ZoomingRotor.scala:84 executed in 0.03 seconds (0.000 gc):

    val outerMask = innerMask.map(x => 1 - x)
    var style: VisualNetwork = new VisualStyleNetwork(
      styleLayers = List(
        VGG19.VGG19_1b2,
        VGG19.VGG19_1c1,
        VGG19.VGG19_1c2,
        VGG19.VGG19_1c3,
        VGG19.VGG19_1c4,
        VGG19.VGG19_1d1,
        VGG19.VGG19_1d2,
        VGG19.VGG19_1d3,
        VGG19.VGG19_1d4
      ),
      styleModifiers = List(
        new MomentMatcher().scale(Math.pow(2, -enhancementCoeff * 2)),
        new GramMatrixEnhancer().setMinMax(-5, 5).scale(Math.pow(2, enhancementCoeff * 2))
      ),
      styleUrls = styleUrl,
      magnification = magnification,
      viewLayer = dims => getKaleidoscopeMask(dims.toArray, outerMask.addRef())
    )
    if (innerCoeff > 0) style = style.asInstanceOf[VisualStyleNetwork].withContent(
      contentLayers = List(
        VGG19.VGG19_0a
      ), contentModifiers = List(
        new ContentMatcher().withMask(innerMask.addRef()).scale(innerCoeff)
      ))
    style

Returns

    VisualStyleNetwork(List(VGG19_1b2, VGG19_1c1, VGG19_1c2, VGG19_1c3, VGG19_1c4, VGG19_1d1, VGG19_1d2, VGG19_1d3, VGG19_1d4),List((com.simiacryptus.mindseye.art.ops.MomentMatcher@4d956492*1.0), (com.simiacryptus.mindseye.art.ops.GramMatrixEnhancer@5cdc81f*1.0)),List(),WrappedArray(http://examples.deepartist.org/TextureTiledRotor/81ff602d-6492-4872-adfc-e339e67781e1/etc/b3b548e5-15b3-4668-8ff8-a0a5052be912.jpg, http://examples.deepartist.org/TextureTiledRotor/81ff602d-6492-4872-adfc-e339e67781e1/etc/38e6440a-9f99-4a4e-936e-337f1f93aba5.jpg),Float,com.simiacryptus.mindseye.art.examples.ZoomingRotor$$Lambda$504/1141489966@1fb1809f,1400,64,1,10000,5.0E8,2.0)

ZoomingRotor.scala:66 executed in 0.00 seconds (0.000 gc):

    new BasicOptimizer {
      override val trainingMinutes: Int = 90
      override val trainingIterations: Int = 10
      override val maxRate = 1e9
  
      override def trustRegion(layer: Layer): TrustRegion = null
  
      override def lineSearchFactory: LineSearchStrategy = {
        super.lineSearchFactory
      }
  
      override def renderingNetwork(dims: Seq[Int]) = getKaleidoscope(dims.toArray)
    }

Returns

    {
      "trainingMinutes" : 90,
      "trainingIterations" : 10,
      "maxRate" : 1.0E9
    }

Subreport: Optimization