From 4d955cd69452e34f74369e62bc741a5c749905a8 Mon Sep 17 00:00:00 2001
From: "Joseph K. Bradley" <joseph@databricks.com>
Date: Wed, 23 Mar 2016 10:51:58 +0000
Subject: [PATCH] [SPARK-14035][MLLIB] Make error message more verbose for
mllib NaiveBayesSuite
## What changes were proposed in this pull request?
Print more info about failed NaiveBayesSuite tests which have exhibited flakiness.
## How was this patch tested?
Ran locally with incorrect check to cause failure.
Author: Joseph K. Bradley <joseph@databricks.com>
Closes #11858 from jkbradley/naive-bayes-bug-log.
---
.../classification/NaiveBayesSuite.scala | 28 ++++++++++++-------
1 file changed, 18 insertions(+), 10 deletions(-)
diff --git a/mllib/src/test/scala/org/apache/spark/mllib/classification/NaiveBayesSuite.scala b/mllib/src/test/scala/org/apache/spark/mllib/classification/NaiveBayesSuite.scala
index cffa1ab700..ab54cb06d5 100644
--- a/mllib/src/test/scala/org/apache/spark/mllib/classification/NaiveBayesSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/mllib/classification/NaiveBayesSuite.scala
@@ -21,6 +21,7 @@ import scala.util.Random
import breeze.linalg.{DenseMatrix => BDM, DenseVector => BDV, Vector => BV}
import breeze.stats.distributions.{Multinomial => BrzMultinomial}
+import org.scalatest.exceptions.TestFailedException
import org.apache.spark.{SparkException, SparkFunSuite}
import org.apache.spark.mllib.linalg.{Vector, Vectors}
@@ -103,17 +104,24 @@ class NaiveBayesSuite extends SparkFunSuite with MLlibTestSparkContext {
piData: Array[Double],
thetaData: Array[Array[Double]],
model: NaiveBayesModel): Unit = {
- def closeFit(d1: Double, d2: Double, precision: Double): Boolean = {
- (d1 - d2).abs <= precision
- }
- val modelIndex = (0 until piData.length).zip(model.labels.map(_.toInt))
- for (i <- modelIndex) {
- assert(closeFit(math.exp(piData(i._2)), math.exp(model.pi(i._1)), 0.05))
- }
- for (i <- modelIndex) {
- for (j <- 0 until thetaData(i._2).length) {
- assert(closeFit(math.exp(thetaData(i._2)(j)), math.exp(model.theta(i._1)(j)), 0.05))
+ val modelIndex = piData.indices.zip(model.labels.map(_.toInt))
+ try {
+ for (i <- modelIndex) {
+ assert(math.exp(piData(i._2)) ~== math.exp(model.pi(i._1)) absTol 0.05)
+ for (j <- thetaData(i._2).indices) {
+ assert(math.exp(thetaData(i._2)(j)) ~== math.exp(model.theta(i._1)(j)) absTol 0.05)
+ }
}
+ } catch {
+ case e: TestFailedException =>
+ def arr2str(a: Array[Double]): String = a.mkString("[", ", ", "]")
+ def msg(orig: String): String = orig + "\nvalidateModelFit:\n" +
+ " piData: " + arr2str(piData) + "\n" +
+ " thetaData: " + thetaData.map(arr2str).mkString("\n") + "\n" +
+ " model.labels: " + arr2str(model.labels) + "\n" +
+ " model.pi: " + arr2str(model.pi) + "\n" +
+ " model.theta: " + model.theta.map(arr2str).mkString("\n")
+ throw e.modifyMessage(_.map(msg))
}
}
--
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