code: def define_network_flags():
      tf.flags.DEFINE_string("dataset", "cora", "Dataset name.")
      tf.flags.DEFINE_string("node_encoder", "gcn", "Encoder name.")
      tf.flags.DEFINE_integer("hidden_dim", 32, "Hidden dimension.")
      tf.flags.DEFINE_integer("layers", 2, "convolution layer number.")
      tf.flags.DEFINE_list("fanouts", [10, 10], "GraphSage fanouts.")
      tf.flags.DEFINE_integer("batch_size", 1024, "Mini-batch size")
      tf.flags.DEFINE_integer("num_epochs", 2000, "Epochs to train")
      tf.flags.DEFINE_integer(
          "log_steps", 10, "Number of steps to print log."
      )
      tf.flags.DEFINE_string("model_dir", "ckpt", "Model checkpoint.")
      tf.flags.DEFINE_float("learning_rate", 0.01, "Learning rate.")
      tf.flags.DEFINE_enum(
          "optimizer",
          "adam",
          ["adam", "adagrad", "sgd", "momentum"],
          "Optimizer algorithm",
      )
      tf.flags.DEFINE_enum(
          "run_mode",
          "train",
          ["train", "evaluate", "infer"],
          "Run mode.",
      )
  
file_path: euler/examples/gae/run_gae.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import tensorflow
  import tf_euler
  from euler_estimator import GaeEstimator
  from gae import GraphAutoEncoder
label_desc: Use image node_id 1 for calling a global function with example usage: define_network_flags() without return types