code: def gen_gp_test_data():
      """Generates test data for the unit tests."""
      # CNNs
      cnns = generate_cnn_architectures()
      np.random.shuffle(cnns)
      X1_tr = cnns[:7]
      Y1_tr = np.array([cnn_syn_func1(x) for x in X1_tr])
      X1_te = cnns[7:]
      Y1_te = np.array([cnn_syn_func1(x) for x in X1_te])
      nn_type_1 = "cnn"
      # MLP regression
      regmlps = generate_mlp_architectures("reg")
      np.random.shuffle(regmlps)
      X2_tr = regmlps[:5]
      Y2_tr = np.array([mlp_syn_func1(x) for x in X2_tr])
      X2_te = regmlps[5:]
      Y2_te = np.array([mlp_syn_func1(x) for x in X2_te])
      nn_type_2 = "mlp-reg"
      # MLP classification
      classmlps = generate_mlp_architectures("class")
      np.random.shuffle(classmlps)
      X3_tr = classmlps[:5]
      Y3_tr = np.array([syn_func1_common(x) for x in X3_tr])
      X3_te = classmlps[5:]
      Y3_te = np.array([syn_func1_common(x) for x in X3_te])
      nn_type_3 = "mlp-class"
      return [
          (X1_tr, Y1_tr, X1_te, Y1_te, nn_type_1),
          (X2_tr, Y2_tr, X2_te, Y2_te, nn_type_2),
          (X3_tr, Y3_tr, X3_te, Y3_te, nn_type_3),
      ]
  
imports: import numpy
  import unittest
  from .syn_nn_functions import syn_func1_common, cnn_syn_func1, mlp_syn_func1
  from .nn_examples import generate_cnn_architectures, generate_mlp_architectures
  from .None import nn_gp
  from ..utils.ancillary_utils import get_list_of_floats_as_str
  from ..utils.base_test_class import BaseTestClass, execute_tests
  from ..utils.option_handler import load_options
label_desc: Use image node_id 1 for calling a global function with example usage: gen_gp_test_data() and returns: list