code: def smooth(y0, y, nxt_y, alpha=0.2):
      nodes = train_idx.tolist() + val_idx.tolist() + test_idx.tolist()
      pbar = tqdm(total=len(nodes))
      batch_size = 50000
      batch_no = 0
      nxt_y.fill(0)
  
      while batch_no < len(nodes):
          batch = nodes[batch_no : batch_no + batch_size]
          batch = paddle.to_tensor(batch, dtype="int64")
          aggr(batch, y, nxt_y, y0, alpha)
          batch_no += batch_size
          pbar.update(batch_size)
  
file_path: PGL/examples/kddcup2021/MAG240M/r_unimp/post_smoothing.py
imports: import paddle
  from tqdm import tqdm
  import pgl
  import numpy
  import torch
  from ogb.lsc import MAG240MDataset, MAG240MEvaluator
  import time
  import sys
  import os
  import numpy
label_desc: Use image node_id 2 for calling a global function with example usage: smooth(y0, y, nxt_y, alpha) without return types