code: def deparallelize(self):
      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: from typing import Tuple
  import numpy
  import torch
  import torch.utils.checkpoint
  from torch import nn
  from torch.nn import CrossEntropyLoss
  from transformers.activations import ACT2FN
  from transformers.modeling_outputs import BaseModelOutputWithPast, CausalLMOutputWithPast
  from transformers.modeling_utils import PreTrainedModel
  from transformers.utils import logging
  from transformers.utils.model_parallel_utils import assert_device_map, get_device_map
  from .configuration_codegen import CodeGenConfig
label_desc: Use image node_id 3 for calling the CodeGenModel obj's underlying member method code with example usage: obj.deparallelize() without return types