code: def add_subparser(
      self, parser: argparse._SubParsersAction
  ) -> argparse.ArgumentParser:
      description = """Find a learning rate range where loss decreases quickly
                           for the specified model and dataset."""
      subparser = parser.add_parser(
          self.name,
          description=description,
          help="Find a learning rate range.",
      )
  
      subparser.add_argument(
          "param_path",
          type=str,
          help="path to parameter file describing the model to be trained",
      )
      subparser.add_argument(
          "-s",
          "--serialization-dir",
          required=True,
          type=str,
          help="The directory in which to save results.",
      )
      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(
          "--start-lr",
          type=float,
          default=1e-5,
          help="learning rate to start the search",
      )
      subparser.add_argument(
          "--end-lr",
          type=float,
          default=10,
          help="learning rate up to which search is done",
      )
      subparser.add_argument(
          "--num-batches",
          type=int,
          default=100,
          help="number of mini-batches to run learning rate finder",
      )
      subparser.add_argument(
          "--stopping-factor",
          type=float,
          default=None,
          help="stop the search when the current loss exceeds the best loss recorded by "
          "multiple of stopping factor",
      )
      subparser.add_argument(
          "--linear",
          action="store_true",
          help="increase learning rate linearly instead of exponential increase",
      )
      subparser.add_argument(
          "-f",
          "--force",
          action="store_true",
          required=False,
          help="overwrite the output directory if it exists",
      )
      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=find_learning_rate_from_args)
  
      return subparser
  
imports: import argparse
  import logging
  import math
  import os
  import re
  from typing import List, Tuple
  import itertools
  from allennlp.commands.subcommand import Subcommand
  from allennlp.common import Params, Tqdm
  from allennlp.common import logging
  from allennlp.common.checks import check_for_gpu, ConfigurationError
  from allennlp.common.util import prepare_environment
  from allennlp.data import Vocabulary
  from allennlp.models import Model
  from allennlp.training import GradientDescentTrainer, Trainer
  from allennlp.training.util import create_serialization_dir, data_loaders_from_params
label_desc: Use image node_id 1 for calling the FindLearningRate obj's underlying member method code with example usage: obj.add_subparser(parser) and returns: subparser