code: def png_rw(self, test_data, reader, writer, dtype, resample=True):
      test_data = test_data.astype(dtype)
      ndim = len(test_data.shape) - 1
      for p in TEST_NDARRAYS:
          output_ext = ".png"
          filepath = f"testfile_{ndim}d"
          saver = SaveImage(
              output_dir=self.test_dir,
              output_ext=output_ext,
              resample=resample,
              separate_folder=False,
              writer=writer,
          )
          test_data = MetaTensor(
              p(test_data),
              meta={
                  "filename_or_obj": f"{filepath}.png",
                  "spatial_shape": (6, 8),
              },
          )
          saver(test_data)
          saved_path = os.path.join(
              self.test_dir, filepath + "_trans" + output_ext
          )
          self.assertTrue(os.path.exists(saved_path))
          loader = LoadImage(image_only=True, reader=reader)
          data = loader(saved_path)
          meta = data.meta
          if meta["original_channel_dim"] == -1:
              _test_data = moveaxis(test_data, 0, -1)
          else:
              _test_data = test_data[0]
          assert_allclose(data, torch.as_tensor(_test_data))
  
imports: from __future__ import annotations
  import itertools
  import os
  import shutil
  import tempfile
  import unittest
  import numpy
  import torch
  from parameterized import parameterized
  from monai.data.image_reader import ITKReader, NibabelReader, NrrdReader, PILReader
  from monai.data.image_writer import ITKWriter, NibabelWriter, PILWriter, register_writer, resolve_writer
  from monai.data.meta_tensor import MetaTensor
  from monai.transforms import LoadImage, SaveImage, moveaxis
  from monai.utils import MetaKeys, OptionalImportError, optional_import
  from tests.utils import TEST_NDARRAYS, assert_allclose
label_desc: Use image node_id 3 for calling the TestLoadSavePNG obj's underlying member method code with example usage: obj.png_rw(test_data, reader, writer, dtype, resample) without return types