1、使用argparse包

import argparse
parser = argparse.ArgumentParser()
parser.add_argument(
      '--learning_rate',
      type=float,
      default=0.01,
      help='Initial learning rate.'
  )
parser.add_argument(
      '--max_steps',
      type=int,
      default=2000,
      help='Number of steps to run trainer.'
 

  )
FLAGS, unparsed = parser.parse_known_args()
# 輸出時，
print（FLAGS.learning_rate)  #輸出=0.01

2、使用tf的包（1）

import tensorflow as tf
FLAGS = tf.app.flags.FLAGS

tf.app.flags.DEFINE_string('train_dir', 'tmp/train/',
                           """Directory where to write event logs """
                           """and checkpoint."""
 
)
tf.app.flags.DEFINE_integer('max_steps', 700,
                            """Number of batches to run.""")
tf.app.flags.DEFINE_boolean('log_device_placement', False,
                            """Whether to log device placement.""")

print(FLAGS.max_steps)   # 輸出=700

3、使用tf的包（2）——簡潔用法

from tensorflow import flags
flags.DEFINE
 
_float("threshold", 0.1, "detection threshold")
flags.DEFINE_string("model", "", "configuration of choice")
flags.DEFINE_string("trainer", "rmsprop", "training algorithm")
FLAGS = flags.FLAGS

print(FLAGS.threshold)   # 輸出=0.1