code: def forward(self, preds_s, preds_t, inputs=None):
      assert preds_s.shape[-2:] == preds_t.shape[-2:]
      N, C, H, W = preds_s.shape
      eps = 1e-5
      if self.align is not None:
          preds_s = self.align(preds_s)
  
      if self.normalize:
          preds_s = feature_norm(preds_s)
          preds_t = feature_norm(preds_t)
  
      softmax_pred_s = self.distill_softmax(preds_s, self.tau)
      softmax_pred_t = self.distill_softmax(preds_t, self.tau)
  
      loss = paddle.sum(
          -softmax_pred_t * paddle.log(eps + softmax_pred_s)
          + softmax_pred_t * paddle.log(eps + softmax_pred_t)
      )
      return self.loss_weight * loss / (C * N)
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import math
  import paddle
  import paddle.nn
  import paddle.nn.functional
  from paddle import ParamAttr
  from ppdet.core.workspace import register
  from ppdet.modeling import ops
  from ppdet.modeling.losses.iou_loss import GIoULoss
  from ppdet.utils.logger import setup_logger
label_desc: Use image node_id 3 for calling the CWDFeatureLoss obj's underlying member method code with example usage: obj.forward(preds_s, preds_t, inputs) and returns: unknown