code: def prepare_inputs_for_generation(
      self,
      decoder_input_ids,
      past_key_values=None,
      attention_mask=None,
      use_cache=None,
      encoder_outputs=None,
      doc_scores=None,
      n_docs=None,
      **kwargs,
  ):
      if past_key_values is not None:
          # if past is defined use only last decoder_input_ids
          decoder_input_ids = decoder_input_ids[:, -1:]
  
      return {
          "input_ids": None,
          "encoder_outputs": encoder_outputs,
          "doc_scores": doc_scores,
          "context_attention_mask": attention_mask,
          "decoder_input_ids": decoder_input_ids,
          "past_key_values": past_key_values,
          "use_cache": use_cache,
          "do_marginalize": True,
          "n_docs": n_docs,
      }
  
imports: import copy
  from dataclasses import dataclass
  from typing import Callable, List, Optional, Tuple, Union
  import torch
  from torch import nn
  from ...configuration_utils import PretrainedConfig
  from ...generation import BeamSearchScorer, GenerationConfig, LogitsProcessorList, StoppingCriteriaList
  from ...modeling_outputs import ModelOutput
  from ...modeling_utils import PreTrainedModel
  from ...utils import add_start_docstrings_to_model_forward, logging, replace_return_docstrings
  from .configuration_rag import RagConfig
  from .retrieval_rag import RagRetriever
label_desc: Use image node_id 4 for calling the RagTokenForGeneration obj's underlying member method code with example usage: obj.prepare_inputs_for_generation(decoder_input_ids, past_key_values, attention_mask, use_cache, encoder_outputs, doc_scores, n_docs) and returns: dict