text: """Exclusive-or (XOR) dataset for binary classification."""
  
  import torch
  
  
  def make_xor(num_samples=500):
      x = torch.rand(num_samples, 2)
      y = torch.zeros(num_samples)
      y[torch.logical_and(x[:, 0] > 0.5, x[:, 1] < 0.5)] = 1
      y[torch.logical_and(x[:, 1] > 0.5, x[:, 0] < 0.5)] = 1
      return x, y
  
  
  class XOR(torch.utils.data.TensorDataset):
      """Exclusive-or (XOR) dataset for binary classification."""
      def __init__(self, num_samples: int = 500):
          x, y = make_xor(num_samples)
          super().__init__(x, y)
  