Github user jkbradley commented on the issue: https://github.com/apache/spark/pull/18896 How about updating the LogisticAggregatorSuite so it catches this error: ``` diff --git a/mllib/src/test/scala/org/apache/spark/ml/optim/aggregator/LogisticAggregatorSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/optim/aggregator/LogisticAggregatorSuite.scala index 2b29c67..a2924ad 100644 --- a/mllib/src/test/scala/org/apache/spark/ml/optim/aggregator/LogisticAggregatorSuite.scala +++ b/mllib/src/test/scala/org/apache/spark/ml/optim/aggregator/LogisticAggregatorSuite.scala @@ -239,7 +239,14 @@ class LogisticAggregatorSuite extends SparkFunSuite with MLlibTestSparkContext { Vectors.dense(coefArray ++ interceptArray), fitIntercept = true, isMultinomial = true) instances.foreach(aggConstantFeature.add) // constant features should not affect gradient - assert(aggConstantFeature.gradient(0) === 0.0) + def validateGradient(grad: Vector): Unit = { + assert(grad(0) === 0.0) + grad.toArray.foreach { gradientValue => + assert(!gradientValue.isNaN && + gradientValue > Double.NegativeInfinity && gradientValue < Double.PositiveInfinity) + } + } + validateGradient(aggConstantFeature.gradient) val binaryCoefArray = Array(1.0, 2.0) val intercept = 1.0 @@ -248,6 +255,6 @@ class LogisticAggregatorSuite extends SparkFunSuite with MLlibTestSparkContext { isMultinomial = false) instances.foreach(aggConstantFeatureBinary.add) // constant features should not affect gradient - assert(aggConstantFeatureBinary.gradient(0) === 0.0) + validateGradient(aggConstantFeatureBinary.gradient) } } ```
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