code: def test_segmentation_models_custom_size():
      ctx = mx.context.current_context()
      num_classes = 5
      width = 96
      height = 64
      x = mx.random.uniform(shape=(1, 3, height, width), ctx=ctx)
  
      net = gcv.model_zoo.FCN(
          num_classes,
          backbone="resnet50",
          aux=False,
          ctx=ctx,
          pretrained_base=True,
          height=height,
          width=width,
      )
      result = net.forward(x)
      assert result[0].shape == (1, num_classes, height, width)
      net = gcv.model_zoo.PSPNet(
          num_classes,
          backbone="resnet50",
          aux=False,
          ctx=ctx,
          pretrained_base=True,
          height=height,
          width=width,
      )
      result = net.forward(x)
      assert result[0].shape == (1, num_classes, height, width)
  
      net = gcv.model_zoo.DeepLabV3(
          num_classes,
          backbone="resnet50",
          aux=False,
          ctx=ctx,
          pretrained_base=True,
          height=height,
          width=width,
      )
      result = net.forward(x)
      assert result[0].shape == (1, num_classes, height, width)
  
      net = gcv.model_zoo.DeepLabV3Plus(
          num_classes,
          backbone="resnet50",
          aux=False,
          ctx=ctx,
          pretrained_base=True,
          height=height,
          width=width,
      )
      result = net.forward(x)
      assert result[0].shape == (1, num_classes, height, width)
  
      net = gcv.model_zoo.DeepLabWV3Plus(
          num_classes,
          backbone="resnet50",
          aux=False,
          ctx=ctx,
          pretrained_base=True,
          height=height,
          width=width,
      )
      result = net.forward(x)
      assert result[0].shape == (1, num_classes, height, width)
  
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 24 for calling a global function with example usage: test_segmentation_models_custom_size() without return types