code: def append_loss_history(loss_history, output):
      for loss in [
          "loss_classifier",
          "loss_box_reg",
          "loss_objectness",
          "loss_rpn_box_reg",
      ]:
          loss_history[loss] += [output[loss]]
      return loss_history
  
file_path: adversarial-robustness-toolbox/examples/get_started_fasterrcnn.py
imports: import os
  import cv2
  import numpy
  import matplotlib.pyplot
  import torch
  import torchvision
  import argparse
  import json
  import yaml
  import pprint
  from art.estimators.object_detection import PyTorchFasterRCNN
  from art.attacks.evasion import RobustDPatch
label_desc: Use image node_id 4 for calling a global function with example usage: append_loss_history(loss_history, output) and returns: loss_history