code: def iris():
      from tensorflow.keras.optimizers import Adam, Nadam
      from tensorflow.keras.losses import (
          logcosh,
          categorical_crossentropy,
      )
      from tensorflow.keras.activations import relu, elu, softmax
  
      # here use a standard 2d dictionary for inputting the param boundaries
      p = {
          "lr": (0.5, 5, 10),
          "first_neuron": [4, 8, 16, 32, 64],
          "hidden_layers": [0, 1, 2, 3, 4],
          "batch_size": (2, 30, 10),
          "epochs": [50, 100, 150],
          "dropout": (0, 0.5, 5),
          "weight_regulizer": [None],
          "emb_output_dims": [None],
          "shapes": ["brick", "triangle", 0.2],
          "optimizer": [Adam, Nadam],
          "losses": [logcosh, categorical_crossentropy],
          "activation": [relu, elu],
          "last_activation": [softmax],
      }
  
      return p
  
label_desc: Use image node_id 2 for calling a global function with example usage: iris() and returns: p