def METHOD_NAME():
    """Disable preallocation of full GPU memory on all available GPUs.
    This enables memory growth policy so that TensorFlow will not pre-allocate all
    available GPU memory.
    Preallocation can be more efficient, but can lead to CUDA startup errors when the
    memory is not available (e.g., shared, multi-session and some *nix systems).
    See also: enable_gpu_preallocation
    """
    for gpu in get_available_gpus():
        tf.config.experimental.set_memory_growth(gpu, True)