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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def image_preprocessing(image_buffer, bbox, train, thread_id=0):
 """Decode and preprocess one image for evaluation or training. Args: image_buffer: JPEG encoded string Tensor bbox: 3-D float Tensor of bounding boxes arranged [1, num_boxes, coords] where each coordinate is [0, 1) and the coordinates are arranged as [ymin, xmin, ymax, xmax]. train: boolean thread_id: integer indicating preprocessing thread Returns: 3-D float Tensor containing an appropriately scaled image Raises: ValueError: if user does not provide bounding box """

  if bbox is None:
    raise ValueError('Please supply a bounding box.')

  image = decode_jpeg(image_buffer)
  height = FLAGS.image_size
  width = FLAGS.image_size

  if train:
    image = distort_image(image, height, width, bbox, thread_id)
  else:
    image = eval_image(image, height, width)

  # Finally, rescale to [-1,1] instead of [0, 1)
  image = tf.subtract(image, 0.5)
  image = tf.multiply(image, 2.0)
  return image