class_docstr: Att conv with edge feature v2
class_docstr_tok: ["Att","conv","with","edge","feature","v2"]
code: def message(
      self, edge_index_i, x_i, x_j, norm, size_i, edge_feature, task_emb
  ):
      if self.msg_direction == "both":
          x_j = torch.cat((x_i, x_j, edge_feature), dim=-1)
      else:
          x_j = torch.cat((x_j, edge_feature), dim=-1)
      x_j = self.linear_value(x_j)
      x_j = x_j.view(-1, self.heads, self.head_channels)
      if task_emb is not None:
          task_emb = task_emb.view(1, 1, self.task_channels)
          alpha = (x_j * self.att_msg).sum(-1) + (
              task_emb * self.att_task
          ).sum(-1)
      else:
          alpha = (x_j * self.att_msg).sum(-1)
      alpha = F.leaky_relu(alpha, self.negative_slope)
      alpha = softmax(alpha, edge_index_i, num_nodes=size_i)
      alpha = alpha.view(-1, self.heads, 1)
      return (
          norm.view(-1, 1) * x_j * alpha
          if norm is not None
          else x_j * alpha
      )
  
imports: import torch
  import torch.nn
  import torch.nn.functional
  from torch.nn import Parameter
  from torch_geometric.nn.conv import MessagePassing
  from torch_geometric.nn.inits import glorot, zeros
  from torch_geometric.utils import add_remaining_self_loops, softmax
  from torch_scatter import scatter_add
  from graphgym.config import cfg
  from graphgym.register import register_layer
label_desc: Use image node_id 5 for calling the GeneralEdgeAttConvv2Layer obj's underlying member method code with example usage: obj.message(edge_index_i, x_i, x_j, norm, size_i, edge_feature, task_emb) and returns: unknown