code: def _MakeTestImage(num_channels, datatype):
      if num_channels == 1:
          test_channel_names = ["L"]
      else:
          test_channel_names = ["R", "G", "B", "A", "P.x", "P.y", "P.z"]
      image = np.zeros([64, 64, num_channels], dtype=datatype)
      for i in range(num_channels):
          # Add a block of color to each channel positioned by the channel index.
          image[i : i + 10, i * 2 : i * 2 + 10, i] = i / float(
              num_channels
          )
      return image, test_channel_names[:num_channels]
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import collections
  import tempfile
  from absl.testing import parameterized
  import Imath
  import numpy
  import OpenEXR
  from six.moves import range
  from tensorflow_graphics.io import exr
  from tensorflow_graphics.util import test_case
label_desc: Use image node_id 2 for calling a global function with example usage: _MakeTestImage(num_channels, datatype) and returns: image,  test_channel_names