code: def th_corrcoef(x):
      """
      mimics np.corrcoef
      """
      # calculate covariance matrix of rows
      mean_x = th.mean(x, 1)
      xm = x.sub(mean_x.expand_as(x))
      c = xm.mm(xm.t())
      c = c / (x.size(1) - 1)
  
      # normalize covariance matrix
      d = th.diag(c)
      stddev = th.pow(d, 0.5)
      c = c.div(stddev.expand_as(c))
      c = c.div(stddev.expand_as(c).t())
  
      # clamp between -1 and 1
      c = th.clamp(c, -1.0, 1.0)
  
      return c
  
imports: import pickle
  import random
  from .optimizers import *
  from .callbacks import *
  import torch
  from pywick.callbacks import *
label_desc: Use image node_id 19 for calling a global function with example usage: th_corrcoef(x) and returns: c