Github user jkbradley commented on a diff in the pull request:
https://github.com/apache/spark/pull/7705#discussion_r35726235
--- Diff:
mllib/src/main/scala/org/apache/spark/mllib/clustering/LDAOptimizer.scala ---
@@ -385,59 +387,52 @@ final class OnlineLDAOptimizer extends LDAOptimizer {
iteration += 1
val k = this.k
val vocabSize = this.vocabSize
- val Elogbeta = dirichletExpectation(lambda).t
- val expElogbeta = exp(Elogbeta)
+ val expElogbeta = exp(LDAUtils.dirichletExpectation(lambda)).t
val alpha = this.alpha.toBreeze
val gammaShape = this.gammaShape
- val stats: RDD[BDM[Double]] = batch.mapPartitions { docs =>
+ val stats: RDD[(BDM[Double], List[BDV[Double]])] = batch.mapPartitions
{ docs =>
val stat = BDM.zeros[Double](k, vocabSize)
- docs.foreach { doc =>
- val termCounts = doc._2
- val (ids: List[Int], cts: Array[Double]) = termCounts match {
- case v: DenseVector => ((0 until v.size).toList, v.values)
- case v: SparseVector => (v.indices.toList, v.values)
- case v => throw new IllegalArgumentException("Online LDA does
not support vector type "
- + v.getClass)
+ var gammaPart = List[BDV[Double]]()
--- End diff --
Should this be allocated as a BDM from the start to avoid extra allocations?
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