def METHOD_NAME(self):
    # TODO: Fix randomization
    kernel = self.create_kernel_no_ard(batch_shape=torch.Size([3, 2]))
    x = self.create_data_double_batch()
    res1 = kernel(x).to_dense()[0, 1]  # Result of first kernel on first batch of data
    randn_weights = kernel.randn_weights
    new_kernel = kernel[0, 1]
    new_kernel._init_weights(randn_weights=randn_weights[0, 1])
    res2 = new_kernel(x[0, 1]).to_dense()  # Should also be result of first kernel on first batch of data.
    self.assertLess(torch.norm(res1 - res2) / res1.norm(), 1e-4)