code: def set_device(func):
      """
      Decorator for setting device.
  
      HF's model parallel uses `torch.cuda.set_device`, which does not vibe well with
      ParlAI.
      """
  
      def wrap(*args, **kwargs):
          self = args[0]
          # self.paralleled implies whether the model has been paralleled.
          # it is set to the opposite of `opt['t5_model_parallel]`
          parallel = hasattr(self, "paralleled") and not self.paralleled
          if torch.cuda.is_available() and parallel:
              torch.cuda.set_device("cuda:0")
          ret = func(*args, **kwargs)
          if torch.cuda.is_available() and parallel:
              torch.cuda.set_device("cuda:0")
          return ret
  
      return wrap
  
imports: import torch
  from typing import Optional, Dict, Any, Tuple
  from transformers import T5ForConditionalGeneration
  from parlai.agents.hugging_face.hugging_face import HF_VERSION
  from parlai.agents.hugging_face.dict import T5DictionaryAgent
  from parlai.core.opt import Opt
  from parlai.core.params import ParlaiParser
  from parlai.core.torch_agent import Batch, TorchAgent
  from parlai.core.torch_generator_agent import TorchGeneratorAgent, TorchGeneratorModel
  from parlai.utils.fsdp import is_fsdp, delay_halving
label_desc: Use image node_id 3 for calling a global function with example usage: set_device(func) and returns: wrap, ret