code: def encode(self, document: "Image", question: str):
      task_prompt = (
          "<s_docvqa><s_question>{user_input}</s_question><s_answer>"
      )
      prompt = task_prompt.replace("{user_input}", question)
      decoder_input_ids = self.pre_processor.tokenizer(
          prompt, add_special_tokens=False, return_tensors="pt"
      ).input_ids
      pixel_values = self.pre_processor(
          document, return_tensors="pt"
      ).pixel_values
  
      return {
          "decoder_input_ids": decoder_input_ids,
          "pixel_values": pixel_values,
      }
  
file_path: transformers/src/transformers/tools/document_question_answering.py
imports: import re
  from ..models.auto import AutoProcessor
  from ..models.vision_encoder_decoder import VisionEncoderDecoderModel
  from ..utils import is_vision_available
  from .base import PipelineTool
label_desc: Use image node_id 2 for calling the DocumentQuestionAnsweringTool obj's underlying member method code with example usage: obj.encode(document, question) and returns: dict