code: def test_dnnl_engine_threading():
      net = gluon.nn.HybridSequential()
      net.add(
          gluon.nn.Conv2D(channels=32, kernel_size=3, activation=None)
      )
      net.initialize(ctx=mx.cpu())
  
      loader = gluon.data.DataLoader(
          Dummy(), batch_size=2, num_workers=1
      )
  
      X = (32, 3, 32, 32)
      # trigger dnnl execution thread
      y = net(mx.np.array(np.ones(X))).asnumpy()
  
      # Use Gluon dataloader to trigger different thread.
      # below line triggers different execution thread
      for _ in loader:
          y = net(mx.np.array(np.ones(X))).asnumpy()
          # output should be 056331709 (non-dnnl mode output)
          assert_almost_equal(y[0, 0, 0, 0], np.array(0.056331709))
          break
  
imports: import sys
  import os
  import numpy
  import mxnet
  import pytest
  from mxnet.test_utils import rand_ndarray, assert_almost_equal
  from mxnet import gluon, context, use_np
  from mxnet.gluon import nn
  from mxnet.test_utils import *
  import itertools
label_desc: Use image node_id 2 for calling a global function with example usage: test_dnnl_engine_threading() without return types