code: def load_data(file_, word2id):
      """Load data for node classification."""
      words_label = []
      line_count = 0
      with open(file_, "r") as reader:
          for line in reader:
              line_count += 1
              tokens = line.strip().split(" ")
              word, label = tokens[0], int(tokens[1]) - 1
              if word in word2id:
                  words_label.append((word2id[word], label))
  
      words_label = np.array(words_label, dtype=np.int64)
      np.random.shuffle(words_label)
  
      logging.info(
          "%d/%d word_label pairs have been loaded"
          % (len(words_label), line_count)
      )
      return words_label
  
imports: import argparse
  import sys
  import os
  import tqdm
  import time
  import math
  import logging
  import random
  import pickle
  import numpy
  import sklearn.metrics
  from sklearn.metrics import f1_score
  import pgl
  import paddle.fluid
  import paddle.fluid.layers
  import Dataset
  from utils import *
label_desc: Use image node_id 2 for calling a global function with example usage: load_data(file_, word2id) and returns: words_label