code: def test_compute_linear_truncated_kernel_no_batch(self):
      x1 = torch.tensor([[1, 0.1, 0.2], [2, 0.3, 0.4]])
      x2 = torch.tensor([[3, 0.5, 0.6], [4, 0.7, 0.8]])
      t_1 = torch.tensor([[0.3584, 0.1856], [0.2976, 0.1584]])
      for nu, fidelity_dims in itertools.product(
          {0.5, 1.5, 2.5}, ([2], [1, 2])
      ):
          kernel = LinearTruncatedFidelityKernel(
              fidelity_dims=fidelity_dims, dimension=3, nu=nu
          )
          kernel.power = 1
          n_fid = len(fidelity_dims)
          if n_fid > 1:
              active_dimsM = [0]
              t_2 = torch.tensor([[0.4725, 0.2889], [0.4025, 0.2541]])
              t_3 = torch.tensor([[0.1685, 0.0531], [0.1168, 0.0386]])
              t = 1 + t_1 + t_2 + t_3
          else:
              active_dimsM = [0, 1]
              t = 1 + t_1
  
          matern_ker = MaternKernel(nu=nu, active_dims=active_dimsM)
          matern_term = matern_ker(x1, x2).to_dense()
          actual = t * matern_term
          res = kernel(x1, x2).to_dense()
          self.assertLess(torch.linalg.norm(res - actual), 1e-4)
          # test diagonal mode
          res_diag = kernel(x1, x2, diag=True)
          self.assertLess(
              torch.linalg.norm(res_diag - actual.diag()), 1e-4
          )
      # make sure that we error out if last_dim_is_batch=True
      with self.assertRaises(NotImplementedError):
          kernel(x1, x2, diag=True, last_dim_is_batch=True)
  
imports: import itertools
  import torch
  from botorch.exceptions import UnsupportedError
  from botorch.models.kernels.linear_truncated_fidelity import LinearTruncatedFidelityKernel
  from botorch.utils.testing import BotorchTestCase
  from gpytorch.kernels.matern_kernel import MaternKernel
  from gpytorch.kernels.rbf_kernel import RBFKernel
  from gpytorch.priors.torch_priors import GammaPrior, NormalPrior
  from gpytorch.test.base_kernel_test_case import BaseKernelTestCase
label_desc: Use image node_id 5 for calling the TestLinearTruncatedFidelityKernel obj's underlying member method code with example usage: obj.test_compute_linear_truncated_kernel_no_batch() without return types