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本文介绍了如何在Ubuntu上以virtualenv方式安装tensorflow。
安装pip和virtualenv：
# Ubuntu/Linux 64-bit
sudo apt-get install Python-pip python-dev python-virtualenv
# Mac OS X
sudo easy_install pip
sudo pip install –upgrade virtualenv
创建 Virtualenv 虚拟环境：
进入你想安装tensorflow的父目录下，然后执行下面命令建立虚拟环境：
virtualenv –system-site-packages tensorflow
激活虚拟环境并安装tensorflow：
对于python27，则执行如下命令：
source ./tensorflow/bin/activate # If using bash
source ./tensorflow/bin/activate.csh # If using csh
(tensorflow)$ # Your prompt should change
# Ubuntu/Linux 64-bit, CPU only:
pip install –upgrade https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-0.6.0-cp27-none-linux_x86_64.whl
# Ubuntu/Linux 64-bit, GPU enabled:
pip install –upgrade https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow-0.6.0-cp27-none-linux_x86_64.whl
# Mac OS X, CPU only:
pip install –upgrade https://storage.googleapis.com/tensorflow/mac/tensorflow-0.6.0-py2-none-any.whl
对于python3则执行如下命令：
source ./tensorflow/bin/activate # If using bash
source ./tensorflow/bin/activate.csh # If using csh
(tensorflow)$ # Your prompt should change
# Ubuntu/Linux 64-bit, CPU only:
pip install –upgrade https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-0.6.0-cp34-none-linux_x86_64.whl
# Ubuntu/Linux 64-bit, GPU enabled:
pip install –upgrade https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow-0.6.0-cp34-none-linux_x86_64.whl
# Mac OS X, CPU only:
pip3 install –upgrade https://storage.googleapis.com/tensorflow/mac/tensorflow-0.6.0-py3-none-any.whl
测试安装：
在终端执行如下命令进入python shell环境：
python
在python shell环境中测试：
>>> import tensorflow as tf
>>> hello = tf.constant(‘Hello, TensorFlow!’)
>>> sess = tf.Session()
>>> print(sess.run(hello))
Hello, TensorFlow!
>>> a = tf.constant(10)
>>> b = tf.constant(32)
>>> print(sess.run(a + b))
42
>>>
• 如果遇到如下错误：
1
2
_mod = imp.load_module(‘_pywrap_tensorflow’, fp, pathname, description)
ImportError: libcudart.so.7.0: cannot open shared object file: No such file or directory
那是你的CUDA安装配置不对：
安装CUDA和CUDNN可以参考 这篇文章 。
且添加如下两行到你的 ~/.bashrc 文件
export LD_LIBRARY_PATH=”$LD_LIBRARY_PATH:/usr/local/cuda/lib64″
export CUDA_HOME=/usr/local/cuda
• 如果遇到如下错误：
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.
>>> import tensorflow
I tensorflow/stream_executor/dso_loader.cc:93] Couldn’t open CUDA library libcublas.so.7.0. LD_LIBRARY_PATH: :/usr/local/cuda/lib64
I tensorflow/stream_executor/cuda/cuda_blas.cc:2188] Unable to load cuBLAS DSO.
I tensorflow/stream_executor/dso_loader.cc:93] Couldn’t open CUDA library libcudnn.so.6.5. LD_LIBRARY_PATH: :/usr/local/cuda/lib64
I tensorflow/stream_executor/cuda/cuda_dnn.cc:1382] Unable to load cuDNN DSO
I tensorflow/stream_executor/dso_loader.cc:93] Couldn’t open CUDA library libcufft.so.7.0. LD_LIBRARY_PATH: :/usr/local/cuda/lib64
I tensorflow/stream_executor/cuda/cuda_fft.cc:343] Unable to load cuFFT DSO.
I tensorflow/stream_executor/dso_loader.cc:101] successfully opened CUDA library libcuda.so locally
I tensorflow/stream_executor/dso_loader.cc:93] Couldn’t open CUDA library libcurand.so.7.0. LD_LIBRARY_PATH: :/usr/local/cuda/lib64
I tensorflow/stream_executor/cuda/cuda_rng.cc:333] Unable to load cuRAND DSO.
由安装报错可知，它使用的是7.0版本，故找不到，而如果你安装的是7.5版本，则可以执行如下命令添加相应链接：
sudo ln -s /usr/local/cuda/lib64/libcudart.so.7.5 /usr/local/cuda/lib64/libcudart.so.7.0
sudo ln -s libcublas.so.7.5 libcublas.so.7.0
sudo ln -s libcudnn.so.4.0.4 libcudnn.so.6.5
sudo ln -s libcufft.so libcufft.so.7.0<br>sudo ln -s libcurand.so libcurand.so.7.0
Ubuntu 15.04下TensorFlow源代码方式安装 http://www.linuxidc.com/Linux/2016-07/133223.htm
如何评价Tensorflow和其它深度学习系统 http://www.linuxidc.com/Linux/2016-07/133221.htm
更多Ubuntu相关信息见Ubuntu 专题页面 http://www.linuxidc.com/topicnews.aspx?tid=2
本文永久更新链接地址：http://www.linuxidc.com/Linux/2016-07/133226.htm
