在我的Ubuntu上安装TensorFlow时,我想将GPU与CUDA一起使用.

但我在官方教程的这一步停了下来:

这究竟在哪里./configure？或者我的源树根在哪里.

我的TensorFlow位于此处/usr/local/lib/python2.7/dist-packages/tensorflow.但我还是没找到./configure.

编辑

./configure根据Salvador Dali的回答,我找到了.但是在执行示例代码时,我收到以下错误:

>>> import tensorflow as tf
>>> hello = tf.constant('Hello, TensorFlow!')
>>> sess = tf.Session()
I tensorflow/core/common_runtime/local_device.cc:25] Local device intra op parallelism threads: 8
E tensorflow/stream_executor/cuda/cuda_driver.cc:466] failed call to cuInit: CUDA_ERROR_NO_DEVICE
I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:86] kernel driver does not appear to be running on this host (cliu-ubuntu): /proc/driver/nvidia/version does not exist
I tensorflow/core/common_runtime/gpu/gpu_init.cc:112] DMA: 
I tensorflow/core/common_runtime/local_session.cc:45] Local session inter op parallelism threads: 8

无法找到cuda设备.

回答 …

当我pip3 list在终端中,它出现以下错误:

cliu@cliu-ubuntu:~$ pip3 list
Exception:
Traceback (most recent call last):
  File "/usr/lib/python3/dist-packages/pip/basecommand.py", line 122, in main
    status = self.run(options, args)
  File "/usr/lib/python3/dist-packages/pip/commands/list.py", line 80, in run
    self.run_listing(options)
  File "/usr/lib/python3/dist-packages/pip/commands/list.py", line 142, in run_listing
    self.output_package_listing(installed_packages)
  File "/usr/lib/python3/dist-packages/pip/commands/list.py", line 151, in output_package_listing
    if dist_is_editable(dist):
  File "/usr/lib/python3/dist-packages/pip/util.py", line 367, in dist_is_editable
    req = FrozenRequirement.from_dist(dist, [])
  File "/usr/lib/python3/dist-packages/pip/__init__.py", line 299, in from_dist
    assert len(specs) == 1 and specs[0][0] == '=='
AssertionError

Storing debug log for failure in /home/cliu/.pip/pip.log 

谁知道如何解决这个问题？

我运行的例子 kaggle_otto_nn.py中Keras与后端theano.当我设置时cnmem=1,出现以下错误:

cliu@cliu-ubuntu:keras-examples$ THEANO_FLAGS=mode=FAST_RUN,device=gpu,floatX=float32,lib.cnmem=1 python kaggle_otto_nn.py
Using Theano backend.
ERROR (theano.sandbox.cuda): ERROR: Not using GPU. Initialisation of device gpu failed:
initCnmem: cnmemInit call failed! Reason=CNMEM_STATUS_OUT_OF_MEMORY. numdev=1

/usr/local/lib/python2.7/dist-packages/Theano-0.8.0rc1-py2.7.egg/theano/tensor/signal/downsample.py:6: UserWarning: downsample module has been moved to the theano.tensor.signal.pool module.
  "downsample module has been moved to the theano.tensor.signal.pool module.")
Traceback (most recent call last):
  File "kaggle_otto_nn.py", line 28, in <module>
    from keras.models import Sequential
  File "build/bdist.linux-x86_64/egg/keras/models.py", line 15, in <module>
  File "build/bdist.linux-x86_64/egg/keras/backend/__init__.py", line 46, in …

我想知道Apache Commons Lang3(org.apache.commons.lang3)与Apache Commons Text(org.apache.commons.text)之间有什么区别？

我看到他们之间有许多相似之处.
对于intance,他们都有StringEscapeUtils:

• org.apache.commons.lang3.StringEscapeUtils,已弃用.
• org.apache.commons.text.StringEscapeUtils

但我也看到了许多不同之处.
那么我应该使用哪一个,Lang3还是Text？
或者这两者的常见用例是什么？

为什么静态方法的实现compare的Long,Integer并Short在Java中的图书馆有什么不同？

用于Long:

public static int compare(long x, long y) {
    return (x < y) ? -1 : ((x == y) ? 0 : 1);
}

用于Integer:

public static int compare(int x, int y) {
    return (x < y) ? -1 : ((x == y) ? 0 : 1);
}

