code: def load_pos_neg(data_path):
      """load_pos_neg"""
      train_eid = []
      train_src = []
      train_dst = []
      with open(data_path) as f:
          eid = 0
          for idx, line in tqdm.tqdm(enumerate(f)):
              src, dst = line.strip().split("\t")
              train_src.append(int(src))
              train_dst.append(int(dst))
              train_eid.append(int(eid))
              eid += 1
      # concate the the pos data and neg data
      train_eid = np.array(train_eid, dtype="int64")
      train_src = np.array(train_src, dtype="int64")
      train_dst = np.array(train_dst, dtype="int64")
  
      returns = {
          "train_data": (train_src, train_dst, train_eid),
      }
      return returns
  
imports: import argparse
  import time
  import glob
  import os
  import numpy
  import pgl
  from pgl.utils.logger import log
  from pgl.utils import paddle_helper
  import paddle
  import paddle.fluid
  import tqdm
  import reader
  import model
label_desc: Use image node_id 2 for calling a global function with example usage: load_pos_neg(data_path) and returns: returns