code: def horizontal_flip(im, prob=0.5):
      """Performs horizontal flip (used for training)."""
      return im[:, ::-1, :] if np.random.uniform() < prob else im
  
file_path: pycls/pycls/datasets/transforms.py
imports: from math import ceil, sqrt
  import cv2
  import numpy
  from PIL import Image
  from pycls.datasets.augment import make_augment
label_desc: Use image node_id 3 for calling a global function with example usage: horizontal_flip(im, prob) and returns: unknown