code: def generate_densenet_test_model_archive():
      print("## Started densenet mar creation")
      model_store_dir = os.path.join(ROOT_DIR, "model_store")
      model_name = "densenet161_v1"
      version = "1.1"
      model_file = os.path.join(
          REPO_ROOT,
          "examples",
          "image_classifier",
          "densenet_161",
          "model.py",
      )
      serialized_model_file_name = "densenet161-8d451a50.pth"
      serialized_model_file_url = f"https://download.pytorch.org/models/{serialized_model_file_name}"
      serialized_file_path = os.path.join(
          model_store_dir, serialized_model_file_name
      )
      extra_files = os.path.join(
          REPO_ROOT,
          "examples",
          "image_classifier",
          "index_to_name.json",
      )
      handler = "image_classifier"
  
      os.makedirs(model_store_dir, exist_ok=True)
      os.chdir(model_store_dir)
      # Download & create DenseNet Model Archive
      urllib.request.urlretrieve(
          serialized_model_file_url, serialized_model_file_name
      )
  
      # create mar command
      cmd = f"torch-model-archiver \
                  --model-name {model_name} \
                  --version {version} \
                  --model-file {model_file} \
                  --serialized-file {serialized_file_path} \
                  --extra-files {extra_files} \
                  --handler {handler} \
                  --force"
      print(
          f"## In directory: {os.getcwd()} | Executing command: {cmd}"
      )
      sys_exit_code = os.system(cmd)
      os.remove(serialized_file_path)
      os.chdir(REPO_ROOT)
      return sys_exit_code
  
file_path: serve/ts_scripts/regression_utils.py
imports: import os
  import sys
  import tempfile
  import urllib.request
  from ts_scripts.shell_utils import rm_file
label_desc: Use image node_id 1 for calling a global function with example usage: generate_densenet_test_model_archive() and returns: sys_exit_code