class_docstr: KLDivLoss
code: def _kldiv(self, x, target, mask=None):
      eps = 1.0e-10
      loss = target * (paddle.log(target + eps) - x)
      if mask is not None:
          loss = loss.flatten(0, 1).sum(axis=1)
          loss = loss.masked_select(mask).mean()
      else:
          # batch mean loss
          loss = paddle.sum(loss) / loss.shape[0]
      return loss
  
imports: import paddle
  import paddle.nn
  import paddle.nn.functional
  from paddle.nn import L1Loss
  from paddle.nn import MSELoss
  from paddle.nn import SmoothL1Loss
label_desc: Use image node_id 2 for calling the KLDivLoss obj's underlying member method code with example usage: obj._kldiv(x, target, mask) and returns: loss