code: def scheduler_creator(optimizer, config):
      """Returns a learning rate scheduler wrapping the optimizer."""
      return torch.optim.lr_scheduler.StepLR(
          optimizer, step_size=5, gamma=0.9
      )
  
imports: from bigdl.orca.learn.pytorch import Estimator
  from unittest import TestCase
  import pytest
  import torch
  import torch.nn
  import os
  import numpy
  from tempfile import TemporaryDirectory
label_desc: Use image node_id 3 for calling a global function with example usage: scheduler_creator(optimizer, config) and returns: torch