class_docstr: Wrapper around Scannet that creates train and test datasets.
  
  Parameters
  ----------
  dataset_opt: omegaconf.DictConfig
      Config dictionary that should contain
  
          - dataroot
          - version
          - max_num_point (optional)
          - use_instance_labels (optional)
          - use_instance_bboxes (optional)
          - donotcare_class_ids (optional)
          - pre_transforms (optional)
          - train_transforms (optional)
          - val_transforms (optional)
class_docstr_tok: ["Wrapper","around","Scannet","that","creates","train","and","test","datasets",".","Parameters","--","--","--","--","--","dataset_opt",":","omegaconf.DictConfig","Config","dictionary","that","should","contain","-","dataroot","-","version","-","max_num_point","(","optional",")","-","use_instance_labels","(","optional",")","-","use_instance_bboxes","(","optional",")","-","donotcare_class_ids","(","optional",")","-","pre_transforms","(","optional",")","-","train_transforms","(","optional",")","-","val_transforms","(","optional",")"]
code: def path_to_submission(self):
      return self.train_dataset.path_to_submission
  
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 2 for calling the ScannetDataset obj's underlying member method code with example usage: obj.path_to_submission() and returns: self