code: def get_basic_args(
      graph_construction_name, graph_embedding_name, decoder_name
  ):
      """
          It will build the template for ``Graph2X`` model.
      Parameters
      ----------
      graph_construction_name: str
          The graph construction method name. Expected in ["dependency", "constituency", \
              "node_emb", "node_emb_refined"].
      graph_embedding_name: str
          The graph embedding name. Expected in ["gcn", "gat", "graphsage", "ggnn"].
      decoder_name: str
          The decoder name. Expected in ["stdrnn", "stdtree"].
  
      Returns
      -------
      template_dict: dict
          The template dict.
          The structure is shown as follows:
              {
                  graph_construction_args: dict,
                  graph_embedding_args: dict,
                  decoder_args: dict
              }
      """
      graph_construction_args = get_graph_construction_args(
          graph_construction_name
      )
      graph_initialization_args = get_graph_initialization_args()
      graph_embedding_args = get_graph_embedding_args(
          graph_embedding_name
      )
      decoder_args = get_decoder_args(decoder_name)
      ret = {
          "graph_construction_args": graph_construction_args,
          "graph_initialization_args": graph_initialization_args,
          "graph_embedding_args": graph_embedding_args,
          "decoder_args": decoder_args,
      }
      return ret
  
imports: from .graph_construction import get_graph_construction_args
  from .graph_embedding import get_graph_embedding_args
  from .graph_initialization import get_graph_initialization_args
  from .prediction.generation import get_decoder_args
label_desc: Use image node_id 1 for calling a global function with example usage: get_basic_args(graph_construction_name, graph_embedding_name, decoder_name) and returns: ret