code: def convert_tensors_to_list(
      model_output: transformers.utils.ModelOutput,
  ):
      """Converts the model output, which consists of a Tuple of Tensors to a Tuple of lists, while preserving the
      original dimensions. The converted output is returned.
      Args:
          model_output (transformers.utils.ModelOutput): The model's output of the forward pass.
      Returns:
          The converted model output as a tuple of lists and the last hidden state tensor also seperately.
      Raises:
          TypeError: If the model output is not a tuple of tensors."""
      # Model ouputs can't be unpacked directly, convert to tuple first
      model_output_tensors = model_output.to_tuple()
      model_output_numpy = []
  
      # Recursively search each tuple entry
      for output_value in model_output_tensors:
          if isinstance(output_value, torch.Tensor):
              model_output_numpy.append(
                  squeeze(output_value.cpu())
                  .numpy()
                  .astype(np.float32)
                  .tolist()
              )
  
          elif isinstance(output_value, tuple):
              model_output_numpy.append(decode_tuple(output_value))
  
      return model_output_numpy, model_output_tensors[0].cpu()
  
imports: import os
  import random
  from typing import Any, Union
  import numpy
  import torch
  from PIL import Image
  from torch import squeeze
  import jsonlines
  import requests
  import transformers
  from adapters import AutoAdapterModel, init
  from transformers import AlbertConfig, BartConfig, BatchEncoding, BeitConfig, BeitImageProcessor, BertConfig, CLIPProcessor, CLIPVisionConfig, CLIPVisionModelWithProjection, DebertaConfig, DebertaV2Config, DistilBertConfig, EncoderDecoderConfig, EncoderDecoderModel, GPT2Config, GPTJConfig, MBartConfig, RobertaConfig, T5Config, ViTConfig, ViTImageProcessor, XLMRobertaConfig
label_desc: Use image node_id 10 for calling a global function with example usage: convert_tensors_to_list(model_output) and returns: model_output_numpy,  model_output_tensors