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[SPARK-10478][ML] Performance, organization, and style improvements for multi-layer perceptron #8648

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[SPARK-10478][ML] Performance, organization, and style improvements for multi-layer perceptron #8648

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611c76f
Documentation and indentation fixes
Sep 7, 2015
7b192db
Refactors unneeded helpers
Sep 7, 2015
12169d7
More doc and style fixes
Sep 7, 2015
bc52b65
Cleans up documentation and uses functional code
Sep 7, 2015
84f8bea
Vectorizes linalg using ufuncs and vector ops
Sep 7, 2015
1f8ef66
Cleans up typos in BreezeUtil
Sep 8, 2015
22ba174
Fixes style issues
Sep 8, 2015
abdba81
Fixes style errors
Sep 8, 2015
f6731ff
Reverts noops and fixes unit tests
Sep 8, 2015
f56e2d5
Reverts flatten/flatMap changes
Sep 11, 2015
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11 changes: 5 additions & 6 deletions mllib/src/main/scala/org/apache/spark/ml/ann/BreezeUtil.scala
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Original file line number Diff line number Diff line change
Expand Up @@ -21,41 +21,40 @@ import breeze.linalg.{DenseMatrix => BDM, DenseVector => BDV}
import com.github.fommil.netlib.BLAS.{getInstance => NativeBLAS}

/**
* In-place DGEMM and DGEMV for Breeze
* In-place DGEMM and DGEMV for Breeze.
*/
private[ann] object BreezeUtil {

// TODO: switch to MLlib BLAS interface
private def transposeString(a: BDM[Double]): String = if (a.isTranspose) "T" else "N"

/**
* DGEMM: C := alpha * A * B + beta * C
* DGEMM: C := alpha * A * B + beta * C.
* @param alpha alpha
* @param a A
* @param b B
* @param beta beta
* @param c C
*/
def dgemm(alpha: Double, a: BDM[Double], b: BDM[Double], beta: Double, c: BDM[Double]): Unit = {
// TODO: add code if matrices isTranspose!!!
require(a.cols == b.rows, "A & B Dimension mismatch!")
require(a.rows == c.rows, "A & C Dimension mismatch!")
require(b.cols == c.cols, "A & C Dimension mismatch!")
require(b.cols == c.cols, "B & C Dimension mismatch!")
NativeBLAS.dgemm(transposeString(a), transposeString(b), c.rows, c.cols, a.cols,
alpha, a.data, a.offset, a.majorStride, b.data, b.offset, b.majorStride,
beta, c.data, c.offset, c.rows)
}

/**
* DGEMV: y := alpha * A * x + beta * y
* DGEMV: y := alpha * A * x + beta * y.
* @param alpha alpha
* @param a A
* @param x x
* @param beta beta
* @param y y
*/
def dgemv(alpha: Double, a: BDM[Double], x: BDV[Double], beta: Double, y: BDV[Double]): Unit = {
require(a.cols == x.length, "A & b Dimension mismatch!")
require(a.cols == x.length, "A & x Dimension mismatch!")
NativeBLAS.dgemv(transposeString(a), a.rows, a.cols,
alpha, a.data, a.offset, a.majorStride, x.data, x.offset, x.stride,
beta, y.data, y.offset, y.stride)
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