code: def forward(self, adj, anext, s_l):
      entropy = (
          (torch.distributions.Categorical(probs=s_l).entropy())
          .sum(-1)
          .mean(-1)
      )
      assert not torch.isnan(entropy)
      return entropy
  
file_path: dgl/examples/pytorch/diffpool/model/loss.py
imports: import torch
  import torch.nn
label_desc: Use image node_id 1 for calling the EntropyLoss obj's underlying member method code with example usage: obj.forward(adj, anext, s_l) and returns: entropy