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 or str
          Boolean value controls whether to load the default pretrained weights for model.
          String value represents the hashtag for a certain version of pretrained weights.
      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.
      """
      return get_squeezenet("1.1", **kwargs)
  
file_path: gluon-cv/gluoncv/model_zoo/squeezenet.py
imports: from mxnet.context import cpu
  from mxnet.gluon.block import HybridBlock
  from mxnet.gluon import nn
  from mxnet.gluon.contrib.nn import HybridConcurrent
label_desc: Use image node_id 5 for calling a global function with example usage: squeezenet1_1() and returns: get_squeezenet