code: def convert_batch_input(form, input_features):
      """Returns a new input and a list of files to be cleaned up."""
      file_index = {}
      files = []
      for k, v in form.multi_items():
          if isinstance(v, UploadFile):
              file_index[v.filename] = v
  
      data = json.loads(form["dataset"])
      for row in data["data"]:
          for i, value in enumerate(row):
              if value in file_index:
                  feature_name = data["columns"][i]
                  if input_features.get(feature_name).type() == AUDIO:
                      row[i] = _write_file(file_index[value], files)
                  else:
                      row[i] = _read_image_buffer(file_index[value])
  
      return data, files
  
imports: import argparse
  import io
  import json
  import logging
  import os
  import sys
  import tempfile
  import pandas
  import torch
  from torchvision.io import decode_image
  from ludwig.api import LudwigModel
  from ludwig.constants import AUDIO, COLUMN
  from ludwig.contrib import add_contrib_callback_args
  from ludwig.globals import LUDWIG_VERSION
  from ludwig.utils.print_utils import get_logging_level_registry, print_ludwig
  from ludwig.utils.server_utils import NumpyJSONResponse
label_desc: Use image node_id 5 for calling a global function with example usage: convert_batch_input(form, input_features) and returns: data,  files