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 = super(
          PIActiveLearningModel, PIActiveLearningModel
      ).add_model_specific_args(parent_parser)
      parser.add_argument("--query_size", type=int, default=100)
      parser.add_argument("--max_sample", type=int, default=-1)
      parser.add_argument("--iterations", type=int, default=20)
      parser.add_argument("--heuristic", type=str, default="bald")
      parser.add_argument("--replicate_in_memory", action="store_true")
      return parser
  
imports: import argparse
  import copy
  from argparse import Namespace
  import torch
  from experiments.ssl_experiments.pimodel_cifar10 import PIModel
  from torch import nn
  from torch.hub import load_state_dict_from_url
  from torch.utils.data import DataLoader
  from torchvision.datasets import CIFAR10
  from torchvision.models import vgg16
  from baal import ActiveLearningDataset, get_heuristic
  from baal.bayesian.dropout import patch_module
  from baal import ActiveLightningModule, BaalTrainer, ResetCallback
label_desc: Use image node_id 6 for calling the PIActiveLearningModel obj's underlying member method code with example usage: obj.add_model_specific_args(parent_parser) and returns: parser