forked from kscience/kmath
Smaller SVD test
This commit is contained in:
parent
e371a4a6db
commit
bd068b2c14
@ -163,7 +163,7 @@ class TestDoubleLinearOpsTensorAlgebra {
|
||||
|
||||
@Test
|
||||
fun testBatchedSVD() = DoubleLinearOpsTensorAlgebra {
|
||||
val tensor = randNormal(intArrayOf(1, 15, 4, 7, 5, 3), 0)
|
||||
val tensor = randNormal(intArrayOf(2, 5, 3), 0)
|
||||
val (tensorU, tensorS, tensorV) = tensor.svd()
|
||||
val tensorSVD = tensorU dot (diagonalEmbedding(tensorS) dot tensorV.transpose())
|
||||
assertTrue(tensor.eq(tensorSVD))
|
||||
@ -171,7 +171,7 @@ class TestDoubleLinearOpsTensorAlgebra {
|
||||
|
||||
@Test
|
||||
fun testBatchedSymEig() = DoubleLinearOpsTensorAlgebra {
|
||||
val tensor = randNormal(shape = intArrayOf(5, 3, 3), 0)
|
||||
val tensor = randNormal(shape = intArrayOf(2, 3, 3), 0)
|
||||
val tensorSigma = tensor + tensor.transpose()
|
||||
val (tensorS, tensorV) = tensorSigma.symEig()
|
||||
val tensorSigmaCalc = tensorV dot (diagonalEmbedding(tensorS) dot tensorV.transpose())
|
||||
|
Loading…
Reference in New Issue
Block a user