code: def evaluate(model, g, labels, mask):
      model.eval()
      with torch.no_grad():
          logits, _ = model(g)
          logits = logits[mask]
          labels = labels[mask]
          return accuracy(logits, labels)
  
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 2 for calling a global function with example usage: evaluate(model, g, labels, mask) and returns: accuracy