You may have noticed tf.app.flags been used in every official TensorFlow v1 tutorial like CIFAR-10 example - link. Yet this module is not documented on the official TensorFlow website, the only documentation is about the tf.app.run.

An example of using this module would be to have a main.py file that contains something like following:

import tensorflow as tf

flags = tf.app.flags
flags.DEFINE_integer("epochs", 10, "number of training epochs")
flags.DEFINE_string("data_dir", "./data/", "path of data for training/validation/testing")
flags.DEFINE_string("log_dir", "./log/", "path of log output")
flags.DEFINE_boolean("is_train", True, "wheter to train with input data or do inference")
flags.DEFINE_float("lr", 0.9, "learning rate")

FLAGS = flags.FLAGS
if __name__ == "__main__":
  # Use the flags to control program execution
  if FLAGS.is_train:
    # Do training

After saving the file, you can check how the help output would look like with python main.py -h.

As of TensorFlow v2 this module does not exist and you may be looking for an alternative. Luckily Python has some popular modules for CLI argument parsing, e.g. argparse or Abseil which has similar use just like tf.app.flags which makes migration painless.

This is how main.py would look like if we use Abseil

from absl import app
from absl import flags

FLAGS = flags.FLAGS

flags.DEFINE_integer("epochs", 10, "number of training epochs")
flags.DEFINE_string("data_dir", "./data/", "path of data for training/validation/testing")
flags.DEFINE_string("log_dir", "./log/", "path of log output")
flags.DEFINE_boolean("is_train", True, "wheter to train with input data or do inference")
flags.DEFINE_float("lr", 0.9, "learning rate")

def main(argv):
  # Use the flags to control program execution
  if FLAGS.is_train:
    # Do training

if __name__ == ‘__main__’:
  app.run(main)

Alternatively, you can use python-fire which is a Google library that can be used to turn function arguments into CLI arguments and do the parsing for you. The same main.py would look like this

import fire

def main(epochs, data_dir, log_dir, is_train, lr):
  # do something

if __name__ == '__main__':
  fire.Fire(main)