code: def GNNPreMP(dim_in, dim_out):
      """
      Wrapper for NN layer before GNN message passing
  
      Args:
          dim_in (int): Input dimension
          dim_out (int): Output dimension
          num_layers (int): Number of layers
  
      """
      return GeneralMultiLayer(
          "linear",
          cfg.gnn.layers_pre_mp,
          dim_in,
          dim_out,
          dim_inner=dim_out,
          final_act=True,
      )
  
imports: import torch
  import torch.nn
  import torch.nn.functional
  import graphgym.register
  from graphgym.config import cfg
  from graphgym.init import init_weights
  from graphgym.models.feature_encoder_pyg import edge_encoder_dict, node_encoder_dict
  from graphgym.models.head_pyg import head_dict
  from graphgym.models.layer_pyg import BatchNorm1dEdge, BatchNorm1dNode, GeneralLayer, GeneralMultiLayer
label_desc: Use image node_id 2 for calling a global function with example usage: GNNPreMP(dim_in, dim_out) and returns: GeneralMultiLayer