code: def translate(
      self, x, scale=(2 / 3, 3 / 2), shift=(-0.2, 0.2), size=3
  ):
      xyz1 = np.random.uniform(low=scale[0], high=scale[1], size=[size])
      xyz2 = np.random.uniform(low=shift[0], high=shift[1], size=[size])
      x = np.add(np.multiply(x, xyz1), xyz2).astype("float32")
      return x
  
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 2 for calling the ShapeNetDataset obj's underlying member method code with example usage: obj.translate(x, scale, shift, size) and returns: x