torch.corrcoef
torch.corrcoef(input) -> Tensor
Estimates the Pearson product-moment correlation coefficient matrix
   of the variables given by the "input" matrix, where rows are the
   variables and columns are the observations.
Note:
 The correlation coefficient matrix R is computed using the
 covariance matrix C as given by R_{ij} = \frac{ C_{ij} } { \sqrt{
 C_{ii} * C_{jj} } }

Note:
 Due to floating point rounding, the resulting array may not be
 Hermitian and its diagonal elements may not be 1. The real and
 imaginary values are clipped to the interval [-1, 1] in an
 attempt to improve this situation.

Parameters:
      input (Tensor) -- A 2D matrix containing multiple
      variables and observations, or a Scalar or 1D vector
      representing a single variable.
Returns:
      (Tensor) The correlation coefficient matrix of the variables.
See also: "torch.cov()" covariance matrix.
Example: