Code from BasicOptimizer.scala:88 executed in 636.99 seconds (11.982 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
Reset training subject: 4111606085236
Reset training subject: 4113702806328
Adding measurement 169a2e07 to history. Total: 0
LBFGS Accumulation History: 1 points
Constructing line search parameters: GD+Trust
th(0)=3.3078661113977432;dx=-2.398122300646646E-7
New Minimum: 3.3078661113977432 > 3.3078655302524567
WOLFE (weak): th(2.154434690031884)=3.3078655302524567; dx=-2.3960532180962573E-7 evalInputDelta=5.811452865600586E-7
New Minimum: 3.3078655302524567 > 3.307864770293236
WOLFE (weak): th(4.308869380063768)=3.307864770293236; dx=-2.394523684417017E-7 evalInputDelta=1.341104507446289E-6
New Minimum: 3.307864770293236 > 3.307862162590027
WOLFE (weak): th(12.926608140191302)=3.307862162590027; dx=-2.395957134021268E-7 evalInputDelta=3.948807716369629E-6
New Minimum: 3.307862162590027 > 3.307850182056427
WOLFE (weak): th(51.70643256076521)=3.307850182056427; dx=-2.3960891052566275E-7 evalInputDelta=1.5929341316223145E-5
New Minimum: 3.307850182056427 > 3.307785138487816
WOLFE (weak): th(258.53216280382605)=3.307785138487816; dx=-2.393775127888034E-7 evalInputDelta=8.097290992736816E-5
New Minimum: 3.307785138487816 > 3.3073792457580566
WOLFE (weak): th(1551.1929768229563)=3.3073792457580566; dx=-2.394756192459156E-7 evalInputDelta=4.8686563968658447E-4
New Minimum: 3.3073792457580566 > 3.3044580668210983
WOLFE (weak): th(10858.350837760694)=3.3044580668210983; dx=-2.39521793649645E-7 evalInputDelta=0.0034080445766448975
New Minimum: 3.3044580668210983 > 3.280591234564781
WOLFE (weak): th(86866.80670208555)=3.280591234564781; dx=-2.388874555062269E-7 evalInputDelta=0.027274876832962036
New Minimum: 3.280591234564781 > 3.0637246668338776
WOLFE (weak): th(781801.26031877)=3.0637246668338776; dx=-2.312628758289036E-7 evalInputDelta=0.24414144456386566
New Minimum: 3.0637246668338776 > 1.6241791993379593
END: th(7818012.6031877)=1.6241791993379593; dx=-1.1711396574041764E-7 evalInputDelta=1.683686912059784
Fitness changed from 3.3078661113977432 to 1.6241791993379593
Iteration 1 complete. Error: 1.6241791993379593 Tot
...skipping 40442 bytes...
2697.509737869)=-1.8667872697114944; dx=-3.2126421796948E-9 evalInputDelta=-6.92903995513916E-6
Armijo: th(3113508.4334392194)=-1.8667917773127556; dx=-3.2076228380865554E-9 evalInputDelta=-2.421438694000244E-6
Armijo: th(3078913.895289895)=-1.8667940646409988; dx=-3.216921513778856E-9 evalInputDelta=-1.341104507446289E-7
WOLFE (weak): th(3061616.6262152325)=-1.8667950853705406; dx=-3.216721355511709E-9 evalInputDelta=8.866190910339355E-7
WOLFE (weak): th(3070265.260752564)=-1.8667946308851242; dx=-3.217994219525366E-9 evalInputDelta=4.3213367462158203E-7
WOLFE (weak): th(3074589.5780212292)=-1.8667943179607391; dx=-3.2168745924137216E-9 evalInputDelta=1.1920928955078125E-7
WOLFE (weak): th(3076751.736655562)=-1.8667942583560944; dx=-3.2170482561521455E-9 evalInputDelta=5.9604644775390625E-8
Armijo: th(3077832.8159727287)=-1.866794154047966; dx=-3.2190464236389108E-9 evalInputDelta=-4.470348358154297E-8
Armijo: th(3077292.2763141454)=-1.8667941763997078; dx=-3.214957563380842E-9 evalInputDelta=-2.2351741790771484E-8
Armijo: th(3077022.006484854)=-1.8667941987514496; dx=-3.2183058382648484E-9 evalInputDelta=0.0
WOLFE (weak): th(3076886.871570208)=-1.8667942807078362; dx=-3.220628634314901E-9 evalInputDelta=8.195638656616211E-8
Armijo: th(3076954.439027531)=-1.8667941838502884; dx=-3.195111662429459E-9 evalInputDelta=-1.4901161193847656E-8
Armijo: th(3076920.6552988696)=-1.8667941838502884; dx=-3.2185498159054475E-9 evalInputDelta=-1.4901161193847656E-8
WOLFE (weak): th(3076903.7634345386)=-1.866794228553772; dx=-3.2135836457262278E-9 evalInputDelta=2.9802322387695312E-8
mu ~= nu (3076903.7634345386): th(1107025.2207783891)=-1.8668387234210968
Fitness changed from -1.8667941987514496 to -1.8668387234210968
Iteration 30 complete. Error: -1.8668387234210968 Total: 55.0841; Orientation: 0.3055; Line Search: 51.8282
<a id="p-21"></a>Iteration 30
<a id="p-20"></a>
Final threshold in iteration 31: -1.8668387234210968 (> -Infinity) after 636.985s (< 3600.000s)
-1.8668387234210968