Perform singular value decomposition. More...
AFAPI void svd (array &u, array &s, array &vt, const array &in) C++ Interface to perform singular value decomposition. More...Perform singular value decomposition.
This function factorizes a matrix \(A\) into two unitary matrices, \(U\) and \(V^T\), and a diagonal matrix \(S\), such that \(A = USV^T\). If \(A\) has \(M\) rows and \(N\) columns ( \(M \times N\)), then \(U\) will be \(M \times M\), \(V\) will be \(N \times N\), and \(S\) will be \(M \times N\). However, for \(S\), this function only returns the non-zero diagonal elements as a sorted (in descending order) 1D array.
To reconstruct the original matrix \(A\) from the individual factors, the following code snippet can be used:
array U, S, Vt;
const int MN = std::min(M, N);
array UU = U(span, seq(MN));
array SS = diag(S, 0,
false).
as(ty);
array VV = Vt(seq(MN), span);
array AA = matmul(UU, SS, VV);
const array as(dtype type) const
Casts the array into another data type.
AFAPI void svd(array &u, array &s, array &vt, const array &in)
C++ Interface to perform singular value decomposition.
When memory is a concern, and \(A\) is dispensable, af::svdInPlace() can be used. However, this in-place version is currently limited to input arrays where \(M \geq N\).
◆ af_svd()C Interface to perform singular value decomposition.
C Interface to perform in-place singular value decomposition.
This function minimizes memory usage if in
is dispensable. Input array in
is limited to arrays where dim0
\(\geq\) dim1
.
C++ Interface to perform singular value decomposition.
C++ Interface to perform in-place singular value decomposition.
This function minimizes memory usage if in
is dispensable. Input array in
is limited to arrays where dim0
\(\geq\) dim1
.
RetroSearch is an open source project built by @garambo | Open a GitHub Issue
Search and Browse the WWW like it's 1997 | Search results from DuckDuckGo
HTML:
3.2
| Encoding:
UTF-8
| Version:
0.7.4