code: def _bounce_to_bbox(points):
      """Bounce potentially unbounded points to [0, 1].
  
      Bouncing occurs by exact reflection, i.e. a pre-bound point at 1.1 is moved
      to 0.9, -0.2 -> 0.2. This theoretically can occur multiple times, e.g.
      2.3 -> -0.7 -> 0.3
  
      Implementation
      points <- points % 2
      return min(2 - points, points)
  
      Args:
        points: float array
  
      Returns:
        tensor with same shape/dtype but values in [0, 1].
      """
      points = points % 2
      return tf.math.minimum(2 - points, points)
  
imports: import collections
  from tensorflow_datasets.core.utils.lazy_imports_utils import tensorflow
label_desc: Use image node_id 3 for calling a global function with example usage: _bounce_to_bbox(points) and returns: tf