class_docstr: Base class for any neural network
class_docstr_tok: ["Base","class","for","any","neural","network"]
docstr: Add model-specific arguments
docstr_tok: ["Add","model-specific","arguments"]
code: def add_arguments(cls, parser: argparse.ArgumentParser):
      """Add model-specific arguments"""
  
      if cls != BaseAnyNNModel:
          return parser
      group = parser.add_argument_group(title=cls.__name__)
      group.add_argument(
          "--model.resume-exclude-scopes",
          type=str,
          default="",
          help="Comma-separated list of parameter scopes (regex strings) to exclude when "
          "loading a pre-trained model",
      )
      group.add_argument(
          "--model.ignore-missing-scopes",
          type=str,
          default="",
          help="Comma-separated list of parameter scopes (regex strings) to ignore "
          "if they are missing from the pre-training model",
      )
      group.add_argument(
          "--model.rename-scopes-map",
          type=JsonValidator(List[List[str]]),
          default=None,
          help="A mapping from checkpoint variable names to match the existing model names."
          " The mapping is represented as a List[List[str]], e.g. [['before', 'after'], ['this', 'that']]."
          " Note: only loading from Yaml file is supported for this argument.",
      )
      group.add_argument(
          "--model.freeze-modules",
          type=str,
          default="",
          help="Comma-separated list of parameter scopes (regex strings) to freeze.",
      )
  
      return parser
  
imports: from __future__ import annotations
  import argparse
  import traceback
  from typing import Any, Dict, List, Mapping, Optional, Tuple
  import torch
  from torch import nn
  from cvnets.layers import norm_layers_tuple
  from cvnets.misc.common import get_tensor_sizes, parameter_list
  from cvnets.misc.init_utils import initialize_weights
  from options.parse_args import JsonValidator
  from utils import logger
  from utils.common_utils import check_frozen_norm_layer
  from utils.ddp_utils import is_master
label_desc: Use image node_id 2 for calling the BaseAnyNNModel obj's underlying member method code with example usage: obj.add_arguments(cls, parser) and returns: parser, parser