BasicOptimizer.scala:89 executed in 39.42 seconds (0.394 gc):

    val lineSearchInstance: LineSearchStrategy = lineSearchFactory
    val trainer = new IterativeTrainer(trainable)
    trainer.setOrientation(orientation())
    trainer.setMonitor(new TrainingMonitor() {
      override def clear(): Unit = trainingMonitor.clear()
  
      override def log(msg: String): Unit = {
        trainingMonitor.log(msg)
        BasicOptimizer.this.log(msg)
      }
  
      override def onStepFail(currentPoint: Step): Boolean = {
        BasicOptimizer.this.onStepFail(trainable.addRef().asInstanceOf[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.addRef().asInstanceOf[Trainable], currentPoint)
        trainingMonitor.onStepComplete(currentPoint)
        super.onStepComplete(currentPoint)
      }
    })
    trainer.setTimeout(trainingMinutes, TimeUnit.MINUTES)
    trainer.setMaxIterations(trainingIterations)
    trainer.setLineSearchFactory((_: CharSequence) => lineSearchInstance)
    trainer.setTerminateThreshold(java.lang.Double.NEGATIVE_INFINITY)
    val result = trainer.run.asInstanceOf[lang.Double]
    trainer.freeRef()
    result
Logging 
Reset training subject: 114733130575100
Reset training subject: 114735938090200
Adding measurement 6489cc75 to history. Total: 0
LBFGS Accumulation History: 1 points
Constructing line search parameters: GD+Trust
th(0)=-28.624221578123734;dx=-1.2986813656888525E-6
Armijo: th(2.154434690031884)=-28.624221578123734; dx=-9.621164936826836E-7 evalInputDelta=0.0
Armijo: th(1.077217345015942)=-28.624221578123734; dx=-9.621623178040332E-7 evalInputDelta=0.0
Armijo: th(0.3590724483386473)=-28.624221578123734; dx=-9.62113812770295E-7 evalInputDelta=0.0
Armijo: th(0.08976811208466183)=-28.624221578123734; dx=-9.61565858126719E-7 evalInputDelta=0.0
Armijo: th(0.017953622416932366)=-28.624221578123734; dx=-9.620900590880894E-7 evalInputDelta=0.0
Armijo: th(0.002992270402822061)=-28.624221578123734; dx=-9.614919083413446E-7 evalInputDelta=0.0
END: th(4.2746720040315154E-4)=-28.624221578123734; dx=-9.620268402718046E-7 evalInputDelta=0.0
Fitness changed from -28.624221578123734 to -28.624221578123734
Static Iteration Total: 28.9537; Orientation: 0.0676; Line Search: 21.0204
Iteration 1 failed. Error: -28.624221578123734
Previous Error: 0.0 -> -28.624221578123734
Retrying iteration 1
Reset training subject: 114762084425200
Adding measurement 26948ea0 to history. Total: 0
LBFGS Accumulation History: 1 points
th(0)=-28.624221578123734;dx=-1.2971399243403952E-6
END: th(9.20950165399361E-4)=-28.624221578123734; dx=-9.616533766723895E-7 evalInputDelta=0.0
Fitness changed from -28.624221578123734 to -28.624221578123734
Static Iteration Total: 10.4625; Orientation: 0.0626; Line Search: 5.3475
Iteration 2 failed. Error: -28.624221578123734
Previous Error: 0.0 -> -28.624221578123734
Optimization terminated 2
Final threshold in iteration 2: -28.624221578123734 (> -Infinity) after 39.416s (< 5400.000s)

Returns

    -28.624221578123734