code: def main(_):
      if FLAGS.gpu == -1:
          device = "/cpu:0"
      else:
          device = "/gpu:{}".format(FLAGS.gpu)
  
      with tf.device(device):
          tf.random.set_seed(FLAGS.seed)
          # Load the dataset and process features and adj matrix
          print("Loading {} dataset...".format(FLAGS.dataset))
          (
              adj,
              features,
              labels,
              idx_train,
              idx_val,
              idx_test,
          ) = load_dataset(
              FLAGS.dataset, FLAGS.sparse_features, FLAGS.normalize_adj
          )
          num_classes = max(labels) + 1
          print("Build model...")
          model = build_model(
              FLAGS.model,
              FLAGS.num_layers,
              FLAGS.mlp_layers,
              FLAGS.hidden_dim,
              num_classes,
              FLAGS.dropout_rate,
              FLAGS.num_heads,
              FLAGS.learn_eps,
              FLAGS.sparse_features,
          )
          print("Start Training...")
          train(
              model, adj, features, labels, idx_train, idx_val, idx_test
          )
  
imports: import time
  from absl import app
  from absl import flags
  import tensorflow
  from utils import load_dataset, build_model, cal_acc
label_desc: Use image node_id 2 for calling a global function with example usage: main(_) without return types