(FM/MVM, etc.): ArrayIndexOutOfBoundsException when scaling about zen HOT 6 OPEN

  import com.github.cloudml.zen.ml.recommendation.{FMModel, FMClassification}
  import org.apache.spark.storage.StorageLevel
  import org.apache.spark.mllib.util.MLUtils

  val storageLevel = StorageLevel.MEMORY_AND_DISK
  val data = MLUtils.loadLibSVMFile(sc, "/witgo/kddb").repartition(96)
  val Array(trainSet, testSet) = data.zipWithUniqueId().map(_.swap).randomSplit(Array(0.9, 0.1))
  trainSet.persist(storageLevel).count()
  testSet.persist(storageLevel).count()

  val numIterations = 100
  val stepSize = 0.1
  val l2 = (0.01, 0.01, 0.01)
  val rank = 32
  val useAdaGrad = true
  val lfm = new FMClassification(trainSet, stepSize, l2, rank, useAdaGrad, 1.0, storageLevel)

  var iter = 0
  var model: FMModel = null
  while (iter < numIterations) {
    val thisItr = math.min(50, numIterations - iter)
    iter += thisItr
    if (model != null) model.factors.unpersist(false)
    lfm.run(thisItr)
    model = lfm.saveModel()
    model.factors.persist(storageLevel)
    model.factors.count()
    val auc = model.loss(testSet)
    println(f"(Iteration $iter/$numIterations) Test AUC:                     $auc%1.6f")
  }