'module' 對象沒有屬性 'SummaryWriter'

Question

我在 Linux CentOS 7 上使用帶有 Python 2.7 的 Tensorflow 版本 0.12.head，當我運行這個時：

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)

我收到此錯誤：

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'

我因為有錯誤運行這兩個命令的問題在Github上的同樣的問題：

>>> 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

我是 Python 和 Tensorflow 的新手。 你知道我該如何解決這個錯誤嗎？

我用FileWriter更改了SummaryWriter ：

writer = tf.train.FileWriter('./my_graph', sess.graph)

我得到了同樣的錯誤，但使用FileWriter函數：

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'

我也在終端中運行它，我得到了相同的結果：

[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'
>>> 

Answer 1

tf.train.SummaryWriter已被棄用，改用tf.summary.FileWriter 。

↳ 將摘要添加到事件文件中

它將在 2016-11-30 之后移除。 更新說明：請切換到tf.summary.FileWriter 。 界面和行為是一樣的； 這只是一個重命名。

< TF Official Migration Page > ✳︎ 包括所有當前已棄用/重命名的功能 ✳︎

Answer 2

在新版本的 TF 中，所有匯總函數都被重命名為.

匯總函數已合並到tf.summary命名空間下。

 Deprecated                                               Replacement
----------------------------------------------------------------------------------
 tf.audio_summary                                         tf.summary.audio
 tf.contrib.deprecated.histogram_summary                  tf.summary.histogram
 tf.contrib.deprecated.scalar_summary                     tf.summary.scalar
 tf.histogram_summary                                     tf.summary.histogram
 tf.image_summary                                         tf.summary.image
 tf.merge_all_summaries                                   tf.summary.merge_all
 tf.merge_summary                                         tf.summary.merge
 tf.scalar_summary                                        tf.summary.scalar
 tf.train.SummaryWriter                                   tf.summary.FileWriter
----------------------------------------------------------------------------------

Answer 3

我遇到了同樣的問題...我正在使用 pything 3.5.2...請參閱下面的解決方案...希望這對您有用...它對我有用（它會在您的 tmp 文件夾中創建一個日志）：

import tensorflow as tf
a = tf.constant(5, name="input_a")
b = tf.constant(3, name="input_a")
c = tf.multiply(a,b, name="mul_c")
d = tf.add(a,b, name="add_d")
e = tf.add(c,d, name="add_e")

sess = tf.Session()
sess.run(e)
output = sess.run(e)

writer = tf.summary.FileWriter('/tmp/tensorflow_logs', graph=sess.graph)

print(sess.run(e))

Answer 4

import tensorflow as tf
a = tf.constant(5, name="input_a")
b = tf.constant(3, name="input_a")
c = tf.multiply(a,b, name="mul_c")
d = tf.add(a,b, name="add_d")
e = tf.add(c,d, name="add_e")

sess = tf.Session()
sess.run(e)
output = sess.run(e)

writer = tf.summary.create_file_writer('/tmp/tensorflow_logs', graph=sess.graph)

print(sess.run(e))

Answer 5

這對我有用。

tf.summary.create_file_writer('/pnplogs')

create_file_writer()為給定的日志目錄（在我的例子中是pnplogs ）創建一個摘要文件pnplogs

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