code: def to_doubleTensor(x: (list, tuple, np.ndarray)):
      """
      Arguments
      ---------
      x : (list, tuple, np.ndarray)
          Input data to be converted to torch double.
  
      Returns
      -------
      tensor : torch.tensor
          Data now in torch.tensor double datatype.
      """
      if isinstance(x, torch.Tensor):
          return x.double()
      if isinstance(x, np.ndarray):
          return torch.from_numpy(x).double()
      else:
          return torch.tensor(x, dtype=torch.double)
  
imports: import os
  import torch
  import logging
  import numpy
  import pickle
  import hashlib
  import csv
  import time
  import torchaudio
  import json
  import re
  from speechbrain.utils.torch_audio_backend import check_torchaudio_backend
label_desc: Use image node_id 10 for calling a global function with example usage: to_doubleTensor(x) and returns: x, torch, torch