Github user jkbradley commented on a diff in the pull request:
https://github.com/apache/spark/pull/5330#discussion_r28267765
--- Diff:
mllib/src/main/scala/org/apache/spark/mllib/tree/model/treeEnsembleModels.scala
---
@@ -131,34 +131,26 @@ class GradientBoostedTreesModel(
val numIterations = trees.length
val evaluationArray = Array.fill(numIterations)(0.0)
- var predictionAndError: RDD[(Double, Double)] = remappedData.map { i =>
- val pred = treeWeights(0) * trees(0).predict(i.features)
- val error = loss.computeError(pred, i.label)
- (pred, error)
- }
+ var predictionAndError =
GradientBoostedTreesModel.computeInitialPredictionAndError(
+ remappedData, treeWeights(0), trees(0), loss)
+
evaluationArray(0) = predictionAndError.values.mean()
- // Avoid the model being copied across numIterations.
val broadcastTrees = sc.broadcast(trees)
- val broadcastWeights = sc.broadcast(treeWeights)
-
(1 until numIterations).map { nTree =>
predictionAndError =
remappedData.zip(predictionAndError).mapPartitions { iter =>
val currentTree = broadcastTrees.value(nTree)
- val currentTreeWeight = broadcastWeights.value(nTree)
- iter.map {
- case (point, (pred, error)) => {
- val newPred = pred + currentTree.predict(point.features) *
currentTreeWeight
- val newError = loss.computeError(newPred, point.label)
- (newPred, newError)
- }
+ val currentTreeWeight = treeWeights(nTree)
--- End diff --
We should make a local (shallow) copy of treeWeights before the map, within
this method:
```
val localTreeWeights = treeWeights
```
Referencing treeWeights, a member of the class, will actually make the
entire class get serialized by the ClosureCleaner. Assigning it to a local val
fixes that.
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