code: def __init__(self, args):
      super(Topkpool, self).__init__()
      self.args = args
  
      missing_keys = list(
          set(
              [
                  "features_num",
                  "num_class",
                  "num_graph_features",
                  "ratio",
                  "dropout",
                  "act",
              ]
          )
          - set(self.args.keys())
      )
      if len(missing_keys) > 0:
          raise Exception("Missing keys: %s." % ",".join(missing_keys))
  
      self.num_features = self.args["features_num"]
      self.num_classes = self.args["num_class"]
      self.ratio = self.args["ratio"]
      self.dropout = self.args["dropout"]
      self.num_graph_features = self.args["num_graph_features"]
  
      self.conv1 = GraphConv(self.num_features, 128)
      self.pool1 = TopKPooling(128, ratio=self.ratio)
      self.conv2 = GraphConv(128, 128)
      self.pool2 = TopKPooling(128, ratio=self.ratio)
      self.conv3 = GraphConv(128, 128)
      self.pool3 = TopKPooling(128, ratio=self.ratio)
  
      self.lin1 = torch.nn.Linear(256 + self.num_graph_features, 128)
      self.lin2 = torch.nn.Linear(128, 64)
      self.lin3 = torch.nn.Linear(64, self.num_classes)
  
file_path: AutoGL/autogl/module/model/pyg/topkpool.py
imports: import torch
  import torch.nn.functional
  from torch_geometric.nn import GraphConv, TopKPooling
  from torch_geometric.nn import global_mean_pool, global_max_pool
  from .None import register_model
  from .base import BaseAutoModel, activate_func
  from ....utils import get_logger
label_desc: Use image node_id 1 to create a new Topkpool object from inherited base classes: torch.nn with example: obj = Topkpool(args)