code: def alexnet(
      pretrained=False,
      filter_size=4,
      _force_nonfinetuned=False,
      **kwargs,
  ):
      """AlexNet model architecture from the
      `"One weird trick..." <https://arxiv.org/abs/1404.5997>`_ paper.
  
      Args:
          pretrained (bool): If True, returns a model pre-trained on ImageNet
          filter_size (int): [4] Antialiasing filter size
      """
      model = AlexNet(filter_size=filter_size, **kwargs)
      if pretrained:
          if filter_size == 4 and not _force_nonfinetuned:
              model.load_state_dict(
                  model_zoo.load_url(
                      model_urls["alexnet_lpf4_finetune"],
                      map_location="cpu",
                      check_hash=True,
                  )["state_dict"]
              )
          else:
              model.load_state_dict(
                  model_zoo.load_url(
                      model_urls["alexnet_lpf%i" % filter_size],
                      map_location="cpu",
                      check_hash=True,
                  )["state_dict"]
              )
      return model
  
file_path: antialiased-cnns/antialiased_cnns/alexnet.py
imports: import torch
  import torch.nn
  import torch.utils.model_zoo
  import numpy
  from antialiased_cnns import *
label_desc: Use image node_id 1 for calling a global function with example usage: alexnet(pretrained, filter_size, _force_nonfinetuned) and returns: model