code: def forward(self, x):
      x = torch.mm(x, self.weight).view(
          -1, self.heads, self.out_channels
      )
      self.g.ndata["x"] = x
      self.g.update_all(self.gat_msg, self.gat_reduce)
      x = self.g.ndata.pop("x")
      x = x.view(-1, self.heads * self.out_channels)
      x = x + self.bias
      return x
  
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 5 for calling the GATConv obj's underlying member method code with example usage: obj.forward(x) and returns: x