code: def squeezenet1_0(**kwargs):
      r"""SqueezeNet 1.0 model from the `"SqueezeNet: AlexNet-level accuracy with 50x fewer parameters
      and <0.5MB model size" <https://arxiv.org/abs/1602.07360>`_ paper.
  
      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("1.0", **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 4 for calling a global function with example usage: squeezenet1_0() and returns: get_squeezenet