torch.vander
torch.vander(x, N=None, increasing=False) -> Tensor
Generates a Vandermonde matrix.
The columns of the output matrix are elementwise powers of the
   input vector x^{(N-1)}, x^{(N-2)}, ..., x^0. If increasing is True,
   the order of the columns is reversed x^0, x^1, ..., x^{(N-1)}. Such
   a matrix with a geometric progression in each row is named for
   Alexandre-Theophile Vandermonde.
Parameters:
      * x (Tensor) -- 1-D input tensor.
  * **N** (*int**, **optional*) -- Number of columns in the
    output. If N is not specified, a square array is returned (N =
    len(x)).

  * **increasing** (*bool**, **optional*) -- Order of the powers
    of the columns. If True, the powers increase from left to
    right, if False (the default) they are reversed.

Returns:
      Vandermonde matrix. If increasing is False, the first column is
      x^{(N-1)}, the second x^{(N-2)} and so forth. If increasing is