code: def get_pred_ratio(
      pred_ratio_mean: List[float], pred_ratio_var: List[float]
  ):
      idx = random.randint(0, len(pred_ratio_mean) - 1)
      prm = pred_ratio_mean[idx]
      prv = pred_ratio_var[idx]
      return random.uniform(prm - prv, prm + prv) if prv > 0 else prm
  
file_path: vissl/vissl/data/ssl_transforms/masked_image_modeling.py
imports: import math
  import random
  from typing import Any, Dict, List, Tuple
  import numpy
  import torch
  from classy_vision.dataset.transforms import register_transform
  from classy_vision.dataset.transforms.classy_transform import ClassyTransform
label_desc: Use image node_id 1 for calling a global function with example usage: get_pred_ratio(pred_ratio_mean, pred_ratio_var) and returns: unknown