class_docstr: Save and restore model and optimizer states.
class_docstr_tok: ["Save","and","restore","model","and","optimizer","states","."]
code: def prepare(self, directory: str):
      # create checkpoint directory if it doesn't
      # already exist
      mkdir(directory)
  
imports: import errno
  import logging
  import os
  import re
  import shutil
  import signal
  import tempfile
  import uuid
  from abc import ABC, abstractmethod
  from glob import glob
  from typing import Any, Dict, Mapping, Optional, Tuple, TYPE_CHECKING
  import torch
  from torch.optim import Optimizer
  from ludwig.api_annotations import DeveloperAPI
  from ludwig.modules.lr_scheduler import LRScheduler
label_desc: Use image node_id 2 for calling the Checkpoint obj's underlying member method code with example usage: obj.prepare(directory) without return types