Code from BasicOptimizer.scala:75 executed in 193.45 seconds (1.884 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: 911064558451800
    Reset training subject: 911068053516300
    Adding measurement 47bfda9e to history. Total: 0
    LBFGS Accumulation History: 1 points
    Constructing line search parameters: GD+Trust
    th(0)=0.6052927374839783;dx=-1.6244991033154975E-8
    Armijo: th(2.154434690031884)=0.6052927374839783; dx=-1.6233555945878048E-8 evalInputDelta=0.0
    Armijo: th(1.077217345015942)=0.6052927374839783; dx=-1.6233546440074766E-8 evalInputDelta=0.0
    Armijo: th(0.3590724483386473)=0.6052927374839783; dx=-1.6233546440074766E-8 evalInputDelta=0.0
    Armijo: th(0.08976811208466183)=0.6052927374839783; dx=-1.6233546440074766E-8 evalInputDelta=0.0
    Armijo: th(0.017953622416932366)=0.6052927374839783; dx=-1.6233546440074766E-8 evalInputDelta=0.0
    WOLFE (weak): th(0.002992270402822061)=0.6052927374839783; dx=-1.6233546440074766E-8 evalInputDelta=0.0
    Armijo: th(0.010472946409877214)=0.6052927374839783; dx=-1.6233546440074766E-8 evalInputDelta=0.0
    Armijo: th(0.006732608406349637)=0.6052927374839783; dx=-1.6233546440074766E-8 evalInputDelta=0.0
    Armijo: th(0.004862439404585849)=0.6052927374839783; dx=-1.6233546440074766E-8 evalInputDelta=0.0
    Armijo: th(0.003927354903703955)=0.6052927374839783; dx=-1.6233546440074766E-8 evalInputDelta=0.0
    Armijo: th(0.0034598126532630075)=0.6052927374839783; dx=-1.6233546440074766E-8 evalInputDelta=0.0
    WOLFE (weak): th(0.003226041528042534)=0.6052927374839783; dx=-1.6233546440074766E-8 evalInputDelta=0.0
    WOLFE (weak): th(0.0033429270906527708)=0.6052927374839783; dx=-1.6233546440074766E-8 evalInputDelta=0.0
    WOLFE (weak): th(0.003401369871957889)=0.6052927374839783; dx=-1.6233546440074766E-8 evalInputDelta=0.0
    Armijo: th(0.0034305912626104483)=0.6052927374839783; dx=-1.6233546440074766E-8 evalInputDelta=0.0
    WOLFE (weak): th(0.0034159805672841687)=0.6052927374839783; dx=-1.6233546440074766E-8 evalInputDelta=0.0
    Armijo: th(0.0034232859149473088)=0.6052927374839783; dx=-1.6233546440074766E-8 evalInputDelta=0.0
    Armijo: th(0.0034196332411157385)=0.6052927374839783; dx=-1.6233546440

...skipping 1726 bytes...

    Delta=0.0
    Armijo: th(0.018404992442285988)=0.6052927374839783; dx=-1.6233546440074766E-8 evalInputDelta=0.0
    WOLFE (weak): th(0.01656449319805739)=0.6052927374839783; dx=-1.6233546440074766E-8 evalInputDelta=0.0
    Armijo: th(0.01748474282017169)=0.6052927374839783; dx=-1.6233546440074766E-8 evalInputDelta=0.0
    WOLFE (weak): th(0.01702461800911454)=0.6052927374839783; dx=-1.6233546440074766E-8 evalInputDelta=0.0
    Armijo: th(0.017254680414643113)=0.6052927374839783; dx=-1.6233546440074766E-8 evalInputDelta=0.0
    Armijo: th(0.017139649211878827)=0.6052927374839783; dx=-1.6233546440074766E-8 evalInputDelta=0.0
    WOLFE (weak): th(0.017082133610496684)=0.6052927374839783; dx=-1.6233546440074766E-8 evalInputDelta=0.0
    Armijo: th(0.017110891411187754)=0.6052927374839783; dx=-1.6233546440074766E-8 evalInputDelta=0.0
    Armijo: th(0.017096512510842217)=0.6052927374839783; dx=-1.6233546440074766E-8 evalInputDelta=0.0
    Armijo: th(0.017089323060669452)=0.6052927374839783; dx=-1.6233546440074766E-8 evalInputDelta=0.0
    Armijo: th(0.01708572833558307)=0.6052927374839783; dx=-1.6233546440074766E-8 evalInputDelta=0.0
    WOLFE (weak): th(0.017083930973039875)=0.6052927374839783; dx=-1.6233546440074766E-8 evalInputDelta=0.0
    WOLFE (weak): th(0.017084829654311472)=0.6052927374839783; dx=-1.6233546440074766E-8 evalInputDelta=0.0
    WOLFE (weak): th(0.017085278994947273)=0.6052927374839783; dx=-1.6233546440074766E-8 evalInputDelta=0.0
    WOLFE (weak): th(0.01708550366526517)=0.6052927374839783; dx=-1.6233546440074766E-8 evalInputDelta=0.0
    WOLFE (weak): th(0.01708561600042412)=0.6052927374839783; dx=-1.6233546440074766E-8 evalInputDelta=0.0
    mu ~= nu (0.01708561600042412): th(0.0)=0.6052927374839783
    Fitness changed from 0.6052927374839783 to 0.6052927374839783
    Static Iteration Total: 87.6670; Orientation: 0.0624; Line Search: 81.1889
    Iteration 2 failed. Error: 0.6052927374839783
    Previous Error: 0.0 -> 0.6052927374839783
    Optimization terminated 2
    Final threshold in iteration 2: 0.6052927374839783 (> -Infinity) after 193.450s (< 1800.000s)
    

Returns:

    0.6052927374839783