code: def compute_average_prediction_error(
      dataset, preds, true_labels_idx=None
  ):
      """Computes the prediction error."""
      true_labels_idx = (
          3 if true_labels_idx is None else true_labels_idx
      )
      return (
          np.linalg.norm(dataset[true_labels_idx] - preds) ** 2
      ) / len(dataset[true_labels_idx])
  
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 5 for calling a global function with example usage: compute_average_prediction_error(dataset, preds, true_labels_idx) and returns: unknown