BasicOptimizer.scala:89 executed in 87.37 seconds (1.331 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: 642773514578600
Reset training subject: 642779504607400
Adding measurement 6e4bf6e2 to history. Total: 0
LBFGS Accumulation History: 1 points
Constructing line search parameters: GD+Trust
th(0)=-42.93506583628906;dx=-1.6383572356151643E-6
Armijo: th(2.154434690031884)=-42.93506583628906; dx=-1.4209746077565905E-6 evalInputDelta=0.0
Armijo: th(1.077217345015942)=-42.93506583628906; dx=-1.4216427005485656E-6 evalInputDelta=0.0
Armijo: th(0.3590724483386473)=-42.93506407718493; dx=-1.4207920006558178E-6 evalInputDelta=-1.7591041299169774E-6
Armijo: th(0.08976811208466183)=-42.93506583628906; dx=-1.4205607606031565E-6 evalInputDelta=0.0
Armijo: th(0.017953622416932366)=-42.93506583628906; dx=-1.4199705339652803E-6 evalInputDelta=0.0
Armijo: th(0.002992270402822061)=-42.93506583628906; dx=-1.4211266120589425E-6 evalInputDelta=0.0
END: th(4.2746720040315154E-4)=-42.93506583628906; dx=-1.4213160474923505E-6 evalInputDelta=0.0
Fitness changed from -42.93506583628906 to -42.93506583628906
Static Iteration Total: 64.1598; Orientation: 0.1411; Line Search: 46.6994
Iteration 1 failed. Error: -42.93506583628906
Previous Error: 0.0 -> -42.93506583628906
Retrying iteration 1
Reset training subject: 642837674523700
Adding measurement 7056e1c1 to history. Total: 0
LBFGS Accumulation History: 1 points
th(0)=-42.93506583628906;dx=-1.6381779600650813E-6
END: th(9.20950165399361E-4)=-42.93506583628906; dx=-1.4213928475343067E-6 evalInputDelta=0.0
Fitness changed from -42.93506583628906 to -42.93506583628906
Static Iteration Total: 23.2091; Orientation: 0.1249; Line Search: 11.7310
Iteration 2 failed. Error: -42.93506583628906
Previous Error: 0.0 -> -42.93506583628906
Optimization terminated 2
Final threshold in iteration 2: -42.93506583628906 (> -Infinity) after 87.369s (< 5400.000s)

Returns

    -42.93506583628906