class_docstr: GPT2 with Retriever Model.
  
  A GPT2 model that receives documents from a retriever.
class_docstr_tok: ["GPT2","with","Retriever","Model",".","A","GPT2","model","that","receives","documents","from","a","retriever","."]
docstr: Override to make sure dimensions of enc_out are appropriate.
  
  :param input:
      input for the decoder
  :param encoder_state:
      RAG encoder states
  :param incr_state:
      incremental decoder state
  
  :return (output, new_incr_state):
      return the output token distribution, as well as new incremental state.
docstr_tok: ["Override","to","make","sure","dimensions","of","enc_out","are","appropriate",".",":","param","input",":","input","for","the","decoder",":","param","encoder_state",":","RAG","encoder","states",":","param","incr_state",":","incremental","decoder","state",":","return","(","output",",","new_incr_state",")",":","return","the","output","token","distribution",",","as","well","as","new","incremental","state","."]
code: def decoder(
      self,
      input: torch.LongTensor,
      encoder_state: Tuple[Any, ...],
      incr_state: Optional[Dict[str, Any]] = None,
  ) -> Tuple[torch.Tensor, Optional[Dict[str, Any]]]:
      """
      Override to make sure dimensions of enc_out are appropriate.
  
      :param input:
          input for the decoder
      :param encoder_state:
          RAG encoder states
      :param incr_state:
          incremental decoder state
  
      :return (output, new_incr_state):
          return the output token distribution, as well as new incremental state.
      """
      enc_out, *_ = encoder_state
      if enc_out.dim() == 2:
          enc_out = enc_out.t()
      else:
          enc_out = enc_out.squeeze(-1)
      dec_out, incr_state = self.seq2seq_decoder(
          input, enc_out, incr_state
      )  # type: ignore
      return dec_out, incr_state
  
imports: from typing import Optional, Type, Tuple, List, Dict, Any
  import torch
  import torch.nn
  from parlai.agents.fid.fid import FidModel, concat_enc_outs
  from parlai.agents.hugging_face.gpt2 import GPT2Decoder, Gpt2Agent
  from parlai.agents.rag.args import RetrieverType
  from parlai.agents.rag.modules import RagModel
  from parlai.agents.rag.retrievers import Document, BLANK_DOC, SearchQuerySearchEngineRetriever, retriever_factory, RagRetriever
  from parlai.core.dict import DictionaryAgent
  from parlai.core.opt import Opt
  import parlai.utils.logging
  from projects.seeker.agents.seeker_modules import ComboFidSearchQuerySearchEngineRetriever
  from projects.seeker.agents.seeker_modules import combo_fid_retriever_factory, interleave_fid_combo_outputs, ComboFidModel
label_desc: Use image node_id 6 for calling the GPT2WithRetrieverModel obj's underlying member method code with example usage: obj.decoder(input, encoder_state, incr_state) and returns: dec_out,  incr_state