code: def cifar_resnet20_v2(**kwargs):
      r"""ResNet-20 V2 model for CIFAR10 from `"Identity Mappings in Deep Residual Networks"
      <https://arxiv.org/abs/1603.05027>`_ paper.
  
      Parameters
      ----------
      pretrained : bool, default False
          Whether to load the pretrained weights for model.
      ctx : Context, default CPU
          The context in which to load the pretrained weights.
      root : str, default '~/.mxnet/models'
          Location for keeping the model parameters.
      norm_layer : object
          Normalization layer used (default: :class:`mxnet.gluon.nn.BatchNorm`)
          Can be :class:`mxnet.gluon.nn.BatchNorm` or :class:`mxnet.gluon.contrib.nn.SyncBatchNorm`.
      norm_kwargs : dict
          Additional `norm_layer` arguments, for example `num_devices=4`
          for :class:`mxnet.gluon.contrib.nn.SyncBatchNorm`.
      """
      return get_cifar_resnet(2, 20, **kwargs)
  
imports: from __future__ import division
  import os
  from mxnet.gluon.block import HybridBlock
  from mxnet.gluon import nn
  from mxnet.gluon.nn import BatchNorm
  from mxnet import cpu
label_desc: Use image node_id 7 for calling a global function with example usage: cifar_resnet20_v2() and returns: get_cifar_resnet