class_docstr: A harness for stopping training.
class_docstr_tok: ["A","harness","for","stopping","training","."]
docstr: Load the summary dict from a training loop checkpoint.
  
  :param path:
      Path of the file where to store the state in.
  
  :return:
      The summary dict of the stopper at the time of saving the checkpoint.
docstr_tok: ["Load","the","summary","dict","from","a","training","loop","checkpoint",".",":","param","path",":","Path","of","the","file","where","to","store","the","state","in",".",":","return",":","The","summary","dict","of","the","stopper","at","the","time","of","saving","the","checkpoint","."]
code: def load_summary_dict_from_training_loop_checkpoint(
      path: Union[str, pathlib.Path]
  ) -> Mapping[str, Any]:
      """Load the summary dict from a training loop checkpoint.
  
      :param path:
          Path of the file where to store the state in.
  
      :return:
          The summary dict of the stopper at the time of saving the checkpoint.
      """
      logger.info(
          f"=> loading stopper summary dict from training loop checkpoint in '{path}'"
      )
      checkpoint = torch.load(path)
      logger.info(
          f"=> loaded stopper summary dictionary from checkpoint in '{path}'"
      )
      return checkpoint["stopper_dict"]
  
file_path: pykeen/src/pykeen/stoppers/stopper.py
imports: import logging
  import pathlib
  from abc import ABC, abstractmethod
  from typing import Any, List, Mapping, Union
  import torch
label_desc: Use image node_id 6 for calling the Stopper obj's underlying member method code with example usage: obj.load_summary_dict_from_training_loop_checkpoint(path) and returns: checkpoint