code: def gat_msg(self, edge):
      alpha = torch.cat([edge.src["x"], edge.dst["x"]], dim=-1)
      alpha = (alpha * self.att).sum(dim=-1)
      alpha = F.leaky_relu(alpha, self.negative_slope)
      return {"m": edge.src["x"], "a": alpha}
  
imports: import dgl.function
  import torch
  import torch.nn.functional
  from dgl.nn.pytorch import EdgeSoftmax
  from torch.nn import Parameter
  from torch_geometric.nn.inits import glorot, zeros
label_desc: Use image node_id 3 for calling the GATConv obj's underlying member method code with example usage: obj.gat_msg(edge) and returns: dict