Code from BasicOptimizer.scala:75 executed in 119.35 seconds (2.803 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]
Reset training subject: 924548964099200
Reset training subject: 924550137888000
Adding measurement 32081bce to history. Total: 0
LBFGS Accumulation History: 1 points
Constructing line search parameters: GD+Trust
th(0)=2.5561771243810654;dx=-2.3419830064770995E-6
New Minimum: 2.5561771243810654 > 2.556176394224167
WOLFE (weak): th(2.154434690031884)=2.556176394224167; dx=-2.3419918225295823E-6 evalInputDelta=7.301568984985352E-7
New Minimum: 2.556176394224167 > 2.5561761520802975
WOLFE (weak): th(4.308869380063768)=2.5561761520802975; dx=-2.3418784624298315E-6 evalInputDelta=9.723007678985596E-7
New Minimum: 2.5561761520802975 > 2.5561742186546326
WOLFE (weak): th(12.926608140191302)=2.5561742186546326; dx=-2.340037076513394E-6 evalInputDelta=2.905726432800293E-6
New Minimum: 2.5561742186546326 > 2.5561655201017857
WOLFE (weak): th(51.70643256076521)=2.5561655201017857; dx=-2.3422672716511155E-6 evalInputDelta=1.1604279279708862E-5
New Minimum: 2.5561655201017857 > 2.5561195835471153
WOLFE (weak): th(258.53216280382605)=2.5561195835471153; dx=-2.3385574988190725E-6 evalInputDelta=5.7540833950042725E-5
New Minimum: 2.5561195835471153 > 2.5558279268443584
WOLFE (weak): th(1551.1929768229563)=2.5558279268443584; dx=-2.3316596388291495E-6 evalInputDelta=3.4919753670692444E-4
New Minimum: 2.5558279268443584 > 2.553836289793253
WOLFE (weak): th(10858.350837760694)=2.553836289793253; dx=-2.275480606197862E-6 evalInputDelta=0.0023408345878124237
New Minimum: 2.553836289793253 > 2.5464802905917168
END: th(86866.80670208555)=2.5464802905917168; dx=-1.5810864220262568E-6 evalInputDelta=0.009696833789348602
Fitness changed from 2.5561771243810654 to 2.5464802905917168
Iteration 1 complete. Error: 2.5464802905917168 Total: 13.6489; Orientation: 0.0082; Line Search: 10.3688
<a id="p-3"></a>Iteration 1
<a id="p-2"></a>
Adding measurement 15cdbd34 to history. Total: 1
LBFGS Accumulation History: 2 points
th(0)=2.5464802905917168;dx=-2.45706461
...skipping 10235 bytes...
85791015625E-7
WOLFE (weak): th(7.61107767945611E-5)=2.540031172335148; dx=-2.5980024106277975E-6 evalInputDelta=0.0
Armijo: th(8.24533415274412E-5)=2.540031410753727; dx=-2.598002152653689E-6 evalInputDelta=-2.384185791015625E-7
WOLFE (weak): th(7.928205916100115E-5)=2.540031172335148; dx=-2.5980024106277975E-6 evalInputDelta=0.0
Armijo: th(8.086770034422117E-5)=2.540031410753727; dx=-2.598002152653689E-6 evalInputDelta=-2.384185791015625E-7
Armijo: th(8.007487975261117E-5)=2.540031410753727; dx=-2.598002152653689E-6 evalInputDelta=-2.384185791015625E-7
WOLFE (weak): th(7.967846945680616E-5)=2.540031172335148; dx=-2.5980024106277975E-6 evalInputDelta=0.0
Armijo: th(7.987667460470866E-5)=2.540031410753727; dx=-2.598002152653689E-6 evalInputDelta=-2.384185791015625E-7
Armijo: th(7.97775720307574E-5)=2.540031410753727; dx=-2.598002152653689E-6 evalInputDelta=-2.384185791015625E-7
WOLFE (weak): th(7.972802074378178E-5)=2.540031172335148; dx=-2.5980024106277975E-6 evalInputDelta=0.0
WOLFE (weak): th(7.97527963872696E-5)=2.540031172335148; dx=-2.5980024106277975E-6 evalInputDelta=0.0
Armijo: th(7.97651842090135E-5)=2.540031410753727; dx=-2.598002152653689E-6 evalInputDelta=-2.384185791015625E-7
WOLFE (weak): th(7.975899029814155E-5)=2.540031172335148; dx=-2.5980024106277975E-6 evalInputDelta=0.0
WOLFE (weak): th(7.976208725357753E-5)=2.540031172335148; dx=-2.5980024106277975E-6 evalInputDelta=0.0
WOLFE (weak): th(7.976363573129552E-5)=2.540031172335148; dx=-2.5980024106277975E-6 evalInputDelta=0.0
Armijo: th(7.976440997015451E-5)=2.540031410753727; dx=-2.598002152653689E-6 evalInputDelta=-2.384185791015625E-7
mu ~= nu (7.976363573129552E-5): th(0.0)=2.540031172335148
Fitness changed from 2.540031172335148 to 2.540031172335148
Static Iteration Total: 33.5488; Orientation: 0.2456; Line Search: 32.1644
Iteration 6 failed. Error: 2.540031172335148
Previous Error: 0.0 -> 2.540031172335148
Retrying iteration 6
Final threshold in iteration 6: 2.540031172335148 (> -Infinity) after 119.349s (< 720.000s)
2.540031172335148