code: def test_kernel_getitem_broadcast(self):
      kernel = self.create_kernel_no_ard(batch_shape=torch.Size([2]))
      x = self.create_data_double_batch()
      kernel = kernel.expand_batch(
          torch.broadcast_shapes(kernel.batch_shape, x.shape[:-2])
      )
  
      idx1 = torch.LongTensor([0, 2, 1]).unsqueeze(-1)
      idx2 = torch.LongTensor([1, 0, 0]).unsqueeze(-2)
      res1 = kernel(x).to_dense()[
          idx1, idx2
      ]  # Result of first kernel on first batch of data
  
      new_kernel = kernel[idx1, idx2]
      res2 = new_kernel(
          x[idx1, idx2]
      ).to_dense()  # Should also be result of first kernel on first batch of data.
  
      self.assertAllClose(res1, res2, rtol=1e-3, atol=1e-5)
  
imports: import pickle
  from abc import abstractmethod
  import torch
  from .base_test_case import BaseTestCase
label_desc: Use image node_id 16 for calling the BaseKernelTestCase obj's underlying member method code with example usage: obj.test_kernel_getitem_broadcast() without return types