code: def maybe_load_model(savedir, container):
    
    if savedir is None:
      return
  
    state_path = os.path.join(os.path.join(savedir, 'training_state.pkl.zip'))
    if container is not None:
      logger.log("Attempting to download model from Azure")
      found_model = container.get(savedir, 'training_state.pkl.zip')
    else:
      found_model = os.path.exists(state_path)
    if found_model:
      state = pickle_load(state_path, compression=True)
      model_dir = "model-{}".format(state["num_iters"])
      if container is not None:
        container.get(savedir, model_dir)
      U.load_state(os.path.join(savedir, model_dir, "saved"))
      logger.log("Loaded models checkpoint at {} iterations".format(
          state["num_iters"]))
      return state
docs: Load model if present at the specified path.