code: def titanic(debug=False):
      from tensorflow.keras.optimizers import Adam, Nadam
  
      # here use a standard 2d dictionary for inputting the param boundaries
      p = {
          "lr": (0.5, 5, 10),
          "first_neuron": [4, 8, 16],
          "batch_size": [20, 30, 40],
          "dropout": (0, 0.5, 5),
          "optimizer": [Adam(), Nadam()],
          "epochs": [50, 100, 150],
          "losses": ["logcosh", "binary_crossentropy"],
          "shapes": ["brick", "triangle", 0.2],
          "hidden_layers": [0, 1, 2, 3, 4],
          "activation": ["relu", "elu"],
          "last_activation": ["sigmoid"],
      }
  
      if debug:
          p = {
              "lr": [0.1, 0.2],
              "first_neuron": [4, 8],
              "batch_size": [20, 30],
              "dropout": [0.2, 0.3],
              "optimizer": [Adam(), Nadam()],
              "epochs": [50, 100],
              "losses": ["logcosh", "binary_crossentropy"],
              "shapes": ["brick", "triangle", 0.2],
              "hidden_layers": [0, 1],
              "activation": ["relu", "elu"],
              "last_activation": ["sigmoid"],
          }
  
      return p
  
label_desc: Use image node_id 1 for calling a global function with example usage: titanic(debug) and returns: p