code: def __init__(self, config):
      super().__init__(config)
      self.transformer = GPT2Model(config)
      self.lm_head = nn.Linear(
          config.n_embd, config.vocab_size, bias=False
      )
  
      # Initialize weights and apply final processing
      self.post_init()
  
imports: from typing import Optional, Tuple, Union
  import torch
  import torch.nn
  from transformers.activations import ACT2FN
  from transformers.models.gpt2.modeling_gpt2 import BaseModelOutputWithPastAndCrossAttentions, GPT2PreTrainedModel
  from transformers.pytorch_utils import Conv1D
label_desc: Use image node_id 1 to create a new GPT2LMHeadModel object from inherited base classes: GPT2PreTrainedModel with example: obj = GPT2LMHeadModel(config)