class_docstr: CheckpointManager is a class abstraction to manage a training job's
  checkpoints/snapshots with different IO and storage.
docstr: Serialize and save checkpoint to given path. State is a dictionary that
  represents the all data to be saved.
  Args:
      state: Dictionary containing data to be saved
      checkpoint_path: path of file to save checkpoint
docstr_tok: ["Serialize","and","save","checkpoint","to","given","path",".","State","is","a","dictionary","that","represents","the","all","data","to","be","saved",".","Args",":","state",":","Dictionary","containing","data","to","be","saved","checkpoint_path",":","path","of","file","to","save","checkpoint"]
code: def save_checkpoint(self, state, checkpoint_path):
      """
      Serialize and save checkpoint to given path. State is a dictionary that
      represents the all data to be saved.
      Args:
          state: Dictionary containing data to be saved
          checkpoint_path: path of file to save checkpoint
      """
      raise NotImplementedError("Not implemented in interface class")
  
imports: import abc
  from typing import List
  import torch
  from pytext.utils.file_io import PathManager
  from pytext.utils.usage import log_class_usage
label_desc: Use image node_id 1 for calling the PyTextCheckpointManagerInterface obj's underlying member method code with example usage: obj.save_checkpoint(state, checkpoint_path) without return types