code: def get_encoder_decoder_hp(model="gin", decoder=None):
      if model == "gin":
          model_hp = {
              # hp from model
              "num_layers": 5,
              "hidden": [64, 64, 64, 64],
              "dropout": 0.5,
              "act": "relu",
              "eps": "False",
              "mlp_layers": 2,
          }
  
      if model == "gat":
          model_hp = {
              "num_layers": 2,
              "hidden": [8],
              "num_hidden_heads": 8,
              "num_output_heads": 8,
              "dropout": 0.6,
              "act": "elu",
          }
      elif model == "gcn":
          model_hp = {
              "num_layers": 2,
              "hidden": [16],
              "dropout": 0.5,
              "act": "relu",
          }
      elif model == "sage":
          model_hp = {
              "num_layers": 2,
              "hidden": [64],
              "dropout": 0.5,
              "act": "relu",
              "agg": "mean",
          }
      else:
          model_hp = {}
  
      if decoder is None or decoder == "addpoolmlp":
          decoder_hp = {"hidden": 64, "act": "relu", "dropout": 0.5}
      elif decoder == "diffpool":
          decoder_hp = {"ratio": 0.8, "dropout": 0.5, "act": "relu"}
      else:
          decoder_hp = {}
  
      return model_hp, decoder_hp
  
label_desc: Use image node_id 1 for calling a global function with example usage: get_encoder_decoder_hp(model, decoder) and returns: model_hp,  decoder_hp