singularValueDecomposition

fun singularValueDecomposition(source: Tensor, wResult: Tensor?, uResult: Tensor?, vtResult: Tensor?)

Perform singular value decomposition of a matrix.

Parameters

source

the matrix to be decomposed. It must be a multi-dimensional tensor of 2 dimensions: MxN. The data type must be DataType.FLOAT64, DataType.FLOAT32, DataType.Image.R_FLOAT, DataType.Image.R_DOUBLE or DataType.Image.R_FLOAT_DYNAMIC.

wResult

an optional result for the W part of the SVD. It must be a multi-dimensional tensor of 2 dimensions. The data type must be DataType.FLOAT64, DataType.FLOAT32, DataType.Image.R_FLOAT, DataType.Image.R_DOUBLE or DataType.Image.R_FLOAT_DYNAMIC. The 2 dimensions must be min(M, N) and 1.

uResult

an optional result for the U part of the SVD. It must be a multi-dimensional tensor of 2 dimensions. The data type must be DataType.FLOAT64, DataType.FLOAT32, DataType.Image.R_FLOAT, DataType.Image.R_DOUBLE or DataType.Image.R_FLOAT_DYNAMIC. The two dimensions must be M and min(M, N).

vtResult

an optional result for the VT part of the SVD. It must be a multi-dimensional tensor of 2 dimensions. The data type must be DataType.FLOAT64, DataType.FLOAT32, DataType.Image.R_FLOAT, DataType.Image.R_DOUBLE or DataType.Image.R_FLOAT_DYNAMIC. The two dimensions must be min(M, N) and N.

Throws

If the usage is not allowed by the SpatialML run-time Framework, or if the framework encounters internal error and cannot perform the requested behavior.