code: def test_pad_images(
      self,
      top_padding,
      left_padding,
      target_height,
      target_width,
      bottom_padding,
      right_padding,
  ):
      image = np.random.uniform(size=(3, 3, 1))
      padded_image = kimage.pad_images(
          image,
          top_padding,
          left_padding,
          target_height,
          target_width,
          bottom_padding,
          right_padding,
      )
      if target_height is None:
          target_height = image.shape[0] + top_padding + bottom_padding
      if target_width is None:
          target_width = image.shape[1] + left_padding + right_padding
      ref_padded_image = tf.image.pad_to_bounding_box(
          image, top_padding, left_padding, target_height, target_width
      )
      self.assertEqual(
          tuple(padded_image.shape), tuple(ref_padded_image.shape)
      )
      self.assertAllClose(
          ref_padded_image.numpy(),
          backend.convert_to_numpy(padded_image),
          atol=1e-5,
      )
  
imports: import math
  import numpy
  import pytest
  import scipy.ndimage
  import tensorflow
  from absl.testing import parameterized
  from keras import backend
  from keras import testing
  from keras.backend.common.keras_tensor import KerasTensor
  from keras.ops import image
label_desc: Use image node_id 5 for calling the ImageOpsCorrectnessTest obj's underlying member method code with example usage: obj.test_pad_images(top_padding, left_padding, target_height, target_width, bottom_padding, right_padding) without return types