class_docstr: The user-facing class that provides metric storage functionalities.
  
  In the future we may add support for storing / logging other types of data if needed.
docstr: Put multiple scalars from keyword arguments.
  
  Examples:
  
      storage.put_scalars(loss=my_loss, accuracy=my_accuracy, smoothing_hint=True)
docstr_tok: ["Put","multiple","scalars","from","keyword","arguments",".","Examples",":","storage.put_scalars","(","loss=my_loss",",","accuracy=my_accuracy",",","smoothing_hint=True",")"]
code: def put_scalars(
      self, *, smoothing_hint=True, cur_iter=None, **kwargs
  ):
      """
      Put multiple scalars from keyword arguments.
  
      Examples:
  
          storage.put_scalars(loss=my_loss, accuracy=my_accuracy, smoothing_hint=True)
      """
      for k, v in kwargs.items():
          self.put_scalar(
              k, v, smoothing_hint=smoothing_hint, cur_iter=cur_iter
          )
  
imports: import datetime
  import json
  import logging
  import os
  import time
  from collections import defaultdict
  from contextlib import contextmanager
  from functools import cached_property
  from typing import Optional
  import torch
  from fvcore.common.history_buffer import HistoryBuffer
  from detectron2.utils.file_io import PathManager
label_desc: Use image node_id 4 for calling the EventStorage obj's underlying member method code with example usage: obj.put_scalars() without return types