code: def forward(self, A_hat, Z):
      Z = self.dropout(Z)
      Z = self.W(Z).view(Z.shape[0], self.out_size, self.num_heads)
  
      # a^T [Wh_i || Wh_j] = a_l Wh_i + a_r Wh_j
      e_l = (Z * self.a_l).sum(dim=1)
      e_r = (Z * self.a_r).sum(dim=1)
      e = e_l[A_hat.row] + e_r[A_hat.col]
  
      a = F.leaky_relu(e)
      A_atten = dglsp.val_like(A_hat, a).softmax()
      a_drop = self.dropout(A_atten.val)
      A_atten = dglsp.val_like(A_atten, a_drop)
      return dglsp.bspmm(A_atten, Z)
  
imports: import pickle
  import dgl.sparse
  import torch
  import torch.nn
  import torch.nn.functional
  from dgl.data.utils import _get_dgl_url, download, get_download_dir
  from torch.optim import Adam
label_desc: Use image node_id 3 for calling the GATConv obj's underlying member method code with example usage: obj.forward(A_hat, Z) and returns: dglsp