code: def deparallelize(self):
      warnings.warn(
          "Like `parallelize`, `deparallelize` is deprecated and will be removed in v5 of Transformers.",
          FutureWarning,
      )
      self.model_parallel = False
      self.device_map = None
      self.first_device = "cpu"
      self.last_device = "cpu"
      self.wte = self.wte.to("cpu")
      for index in range(len(self.h)):
          self.h[index] = self.h[index].to("cpu")
      self.ln_f = self.ln_f.to("cpu")
      torch.cuda.empty_cache()
  
imports: import warnings
  from typing import Optional, Tuple, Union
  import torch
  import torch.fx
  import torch.utils.checkpoint
  from torch import nn
  from torch.nn import BCEWithLogitsLoss, CrossEntropyLoss, MSELoss
  from ...activations import ACT2FN
  from ...modeling_outputs import BaseModelOutputWithPast, CausalLMOutputWithPast, QuestionAnsweringModelOutput, SequenceClassifierOutputWithPast
  from ...modeling_utils import PreTrainedModel
  from ...utils import add_code_sample_docstrings, add_start_docstrings, add_start_docstrings_to_model_forward, is_torch_fx_proxy, logging
  from ...utils.model_parallel_utils import assert_device_map, get_device_map
  from .configuration_gptj import GPTJConfig
label_desc: Use image node_id 3 for calling the GPTJModel obj's underlying member method code with example usage: obj.deparallelize() without return types