code: def pad_images(
      images,
      top_padding=None,
      left_padding=None,
      target_height=None,
      target_width=None,
      bottom_padding=None,
      right_padding=None,
  ):
      """Pad `images` with zeros to the specified `height` and `width`.
  
      Args:
          images: 4D Tensor of shape `(batch, height, width, channels)` or 3D
              Tensor of shape `(height, width, channels)`.
          top_padding: Number of rows of zeros to add on top.
          bottom_padding: Number of rows of zeros to add at the bottom.
          left_padding: Number of columns of zeros to add on the left.
          right_padding: Number of columns of zeros to add on the right.
          target_height: Height of output images.
          target_width: Width of output images.
  
      Returns:
          If `images` were 4D, a 4D float Tensor of shape
              `(batch, target_height, target_width, channels)`
          If `images` were 3D, a 3D float Tensor of shape
              `(target_height, target_width, channels)`
  
      Example:
  
      >>> images = np.random.random((15, 25, 3))
      >>> padded_images = keras.ops.image.pad_images(
      ...     images, 2, 3, target_height=20, target_width=30
      ... )
      >>> padded_images.shape
      (20, 30, 3)
  
      >>> batch_images = np.random.random((2, 15, 25, 3))
      >>> padded_batch = keras.ops.image.pad_images(
      ...     batch_images, 2, 3, target_height=20, target_width=30
      ... )
      >>> padded_batch.shape
      (2, 20, 30, 3)"""
  
      if any_symbolic_tensors((images,)):
          return PadImages(
              top_padding,
              bottom_padding,
              left_padding,
              right_padding,
              target_height,
              target_width,
          ).symbolic_call(images)
  
      return _pad_images(
          images,
          top_padding,
          bottom_padding,
          left_padding,
          right_padding,
          target_height,
          target_width,
      )
  
imports: from keras import backend
  from keras import ops
  from keras.api_export import keras_export
  from keras.backend import KerasTensor
  from keras.backend import any_symbolic_tensors
  from keras.ops.operation import Operation
  from keras.ops.operation_utils import compute_conv_output_shape
label_desc: Use image node_id 7 for calling a global function with example usage: pad_images(images, top_padding, left_padding, target_height, target_width, bottom_padding, right_padding) and returns: _pad_images, PadImages