code: def test_segmentation_models():
      ctx = mx.context.current_context()
      x = mx.random.uniform(shape=(1, 3, 480, 480), ctx=ctx)
      models = [
          "fcn_resnet101_coco",
          "psp_resnet101_coco",
          "deeplab_resnet101_coco",
          "fcn_resnet101_voc",
          "psp_resnet101_voc",
          "deeplab_resnet101_voc",
          "fcn_resnet50_ade",
          "psp_resnet50_ade",
          "deeplab_resnet50_ade",
          "fcn_resnet101_ade",
          "psp_resnet101_ade",
          "deeplab_resnet101_ade",
          "deeplab_resnest200_ade",
          "psp_resnet101_citys",
          "deeplab_resnet152_voc",
          "deeplab_resnet152_coco",
          "deeplab_v3b_plus_wideresnet_citys",
          "icnet_resnet50_citys",
          "deeplab_resnet50_citys",
          "deeplab_resnet101_citys",
      ]
      _test_model_list(
          models, ctx, x, pretrained=True, pretrained_base=True
      )
      _test_model_list(
          models, ctx, x, pretrained=False, pretrained_base=False
      )
      _test_model_list(
          models, ctx, x, pretrained=False, pretrained_base=True
      )
  
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 23 for calling a global function with example usage: test_segmentation_models() without return types