code: def test_dnnl_ndarray_slice():
      ctx = mx.cpu()
      net = gluon.nn.HybridSequential()
      net.add(
          gluon.nn.Conv2D(channels=32, kernel_size=3, activation=None)
      )
      net.initialize(ctx=ctx)
      x = mx.np.array(np.ones([32, 3, 224, 224]), ctx=ctx)
      y = net(x)
  
      # trigger computation on ndarray slice
      assert_almost_equal(
          y[0].asnumpy()[0, 0, 0], np.array(0.056331709)
      )
  
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 1 for calling a global function with example usage: test_dnnl_ndarray_slice() without return types