code: def test_center_net_models():
      ctx = mx.context.current_context()
      x = mx.random.uniform(
          shape=(1, 3, 512, 512), ctx=ctx
      )  # allow non-squre and larger inputs
      models = [
          "center_net_resnet18_v1b_voc",
          "center_net_resnet50_v1b_coco",
      ]
      if not mx.context.current_context().device_type == "gpu":
          models = ["center_net_resnet18_v1b_voc"]
      if hasattr(
          mx.gluon.contrib.cnn, "ModulatedDeformableConvolution"
      ):
          models.append("center_net_resnet18_v1b_dcnv2_voc")
      _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 11 for calling a global function with example usage: test_center_net_models() without return types