BasicOptimizer.scala:89 executed in 34.97 seconds (0.568 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: 42768464177100
Reset training subject: 42770826002500
Adding measurement 5315d76a to history. Total: 0
LBFGS Accumulation History: 1 points
Constructing line search parameters: GD+Trust
th(0)=-49.338226599734014;dx=-1.677106216856115E-6
Armijo: th(2.154434690031884)=-49.338226599734014; dx=-1.295181620939432E-6 evalInputDelta=0.0
Armijo: th(1.077217345015942)=-49.338226599734014; dx=-1.2945434460905147E-6 evalInputDelta=0.0
Armijo: th(0.3590724483386473)=-49.33822482723546; dx=-1.2948556443128166E-6 evalInputDelta=-1.7724985568179363E-6
Armijo: th(0.08976811208466183)=-49.33822482723546; dx=-1.2951746980374522E-6 evalInputDelta=-1.7724985568179363E-6
Armijo: th(0.017953622416932366)=-49.338226599734014; dx=-1.2939966945172533E-6 evalInputDelta=0.0
Armijo: th(0.002992270402822061)=-49.338226599734014; dx=-1.2943957368304724E-6 evalInputDelta=0.0
END: th(4.2746720040315154E-4)=-49.338226599734014; dx=-1.2950468511214384E-6 evalInputDelta=0.0
Fitness changed from -49.338226599734014 to -49.338226599734014
Static Iteration Total: 25.3121; Orientation: 0.0627; Line Search: 18.3960
Iteration 1 failed. Error: -49.338226599734014
Previous Error: 0.0 -> -49.338226599734014
Retrying iteration 1
Reset training subject: 42793776464900
Adding measurement 45fe5d95 to history. Total: 0
LBFGS Accumulation History: 1 points
th(0)=-49.338226599734014;dx=-1.6754019359208316E-6
END: th(9.20950165399361E-4)=-49.338226599734014; dx=-1.2947660286883075E-6 evalInputDelta=0.0
Fitness changed from -49.338226599734014 to -49.338226599734014
Static Iteration Total: 9.6572; Orientation: 0.0682; Line Search: 4.7730
Iteration 2 failed. Error: -49.338226599734014
Previous Error: 0.0 -> -49.338226599734014
Optimization terminated 2
Final threshold in iteration 2: -49.338226599734014 (> -Infinity) after 34.970s (< 5400.000s)

Returns

    -49.338226599734014