code: def test_eye(self, device, dtype):
      input_tensor = torch.stack(
          [
              torch.eye(2, dtype=dtype, device=device) * 255,
              torch.eye(2, dtype=dtype, device=device) * 150,
          ]
      ).view(2, -1, 2, 2)
  
      expected_tensor = tensor(
          [
              [
                  [[1.0, 1.0], [1.0, 1.0]],
                  [[1.0, 0.0], [0.0, 1.0]],
                  [[0.0, 0.0], [0.0, 0.0]],
              ],
              [
                  [[1.0, 1.0], [1.0, 1.0]],
                  [[1.0, 0.0], [0.0, 1.0]],
                  [[0.0, 0.0], [0.0, 0.0]],
              ],
          ],
          device=device,
          dtype=dtype,
      )
  
      actual = apply_colormap(
          input_tensor, AUTUMN(device=device, dtype=dtype)
      )
      self.assert_close(actual, expected_tensor)
  
file_path: kornia/test/color/test_colormap.py
imports: import pytest
  import torch
  from torch.autograd import gradcheck
  from kornia.color import AUTUMN, ApplyColorMap, apply_colormap
  from kornia.core import tensor
  from kornia.testing import BaseTester, assert_close, tensor_to_gradcheck_var
label_desc: Use image node_id 2 for calling the TestApplyColorMap obj's underlying member method code with example usage: obj.test_eye(device, dtype) without return types