walterddr commented on a change in pull request #9732: [FLINK-14153][ml] Add to
BLAS a method that performs DenseMatrix and SparseVector multiplication.
URL: https://github.com/apache/flink/pull/9732#discussion_r336805138
##########
File path:
flink-ml-parent/flink-ml-lib/src/main/java/org/apache/flink/ml/common/linalg/BLAS.java
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@@ -55,24 +78,34 @@ public static void axpy(double a, SparseVector x,
DenseVector y) {
* y += a * x .
*/
public static void axpy(double a, DenseMatrix x, DenseMatrix y) {
- assert x.m == y.m && x.n == y.n : "Matrix dimension
mismatched.";
+ Preconditions.checkArgument(x.m == y.m && x.n == y.n, "Matrix
dimension mismatched.");
F2J_BLAS.daxpy(x.data.length, a, x.data, 1, y.data, 1);
}
+ /**
+ * y[yOffset:yOffset+n] += a * x[xOffset:xOffset+n] .
+ */
+ public static void axpy(int n, double a, double[] x, int xOffset,
double[] y, int yOffset) {
+ F2J_BLAS.daxpy(n, a, x, xOffset, 1, y, yOffset, 1);
Review comment:
A higher level question:
Maybe it is good to clarify when to use `F2J_BLAS` vs `NATIVE_BLAS`.
I found a very [interesting
read](https://issues.apache.org/jira/browse/SPARK-21305) from SPARK's mailing
list and seems like there are some considerations regarding this.
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