code: def __init__(self, path, num_points):
      import h5py
  
      self.f = h5py.File(path)
      self.num_points = num_points
  
      self.n_train = self.f["train/data"].shape[0]
      self.n_valid = int(self.n_train / 5)
      self.n_train -= self.n_valid
      self.n_test = self.f["test/data"].shape[0]
  
file_path: dgl/examples/pytorch/pointcloud/edgeconv/modelnet.py
imports: import numpy
  from torch.utils.data import Dataset
label_desc: Use image node_id 1 to create a new ModelNet object from inherited base classes: object with example: obj = ModelNet(path, num_points)