code: def test_tiff_file_dataset():
      """Test case for TIFFDataset."""
      width = 560
      height = 320
      channels = 4
  
      images = []
      for filename in [
          "small-00.png",
          "small-01.png",
          "small-02.png",
          "small-03.png",
          "small-04.png",
      ]:
          with open(
              os.path.join(
                  os.path.dirname(os.path.abspath(__file__)),
                  "test_image",
                  filename,
              ),
              "rb",
          ) as f:
              png_contents = f.read()
          image_v = tf.image.decode_png(png_contents, channels=channels)
          assert image_v.shape == [height, width, channels]
          images.append(image_v)
  
      filename = os.path.join(
          os.path.dirname(os.path.abspath(__file__)),
          "test_image",
          "small.tiff",
      )
  
      num_repeats = 2
  
      dataset = tfio.experimental.IODataset.from_tiff(filename).repeat(
          num_repeats
      )
      i = 0
      for v in dataset:
          np.all(images[i % 5] == v)
          i += 1
      assert i == 10
  
imports: import os
  import numpy
  import tensorflow
  import tensorflow_io
label_desc: Use image node_id 3 for calling a global function with example usage: test_tiff_file_dataset() without return types