code: def add_custom_training_arguments(
      group: _ArgumentGroup,
  ) -> _ArgumentGroup:
      """Define arguments for training with Custom architecture."""
      group.add_argument(
          "--optimizer-warmup-steps",
          default=25000,
          type=int,
          help="Optimizer warmup steps",
      )
      group.add_argument(
          "--noam-lr",
          default=10.0,
          type=float,
          help="Initial value of learning rate",
      )
      group.add_argument(
          "--noam-adim",
          default=0,
          type=int,
          help="Most dominant attention dimension for scheduler.",
      )
      group.add_argument(
          "--transformer-warmup-steps",
          type=int,
          help="Optimizer warmup steps. The parameter is deprecated, "
          "please use --optimizer-warmup-steps instead.",
          dest="optimizer_warmup_steps",
      )
      group.add_argument(
          "--transformer-lr",
          type=float,
          help="Initial value of learning rate. The parameter is deprecated, "
          "please use --noam-lr instead.",
          dest="noam_lr",
      )
      group.add_argument(
          "--adim",
          type=int,
          help="Most dominant attention dimension for scheduler. "
          "The parameter is deprecated, please use --noam-adim instead.",
          dest="noam_adim",
      )
  
      return group
  
file_path: espnet/espnet/nets/pytorch_backend/transducer/arguments.py
imports: import ast
  from argparse import _ArgumentGroup
  from distutils.util import strtobool
label_desc: Use image node_id 7 for calling a global function with example usage: add_custom_training_arguments(group) and returns: group