code: def test_functional(self, device):
      pts = (
          torch.tensor([1.0, 0], device=device, dtype=torch.float64)
          .view(1, 1, 2)
          .tile(1, 6, 1)
      )
      lines = torch.tensor(
          [
              [0.0, 1.0, 0.0],
              [0.0, 1.0, 1.0],
              [1.0, 0.0, 0.0],
              [1.0, 0.0, 1.0],
              [1.0, 1.0, 0.0],
              [1.0, 1.0, 1.0],
          ],
          device=device,
          dtype=torch.float64,
      ).view(1, 6, 3)
      distances = kgl.point_line_distance(pts, lines)
      distances_expected = torch.tensor(
          [
              0.0,
              1.0,
              1.0,
              2.0,
              torch.sqrt(torch.tensor(2, dtype=torch.float64)) / 2,
              torch.sqrt(torch.tensor(2, dtype=torch.float64)),
          ],
          device=device,
      ).view(1, 6)
      assert_close(distances, distances_expected, rtol=1e-6, atol=1e-6)
  
imports: import pytest
  import torch
  from torch.autograd import gradcheck
  import kornia
  import kornia.geometry.linalg
  import kornia.testing
  from kornia.testing import BaseTester, assert_close
label_desc: Use image node_id 4 for calling the TestPointsLinesDistances obj's underlying member method code with example usage: obj.test_functional(device) without return types