Question

我有2个脚本：

脚本1（我拥有）
脚本2（Tensorboard库TensorFlow 1.12，无法修改代码）

脚本2使用argparse定义其标志。标志logdir在script2中定义，但是需要在script1中设置值。

它由tensorboard.main.run_main

运行

parser.add_argument(
        '--logdir',
        metavar='PATH',
        type=str,
        default='',
        help='''\

我的代码：

from __future__ import absolute_import
from __future__ import division
from __future__ import print_function

from threading import Thread

import logging
import os
import tensorboard.main as tb_main
import tensorflow as tf

# Environment variable containing port to launch TensorBoard on, set by TonY.
TB_PORT_ENV_VAR = 'TB_PORT'

tf.flags.DEFINE_string('data_dir', '/tmp/', 'Directory for storing input data')
tf.flags.DEFINE_string('working_dir', '/tmp/working_dir', 'Directory under which events and output will be stored (in separate subdirectories).')

# Training parameters
tf.flags.DEFINE_integer("steps", 2500, "The number of training steps to execute.")
tf.flags.DEFINE_integer("batch_size", 64, "The batch size per step.")
#   tf.flags.DEFINE_string('logdir', '/tmp/input_data',
#                           'Directory for storing input data')

FLAGS = tf.flags.FLAGS


def start_tensorboard(checkpoint_dir):
    FLAGS.logdir = checkpoint_dir
    if TB_PORT_ENV_VAR in os.environ:
        FLAGS.port = os.environ[TB_PORT_ENV_VAR]
    tb_thread = Thread(target=tb_main.run_main)
    tb_thread.daemon = True

    logging.info(
        "Starting TensorBoard with --logdir=" + checkpoint_dir + " in daemon "
                                                                                                                             "thread...")
    tb_thread.start()


def main(_):
    # Create some variables.
    start_tensorboard(FLAGS.working_dir)
    v1 = tf.get_variable("v1", shape=[3], initializer=tf.zeros_initializer)
    v2 = tf.get_variable("v2", shape=[5], initializer=tf.zeros_initializer)

    inc_v1 = v1.assign(v1 + 1)
    dec_v2 = v2.assign(v2 - 1)

    # Add an op to initialize the variables.
    init_op = tf.global_variables_initializer()

    # Add ops to save and restore all the variables.
    saver = tf.train.Saver()

    # Later, launch the model, initialize the variables, do some work, and save
    #  the
    # variables to disk.
    with tf.Session() as sess:
        sess.run(init_op)
        # Do some work with the model.
        inc_v1.op.run()
        dec_v2.op.run()
        # Save the variables to disk.
        save_path = saver.save(sess, "/tmp/model.ckpt")
        print("Model saved in path: %s" % save_path)


if __name__ == '__main__':
    tf.app.run()

由于在第一个脚本中未定义我的标志而导致的错误是：

absl.flags._exceptions.UnrecognizedFlagError: Unknown command line flag 'logdir'

如果我定义了它（在上面评论），我得到：

absl.flags._exceptions.DuplicateFlagError: The flag 'help' is defined twice. First from tensorflow.python.platform.app, Second from absl.app.  Description from first occurrence: show this help

ABSL标志，Python将标志从脚本1传递到script2并避免重复

0 个答案: