code: def message(self, x_i, x_j, edge_index, size):
      if self.cached_norm is None:
          row, col = edge_index
          deg = pyg_utils.degree(row, size[0], dtype=x_j.dtype)
          deg_inv_sqrt = deg.pow(-0.5)
          norm = deg_inv_sqrt[row] * deg_inv_sqrt[col]
          if self.cache:
              self.cached_norm = norm
      else:
          norm = self.cached_norm
      return norm.view(-1, 1) * x_j
  
file_path: deepsnap/examples/graph_classification/skip_models.py
imports: import torch
  import torch.nn
  import torch.nn.functional
  import torch_geometric.nn
  import torch_geometric.utils
label_desc: Use image node_id 4 for calling the SimpleConv obj's underlying member method code with example usage: obj.message(x_i, x_j, edge_index, size) and returns: unknown