code: def add_subparser(
      self, parser: argparse._SubParsersAction
  ) -> argparse.ArgumentParser:
      description = (
          """Run the specified model against a JSON-lines input file."""
      )
      subparser = parser.add_parser(
          self.name,
          description=description,
          help="Use a trained model to make predictions.",
      )
  
      subparser.add_argument(
          "archive_file",
          type=str,
          help="the archived model to make predictions with",
      )
      subparser.add_argument(
          "input_file",
          type=str,
          help="path to or url of the input file",
      )
  
      subparser.add_argument(
          "--output-file", type=str, help="path to output file"
      )
      subparser.add_argument(
          "--weights-file",
          type=str,
          help="a path that overrides which weights file to use",
      )
  
      batch_size = subparser.add_mutually_exclusive_group(
          required=False
      )
      batch_size.add_argument(
          "--batch-size",
          type=int,
          default=1,
          help="The batch size to use for processing",
      )
  
      subparser.add_argument(
          "--silent",
          action="store_true",
          help="do not print output to stdout",
      )
  
      cuda_device = subparser.add_mutually_exclusive_group(
          required=False
      )
      cuda_device.add_argument(
          "--cuda-device",
          type=int,
          default=-1,
          help="id of GPU to use (if any)",
      )
  
      subparser.add_argument(
          "--use-dataset-reader",
          action="store_true",
          help="Whether to use the dataset reader of the original model to load Instances. "
          "The validation dataset reader will be used if it exists, otherwise it will "
          "fall back to the train dataset reader. This behavior can be overridden "
          "with the --dataset-reader-choice flag.",
      )
  
      subparser.add_argument(
          "--dataset-reader-choice",
          type=str,
          choices=["train", "validation"],
          default="validation",
          help="Indicates which model dataset reader to use if the --use-dataset-reader "
          "flag is set.",
      )
  
      subparser.add_argument(
          "--multitask-head",
          type=str,
          default=None,
          help="If you are using a dataset reader to make predictions, and the model is a"
          "multitask model, you have to specify the name of the model head to use here.",
      )
  
      subparser.add_argument(
          "-o",
          "--overrides",
          type=str,
          default="",
          help=(
              "a json(net) structure used to override the experiment configuration, e.g., "
              "'{\"iterator.batch_size\": 16}'.  Nested parameters can be specified either"
              " with nested dictionaries or with dot syntax."
          ),
      )
  
      subparser.add_argument(
          "--predictor",
          type=str,
          help="optionally specify a specific predictor to use",
      )
  
      subparser.add_argument(
          "--predictor-args",
          type=str,
          default="",
          help=(
              "an optional JSON structure used to provide additional parameters to the predictor"
          ),
      )
  
      subparser.add_argument(
          "--file-friendly-logging",
          action="store_true",
          default=False,
          help="outputs tqdm status on separate lines and slows tqdm refresh rate",
      )
  
      subparser.set_defaults(func=_predict)
  
      return subparser
  
imports: from typing import List, Iterator, Optional
  import argparse
  import sys
  import json
  from allennlp.commands.subcommand import Subcommand
  from allennlp.common import logging
  from allennlp.common.checks import check_for_gpu, ConfigurationError
  from allennlp.common.file_utils import cached_path, open_compressed
  from allennlp.common.util import lazy_groups_of
  from allennlp.data.dataset_readers import MultiTaskDatasetReader
  from allennlp.models.archival import load_archive
  from allennlp.predictors.predictor import Predictor, JsonDict
  from allennlp.data import Instance
label_desc: Use image node_id 1 for calling the Predict obj's underlying member method code with example usage: obj.add_subparser(parser) and returns: subparser