class_docstr: Ogbn Arxiv Dataset import and implementation.
  
  Attributes:
  
      graph (pgl.Graph): The :code:`Graph` data object.
  
      feature (numpy.ndarray): The feature of all nodes.
  
      y (numpy.ndarray): Labels for each nodes.
  
      num_classes (int): Number of classes.
  
      train_index (numpy.ndarray): The index for nodes in training set.
  
      val_index (numpy.ndarray): The index for nodes in validation set.
  
      test_index (numpy.ndarray): The index for nodes in test set.
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code: def _load_data(self):
      split_idx = self.dataset.get_idx_split()
      train_idx = split_idx["train"]
      valid_idx = split_idx["valid"]
      test_idx = split_idx["test"]
      ogb_graph, label = self.dataset[0]
  
      edges = ogb_graph["edge_index"].T
      graph = Graph(num_nodes=ogb_graph["num_nodes"], edges=edges)
  
      self.graph = graph
      self.feature = ogb_graph["node_feat"]
      self.y = label
      self.num_classes = self.dataset.num_classes
      self.train_index = train_idx
      self.val_index = valid_idx
      self.test_index = test_idx
  
imports: import os
  import io
  import sys
  import numpy
  import pickle
  from pgl.graph import Graph
label_desc: Use image node_id 2 for calling the OgbnArxivDataset obj's underlying member method code with example usage: obj._load_data() without return types