parameters: (**kwargs)
return_statement: return get_resnet(1, 152, **kwargs)
docstring: r"""ResNet-152 V1 model from `"Deep Residual Learning for Image Recognition"
      <http://arxiv.org/abs/1512.03385>`_ 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"""ResNet-152 V1 model from `"Deep Residual Learning for Image Recognition"
      <http://arxiv.org/abs/1512.03385>`_ paper.
docstring_tokens: r ResNet - 152 V1 model from Deep Residual Learning for Image Recognition <http : // arxiv . org / abs / 1512 . 03385 > _ paper .
function: def resnet152_v1(**kwargs):
      r"""ResNet-152 V1 model from `"Deep Residual Learning for Image Recognition"
      <http://arxiv.org/abs/1512.03385>`_ 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.
      """
      return get_resnet(1, 152, **kwargs)
function_tokens: def resnet152_v1 ( * * kwargs ) : return get_resnet ( 1 , 152 , * * kwargs )