code: def __init__(
      self,
      in_feats,
      n_hidden,
      n_classes,
      n_layers,
      aggreagte_type,
      output_size,
      dropout,
  ):
      super(GCN, self).__init__()
      self.layers = nn.ModuleList()
      self.model = GraphSAGE(
          n_layers,
          in_feats,
          n_hidden,
          output_size,
          aggreagte_type,
          direction_option=args.direction_option,
          feat_drop=0.6,
          bias=True,
          activation=nn.ReLU,
      )
      # output layer
      # self.classifier=FeedForwardNN(output_size,n_classes,[16],nn.Sigmoid())
      self.classifier = BiLSTMFeedForwardNN(output_size, n_classes, 16)
      self.dropout = nn.Dropout(p=dropout)
  
file_path: graph4nlp/graph4nlp/pytorch/test/node_classification/node_classification_test.py
imports: import argparse
  import time
  import networkx
  import numpy
  import torch
  import torch.nn
  from dgl import DGLGraph
  from dgl.data import load_data, register_data_args
  from ...data.data import GraphData
  from ...modules.graph_embedding_learning.graphsage import GraphSAGE
  from ...modules.prediction.classification.node_classification.BiLSTMFeedForwardNN import BiLSTMFeedForwardNN
label_desc: Use image node_id 1 to create a new GCN object from inherited base classes: nn with example: obj = GCN(in_feats, n_hidden, n_classes, n_layers, aggreagte_type, output_size, dropout)