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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