code: def __init__(self, input_size, output_size):
      super(GNNLayer, self).__init__()
      self.linear_out = nn.Linear(input_size, output_size, bias=False)
  
imports: import argparse
  import os
  import time
  import dgl
  import dgl.function
  import networkx
  import numpy
  import torch
  import torch.backends.cudnn
  import torch.nn
  import torch.nn.functional
  from dgl import DGLGraph
  from dgl.data import load_data, register_data_args
  from scipy import sparse
  from ...modules.graph_construction import NodeEmbeddingBasedGraphConstruction, NodeEmbeddingBasedRefinedGraphConstruction
  from ...modules.utils.vocab_utils import VocabModel
  from ..utils import EarlyStopping
label_desc: Use image node_id 1 to create a new GNNLayer object from inherited base classes: nn with example: obj = GNNLayer(input_size, output_size)