code: def get_encoder_decoder_hp(
      model="gin", decoder=None, decoupled=False
  ):
      if model == "gin":
          model_hp = {
              # hp from model
              "num_layers": 2,
              "hidden": [64],
              "dropout": 0.5,
              "act": "relu",
              "eps": "False",
              "mlp_layers": 2,
          }
  
      if model == "gat":
          if decoupled:
              model_hp = {
                  "num_layers": 2,
                  "hidden": [8],
                  "num_hidden_heads": 8,
                  "num_output_heads": 1,
                  "dropout": 0.6,
                  "act": "elu",
              }
          else:
              model_hp = {
                  "num_layers": 2,
                  "hidden": [8],
                  "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 = {}
  
      return model_hp, {}
  
label_desc: Use image node_id 1 for calling a global function with example usage: get_encoder_decoder_hp(model, decoder, decoupled) and returns: model_hp,  dict