code: def read_label_mapping(
      filename, label_from="raw_category", label_to="nyu40id"
  ):
      assert os.path.isfile(filename)
      mapping = dict()
      with open(filename) as csvfile:
          reader = csv.DictReader(csvfile, delimiter="\t")
          for row in reader:
              mapping[row[label_from]] = int(row[label_to])
      if represents_int(list(mapping.keys())[0]):
          mapping = {int(k): v for k, v in mapping.items()}
      return mapping
  
imports: import os
  import os.path
  import shutil
  import json
  import torch
  from glob import glob
  import sys
  import csv
  import logging
  import numpy
  from plyfile import PlyData, PlyElement
  from torch_geometric.data import Data, InMemoryDataset, download_url, extract_zip
  import torch_geometric.transforms
  import multiprocessing
  import pandas
  import tempfile
  import urllib
  from urllib.request import urlopen
  from torch_points3d.datasets.base_dataset import BaseDataset
  import torch_points3d.core.data_transform
  from .None import IGNORE_LABEL
label_desc: Use image node_id 7 for calling a global function with example usage: read_label_mapping(filename, label_from, label_to) and returns: mapping