code: def train_data():
      train_x = torch.linspace(0, 1, 10)
      train_y = torch.sign(torch.cos(train_x * (4 * pi))).add(1).div(2)
      return train_x, train_y
  
file_path: gpytorch/test/examples/test_simple_gp_classification.py
imports: import os
  import random
  import unittest
  from math import pi
  import torch
  from torch import optim
  import gpytorch
  from gpytorch.likelihoods import BernoulliLikelihood
  from gpytorch.models import ApproximateGP
  from gpytorch.variational import CholeskyVariationalDistribution, UnwhitenedVariationalStrategy
label_desc: Use image node_id 1 for calling a global function with example usage: train_data() and returns: train_x,  train_y