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[SPARK-10353][MLLIB] BLAS gemm not scaling when beta = 0.0 for some subset of matrix multiplications #8525

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[SPARK-10353][MLLIB] BLAS gemm not scaling when beta = 0.0 for some subset of matrix multiplications #8525

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4378ce8
fix not scaling with beta = 0.0
brkyvz Aug 30, 2015
b535b53
updated comment
brkyvz Aug 30, 2015
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26 changes: 10 additions & 16 deletions mllib/src/main/scala/org/apache/spark/mllib/linalg/BLAS.scala
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Original file line number Diff line number Diff line change
Expand Up @@ -305,6 +305,8 @@ private[spark] object BLAS extends Serializable with Logging {
"The matrix C cannot be the product of a transpose() call. C.isTransposed must be false.")
if (alpha == 0.0 && beta == 1.0) {
logDebug("gemm: alpha is equal to 0 and beta is equal to 1. Returning C.")
} else if (alpha == 0.0) {
f2jBLAS.dscal(C.values.length, beta, C.values, 1)
} else {
A match {
case sparse: SparseMatrix => gemm(alpha, sparse, B, beta, C)
Expand Down Expand Up @@ -408,8 +410,8 @@ private[spark] object BLAS extends Serializable with Logging {
}
}
} else {
// Scale matrix first if `beta` is not equal to 0.0
if (beta != 0.0) {
// Scale matrix first if `beta` is not equal to 1.0
if (beta != 1.0) {
f2jBLAS.dscal(C.values.length, beta, C.values, 1)
}
// Perform matrix multiplication and add to C. The rows of A are multiplied by the columns of
Expand Down Expand Up @@ -470,8 +472,10 @@ private[spark] object BLAS extends Serializable with Logging {
s"The columns of A don't match the number of elements of x. A: ${A.numCols}, x: ${x.size}")
require(A.numRows == y.size,
s"The rows of A don't match the number of elements of y. A: ${A.numRows}, y:${y.size}")
if (alpha == 0.0) {
logDebug("gemv: alpha is equal to 0. Returning y.")
if (alpha == 0.0 && beta == 1.0) {
logDebug("gemv: alpha is equal to 0 and beta is equal to 1. Returning y.")
} else if (alpha == 0.0) {
scal(beta, y)
} else {
(A, x) match {
case (smA: SparseMatrix, dvx: DenseVector) =>
Expand Down Expand Up @@ -526,11 +530,6 @@ private[spark] object BLAS extends Serializable with Logging {
val xValues = x.values
val yValues = y.values

if (alpha == 0.0) {
scal(beta, y)
return
}

if (A.isTransposed) {
var rowCounterForA = 0
while (rowCounterForA < mA) {
Expand Down Expand Up @@ -581,11 +580,6 @@ private[spark] object BLAS extends Serializable with Logging {
val Arows = if (!A.isTransposed) A.rowIndices else A.colPtrs
val Acols = if (!A.isTransposed) A.colPtrs else A.rowIndices

if (alpha == 0.0) {
scal(beta, y)
return
}

if (A.isTransposed) {
var rowCounter = 0
while (rowCounter < mA) {
Expand All @@ -604,7 +598,7 @@ private[spark] object BLAS extends Serializable with Logging {
rowCounter += 1
}
} else {
scal(beta, y)
if (beta != 1.0) scal(beta, y)

var colCounterForA = 0
var k = 0
Expand Down Expand Up @@ -659,7 +653,7 @@ private[spark] object BLAS extends Serializable with Logging {
rowCounter += 1
}
} else {
scal(beta, y)
if (beta != 1.0) scal(beta, y)
// Perform matrix-vector multiplication and add to y
var colCounterForA = 0
while (colCounterForA < nA) {
Expand Down
5 changes: 5 additions & 0 deletions mllib/src/test/scala/org/apache/spark/mllib/linalg/BLASSuite.scala
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Expand Up @@ -204,6 +204,7 @@ class BLASSuite extends SparkFunSuite {
val C14 = C1.copy
val C15 = C1.copy
val C16 = C1.copy
val C17 = C1.copy
val expected2 = new DenseMatrix(4, 2, Array(2.0, 1.0, 4.0, 2.0, 4.0, 0.0, 4.0, 3.0))
val expected3 = new DenseMatrix(4, 2, Array(2.0, 2.0, 4.0, 2.0, 8.0, 0.0, 6.0, 6.0))
val expected4 = new DenseMatrix(4, 2, Array(5.0, 0.0, 10.0, 5.0, 0.0, 0.0, 5.0, 0.0))
Expand All @@ -217,6 +218,10 @@ class BLASSuite extends SparkFunSuite {
assert(C2 ~== expected2 absTol 1e-15)
assert(C3 ~== expected3 absTol 1e-15)
assert(C4 ~== expected3 absTol 1e-15)
gemm(1.0, dA, B, 0.0, C17)
assert(C17 ~== expected absTol 1e-15)
gemm(1.0, sA, B, 0.0, C17)
assert(C17 ~== expected absTol 1e-15)

withClue("columns of A don't match the rows of B") {
intercept[Exception] {
Expand Down