code: def test_dict(self):
      # simulate complicated input data
      test_data = {
          "img": np.array([1.0, 2.0], dtype=np.float32),
          "meta": {
              "dims": 3,
              "size": np.array([1, 2, 3]),
              "path": "temp/test",
          },
          "extra": None,
      }
      for dtype in ("tensor", "numpy"):
          result = EnsureType(data_type=dtype, track_meta=False)(
              test_data
          )
          self.assertTrue(isinstance(result, dict))
          self.assertTrue(
              isinstance(
                  result["img"],
                  torch.Tensor if dtype == "tensor" else np.ndarray,
              )
          )
          assert_allclose(
              result["img"],
              torch.as_tensor([1.0, 2.0]),
              type_test=False,
          )
          self.assertTrue(
              isinstance(
                  result["meta"]["size"],
                  torch.Tensor if dtype == "tensor" else np.ndarray,
              )
          )
          assert_allclose(
              result["meta"]["size"],
              torch.as_tensor([1, 2, 3]),
              type_test=False,
          )
          self.assertEqual(result["meta"]["path"], "temp/test")
          self.assertEqual(result["extra"], None)
  
file_path: MONAI/tests/test_ensure_type.py
imports: from __future__ import annotations
  import unittest
  import numpy
  import torch
  from monai.data import MetaTensor
  from monai.transforms import EnsureType
  from tests.utils import assert_allclose
label_desc: Use image node_id 5 for calling the TestEnsureType obj's underlying member method code with example usage: obj.test_dict() without return types