code: def test_autom8():
      import talos
      import wrangle
  
      from tensorflow.keras.optimizers import Adam
  
      print("\n >>> start AutoParams()... \n")
  
      p = talos.autom8.AutoParams()
      p.params
      p = talos.autom8.AutoParams(p.params)
      p.resample_params(5)
  
      p.activations(["relu"])
      p.batch_size(20, 50, 2)
      p.dropout(0, 0.22, 0.04)
      p.epochs(5, 10, 1)
      p.kernel_initializers(["zeros"])
      p.last_activations(["softmax"])
      p.layers(0, 2, 1)
      p.losses([talos.utils.metrics.f1score])
      p.lr([0.01])
      p.networks(["dense"])
      p.neurons(1, 5, 1)
      p.optimizers([Adam])
      p.shapes(["brick"])
      p.shapes_slope(0, 0.2, 0.01)
  
      p.resample_params(1)
  
      print("finised AutoParams() \n")
  
      # # # # # # # # # # # # # # # #
  
      print(
          "\n >>> start AutoModel(), AutoScan() and AutoPredict()... \n"
      )
  
      x, y = wrangle.utils.create_synth_data("binary", 50, 10, 1)
      p.losses(["binary_crossentropy"])
      auto = talos.autom8.AutoScan("binary", "test_a", 1)
      scan_object = auto.start(x, y, params=p.params)
      talos.autom8.AutoPredict(scan_object, x, y, x, "binary")
  
      x, y = wrangle.utils.create_synth_data("multi_label", 50, 10, 4)
      p.losses(["categorical_crossentropy"])
      auto = talos.autom8.AutoScan("multi_label", "test_b", 1)
      auto.start(x, y)
      talos.autom8.AutoPredict(scan_object, x, y, x, "multi_label")
  
      x, y = wrangle.utils.create_synth_data("multi_class", 50, 10, 3)
      p.losses(["sparse_categorical_crossentropy"])
      auto = talos.autom8.AutoScan("multi_class", "test_c", 1)
      auto.start(x, y, params=p.params)
      talos.autom8.AutoPredict(scan_object, x, y, x, "multi_class")
  
      x, y = wrangle.utils.create_synth_data("continuous", 50, 10, 1)
      p.losses(["mae"])
      auto = talos.autom8.AutoScan("continuous", "test_d", 1)
      auto.start(x, y, params=p.params)
      talos.autom8.AutoPredict(scan_object, x, y, x, "continuous")
  
      print("finised AutoModel(), AutoScan() and AutoPredict() \n")
  
label_desc: Use image node_id 1 for calling a global function with example usage: test_autom8() without return types