code: def forward(self, graph, feat, get_attention=False):
      x = super().forward(graph, feat, get_attention=get_attention)
      if get_attention:
          x = x[0]
      out = x
      if self.concat:
          out = out.view(-1, self._num_heads * self._out_feats)
      else:
          out = out.mean(dim=1)
      return out
  
imports: import torch
  from torch import nn
  import torch.nn.functional
  import dgl
  from dgl.nn.pytorch.conv import *
  import dgl.function
  import math
  from dgl.utils import expand_as_pair
  from dgl.nn.functional import edge_softmax
  from torch.nn import Parameter
  import torch
  from torch import Tensor
  from ..scatter_utils import *
  from typing import Optional, Tuple, Union
label_desc: Use image node_id 2 for calling the GATConvC obj's underlying member method code with example usage: obj.forward(graph, feat, get_attention) and returns: out