docstr: y_pred should be two projections
code: def __call__(self, inputs, y_pred, y_true=None, is_val=False):
      """
      y_pred should be two projections
      """
      # covar_mat = torch.abs(th_matrixcorr(y_pred[0].data, y_pred[1].data))
      covar_mat = torch.abs(
          th_matrixcorr(y_pred[0].detach(), y_pred[1].detach())
      )  # changed after pytorch 0.4
      upper_sum = torch.sum(torch.triu(covar_mat, 1))
      lower_sum = torch.sum(torch.tril(covar_mat, -1))
      self.anticorr_sum += upper_sum
      self.anticorr_sum += lower_sum
      self.total_count += covar_mat.size(0) * (covar_mat.size(1) - 1)
      return self.anticorr_sum / self.total_count
  
imports: import torch
  from .utils import th_matrixcorr
  from .meters.averagemeter import AverageMeter
  from .callbacks import Callback
  from .losses import lovaszloss, hingeloss, dice_coeff
label_desc: Use image node_id 3 for calling the ProjectionAntiCorrelation obj's underlying member method code with example usage: obj.__call__(inputs, y_pred, y_true, is_val) and returns: unknown