Github user AnthonyTruchet commented on a diff in the pull request:

    https://github.com/apache/spark/pull/16037#discussion_r90422375
  
    --- Diff: 
mllib/src/main/scala/org/apache/spark/mllib/optimization/LBFGS.scala ---
    @@ -241,16 +241,27 @@ object LBFGS extends Logging {
           val bcW = data.context.broadcast(w)
           val localGradient = gradient
     
    -      val (gradientSum, lossSum) = data.treeAggregate((Vectors.zeros(n), 
0.0))(
    -          seqOp = (c, v) => (c, v) match { case ((grad, loss), (label, 
features)) =>
    -            val l = localGradient.compute(
    -              features, label, bcW.value, grad)
    -            (grad, loss + l)
    -          },
    -          combOp = (c1, c2) => (c1, c2) match { case ((grad1, loss1), 
(grad2, loss2)) =>
    -            axpy(1.0, grad2, grad1)
    -            (grad1, loss1 + loss2)
    -          })
    +      // Given (current accumulated gradient, current loss) and (label, 
features)
    +      // tuples, updates the current gradient and current loss
    +      val seqOp = (c: (Vector, Double), v: (Double, Vector)) =>
    +        (c, v) match {
    +          case ((grad, loss), (label, features)) =>
    +            val denseGrad = grad.toDense
    +            val l = localGradient.compute(features, label, bcW.value, 
denseGrad)
    +            (denseGrad, loss + l)
    +        }
    +
    +      // Adds two (gradient, loss) tuples
    +      val combOp = (c1: (Vector, Double), c2: (Vector, Double)) =>
    +        (c1, c2) match { case ((grad1, loss1), (grad2, loss2)) =>
    +          val denseGrad1 = grad1.toDense
    +          val denseGrad2 = grad2.toDense
    +          axpy(1.0, denseGrad2, denseGrad1)
    +          (grad1, loss1 + loss2)
    --- End diff --
    
    done, thanks for spotting.


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