code: def cifar_wideresnet28_10(**kwargs):
      r"""WideResNet-28-10 model for CIFAR10 from `"Wide Residual Networks"
      <https://arxiv.org/abs/1605.07146>`_ paper.
  
      Parameters
      ----------
      drop_rate: float
          The rate of dropout.
      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_wide_resnet(28, 10, **kwargs)
  
file_path: gluon-cv/gluoncv/model_zoo/cifarwideresnet.py
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 4 for calling a global function with example usage: cifar_wideresnet28_10() and returns: get_cifar_wide_resnet