torch.linalg.vander
torch.linalg.vander(x, N=None) -> Tensor
Generates a Vandermonde matrix.
Returns the Vandermonde matrix V
  V = \begin{pmatrix}         1 & x_1 & x_1^2 & \dots &
  x_1^{N-1}\\         1 & x_2 & x_2^2 & \dots & x_2^{N-1}\\
  1 & x_3 & x_3^2 & \dots & x_3^{N-1}\\         \vdots & \vdots &
  \vdots & \ddots &\vdots \\         1 & x_n & x_n^2 & \dots &
  x_n^{N-1}     \end{pmatrix}.

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 call
     "linalg.vander(x, N).flip(-1)".

Parameters: