code: def inceptionv4(pretrained="imagenet"):
      """Pretrained InceptionV4 model"""
      settings = pretrained_settings["inceptionv4"][pretrained]
  
      # both 'imagenet'&'imagenet+background' are loaded from same parameters
      model = InceptionV4(num_classes=1001)
      model.load_state_dict(model_zoo.load_url(settings["url"]))
  
      if pretrained == "imagenet":
          new_last_linear = nn.Linear(1536, settings["num_classes"])
          new_last_linear.weight.data = model.last_linear.weight.data[
              1:
          ]
          new_last_linear.bias.data = model.last_linear.bias.data[1:]
          model.last_linear = new_last_linear
  
      model.input_space = settings["input_space"]
      model.input_size = settings["input_size"]
      model.input_range = settings["input_range"]
      model.mean = settings["mean"]
      model.std = settings["std"]
      return model
  
imports: import torch
  import torch.nn
  import torch.utils.model_zoo
  import os
  import sys
label_desc: Use image node_id 1 for calling a global function with example usage: inceptionv4(pretrained) and returns: model