parameters: (**kwargs)
return_statement: return get_vgg(16, **kwargs)
docstring: r"""VGG-16 model with batch normalization from the
      `"Very Deep Convolutional Networks for Large-Scale Image Recognition"
      <https://arxiv.org/abs/1409.1556>`_ paper.
  
      Parameters
      ----------
      pretrained : bool, default False
          Whether to load the pretrained weights for model.
      device : Device, default CPU
          The device in which to load the pretrained weights.
      root : str, default '$MXNET_HOME/models'
          Location for keeping the model parameters.
docstring_summary: r"""VGG-16 model with batch normalization from the
      `"Very Deep Convolutional Networks for Large-Scale Image Recognition"
      <https://arxiv.org/abs/1409.1556>`_ paper.
docstring_tokens: r VGG - 16 model with batch normalization from the Very Deep Convolutional Networks for Large - Scale Image Recognition <https : // arxiv . org / abs / 1409 . 1556 > _ paper .
function: def vgg16_bn(**kwargs):
      r"""VGG-16 model with batch normalization from the
      `"Very Deep Convolutional Networks for Large-Scale Image Recognition"
      <https://arxiv.org/abs/1409.1556>`_ paper.
  
      Parameters
      ----------
      pretrained : bool, default False
          Whether to load the pretrained weights for model.
      device : Device, default CPU
          The device in which to load the pretrained weights.
      root : str, default '$MXNET_HOME/models'
          Location for keeping the model parameters.
      """
      kwargs['batch_norm'] = True
      return get_vgg(16, **kwargs)
function_tokens: def vgg16_bn ( * * kwargs ) : kwargs [ 'batch_norm' ] = True return get_vgg ( 16 , * * kwargs )