code: def test_range(self, device, dtype, min_val, max_val):
      x = torch.rand(1, 2, 4, 5, device=device, dtype=dtype)
      out = kornia.enhance.normalize_min_max(
          x, min_val=min_val, max_val=max_val
      )
      self.assert_close(
          out.min(),
          torch.tensor(min_val, device=device, dtype=dtype),
          low_tolerance=True,
      )
      self.assert_close(
          out.max(),
          torch.tensor(max_val, device=device, dtype=dtype),
          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 4 for calling the TestNormalizeMinMax obj's underlying member method code with example usage: obj.test_range(device, dtype, min_val, max_val) without return types