371273E-7 evalInputDelta=0.0
    Armijo: th(0.006732608406349637)=14.44688205420971; dx=-2.952436390371273E-7 evalInputDelta=0.0
    Armijo: th(0.004862439404585849)=14.44688205420971; dx=-2.952436390371273E-7 evalInputDelta=0.0
    Armijo: th(0.003927354903703955)=14.44688205420971; dx=-2.952436390371273E-7 evalInputDelta=0.0
    Armijo: th(0.0034598126532630075)=14.44688205420971; dx=-2.952436390371273E-7 evalInputDelta=0.0
    Armijo: th(0.003226041528042534)=14.44688205420971; dx=-2.952436390371273E-7 evalInputDelta=0.0
    Armijo: th(0.003109155965432297)=14.44688205420971; dx=-2.952436390371273E-7 evalInputDelta=0.0
    Armijo: th(0.003050713184127179)=14.44688205420971; dx=-2.952436390371273E-7 evalInputDelta=0.0
    Armijo: th(0.0030214917934746196)=14.44688205420971; dx=-2.952436390371273E-7 evalInputDelta=0.0
    WOLFE (weak): th(0.0030068810981483405)=14.44688205420971; dx=-2.952436390371273E-7 evalInputDelta=0.0
    Armijo: th(0.00301418644581148)=14.44688205420971; dx=-2.952436390371273E-7 evalInputDelta=0.0
    Armijo: th(0.0030105337719799103)=14.44688205420971; dx=-2.952436390371273E-7 evalInputDelta=0.0
    Armijo: th(0.00300870743506

...skipping 1614 bytes...

    .952436390371273E-7 evalInputDelta=0.0
    Armijo: th(0.01620277682346355)=14.44688205420971; dx=-2.952436390371273E-7 evalInputDelta=0.0
    WOLFE (weak): th(0.014582499141117195)=14.44688205420971; dx=-2.952436390371273E-7 evalInputDelta=0.0
    Armijo: th(0.015392637982290371)=14.44688205420971; dx=-2.952436390371273E-7 evalInputDelta=0.0
    WOLFE (weak): th(0.014987568561703784)=14.44688205420971; dx=-2.952436390371273E-7 evalInputDelta=0.0
    Armijo: th(0.015190103271997078)=14.44688205420971; dx=-2.952436390371273E-7 evalInputDelta=0.0
    Armijo: th(0.01508883591685043)=14.44688205420971; dx=-2.952436390371273E-7 evalInputDelta=0.0
    WOLFE (weak): th(0.015038202239277107)=14.44688205420971; dx=-2.952436390371273E-7 evalInputDelta=0.0
    Armijo: th(0.015063519078063768)=14.44688205420971; dx=-2.952436390371273E-7 evalInputDelta=0.0
    Armijo: th(0.015050860658670437)=14.44688205420971; dx=-2.952436390371273E-7 evalInputDelta=0.0
    Armijo: th(0.015044531448973771)=14.44688205420971; dx=-2.9524363903622395E-7 evalInputDelta=0.0
    Armijo: th(0.01504136684412544)=14.44688205420971; dx=-2.952436390371273E-7 evalInputDelta=0.0
    WOLFE (weak): th(0.015039784541701275)=14.44688205420971; dx=-2.952436390371273E-7 evalInputDelta=0.0
    WOLFE (weak): th(0.015040575692913357)=14.44688205420971; dx=-2.952436390371273E-7 evalInputDelta=0.0
    WOLFE (weak): th(0.015040971268519398)=14.44688205420971; dx=-2.952436390371273E-7 evalInputDelta=0.0
    WOLFE (weak): th(0.015041169056322419)=14.44688205420971; dx=-2.952436390371273E-7 evalInputDelta=0.0
    WOLFE (weak): th(0.01504126795022393)=14.44688205420971; dx=-2.952436390371273E-7 evalInputDelta=0.0
    mu ~= nu (0.01504126795022393): th(0.0)=14.44688205420971
    Fitness changed from 14.44688205420971 to 14.44688205420971
    Static Iteration Total: 4805.5815; Orientation: 0.6351; Line Search: 4428.2195
    Iteration 2 failed. Error: 14.44688205420971
    Previous Error: 0.0 -> 14.44688205420971
    Optimization terminated 2
    Final threshold in iteration 2: 14.44688205420971 (> -Infinity) after 10532.686s (< 7200.000s)
    

Returns:

    14.44688205420971