code: def get_epoch_lr(cur_epoch, cfg):
      """
      Retrieves the lr for the given epoch (as specified by the lr policy).
      Args:
          cfg (config): configs of hyper-parameters of ADAM, includes base
          learning rate, betas, and weight decay.
          cur_epoch (float): the number of epoch of the current training stage.
      """
      return lr_policy.get_lr_at_epoch(cfg, cur_epoch)
  
file_path: SlowFast/slowfast/models/optimizer.py
imports: import torch
  import slowfast.utils.lr_policy
label_desc: Use image node_id 3 for calling a global function with example usage: get_epoch_lr(cur_epoch, cfg) and returns: lr_policy