zhengruifeng commented on a change in pull request #32991:
URL: https://github.com/apache/spark/pull/32991#discussion_r655428600
##########
File path: mllib-local/src/main/scala/org/apache/spark/ml/impl/Utils.scala
##########
@@ -99,30 +97,44 @@ private[spark] object Utils {
/**
* Perform in-place softmax conversion.
*/
- def softmax(values: Array[Double]): Unit = {
+ def softmax(array: Array[Double]): Unit =
+ softmax(array, array.length, 0, 1, array)
+
+ /**
+ * Perform softmax conversion.
+ */
+ def softmax(
+ input: Array[Double],
+ n: Int,
+ offset: Int,
+ step: Int,
+ output: Array[Double]): Unit = {
var maxValue = Double.MinValue
- var i = 0
- while (i < values.length) {
- val value = values(i)
- if (value.isPosInfinity) {
- java.util.Arrays.fill(values, 0)
- values(i) = 1.0
+ var i = offset
+ val end = offset + step * n
+ while (i < end) {
+ val v = input(i)
+ if (v.isPosInfinity) {
+ var j = offset
+ while (j < end) { output(j) = 0.0; j += step }
+ output(i) = 1.0
return
- } else if (value > maxValue) {
- maxValue = value
+ } else if (v > maxValue) {
+ maxValue = v
}
- i += 1
+ i += step
}
var sum = 0.0
- i = 0
- while (i < values.length) {
- val exp = math.exp(values(i) - maxValue)
- values(i) = exp
+ i = offset
+ while (i < end) {
+ val exp = math.exp(input(i) - maxValue)
+ output(i) = exp
sum += exp
- i += 1
+ i += step
}
- BLAS.javaBLAS.dscal(values.length, 1.0 / sum, values, 1)
+ i = offset
+ while (i < end) { output(i) /= sum; i += step }
Review comment:
existing result is:
master:
```
Row(features=DenseVector([0.1, 0.1, 0.25, 0.25]),
rawPrediction=DenseVector([-11.6082, -8.1583, 22.1776]),
probability=DenseVector([0.0, 0.0, 1.0]), prediction=2.0)
```
if we use dscal here, then
```
Row(features=DenseVector([0.1, 0.1, 0.25, 0.25]),
rawPrediction=DenseVector([-11.824, -8.298, 22.5299]),
probability=DenseVector([0.0, 0.0, 1.0]), prediction=2.0)
```
maybe OK to change the pytest
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