From ee694cdff6fdb47f23370038f87f8594a80a8f27 Mon Sep 17 00:00:00 2001
From: wangmiao1981 <wm624@hotmail.com>
Date: Sat, 29 Apr 2017 10:58:48 -0700
Subject: [PATCH] [SPARK-20533][SPARKR] SparkR Wrappers Model should be private
and value should be lazy
## What changes were proposed in this pull request?
MultilayerPerceptronClassifierWrapper model should be private.
LogisticRegressionWrapper.scala rFeatures and rCoefficients should be lazy.
## How was this patch tested?
Unit tests.
Author: wangmiao1981 <wm624@hotmail.com>
Closes #17808 from wangmiao1981/lazy.
---
.../org/apache/spark/ml/r/LogisticRegressionWrapper.scala | 4 ++--
.../spark/ml/r/MultilayerPerceptronClassifierWrapper.scala | 6 +++---
2 files changed, 5 insertions(+), 5 deletions(-)
diff --git a/mllib/src/main/scala/org/apache/spark/ml/r/LogisticRegressionWrapper.scala b/mllib/src/main/scala/org/apache/spark/ml/r/LogisticRegressionWrapper.scala
index c96f99cb83..703bcdf4ca 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/r/LogisticRegressionWrapper.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/r/LogisticRegressionWrapper.scala
@@ -40,13 +40,13 @@ private[r] class LogisticRegressionWrapper private (
private val lrModel: LogisticRegressionModel =
pipeline.stages(1).asInstanceOf[LogisticRegressionModel]
- val rFeatures: Array[String] = if (lrModel.getFitIntercept) {
+ lazy val rFeatures: Array[String] = if (lrModel.getFitIntercept) {
Array("(Intercept)") ++ features
} else {
features
}
- val rCoefficients: Array[Double] = {
+ lazy val rCoefficients: Array[Double] = {
val numRows = lrModel.coefficientMatrix.numRows
val numCols = lrModel.coefficientMatrix.numCols
val numColsWithIntercept = if (lrModel.getFitIntercept) numCols + 1 else numCols
diff --git a/mllib/src/main/scala/org/apache/spark/ml/r/MultilayerPerceptronClassifierWrapper.scala b/mllib/src/main/scala/org/apache/spark/ml/r/MultilayerPerceptronClassifierWrapper.scala
index d34de30931..48c87743de 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/r/MultilayerPerceptronClassifierWrapper.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/r/MultilayerPerceptronClassifierWrapper.scala
@@ -36,11 +36,11 @@ private[r] class MultilayerPerceptronClassifierWrapper private (
import MultilayerPerceptronClassifierWrapper._
- val mlpModel: MultilayerPerceptronClassificationModel =
+ private val mlpModel: MultilayerPerceptronClassificationModel =
pipeline.stages(1).asInstanceOf[MultilayerPerceptronClassificationModel]
- val weights: Array[Double] = mlpModel.weights.toArray
- val layers: Array[Int] = mlpModel.layers
+ lazy val weights: Array[Double] = mlpModel.weights.toArray
+ lazy val layers: Array[Int] = mlpModel.layers
def transform(dataset: Dataset[_]): DataFrame = {
pipeline.transform(dataset)
--
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