code: def main(argv: List[str]) -> None:
      """
      Use torch.package to package the torchrec DLRM Model.
  
      Args:
          argv (List[str]): command line args.
  
      Returns:
          None.
      """
  
      args = parse_args(argv)
  
      model_config = DLRMModelConfig(
          dense_arch_layer_sizes=list(
              map(int, args.dense_arch_layer_sizes.split(","))
          ),
          dense_in_features=args.num_dense_features,
          embedding_dim=args.embedding_dim,
          id_list_features_keys=args.sparse_feature_names.split(","),
          num_embeddings_per_feature=list(
              map(int, args.num_embeddings_per_feature.split(","))
          ),
          num_embeddings=args.num_embeddings,
          over_arch_layer_sizes=list(
              map(int, args.over_arch_layer_sizes.split(","))
          ),
      )
  
      DLRMPredictFactoryPackager.save_predict_factory(
          DLRMPredictFactory,
          {"config.pkl": model_config},
          args.output_path,
          {},
      )
      print(f"Package is saved to {args.output_path}")
  
file_path: torchrec/examples/inference/dlrm_packager.py
imports: import argparse
  import sys
  from typing import List
  from dlrm_predict import DLRMModelConfig, DLRMPredictFactory
  from torch.package import PackageExporter
  from torchrec.datasets.criteo import DEFAULT_CAT_NAMES, DEFAULT_INT_NAMES
  from torchrec.inference.model_packager import PredictFactoryPackager
label_desc: Use image node_id 2 for calling a global function with example usage: main(argv) without return types