code: def test_zca_unbiased(self, unbiased, device, dtype):
      data = torch.tensor(
          [[0, 1], [1, 0], [-1, 0], [0, -1]], device=device, dtype=dtype
      )
  
      if unbiased:
          unbiased_val = 1.5
      else:
          unbiased_val = 2.0
  
      expected = torch.sqrt(
          unbiased_val * torch.abs(data)
      ) * torch.sign(data)
  
      zca = kornia.enhance.ZCAWhitening(unbiased=unbiased).fit(data)
  
      actual = zca(data)
  
      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 1 for calling the TestZCA obj's underlying member method code with example usage: obj.test_zca_unbiased(unbiased, device, dtype) without return types