class_docstr: CheckpointManager is a class abstraction to manage a training job's
  checkpoints/snapshots with different IO and storage.
docstr: Loads a checkpoint/snapshot from disk.
  Args:
      load_path (str): the file path from which to load
  Returns: De-serialized state (dictionary) that was saved
docstr_tok: ["Loads","a","checkpoint\/snapshot","from","disk",".","Args",":","load_path","(","str",")",":","the","file","path","from","which","to","load","Returns",":","De-serialized","state","(","dictionary",")","that","was","saved"]
code: def load(self, load_path: str):
      """
      Loads a checkpoint/snapshot from disk.
      Args:
          load_path (str): the file path from which to load
      Returns: De-serialized state (dictionary) that was saved
      """
      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 3 for calling the PyTextCheckpointManagerInterface obj's underlying member method code with example usage: obj.load(load_path) without return types