code: def round_sigfigs(
      x: Union[float, "torch.Tensor"], sigfigs=4
  ) -> float:
      """
      Round value to specified significant figures.
  
      :param x: input number
      :param sigfigs: number of significant figures to return
  
      :returns: float number rounded to specified sigfigs
      """
      x_: float
      if __TORCH_AVAILABLE and isinstance(x, torch.Tensor):
          x_ = x.item()
      else:
          x_ = x  # type: ignore
  
      try:
          if x_ == 0:
              return 0
          return round(
              x_, -(math.floor(math.log10(abs(x_)) - sigfigs + 1))
          )
      except (ValueError, OverflowError) as ex:
          if (
              x_ in [float("inf"), float("-inf")] or x_ != x_
          ):  # inf or nan
              return x_
          else:
              raise ex
  
imports: from collections import deque, OrderedDict
  from typing import Union, Optional, Set, Any, Dict, List, Tuple
  from datetime import timedelta
  import functools
  import math
  import time
  import re
  import shutil
  import json
  import os
  from parlai.core.message import Message
  from parlai.utils.strings import colorize
  from parlai.utils.io import PathManager
  import parlai.utils.logging
label_desc: Use image node_id 7 for calling a global function with example usage: round_sigfigs(x, sigfigs) and returns: round, int, x_