code: def test(model, data, mask):
      model.eval()
  
      if hasattr(model, "cls_forward"):
          out = model.cls_forward(data)[mask]
      else:
          out = model(data)[mask]
      pred = out.max(1)[1]
      acc = pred.eq(data.y[mask]).sum().item() / mask.sum().item()
      return acc
  
file_path: AutoGL/test/performance/node_classification/pyg/model_decouple.py
imports: import os
  import pickle
  import numpy
  from tqdm import tqdm
  import torch
  import torch.nn.functional
  from torch_geometric.datasets import Planetoid
  import torch_geometric.transforms
  from autogl.module.model.encoders import GCNEncoderMaintainer, GATEncoderMaintainer, SAGEEncoderMaintainer
  from autogl.module.model.decoders import LogSoftmaxDecoderMaintainer
  from autogl.solver.utils import set_seed
  from helper import get_encoder_decoder_hp
  import logging
label_desc: Use image node_id 1 for calling a global function with example usage: test(model, data, mask) and returns: acc