code: def load_reddit_data():
      dataset = pgl.dataset.RedditDataset()
      log.info("Preprocess finish")
      log.info("Train Examples: %s" % len(dataset.train_index))
      log.info("Val Examples: %s" % len(dataset.val_index))
      log.info("Test Examples: %s" % len(dataset.test_index))
      log.info("Num nodes %s" % dataset.graph.num_nodes)
      log.info("Num edges %s" % dataset.graph.num_edges)
      log.info("Average Degree %s" % np.mean(dataset.graph.indegree()))
  
      graph = dataset.graph
      train_index = dataset.train_index
      val_index = dataset.val_index
      test_index = dataset.test_index
  
      train_label = dataset.train_label
      val_label = dataset.val_label
      test_label = dataset.test_label
      feature = dataset.feature
  
      return (
          graph,
          (train_index, val_index, test_index),
          (train_label, val_label, test_label),
          feature,
      )
  
file_path: PGL/examples/gnn_depoly/node_classification_with_sampling/train.py
imports: import os
  import sys
  import argparse
  import numpy
  import paddle
  import pgl
  import paddle.nn
  from paddle.io import Dataset, DataLoader
  from pgl.utils.logger import log
  from paddle.optimizer import Adam
  from paddle.framework import core
  from dataset import ShardedDataset
  from models import GraphSage, GAT
label_desc: Use image node_id 1 for calling a global function with example usage: load_reddit_data() and returns: graph,  train_index,  val_index,  test_index,  train_label,  val_label,  test_label,  feature