code: def __init__(
      self,
      opt: Opt,
      decoder: T5Stack,
      padding_idx: Optional[int] = None,
  ):
      super().__init__()
      self.stack = decoder
      self.padding_idx = padding_idx
      self.paralleled = not opt["t5_model_parallel"]
  
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 1 to create a new ParlaiT5Decoder object from inherited base classes: torch.nn with example: obj = ParlaiT5Decoder(opt, decoder, padding_idx)