Code from BasicOptimizer.scala:88 executed in 620.96 seconds (10.785 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: 2194757931371
Reset training subject: 2196967165002
Adding measurement 78621bae to history. Total: 0
LBFGS Accumulation History: 1 points
Constructing line search parameters: GD+Trust
th(0)=3.4790104925632477;dx=-2.41319673111678E-7
New Minimum: 3.4790104925632477 > 3.479009911417961
WOLFE (weak): th(2.154434690031884)=3.479009911417961; dx=-2.4154808146864773E-7 evalInputDelta=5.811452865600586E-7
New Minimum: 3.479009911417961 > 3.4790089577436447
WOLFE (weak): th(4.308869380063768)=3.4790089577436447; dx=-2.4158937682686154E-7 evalInputDelta=1.5348196029663086E-6
New Minimum: 3.4790089577436447 > 3.479006513953209
WOLFE (weak): th(12.926608140191302)=3.479006513953209; dx=-2.416131755713251E-7 evalInputDelta=3.978610038757324E-6
New Minimum: 3.479006513953209 > 3.478994771838188
WOLFE (weak): th(51.70643256076521)=3.478994771838188; dx=-2.41421631583243E-7 evalInputDelta=1.5720725059509277E-5
New Minimum: 3.478994771838188 > 3.4789308607578278
WOLFE (weak): th(258.53216280382605)=3.4789308607578278; dx=-2.4152564615030907E-7 evalInputDelta=7.963180541992188E-5
New Minimum: 3.4789308607578278 > 3.4785320311784744
WOLFE (weak): th(1551.1929768229563)=3.4785320311784744; dx=-2.415992027839389E-7 evalInputDelta=4.784613847732544E-4
New Minimum: 3.4785320311784744 > 3.475661963224411
WOLFE (weak): th(10858.350837760694)=3.475661963224411; dx=-2.415360645057048E-7 evalInputDelta=0.00334852933883667
New Minimum: 3.475661963224411 > 3.4522183388471603
WOLFE (weak): th(86866.80670208555)=3.4522183388471603; dx=-2.4126108364180797E-7 evalInputDelta=0.02679215371608734
New Minimum: 3.4522183388471603 > 3.2393296509981155
WOLFE (weak): th(781801.26031877)=3.2393296509981155; dx=-2.3355566155534028E-7 evalInputDelta=0.23968084156513214
New Minimum: 3.2393296509981155 > 1.7766670137643814
END: th(7818012.6031877)=1.7766670137643814; dx=-1.2216017501023915E-7 evalInputDelta=1.7023434787988663
Fitness changed from 3.4790104925632477 to 1.7766670137643814
Iteration 1 complete. Error: 1.7766670137643814
...skipping 39884 bytes...
250507)=-1.8633724600076675; dx=-3.0994306578768705E-9 evalInputDelta=-5.811452865600586E-7
WOLFE (weak): th(3173051.159887549)=-1.8633788526058197; dx=-3.100606188476084E-9 evalInputDelta=5.811452865600586E-6
WOLFE (weak): th(3227758.9385062996)=-1.8633757084608078; dx=-3.0877856725405604E-9 evalInputDelta=2.6673078536987305E-6
WOLFE (weak): th(3255112.827815675)=-1.86337411403656; dx=-3.100491911458807E-9 evalInputDelta=1.0728836059570312E-6
WOLFE (weak): th(3268789.772470363)=-1.8633732944726944; dx=-3.100655159113634E-9 evalInputDelta=2.5331974029541016E-7
Armijo: th(3275628.2447977066)=-1.8633726686239243; dx=-3.1024615043710723E-9 evalInputDelta=-3.725290298461914E-7
WOLFE (weak): th(3272209.0086340345)=-1.863373063504696; dx=-3.0980966460011836E-9 evalInputDelta=2.2351741790771484E-8
Armijo: th(3273918.6267158706)=-1.8633728474378586; dx=-3.0998235779821586E-9 evalInputDelta=-1.9371509552001953E-7
Armijo: th(3273063.8176749526)=-1.863372951745987; dx=-3.1003485944932125E-9 evalInputDelta=-8.940696716308594E-8
Armijo: th(3272636.4131544936)=-1.86337298899889; dx=-3.099156475213885E-9 evalInputDelta=-5.21540641784668E-8
Armijo: th(3272422.7108942643)=-1.8633730113506317; dx=-3.100692565345778E-9 evalInputDelta=-2.9802322387695312E-8
Armijo: th(3272315.8597641494)=-1.8633729964494705; dx=-3.0979337780314824E-9 evalInputDelta=-4.470348358154297E-8
Armijo: th(3272262.434199092)=-1.8633730337023735; dx=-3.099070752032452E-9 evalInputDelta=-7.450580596923828E-9
Armijo: th(3272235.7214165633)=-1.86337298899889; dx=-3.097471066072601E-9 evalInputDelta=-5.21540641784668E-8
mu ~= nu (3272209.0086340345): th(1750648.9158000269)=-1.8634218946099281
Fitness changed from -1.863373041152954 to -1.8634218946099281
Iteration 30 complete. Error: -1.8634218946099281 Total: 53.3447; Orientation: 0.3045; Line Search: 50.9008
<a id="p-21"></a>Iteration 30
<a id="p-20"></a>
Final threshold in iteration 31: -1.8634218946099281 (> -Infinity) after 620.960s (< 3600.000s)
-1.8634218946099281