Je suis en utilisant Tensorflow la version 0.12.tête avec Python 2.7 sous linux CentOS 7 et lorsque je l'exécute:
import tensorflow as tf
a = tf.constant(5, name="input_a")
b = tf.constant(3, name="input_b")
c = tf.mul(a, b, name="mul_c")
d = tf.add(a, b, name="add_d")
e = tf.add(c, d, name="add_e")
sess = tf.Session()
output = sess.run(e)
writer = tf.train.SummaryWriter('./my_graph', sess.graph)
J'obtiens cette erreur:
AttributeError Traceback (most recent call last) <ipython-input-6-29c037e85eec> in <module>()
----> 1 writer = tf.train.SummaryWriter('./my_graph', sess.graph)
AttributeError: 'module' object has no attribute 'SummaryWriter'
J'ai l'exécution de ces deux commandes, car il y a un bug question sur Github pour le même problème:
>>> import six
>>> print(six.__version__)
1.10.0
>>> print(dir(six.moves.queue)) ['Empty', 'Full', 'LifoQueue', 'PriorityQueue', 'Queue', '__all__', '__builtins__', '__doc__', '__file__', '__name__', '__package__', '_threading', '_time', 'deque', 'heapq']
>>> print(six.moves.queue.__file__) /usr/lib64/python2.7/Queue.pyc
Je suis débutant en Python et en Tensorflow. Savez-vous comment puis-je corriger cette erreur?
J'ai changé d' SummaryWriter
avec FileWriter
:
writer = tf.train.FileWriter('./my_graph', sess.graph)
Et j'obtiens la même erreur, mais avec FileWriter
fonction de:
AttributeError Traceback (most recent call last)
<ipython-input-8-daa50ea2b8f9> in <module>()
----> 1 writer = tf.train.FileWriter('./my_graph', sess.graph)
AttributeError: 'module' object has no attribute 'FileWriter'
J'ai également exécuter dans un terminal et j'obtiens le même résultat:
[VansFannel@localhost ~]$ python
Python 2.7.5 (default, Nov 6 2016, 00:28:07)
[GCC 4.8.5 20150623 (Red Hat 4.8.5-11)] on linux2
Type "help", "copyright", "credits" or "license" for more information.
>>> import tensorflow as tf
W tensorflow/core/platform/cpu_feature_guard.cc:95] The TensorFlow library wasn't compiled to use SSE4.2 instructions, but these are available on your machine and could speed up CPU computations.
W tensorflow/core/platform/cpu_feature_guard.cc:95] The TensorFlow library wasn't compiled to use AVX instructions, but these are available on your machine and could speed up CPU computations.
>>> a = tf.constant(5, name="input_a")
>>> b = tf.constant(3, name="input_b")
>>> c = tf.mul(a, b, name="mul_c")
>>> d = tf.add(a, b, name="add_d")
>>> e = tf.add(c, d, name="add_e")
>>> sess = tf.Session()
>>> output = sess.run(e)
>>> writer = tf.train.FileWriter('./my_graph', sess.graph)
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
AttributeError: 'module' object has no attribute 'FileWriter'
>>>