code: def box_list_scale(boxlist, y_scale, x_scale, scope=None):
      """scale box coordinates in x and y dimensions.
  
      Args:
        boxlist: BoxList holding N boxes
        y_scale: (float) scalar tensor
        x_scale: (float) scalar tensor
        scope: name scope.
  
      Returns:
        boxlist: BoxList holding N boxes
      """
      with tf.name_scope(scope, "Scale"):
          y_scale = tf.cast(y_scale, tf.float32)
          x_scale = tf.cast(x_scale, tf.float32)
          y_min, x_min, y_max, x_max = tf.split(
              value=boxlist.get(), num_or_size_splits=4, axis=1
          )
          y_min = y_scale * y_min
          y_max = y_scale * y_max
          x_min = x_scale * x_min
          x_max = x_scale * x_max
          scaled_boxlist = box_list.BoxList(
              tf.concat([y_min, x_min, y_max, x_max], 1)
          )
          return _copy_extra_fields(scaled_boxlist, boxlist)
  
file_path: DALI/docs/examples/use_cases/tensorflow/efficientdet/pipeline/tf/preprocessor.py
imports: import tensorflow.compat.v1
  from pipeline.anchors_utils import box_list
label_desc: Use image node_id 9 for calling a global function with example usage: box_list_scale(boxlist, y_scale, x_scale, scope) and returns: _copy_extra_fields