code: def test_classification_models():
      ctx = mx.context.current_context()
      x = mx.random.uniform(shape=(2, 3, 32, 32), ctx=ctx)
      cifar_models = [
          "cifar_resnet20_v1",
          "cifar_resnet56_v1",
          "cifar_resnet110_v1",
          "cifar_resnet20_v2",
          "cifar_resnet56_v2",
          "cifar_resnet110_v2",
          "cifar_wideresnet16_10",
          "cifar_wideresnet28_10",
          "cifar_wideresnet40_8",
          "cifar_resnext29_32x4d",
          "cifar_resnext29_16x64d",
          "cifar_residualattentionnet56",
          "cifar_residualattentionnet92",
          "cifar_residualattentionnet452",
      ]
      _test_model_list(cifar_models, ctx, x)
  
imports: from __future__ import print_function
  import warnings
  import logging
  import mxnet
  from mxnet.contrib.quantization import *
  from ..unittests.common import try_gpu, with_cpu
  import gluoncv
label_desc: Use image node_id 5 for calling a global function with example usage: test_classification_models() without return types