code: def same_model(model1, model2):
      for p1, p2 in zip(model1.parameters(), model2.parameters()):
          if p1.data.ne(p2.data).sum() > 0:
              return False
      return True
  
file_path: dgl/examples/pytorch/hilander/PSS/Smooth_AP/src/finetune_1head.py
imports: import warnings
  import argparse
  import datetime
  import os
  import random
  import matplotlib
  import numpy
  from pathlib import Path
  import auxiliaries
  import datasets
  import evaluate
  import losses
  import netlib
  import torch.multiprocessing
  from tensorboardX import SummaryWriter
  from tqdm import tqdm
  import time
  import time
label_desc: Use image node_id 1 for calling a global function with example usage: same_model(model1, model2) and returns: True, False