code: def define_device(device_name):
      """
      Define the device to use during training and inference.
      If auto it will detect automatically whether to use cuda or cpu
  
      Parameters
      ----------
      device_name : str
          Either "auto", "cpu" or "cuda"
  
      Returns
      -------
      str
          Either "cpu" or "cuda"
      """
      if device_name == "auto":
          if torch.cuda.is_available():
              return "cuda"
          else:
              return "cpu"
      elif device_name == "cuda" and not torch.cuda.is_available():
          return "cpu"
      else:
          return device_name
  
imports: from torch.utils.data import Dataset
  from torch.utils.data import DataLoader, WeightedRandomSampler
  import torch
  import numpy
  import scipy
  import json
  from sklearn.utils import check_array
  import pandas
  import warnings
label_desc: Use image node_id 8 for calling a global function with example usage: define_device(device_name) and returns: str, str, str, device_name