code: def test_imagenet_models():
      ctx = mx.context.current_context()
  
      # 224x224
      x = mx.random.uniform(shape=(2, 3, 224, 224), ctx=ctx)
      models = [
          "resnet18_v1",
          "resnet34_v1",
          "resnet50_v1",
          "resnet101_v1",
          "resnet152_v1",
          "resnet18_v1b",
          "resnet34_v1b",
          "resnet50_v1b_gn",
          "resnet50_v1b",
          "resnet101_v1b",
          "resnet152_v1b",
          "resnet50_v1c",
          "resnet101_v1c",
          "resnet152_v1c",
          "resnet50_v1d",
          "resnet101_v1d",
          "resnet152_v1d",
          "resnet50_v1e",
          "resnet101_v1e",
          "resnet152_v1e",
          "resnet18_v2",
          "resnet34_v2",
          "resnet50_v2",
          "resnet101_v2",
          "resnet152_v2",
          "resnest50",
          "resnest101",
          "resnest200",
          "resnest269",
          "resnext50_32x4d",
          "resnext101_32x4d",
          "resnext101_64x4d",
          "se_resnext50_32x4d",
          "se_resnext101_32x4d",
          "se_resnext101_64x4d",
          "se_resnet18_v1",
          "se_resnet34_v1",
          "se_resnet50_v1",
          "se_resnet101_v1",
          "se_resnet152_v1",
          "se_resnet18_v2",
          "se_resnet34_v2",
          "se_resnet50_v2",
          "se_resnet101_v2",
          "se_resnet152_v2",
          "senet_154",
          "squeezenet1.0",
          "squeezenet1.1",
          "mobilenet1.0",
          "mobilenet0.75",
          "mobilenet0.5",
          "mobilenet0.25",
          "mobilenetv2_1.0",
          "mobilenetv2_0.75",
          "mobilenetv2_0.5",
          "mobilenetv2_0.25",
          "mobilenetv3_large",
          "mobilenetv3_small",
          "densenet121",
          "densenet161",
          "densenet169",
          "densenet201",
          "darknet53",
          "alexnet",
          "googlenet",
          "vgg11",
          "vgg11_bn",
          "vgg13",
          "vgg13_bn",
          "vgg16",
          "vgg16_bn",
          "vgg19",
          "vgg19_bn",
          "residualattentionnet56",
          "residualattentionnet92",
          "residualattentionnet128",
          "residualattentionnet164",
          "residualattentionnet200",
          "residualattentionnet236",
          "residualattentionnet452",
          "resnet18_v1b_0.89",
          "resnet50_v1d_0.86",
          "resnet50_v1d_0.48",
          "resnet50_v1d_0.37",
          "resnet50_v1d_0.11",
          "resnet101_v1d_0.76",
          "resnet101_v1d_0.73",
      ]
      _test_model_list(models, ctx, x)
  
      # 299x299
      x = mx.random.uniform(shape=(2, 3, 299, 299), ctx=ctx)
      models = [
          "inceptionv3",
          "nasnet_5_1538",
          "nasnet_7_1920",
          "nasnet_6_4032",
          "xception",
      ]
      _test_model_list(models, ctx, x)
  
      # 331x331
      x = mx.random.uniform(shape=(2, 3, 331, 331), ctx=ctx)
      models = ["nasnet_5_1538", "nasnet_7_1920", "nasnet_6_4032"]
      _test_model_list(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 6 for calling a global function with example usage: test_imagenet_models() without return types