code: def evaluate(model, g, features, labels, mask):
      model.eval()
      with th.no_grad():
          logits = model(g, features)
          logits = logits[mask]
          labels = labels[mask]
          _, indices = th.max(logits, dim=1)
          correct = th.sum(indices == labels)
          return correct.item() * 1.0 / len(labels)
  
file_path: dgl/tutorials/models/1_gnn/1_gcn.py
imports: import os
  import dgl
  import dgl.function
  import torch
  import torch.nn
  import torch.nn.functional
  from dgl import DGLGraph
  from dgl.data import CoraGraphDataset
  import time
  import numpy
label_desc: Use image node_id 2 for calling a global function with example usage: evaluate(model, g, features, labels, mask) and returns: unknown