code: def prepare_inputs_for_generation(
      self,
      decoder_input_ids,
      past=None,
      attention_mask=None,
      head_mask=None,
      decoder_head_mask=None,
      cross_attn_head_mask=None,
      use_cache=None,
      encoder_outputs=None,
      decoder_encoder_input_ids=None,
      **kwargs,
  ):
      # cut decoder_input_ids if past is used
      if past is not None:
          cut_decoder_input_ids = decoder_input_ids[:, -1:]
      else:
          cut_decoder_input_ids = decoder_input_ids
  
      if "full_hidden_states" not in kwargs:
          kwargs["full_hidden_states"] = []  # initializing the list
  
      return {
          "input_ids": None,  # encoder_outputs is defined. input_ids not needed
          "encoder_input_ids": decoder_encoder_input_ids,
          "encoder_outputs": encoder_outputs,
          "past_key_values": past,
          "decoder_input_ids": cut_decoder_input_ids,  # last decoder_input_ids
          "full_decoder_input_ids": decoder_input_ids,  # full_decoder_input_ids
          "full_hidden_states": kwargs["full_hidden_states"],
          "decoder_linking": kwargs["decoder_linking"],
          "decoder_pairing": kwargs["decoder_pairing"],
          "attention_mask": attention_mask,
          "head_mask": head_mask,
          "decoder_head_mask": decoder_head_mask,
          "cross_attn_head_mask": cross_attn_head_mask,
          "use_cache": use_cache,
      }
  
imports: import sys
  import os
  from typing import Optional, Tuple, Any, Dict, Iterable
  import logging
  import torch
  import torch.utils.checkpoint
  from torch import nn
  import torch.nn.init
  import torch.nn.functional
  from transformers.models.t5.modeling_t5 import T5PreTrainedModel, T5Model, T5_INPUTS_DOCSTRING, _CONFIG_FOR_DOC
  from transformers.file_utils import add_start_docstrings_to_model_forward, replace_return_docstrings
  from .modeling_outputs import MySeq2SeqLMOutput
  from util import logsumexp, dummy_padding, prepare_pair_embeddings, one_hot_ignore_negative, batched_masked_select
label_desc: Use image node_id 6 for calling the T5Coref obj's underlying member method code with example usage: obj.prepare_inputs_for_generation(decoder_input_ids, past, attention_mask, head_mask, decoder_head_mask, cross_attn_head_mask, use_cache, encoder_outputs, decoder_encoder_input_ids) and returns: dict