class_docstr: Wrapper for a TransformerGeneratorModel to unflatten/flatten the incremental state.
  
  Unflattening/flattening will occur before passing the incremental state into and out
  of .reorder_decoder_incremental_state(). We also support .output(), which is also
  traced.
code: def output(self, tensor: torch.Tensor) -> torch.Tensor:
      return self.module.output(tensor)
  
imports: from collections import defaultdict
  from typing import Dict, List, Optional, Tuple
  import torch.jit
  from parlai.agents.bart.bart import BartAgent
  from parlai.core.dict import DictionaryAgent
  from parlai.core.torch_agent import TorchAgent
  from parlai.utils.bpe import Gpt2BpeHelper, SubwordBPEHelper
  from parlai.torchscript.tokenizer import ScriptableDictionaryAgent
  from torch import nn
label_desc: Use image node_id 2 for calling the ModelIncrStateFlattener obj's underlying member method code with example usage: obj.output(tensor) and returns: self