code: def __init__(self, backbone_cfg=None):
      super().__init__()
      self._backbone_model = GPT2Model.from_cfg(backbone_cfg)
      self._lm_head = nn.Dense(
          units=backbone_cfg.MODEL.vocab_size,
          in_units=backbone_cfg.MODEL.units,
          use_bias=False,
          flatten=False,
      )
      self._lm_head.weight = self._backbone_model._embed.weight
  
imports: import os
  from typing import Tuple
  import mxnet
  from mxnet import use_np, np, npx
  from mxnet.gluon import HybridBlock, nn
  from .base import BACKBONE_REGISTRY
  from ..base import get_model_zoo_home_dir, get_repo_model_zoo_url, get_model_zoo_checksum_dir
  from ..utils.config import CfgNode
  from ..utils.misc import load_checksum_stats, download
  from ..utils.registry import Registry
  from ..initializer import TruncNorm
  from ..attention_cell import MultiHeadAttentionCell
  from ..layers import get_activation, PositionalEmbedding
  from ..data.tokenizers import HuggingFaceByteBPETokenizer
label_desc: Use image node_id 1 to create a new GPT2ForLM object from inherited base classes: HybridBlock with example: obj = GPT2ForLM(backbone_cfg)