code: def squeezenet1_1(**kwargs):
      r"""SqueezeNet 1.1 model from the `official SqueezeNet repo
      <https://github.com/DeepScale/SqueezeNet/tree/master/SqueezeNet_v1.1>`_.
      SqueezeNet 1.1 has 2.4x less computation and slightly fewer parameters
      than SqueezeNet 1.0, without sacrificing accuracy.
  
      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_squeezenet("1.1", **kwargs)
  
file_path: mxnet/python/mxnet/gluon/model_zoo/vision/squeezenet.py
imports: import os
  from ....device import cpu
  from ...block import HybridBlock
  from ...None import nn
  from ....None import base
  from ....util import use_np, wrap_ctx_to_device_func
label_desc: Use image node_id 5 for calling a global function with example usage: squeezenet1_1() and returns: get_squeezenet