class_docstr: Runs the training of a graph classification model using the augmented
  data generated by the already trained generator. Check
  :obj:`examples.auggraph.GraphAug.run_aug_cls` for examples on how to run
  this augmented classifier model.
  
  Args:
      data_root_path (string): Directory where datasets should be saved.
      dataset_name (:class:`dig.auggraph.method.GraphAug.constants.enums.DatasetName`):
          Name of the graph dataset.
      conf (dict): Hyperparameters for the model. Check
          :obj:`examples.auggraph.GraphAug.conf.aug_cls_conf` for examples on
          how to define the conf dictionary for the augmented classifier
          model.
class_docstr_tok: ["Runs","the","training","of","a","graph","classification","model","using","the","augmented","data","generated","by","the","already","trained","generator",".","Check",":","obj",":","`","examples.auggraph.GraphAug.run_aug_cls","`","for","examples","on","how","to","run","this","augmented","classifier","model",".","Args",":","data_root_path","(","string",")",":","Directory","where","datasets","should","be","saved",".","dataset_name","(",":","class",":","`","dig.auggraph.method.GraphAug.constants.enums.DatasetName","`",")",":","Name","of","the","graph","dataset",".","conf","(","dict",")",":","Hyperparameters","for","the","model",".","Check",":","obj",":","`","examples.auggraph.GraphAug.conf.aug_cls_conf","`","for","examples","on","how","to","define","the","conf","dictionary","for","the","augmented","classifier","model","."]
code: def __init__(self, data_root_path, dataset_name, conf):
      self.conf = conf
      self.dataset = self._get_dataset(data_root_path, dataset_name)
      self.augmenter = self._get_aug_model()
      self.model = self._get_model()
      self.device = torch.device(
          "cuda" if torch.cuda.is_available() else "cpu"
      )
      self.train_data_trans = AUG_trans(
          self.augmenter,
          self.device,
          pre_trans=self.data_trans,
          post_trans=self.data_trans,
      )
      self.dataset_name = dataset_name
  
imports: import os
  import torch
  import torch.nn.functional
  import numpy
  from torch_geometric.loader import DataLoader
  from torch_geometric.datasets import TUDataset
  from sklearn.model_selection import KFold, train_test_split
  from dig.auggraph.method.GraphAug.model import GIN, GCN
  from dig.auggraph.dataset.aug_dataset import DegreeTrans, Subset, AUG_trans
  from dig.auggraph.method.GraphAug.aug import Augmenter
  from dig.auggraph.method.GraphAug.constants import *
label_desc: Use image node_id 1 to create a new RunnerAugCls object from inherited base classes: object with example: obj = RunnerAugCls(data_root_path, dataset_name, conf)