xuyang1706 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_r336986571
##########
File path:
flink-ml-parent/flink-ml-lib/src/main/java/org/apache/flink/ml/common/linalg/BLAS.java
##########
@@ -131,19 +168,56 @@ public static void gemm(double alpha, DenseMatrix matA,
boolean transA, DenseMat
}
/**
- * y := alpha * A * x + beta * y .
+ * Check the compatibility of matrix and vector sizes in
<code>gemv</code>.
*/
- public static void gemv(double alpha, DenseMatrix matA, boolean transA,
- DenseVector x, double
beta, DenseVector y) {
+ private static void gemvDimensionCheck(DenseMatrix matA, boolean
transA, Vector x, Vector y) {
if (transA) {
- assert (matA.numCols() == y.size() && matA.numRows() ==
x.size()) : "Matrix and vector size mismatched.";
+ Preconditions.checkArgument(matA.numCols() == y.size()
&& matA.numRows() == x.size(),
+ "Matrix and vector size mismatched.");
} else {
- assert (matA.numRows() == y.size() && matA.numCols() ==
x.size()) : "Matrix and vector size mismatched.";
+ Preconditions.checkArgument(matA.numRows() == y.size()
&& matA.numCols() == x.size(),
+ "Matrix and vector size mismatched.");
}
+ }
+
+ /**
+ * y := alpha * A * x + beta * y .
+ */
+ public static void gemv(double alpha, DenseMatrix matA, boolean transA,
+ DenseVector x, double
beta, DenseVector y) {
+ gemvDimensionCheck(matA, transA, x, y);
final int m = matA.numRows();
final int n = matA.numCols();
final int lda = matA.numRows();
final String ta = transA ? "T" : "N";
NATIVE_BLAS.dgemv(ta, m, n, alpha, matA.getData(), lda,
x.getData(), 1, beta, y.getData(), 1);
Review comment:
We consistently use F2J_BLAS for level-1 routines such as scal/axpy/asum,
and use NATIVE_BLAS for level-2/level-3 routines such as gemv, gemm. As for the
gemv case here, we use NATIVE_BLAS for the dense case. But for the sparse case,
the BLAS library is not directly applicable because it is a library for dense
linear algebra. So we implement gemv for SparseVector by hand, using F2J_BLAS
to do axpy(level-1 routine) during the course.
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