class_docstr: BART Agent.
  
  Relies on the BART model implemented in fairseq.
  
  If you have a fine-tuned BART model from fairseq, you can specify the
  `--init-fairseq-model` arg, which will convert your fine-tuned model
  to a ParlAI model.
class_docstr_tok: ["BART","Agent",".","Relies","on","the","BART","model","implemented","in","fairseq",".","If","you","have","a","fine-tuned","BART","model","from","fairseq",",","you","can","specify","the","`","--","init-fairseq-model","`","arg",",","which","will","convert","your","fine-tuned","model","to","a","ParlAI","model","."]
docstr: Override to seed decoder with EOS BOS token.
docstr_tok: ["Override","to","seed","decoder","with","EOS","BOS","token","."]
code: def _get_initial_decoder_input(
      self, bsz: int, beam_size: int, dev: torch.device
  ) -> torch.LongTensor:
      """
      Override to seed decoder with EOS BOS token.
      """
      return (
          torch.LongTensor([self.END_IDX, self.START_IDX])  # type: ignore
          .expand(bsz * beam_size, 2)
          .to(dev)
      )
  
imports: import os
  import torch
  from typing import Optional, Dict, Any
  from parlai.agents.bart.convert_fairseq_to_parlai import ConversionScript
  from parlai.agents.bart.modules import BartModel
  from parlai.agents.transformer.transformer import TransformerGeneratorAgent
  from parlai.core.agents import compare_init_model_opts
  from parlai.core.message import Message
  from parlai.core.opt import Opt
  from parlai.core.params import ParlaiParser
  from parlai.core.torch_agent import History
  from parlai.utils.typing import TShared
  from parlai.utils.io import PathManager
  from parlai.zoo.bart.build import download, CONVERSION_ARGS, BART_ARGS
label_desc: Use image node_id 8 for calling the BartAgent obj's underlying member method code with example usage: obj._get_initial_decoder_input(bsz, beam_size, dev) and returns: torch