code: def __init__(self, num_nodes):
      trainer_id = int(os.getenv("PADDLE_TRAINER_ID", "0"))
      trainer_count = int(os.getenv("PADDLE_TRAINERS_NUM", "1"))
      train_usr = np.arange(trainer_id, num_nodes, trainer_count)
      # self.data = (train_usr, train_usr)
      self.data = train_usr
  
imports: import os
  import argparse
  import traceback
  import re
  import io
  import yaml
  import numpy
  from easydict import EasyDict
  from pgl.utils import paddle_helper
  from pgl.graph_wrapper import BatchGraphWrapper
  import propeller.paddle
  from propeller.paddle.data import Dataset
  import paddle.fluid
  import paddle.fluid.layers
  import logging
  from propeller import log
  from ernie.tokenizing_ernie import ErnieTokenizer
  from ernie.tokenizing_ernie import ErnieTinyTokenizer
  from dataset.graph_reader import BatchGraphGenerator
  from models.encoder import Encoder
  from models.pretrain_model_loader import PretrainedModelLoader
  from models.loss import Loss
  from optimization import optimization
label_desc: Use image node_id 1 to create a new PredictData object from inherited base classes: object with example: obj = PredictData(num_nodes)