code: def sqnxt23v5_w2(**kwargs):
      """
      0.5-SqNxt-23v5 model from 'SqueezeNext: Hardware-Aware Neural Network Design,' https://arxiv.org/abs/1803.10615.
  
      Parameters:
      ----------
      pretrained : bool, default False
          Whether to load the pretrained weights for model.
      root : str, default '~/.torch/models'
          Location for keeping the model parameters.
      """
      return get_squeezenext(
          version="23v5",
          width_scale=2.0,
          model_name="sqnxt23v5_w2",
          **kwargs,
      )
  
imports: import numpy
  import torch
  from torch.autograd import Variable
  from pytorch2keras.converter import pytorch_to_keras
  import os
  import torch.nn
  import torch.nn.init
label_desc: Use image node_id 7 for calling a global function with example usage: sqnxt23v5_w2() and returns: get_squeezenext