code: def concord_index(y, y_pred):
      """
      Calculate the Concordance Index (CI), which is a metric to measure the proportion of `concordant pairs
      <https://en.wikipedia.org/wiki/Concordant_pair>`_ between real and
      predict values.
  
      Args:
          y (array): real values.
          y_pred (array): predicted values.
      """
      total_loss = 0
      pair = 0
      for i in range(1, len(y)):
          for j in range(0, i):
              if i is not j:
                  if y[i] > y[j]:
                      pair += 1
                      total_loss += 1 * (
                          y_pred[i] > y_pred[j]
                      ) + 0.5 * (y_pred[i] == y_pred[j])
  
      if pair:
          return total_loss / pair
      else:
          return 0
  
label_desc: Use image node_id 1 for calling a global function with example usage: concord_index(y, y_pred) and returns: unknown, int