code: def nasnetamobile(pretrained="imagenet"):
      """Pretrained version of NASNet_mobile"""
      model = NASNetAMobile(
          num_classes=1000
      )  # both 'imagenet'&'imagenet+background' are loaded from same parameters
      if pretrained:
          settings = pretrained_settings["nasnetamobile"][pretrained]
          model.load_state_dict(
              model_zoo.load_url(settings["url"], map_location=None)
          )
  
          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"]
      else:
          settings = pretrained_settings["nasnetamobile"]["imagenet"]
          model = NASNetAMobile(num_classes=1000)
          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
label_desc: Use image node_id 1 for calling a global function with example usage: nasnetamobile(pretrained) and returns: model