def _get_positive_mask()

in trainer/loss.py [0:0]


    def _get_positive_mask(self, batch_size):
        diag = np.eye(batch_size)
        mask = torch.from_numpy((diag))
        mask = (1 - mask)
        return mask.cuda(non_blocking=True)