code: def forward(self, x: Union[Tensor, OptPairTensor], edge_index: Adj):
      H, C = self.heads, self.out_channels
  
      x = self.lin(x).view(-1, H, C)
      alpha = (x * self.att).sum(dim=-1)
  
      if self.add_self_loops:
          if isinstance(edge_index, Tensor):
              num_nodes = x.size(0)
              edge_index, _ = remove_self_loops(edge_index)
              edge_index, _ = add_self_loops(
                  edge_index, num_nodes=num_nodes
              )
          elif isinstance(edge_index, SparseTensor):
              edge_index = set_diag(edge_index)
  
      out = self.propagate(edge_index, x=x, alpha=alpha)
  
      if self.concat:
          out = out.view(-1, self.heads * self.out_channels)
      else:
          out = out.mean(dim=1)
  
      if self.bias is not None:
          out += self.bias
  
      return out
  
imports: from torch_geometric.nn import MessagePassing
  from torch_geometric.utils import softmax
  import torch
  import torch.nn
  import torch.nn.functional
  from torch_geometric.nn import GCNConv, SAGEConv, GATConv, ARMAConv, ChebConv, GatedGraphConv, SGConv
  from typing import Union, Tuple, Optional
  from torch_geometric.typing import OptPairTensor, Adj, Size, NoneType, OptTensor
  import torch
  from torch import Tensor
  import torch.nn.functional
  from torch.nn import Parameter, Linear
  from torch_sparse import SparseTensor, set_diag
  from torch_geometric.nn.conv import MessagePassing
  from torch_geometric.utils import remove_self_loops, add_self_loops, softmax
  from torch_geometric.nn.inits import glorot, zeros
  import torch
  import torch.nn
  import torch.nn.functional
  import torch.nn.functional
  from torch.nn import Parameter
  from torch_geometric.nn.inits import glorot, zeros
  from torch_geometric.utils import softmax
  from torch_scatter import scatter_add
  import numpy
  from ..graph_nas_macro import GeoLayer
label_desc: Use image node_id 3 for calling the GATConv2 obj's underlying member method code with example usage: obj.forward(x, edge_index) and returns: out