Tensorflow überwachte Sitzung Verwendung

Question

Ich habe den folgenden Code, um einfache arithmetische Berechnungen durchzuführen. Ich versuche, Fehlertoleranz darin zu implementieren, indem ich eine überwachte Trainingseinheit verwende.

import tensorflow as tf 

global_step_tensor = tf.Variable(10, trainable=False, name='global_step') 

cluster = tf.train.ClusterSpec({"local": ["localhost:2222", "localhost:2223","localhost:2224", "localhost:2225"]}) 
x = tf.constant(2) 

with tf.device("/job:local/task:0"): 
    y1 = x + 300 

with tf.device("/job:local/task:1"): 
    y2 = x**2 

with tf.device("/job:local/task:2"): 
    y3 = 5*x 

with tf.device("/job:local/task:3"): 
    y0 = x - 66 
    y = y0 + y1 + y2 + y3 

ChiefSessionCreator = tf.train.ChiefSessionCreator(scaffold=None, master='localhost:2222', config='grpc://localhost:2222', checkpoint_dir='/home/tensorflow/codes/checkpoints') 
saver_hook = tf.train.CheckpointSaverHook(checkpoint_dir='/home/tensorflow/codes/checkpoints', save_secs=10, save_steps=None, saver=y, checkpoint_basename='model.ckpt', scaffold=None) 
summary_hook = tf.train.SummarySaverHook(save_steps=None, save_secs=10, output_dir='/home/tensorflow/codes/savepoints', summary_writer=None, scaffold=None, summary_op=y) 

with tf.train.MonitoredTrainingSession(master='localhost:2222', is_chief=True, checkpoint_dir='/home/tensorflow/codes/checkpoints', 
    scaffold=None, hooks=[saver_hook, summary_hook], chief_only_hooks=None, save_checkpoint_secs=10, save_summaries_steps=None, config='grpc://localhost:2222') as sess: 

    while not sess.should_stop(): 
     sess.run(model) 

    while not sess.should_stop(): 
     print(sess.run(y0)) 
     print('\n') 

    while not sess.should_stop(): 
     print(sess.run(y1)) 
     print('\n') 

    while not sess.should_stop(): 
     print(sess.run(y2)) 
     print('\n') 

    while not sess.should_stop(): 
     print(sess.run(y3)) 
     print('\n') 

    while not sess.should_stop(): 
     result = sess.run(y) 
     print(result) 

Aber es wirft den folgenden Fehler: -

Traceback (most recent call last): 
    File "add_1.py", line 36, in <module> 
    scaffold=None, hooks=[saver_hook, summary_hook], chief_only_hooks=None, save_checkpoint_secs=10, save_summaries_steps=None, config='grpc://localhost:2222') as sess: 
    File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/training/monitored_session.py", line 289, in MonitoredTrainingSession 
    return MonitoredSession(session_creator=session_creator, hooks=hooks) 
    File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/training/monitored_session.py", line 447, in __init__ 
    self._sess = _RecoverableSession(self._coordinated_creator) 
    File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/training/monitored_session.py", line 618, in __init__ 
    _WrappedSession.__init__(self, self._sess_creator.create_session()) 
    File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/training/monitored_session.py", line 505, in create_session 
    self.tf_sess = self._session_creator.create_session() 
    File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/training/monitored_session.py", line 341, in create_session 
    init_fn=self._scaffold.init_fn) 
    File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/training/session_manager.py", line 227, in prepare_session 
    config=config) 
    File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/training/session_manager.py", line 153, in _restore_checkpoint 
    sess = session.Session(self._target, graph=self._graph, config=config) 
    File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/client/session.py", line 1186, in __init__ 
    super(Session, self).__init__(target, graph, config=config) 
    File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/client/session.py", line 540, in __init__ 
    % type(config)) 
TypeError: config must be a tf.ConfigProto, but got <type 'str'> 
Exception AttributeError: "'Session' object has no attribute '_session'" in <bound method Session.__del__ of <tensorflow.python.client.session.Session object at 0x7fb1bac14ed0>> ignored 

, die meiner Meinung nach zu falschen Argument Config gegeben zurückzuführen ist. Benutze ich die Parameter richtig? Bitte um Rat.

Answer 1

Erste Ausgabe ist in den folgenden Zeilen. Es verwendet eine lokale Sitzung für eine verteilte (dem Gerät zugewiesene) Operation. Warum brauchst du das?

sess = tf.Session() 
tf.train.global_step(sess, global_step_tensor) 

Zweite Ausgabe: -Code verwendet WorkerSessionCreator. Eine Maschine sollte Chef sein. In diesem Fall sollte ChiefSessionCreator verwendet werden. Ich empfehle, folgende tf.train.MonitoredTrainingSession zu verwenden.

Dritte Ausgabe: sess.should_stop() sollte vor jedem run überprüft werden.