Github user feynmanliang commented on a diff in the pull request:
https://github.com/apache/spark/pull/8648#discussion_r41700924
--- Diff: mllib/src/main/scala/org/apache/spark/ml/ann/Layer.scala ---
@@ -260,127 +263,126 @@ private[ann] trait ActivationFunction extends
Serializable {
}
/**
- * Implements in-place application of functions
+ * Implements in-place application of functions.
*/
private[ann] object ActivationFunction {
- def apply(x: BDM[Double], y: BDM[Double], func: Double => Double): Unit
= {
- var i = 0
- while (i < x.rows) {
- var j = 0
- while (j < x.cols) {
- y(i, j) = func(x(i, j))
- j += 1
- }
- i += 1
- }
+ def apply(x: BDM[Double], y: BDM[Double], func: UFunc with MappingUFunc)(
+ implicit impl: func.Impl[BDM[Double], BDM[Double]]): Unit = {
+ y := func(x)
}
def apply(
- x1: BDM[Double],
- x2: BDM[Double],
- y: BDM[Double],
- func: (Double, Double) => Double): Unit = {
- var i = 0
- while (i < x1.rows) {
- var j = 0
- while (j < x1.cols) {
- y(i, j) = func(x1(i, j), x2(i, j))
- j += 1
- }
- i += 1
- }
+ x1: BDM[Double],
+ x2: BDM[Double],
+ y: BDM[Double],
+ func: UFunc with MappingUFunc)(
+ implicit impl: func.Impl2[BDM[Double], BDM[Double], BDM[Double]]):
Unit = {
+ y := func(x1, x2)
}
}
/**
- * Implements SoftMax activation function
+ * Implements Softmax activation function.
*/
private[ann] class SoftmaxFunction extends ActivationFunction {
override def eval(x: BDM[Double], y: BDM[Double]): Unit = {
- var j = 0
- // find max value to make sure later that exponent is computable
- while (j < x.cols) {
- var i = 0
- var max = Double.MinValue
- while (i < x.rows) {
- if (x(i, j) > max) {
- max = x(i, j)
- }
- i += 1
- }
- var sum = 0.0
- i = 0
- while (i < x.rows) {
- val res = Math.exp(x(i, j) - max)
- y(i, j) = res
- sum += res
- i += 1
- }
- i = 0
- while (i < x.rows) {
- y(i, j) /= sum
- i += 1
- }
- j += 1
+ (0 until x.cols).foreach { j =>
+ // subtract max value to prevent overflow during exp
+ // does not affect correctness since we normalize right after
+ val maxVal = Bmax(x(::, j))
+ y(::, j) := breeze.numerics.exp(x(::, j) - maxVal)
+ y(::, j) :/= Bsum(y(::, j))
--- End diff --
@mengxr [Local benchmarks
here](https://gist.github.com/feynmanliang/bc64b82a1258c4e86b9a). Performance
is more or less equivalent.
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