code: def get_mobilenet(
      multiplier,
      pretrained=False,
      device=cpu(),
      root=os.path.join(base.data_dir(), "models"),
      **kwargs,
  ):
      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.
      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.
      """
      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(f"mobilenet{version_suffix}", root=root),
              device=device,
          )
      return net
  
imports: import os
  from ...None import nn
  from ....device import cpu
  from ...block import HybridBlock
  from ....None import base, np
  from ....util import use_np, wrap_ctx_to_device_func
label_desc: Use image node_id 3 for calling a global function with example usage: get_mobilenet(multiplier, pretrained, device, root) and returns: net