code: def evaluate_linear_op(self, lazy_tensor):
      res = to_dense(
          gpytorch.Module.__call__(
              lazy_tensor.kernel.base_kernel,
              lazy_tensor.x1.transpose(-1, -2).unsqueeze(-1),
              lazy_tensor.x2.transpose(-1, -2).unsqueeze(-1),
          )
      ).sum(0)
      return res
  
imports: import math
  import unittest
  from unittest.mock import MagicMock, patch
  import linear_operator
  import torch
  from linear_operator import to_dense
  from linear_operator.test.linear_operator_test_case import LinearOperatorTestCase
  import gpytorch
label_desc: Use image node_id 2 for calling the TestLazyEvaluatedKernelTensorAdditive obj's underlying member method code with example usage: obj.evaluate_linear_op(lazy_tensor) and returns: res