code: def save_training_logs(
      cls,
      log_file: str,
      embedding_name: str,
      model_name: str,
      logs: List,
      **kwargs: Dict,
  ):
      if not os.path.exists(log_file):
          data = {}
      else:
          data = json.loads(open(log_file, "r").read())
  
      if embedding_name not in data:
          data[embedding_name] = {}
  
      data[embedding_name][model_name] = {"logs": logs, **kwargs}
  
      with open(log_file, "w") as f:
          f.write(json.dumps(data, indent=2))
  
imports: import os
  import json
  from typing import List, Dict
label_desc: Use image node_id 1 for calling the BenchMarkHelper obj's underlying member method code with example usage: obj.save_training_logs(cls, log_file, embedding_name, model_name, logs) without return types