code: def test_cardinality(self, device, dtype, input_shape):
      x = torch.rand(input_shape, device=device, dtype=dtype)
      assert kornia.enhance.normalize_min_max(x).shape == input_shape
  
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 3 for calling the TestNormalizeMinMax obj's underlying member method code with example usage: obj.test_cardinality(device, dtype, input_shape) without return types