docstr: Update classifier's weight by training a linear supervised model.
docstr_tok: ["Update","classifier","'s","weight","by","training","a","linear","supervised","model","."]
code: def update_embeds(self, embeds, lazy_adj, args):
      """Update classifier's weight by training a linear supervised model."""
      pred_label = self(embeds).data
      clf_weight = self.linear_clf.W.weight.data
  
      # Update the smoothness loss via LGC.
      embeds = dglsp.spmm(lazy_adj, embeds)
  
      # Update the supervised loss via SEB.
      deriv_sup = 2 * dglsp.matmul(
          dglsp.spmm(
              self.label_idx_mat, -self.label_one_hot + pred_label
          ),
          clf_weight,
      )
      embeds = embeds - args.lr_sup * deriv_sup
  
      args.lr_sup = args.lr_sup * args.decline
      return embeds
  
file_path: dgl/examples/pytorch/ogc/ogc.py
imports: import dgl.sparse
  import torch.nn
  import torch.nn.functional
  from utils import LinearNeuralNetwork
label_desc: Use image node_id 3 for calling the OGC obj's underlying member method code with example usage: obj.update_embeds(embeds, lazy_adj, args) and returns: embeds