class_docstr: Horizontally flip image and boxes [cxcywh format] with probability `p`.
code: def __call__(self, features):
      rnd = tf.random.uniform(
          [], minval=0.0, maxval=1.0, dtype=tf.float32
      )
      if rnd < self.p:
          return hflip(
              identity(features)
          )  # Identity helps avoid autograph errors.
      else:
          return identity(features)
  
imports: from typing import Any, Dict
  import tensorflow
label_desc: Use image node_id 2 for calling the RandomHorizontalFlip obj's underlying member method code with example usage: obj.__call__(features) and returns: hflip, identity