code: def test_values(self, device, dtype):
      x = torch.tensor(
          [[[[0.0, 1.0, 3.0], [-1.0, 4.0, 3.0], [9.0, 5.0, 2.0]]]],
          device=device,
          dtype=dtype,
      )
  
      expected = torch.tensor(
          [[[[-0.8, -0.6, -0.2], [-1.0, 0.0, -0.2], [1.0, 0.2, -0.4]]]],
          device=device,
          dtype=dtype,
      )
  
      actual = kornia.enhance.normalize_min_max(
          x, min_val=-1.0, max_val=1.0
      )
      self.assert_close(actual, expected, low_tolerance=True)
  
imports: import pytest
  import torch
  from torch.autograd import gradcheck
  import kornia
  import kornia.testing
  from kornia.testing import BaseTester
label_desc: Use image node_id 5 for calling the TestNormalizeMinMax obj's underlying member method code with example usage: obj.test_values(device, dtype) without return types