用于Short:

public static int compare(short x, short y) {
    return x - y;
}

在开始我的时候spark-shell,我收到了很多WARN消息.但我无法理解他们.我应该注意哪些重要问题？或者我错过了任何配置？或者这些WARN消息是正常的.

cliu@cliu-ubuntu:Apache-Spark$ spark-shell 
log4j:WARN No appenders could be found for logger (org.apache.hadoop.metrics2.lib.MutableMetricsFactory).
log4j:WARN Please initialize the log4j system properly.
log4j:WARN See http://logging.apache.org/log4j/1.2/faq.html#noconfig for more info.
Using Spark's repl log4j profile: org/apache/spark/log4j-defaults-repl.properties
To adjust logging level use sc.setLogLevel("INFO")
Welcome to
      ____              __
     / __/__  ___ _____/ /__
    _\ \/ _ \/ _ `/ __/  '_/
   /___/ .__/\_,_/_/ /_/\_\   version 1.5.2
      /_/

Using Scala version 2.10.4 (Java HotSpot(TM) 64-Bit Server VM, Java 1.8.0_66)
Type in expressions …

我在以下代码中对原始字符串有一些困惑:

import re

text2 = 'Today is 11/27/2012. PyCon starts 3/13/2013.'
text2_re = re.sub(r'(\d+)/(\d+)/(\d+)', r'\3-\1-\2', text2)
print (text2_re) #output: Today is 2012-11-27. PyCon starts 2013-3-13.

print (r'(\d+)/(\d+)/(\d+)') #output: (\d+)/(\d+)/(\d+)

正如我理解原始字符串,没有r,\被视为转义字符; 使用r,反斜杠\被视为字体.

但是,我在上面的代码中无法理解的是:在正则表达式第5行中,即使有一个r,里面的" \ d "被视为一个数字[0-9]而不是一个反斜杠\加一个信d.

在第二个打印行8中,所有字符都被视为原始字符串.

有什么不同？

附加版:

我做了以下四种变化,有或没有r:

import re

text2 = 'Today is 11/27/2012. PyCon starts 3/13/2013.'
text2_re = re.sub(r'(\d+)/(\d+)/(\d+)', r'\3-\1-\2', text2)
text2_re1 = re.sub('(\d+)/(\d+)/(\d+)', r'\3-\1-\2', text2)
text2_re2 = re.sub(r'(\d+)/(\d+)/(\d+)', …

我正在尝试导入模块,keras.utils.data_utils但它无法正常工作.但是,我可以在这里找到这个模块.它确实存在.为什么我不能导入它,而我可以导入其他模块,如keras.models和keras.layers.core？

cliu@cliu-ubuntu:bin$ python
Python 2.7.9 (default, Apr  2 2015, 15:33:21) 
[GCC 4.9.2] on linux2
Type "help", "copyright", "credits" or "license" for more information.
>>> from __future__ import print_function
>>> from keras.models import Sequential 
>>> from keras.layers.core import Dense, Activation, Dropout 
>>> from keras.layers.recurrent import LSTM
>>> from keras.utils.data_utils import get_file
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
ImportError: No module named data_utils

编辑:

请看这里的答案.

我正在遵循Flink的快速入门示例：监视Wikipedia编辑流。

该示例使用Java，并且正在Scala中实现，如下所示：

/**
 * Wikipedia Edit Monitoring
 */
object WikipediaEditMonitoring {
  def main(args: Array[String]) {
    // set up the execution environment
    val env: StreamExecutionEnvironment = StreamExecutionEnvironment.getExecutionEnvironment

    val edits: DataStream[WikipediaEditEvent] = env.addSource(new WikipediaEditsSource)

    val result = edits.keyBy( _.getUser )
      .timeWindow(Time.seconds(5))
      .fold(("", 0L)) {
        (acc: (String, Long), event: WikipediaEditEvent) => {
          (event.getUser, acc._2 + event.getByteDiff)
        }
      }

    result.print

    // execute program
    env.execute("Wikipedia Edit Monitoring")
  }
}

但是，foldFlink中的功能已被弃用，aggregate建议使用该功能。

但我没有找到有关如何转换的过时的例子或教程fold来aggregrate。 …

在ScalaTest中,我有以下检查:

"abc".r shouldBe "abc".r

但它并不平等.我不明白.

abc was not equal to abc
ScalaTestFailureLocation: com.ing.cybrct.flink.clickstream.ConfigsTest$$anonfun$6 at (ConfigsTest.scala:97)
Expected :abc
Actual   :abc