code: def __getitem__(self, i):
      inds = np.random.choice(
          self.data[i].shape[0], self.num_points, replace=True
      )
      x = self.data[i][inds, : self.dim]
      y = self.label[i][inds]
      cat = self.category[i]
      if self.mode == "train":
          x = self.translate(x, size=self.dim)
      x = x.astype(np.float)
      y = y.astype(np.int)
      return x, y, cat
  
imports: import json
  import os
  from zipfile import ZipFile
  import dgl
  import numpy
  import tqdm
  from dgl.data.utils import download, get_download_dir
  from scipy.sparse import csr_matrix
  from torch.utils.data import Dataset
label_desc: Use image node_id 4 for calling the ShapeNetDataset obj's underlying member method code with example usage: obj.__getitem__(i) and returns: x,  y,  cat