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[SPARK-16880][ML][MLLib] make ann training data persisted if needed #14483

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[SPARK-16880][ML][MLLib] make ann training data persisted if needed #14483

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9 changes: 7 additions & 2 deletions mllib/src/main/scala/org/apache/spark/ml/ann/Layer.scala
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Expand Up @@ -26,6 +26,7 @@ import org.apache.spark.mllib.linalg.{Vector => OldVector, Vectors => OldVectors
import org.apache.spark.mllib.linalg.VectorImplicits._
import org.apache.spark.mllib.optimization._
import org.apache.spark.rdd.RDD
import org.apache.spark.storage.StorageLevel
import org.apache.spark.util.random.XORShiftRandom

/**
Expand Down Expand Up @@ -810,9 +811,13 @@ private[ml] class FeedForwardTrainer(
getWeights
}
// TODO: deprecate standard optimizer because it needs Vector
val newWeights = optimizer.optimize(dataStacker.stack(data).map { v =>
val trainData = dataStacker.stack(data).map { v =>
(v._1, OldVectors.fromML(v._2))
}, w)
}
val handlePersistence = trainData.getStorageLevel == StorageLevel.NONE
if (handlePersistence) trainData.persist(StorageLevel.MEMORY_AND_DISK)
val newWeights = optimizer.optimize(trainData, w)
if (handlePersistence) trainData.unpersist()
topology.model(newWeights)
}

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