code: def parallel_gpu_jobs(allow_growth=True, fraction=0.5):
      """Sets the max used memory as a fraction for tensorflow
      backend
  
      allow_growth :: True of False
  
      fraction :: a float value (e.g. 0.5 means 4gb out of 8gb)
  
      """
  
      import keras.backend as K
      import tensorflow as tf
  
      gpu_options = tf.compat.v1.GPUOptions(
          allow_growth=allow_growth,
          per_process_gpu_memory_fraction=fraction,
      )
      config = tf.compat.v1.ConfigProto(gpu_options=gpu_options)
      session = tf.compat.v1.Session(config=config)
      tf.compat.v1.keras.backend.set_session(session)
  
label_desc: Use image node_id 1 for calling a global function with example usage: parallel_gpu_jobs(allow_growth, fraction) without return types