class_docstr:     Pytorch Lightning module for semi-supervised learning.
  
  Args:
      active_dataset (ActiveLearningDataset): active learning dataset
      hparams (Namespace): hyper-parameters for the module
      **kwargs (**dict): extra arguments
class_docstr_tok: ["Pytorch","Lightning","module","for","semi-supervised","learning",".","Args",":","active_dataset","(","ActiveLearningDataset",")",":","active","learning","dataset","hparams","(","Namespace",")",":","hyper-parameters","for","the","module","*","*","kwargs","(","*","*","dict",")",":","extra","arguments"]
docstr: Add model specific arguments to argparser.
  
  Args:
      parent_parser (argparse.ArgumentParser): parent parser to which to add arguments
  
  Returns:
      argparser with added arguments
docstr_tok: ["Add","model","specific","arguments","to","argparser",".","Args",":","parent_parser","(","argparse.ArgumentParser",")",":","parent","parser","to","which","to","add","arguments","Returns",":","argparser","with","added","arguments"]
code: def add_model_specific_args(parent_parser):
      """
      Add model specific arguments to argparser.
  
      Args:
          parent_parser (argparse.ArgumentParser): parent parser to which to add arguments
  
      Returns:
          argparser with added arguments
      """
      parser = argparse.ArgumentParser(
          parents=[parent_parser],
          add_help=True,
          conflict_handler="resolve",
      )
      parser.add_argument(
          "--p",
          default=None,
          type=float,
          help="Probability of selecting labeled batch",
      )
      parser.add_argument(
          "--num_steps",
          default=None,
          type=int,
          help="Number of steps per epoch",
      )
      parser.add_argument("--batch-size", default=32, type=int)
      parser.add_argument("--workers", default=4, type=int)
  
      return parser
  
file_path: baal/baal/utils/ssl_module.py
imports: import argparse
  import typing
  from argparse import Namespace
  from typing import Dict
  import pytorch_lightning
  from baal.active import ActiveLearningDataset
  from baal.utils.ssl_iterator import SemiSupervisedIterator
label_desc: Use image node_id 6 for calling the SSLModule obj's underlying member method code with example usage: obj.add_model_specific_args(parent_parser) and returns: parser