code: def get_model(name, **kwargs):
      """Returns a pre-defined model by name
  
      Parameters
      ----------
      name : str
          Name of the model.
      pretrained : bool
          Whether to load the pretrained weights for model.
      classes : int
          Number of classes for the output layer.
      ctx : Context, default CPU
          The context in which to load the pretrained weights.
      root : str, default '$MXNET_HOME/models'
          Location for keeping the model parameters.
  
      Returns
      -------
      gluon.HybridBlock
          The model.
      """
      models = {
          "resnet18_v1": resnet18_v1,
          "resnet34_v1": resnet34_v1,
          "resnet50_v1": resnet50_v1,
          "resnet101_v1": resnet101_v1,
          "resnet152_v1": resnet152_v1,
          "resnet18_v2": resnet18_v2,
          "resnet34_v2": resnet34_v2,
          "resnet50_v2": resnet50_v2,
          "resnet101_v2": resnet101_v2,
          "resnet152_v2": resnet152_v2,
          "vgg11": vgg11,
          "vgg13": vgg13,
          "vgg16": vgg16,
          "vgg19": vgg19,
          "vgg11_bn": vgg11_bn,
          "vgg13_bn": vgg13_bn,
          "vgg16_bn": vgg16_bn,
          "vgg19_bn": vgg19_bn,
          "alexnet": alexnet,
          "densenet121": densenet121,
          "densenet161": densenet161,
          "densenet169": densenet169,
          "densenet201": densenet201,
          "squeezenet1.0": squeezenet1_0,
          "squeezenet1.1": squeezenet1_1,
          "inceptionv3": inception_v3,
          "mobilenet1.0": mobilenet1_0,
          "mobilenet0.75": mobilenet0_75,
          "mobilenet0.5": mobilenet0_5,
          "mobilenet0.25": mobilenet0_25,
          "mobilenetv2_1.0": mobilenet_v2_1_0,
          "mobilenetv2_0.75": mobilenet_v2_0_75,
          "mobilenetv2_0.5": mobilenet_v2_0_5,
          "mobilenetv2_0.25": mobilenet_v2_0_25,
      }
      name = name.lower()
      if name not in models:
          raise ValueError(
              "Model {} is not supported. Available options are\n\t{}".format(
                  name, "\n\t".join(sorted(models.keys()))
              )
          )
      return models[name](**kwargs)
  
imports: from .alexnet import *
  from .densenet import *
  from .inception import *
  from .resnet import *
  from .squeezenet import *
  from .vgg import *
  from .mobilenet import *
label_desc: Use image node_id 1 for calling a global function with example usage: get_model(name) and returns: models