code: def log_dir():
      log_dir = (
          FLAGS.base_log_dir
          + "/unsup-"
          + FLAGS.train_prefix.split("/")[-2]
      )
      log_dir += "/{model:s}_{model_size:s}_{lr:0.6f}/".format(
          model=FLAGS.model,
          model_size=FLAGS.model_size,
          lr=FLAGS.learning_rate,
      )
      if not os.path.exists(log_dir):
          os.makedirs(log_dir)
      return log_dir
  
file_path: GraphSAGE/graphsage/unsupervised_train.py
imports: from __future__ import division
  from __future__ import print_function
  import os
  import time
  import tensorflow
  import numpy
  from graphsage.models import SampleAndAggregate, SAGEInfo, Node2VecModel
  from graphsage.minibatch import EdgeMinibatchIterator
  from graphsage.neigh_samplers import UniformNeighborSampler
  from graphsage.utils import load_data
label_desc: Use image node_id 1 for calling a global function with example usage: log_dir() and returns: log_dir