text: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from __future__ import unicode_literals
  
  import os
  import torch
  import unittest
  from torch.autograd import Variable
  from gpytorch.lazy import ToeplitzLazyVariable
  
  
  def make_sum_lazy_var():
      c1 = Variable(torch.Tensor([5, 1, 2, 0]), requires_grad=True)
      t1 = ToeplitzLazyVariable(c1)
      c2 = Variable(torch.Tensor([6, 0, 1, -1]), requires_grad=True)
      t2 = ToeplitzLazyVariable(c2)
      return t1 + t2
  
  
  class TestSumLazyVariable(unittest.TestCase):
  
      def setUp(self):
          if os.getenv('UNLOCK_SEED') is None or os.getenv('UNLOCK_SEED').lower() == 'false':
              self.rng_state = torch.get_rng_state()
              torch.manual_seed(0)
  
          self.t1, self.t2 = make_sum_lazy_var().lazy_vars
          self.t1_eval = self.t1.evaluate().data
          self.t2_eval = self.t2.evaluate().data
  
      def tearDown(self):
          if hasattr(self, 'rng_state'):
              torch.set_rng_state(self.rng_state)
  
      def test_add_diag(self):
          diag = Variable(torch.Tensor([4]))
          lazy_var = make_sum_lazy_var().add_diag(diag)
          self.assertTrue(torch.equal(
              lazy_var.evaluate().data,
              (self.t1_eval + self.t2_eval + torch.eye(4) * 4),
          ))
  
      def test_add_jitter(self):
          lazy_var = make_sum_lazy_var().add_jitter()
          self.assertLess(
              torch.max(torch.abs(
                  lazy_var.evaluate().data - (self.t1_eval + self.t2_eval)
              )),
              1e-1,
          )
  
      def test_inv_matmul(self):
          mat = torch.randn(4, 4)
          res = make_sum_lazy_var().inv_matmul(Variable(mat))
          self.assertLess(
              torch.norm(
                  res.data - (self.t1_eval + self.t2_eval).inverse().matmul(mat)
              ),
              1e-3,
          )
  
      def test_getitem(self):
          res = make_sum_lazy_var()[1, 1]
          self.assertLess(
              torch.norm(res.data - (self.t1_eval + self.t2_eval)[1, 1]),
              1e-3,
          )
  
  
  if __name__ == '__main__':
      unittest.main()
  