class_docstr: Weighted MSE loss layer
class_docstr_tok: ["Weighted","MSE","loss","layer"]
code: def forward(self, pred, gt, mask):
      assert pred.size() == gt.size()
      loss = ((pred - gt) ** 2) * mask
      loss = loss.mean()
      return loss
  
file_path: gluon-cv/gluoncv/torch/nn/keypoint_loss.py
imports: import torch
  import torch.nn
label_desc: Use image node_id 2 for calling the WeightedMSELoss obj's underlying member method code with example usage: obj.forward(pred, gt, mask) and returns: loss