code: def forward(self, x, adj, log=False):
      s_l_init = self.assign_mat(x, adj)
      s_l = F.softmax(s_l_init, dim=-1)
      return s_l
  
file_path: dgl/examples/pytorch/diffpool/model/tensorized_layers/assignment.py
imports: import torch
  from torch import nn
  from torch.autograd import Variable
  from torch.nn import functional
  from model.tensorized_layers.graphsage import BatchedGraphSAGE
label_desc: Use image node_id 2 for calling the DiffPoolAssignment obj's underlying member method code with example usage: obj.forward(x, adj, log) and returns: s_l