code: def load():
      dataset = pgl.dataset.CoraDataset()
  
      indegree = dataset.graph.indegree()
      dataset.graph.node_feat["words"] = normalize(
          dataset.graph.node_feat["words"]
      )
  
      dataset.graph.tensor()
      train_index = dataset.train_index
      dataset.train_label = paddle.to_tensor(
          np.expand_dims(dataset.y[train_index], -1)
      )
      dataset.train_index = paddle.to_tensor(
          np.expand_dims(train_index, -1)
      )
  
      val_index = dataset.val_index
      dataset.val_label = paddle.to_tensor(
          np.expand_dims(dataset.y[val_index], -1)
      )
      dataset.val_index = paddle.to_tensor(
          np.expand_dims(val_index, -1)
      )
  
      test_index = dataset.test_index
      dataset.test_label = paddle.to_tensor(
          np.expand_dims(dataset.y[test_index], -1)
      )
      dataset.test_index = paddle.to_tensor(
          np.expand_dims(test_index, -1)
      )
  
      return dataset
  
file_path: PGL/examples/gnn_depoly/node_classification_with_full_graph/train.py
imports: import os
  import sys
  import argparse
  import numpy
  import paddle
  import pgl
  import paddle.nn
  from pgl.utils.logger import log
  from paddle.optimizer import Adam
  from models import GCN, GAT, GraphSage
label_desc: Use image node_id 2 for calling a global function with example usage: load() and returns: dataset