code: def __init__(
      self,
      in_feats,
      out_feats,
      num_heads,
      feat_drop=0.0,
      attn_drop=0.0,
      negative_slope=0.2,
      residual=False,
      activation=None,
      allow_zero_in_degree=False,
      bias=True,
      concat=False,
  ):
      super(GATConvC, self).__init__(
          in_feats,
          out_feats,
          num_heads,
          feat_drop,
          attn_drop,
          negative_slope,
          residual,
          activation,
          allow_zero_in_degree,
          bias,
      )
      self.concat = concat
  
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 1 to create a new GATConvC object from inherited base classes: GATConv with example: obj = GATConvC(in_feats, out_feats, num_heads, feat_drop, attn_drop, negative_slope, residual, activation, allow_zero_in_degree, bias, concat)