torch.linalg.vander¶
- torch.linalg.vander(x, N=None) Tensor ¶
Generates a Vandermonde matrix.
Returns the Vandermonde matrix
for N > 1. If
N
= None, then N = x.size(-1) so that the output is a square matrix.Supports inputs of float, double, cfloat, cdouble, and integral dtypes. Also supports batches of vectors, and if
x
is a batch of vectors then the output has the same batch dimensions.Differences with numpy.vander:
Unlike numpy.vander, this function returns the powers of
x
in ascending order. To get them in the reverse order calllinalg.vander(x, N).flip(-1)
.
- Parameters
x (Tensor) – tensor of shape (*, n) where * is zero or more batch dimensions consisting of vectors.
- Keyword Arguments
N (int, optional) – Number of columns in the output. Default: x.size(-1)
Example:
>>> x = torch.tensor([1, 2, 3, 5]) >>> linalg.vander(x) tensor([[ 1, 1, 1, 1], [ 1, 2, 4, 8], [ 1, 3, 9, 27], [ 1, 5, 25, 125]]) >>> linalg.vander(x, N=3) tensor([[ 1, 1, 1], [ 1, 2, 4], [ 1, 3, 9], [ 1, 5, 25]])