code: def get_neural_network_data(desc):
      """
      Return input and test data for a neural network.
  
      Parameters
      ----------
      desc : string
          model name. One of 131 or 2353.
      """
      if desc == "131":
          # build data with 1 input and 1 output and 500 data points
          x = np.random.uniform(-1, 1, 500)
          y = np.sin(x)
          x_test = np.random.uniform(-1, 1, 5)
          return x, y, x_test
  
      elif desc == "2353":
          # build data with 2 inputs, 3 outputs, and 500 data points
          np.random.seed(42)
          x = np.random.uniform([-1, 2], [1, 3], (500, 2))
          y1 = np.sin(x[:, 0] * x[:, 1])
          y2 = x[:, 0] + x[:, 1]
          y3 = np.cos(x[:, 0] / x[:, 1])
          y = np.column_stack((y1, y2, y3))
          x_test = np.random.uniform([-1, 2], [1, 3], (5, 2))
          return x, y, x_test
  
      return None
  
file_path: OMLT/tests/conftest.py
imports: from pathlib import Path
  import numpy
  import pytest
  from pyomo.common.fileutils import this_file_dir
  from omlt.neuralnet.layer import DenseLayer, InputLayer
  from omlt.neuralnet.network_definition import NetworkDefinition
label_desc: Use image node_id 1 for calling a global function with example usage: get_neural_network_data(desc) and returns: None, x,  y,  x_test, x,  y,  x_test