class_docstr: Wrap T5 in ParlAI.
class_docstr_tok: ["Wrap","T5","in","ParlAI","."]
docstr: Not *quite* sure how to reconcile this with HF.
docstr_tok: ["Not","*","quite","*","sure","how","to","reconcile","this","with","HF","."]
code: def reorder_decoder_incremental_state(
      self, incremental_state: Dict[int, dict], inds: torch.Tensor
  ) -> Dict[int, dict]:
      """
      Not *quite* sure how to reconcile this with HF.
      """
      return {}
  
imports: import torch
  from typing import Optional, Dict, Any, Tuple
  from transformers import T5ForConditionalGeneration
  from parlai.agents.hugging_face.hugging_face import HF_VERSION
  from parlai.agents.hugging_face.dict import T5DictionaryAgent
  from parlai.core.opt import Opt
  from parlai.core.params import ParlaiParser
  from parlai.core.torch_agent import Batch, TorchAgent
  from parlai.core.torch_generator_agent import TorchGeneratorAgent, TorchGeneratorModel
  from parlai.utils.fsdp import is_fsdp, delay_halving
label_desc: Use image node_id 4 for calling the ParlaiT5Model obj's underlying member method code with example usage: obj.reorder_decoder_incremental_state(incremental_state, inds) and returns: dict