class_docstr: Hugging Face GPT2 Model.
  
  GPT2 is a multi-layer decoder-only Transformer. As such, the encoder
  is simply an identity layer. The decoder is initialized with pretrained
  weights from Hugging Face. Read more about this model here
  <https://huggingface.co/transformers/model_doc/gpt2.html>.
class_docstr_tok: ["Hugging","Face","GPT2","Model",".","GPT2","is","a","multi-layer","decoder-only","Transformer",".","As","such",",","the","encoder","is","simply","an","identity","layer",".","The","decoder","is","initialized","with","pretrained","weights","from","Hugging","Face",".","Read","more","about","this","model","here","<","https",":","\/\/huggingface.co\/transformers\/model_doc\/gpt2.html",">","."]
code: def _get_decoder(self, opt, dict):
      return GPT2Decoder(opt, dict)
  
imports: from typing import Optional
  from parlai.core.params import ParlaiParser
  from parlai.core.opt import Opt
  import os
  import torch
  from parlai.agents.hugging_face.dict import Gpt2DictionaryAgent
  from parlai.core.torch_generator_agent import TorchGeneratorAgent, TorchGeneratorModel
  from parlai.utils.io import PathManager
  from parlai.utils.misc import warn_once
  from parlai.utils.torch import IdentityLayer, padded_tensor
label_desc: Use image node_id 2 for calling the HFGPT2Model obj's underlying member method code with example usage: obj._get_decoder(opt, dict) and returns: GPT2Decoder