code: def get_mobilenet(multiplier, pretrained=False, ctx=cpu(),
                    root=os.path.join(base.data_dir(), 'models'), **kwargs):
      r
      net = MobileNet(multiplier, **kwargs)
  
      if pretrained:
          from ..model_store import get_model_file
          version_suffix = '{0:.2f}'.format(multiplier)
          if version_suffix in ('1.00', '0.50'):
              version_suffix = version_suffix[:-1]
          net.load_parameters(
              get_model_file('mobilenet%s' % version_suffix, root=root), ctx=ctx)
      return net
docs: r"""MobileNet model from the
      `"MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications"
      <https://arxiv.org/abs/1704.04861>`_ paper.
  
      Parameters
      ----------
      multiplier : float
          The width multiplier for controling the model size. Only multipliers that are no
          less than 0.25 are supported. The actual number of channels is equal to the original
          channel size multiplied by this multiplier.
      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_HOME/models
          Location for keeping the model parameters.