tensorflow的Virtualenv安装方式安装
linux-dash
A beautiful web dashboard for Linux
项目地址:https://gitcode.com/gh_mirrors/li/linux-dash

·
http://www.cnblogs.com/simplelovecs/p/5149982.html
本文介绍了如何在ubuntu上以virtualenv方式安装tensorflow。
安装pip和virtualenv:
1
2
3
4
5
6
|
# 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:
1
|
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:
1
2
3
4
5
6
7
8
9
10
11
12
|
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:
1
2
3
4
5
6
7
8
9
10
11
12
|
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:
1
|
python
|
在python shell环境中测试:
1
2
3
4
5
6
7
8
9
10
|
>>> 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
1
2
|
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:
1
2
3
4
5
6
7
8
9
10
11
12
13
|
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:
1
2
3
4
|
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
|
---------------------- 笨笨,简单爱...努力,加油!~~~ ----------------------




A beautiful web dashboard for Linux
最近提交(Master分支:2 天前 )
186a802e
added ecosystem file for PM2 5 年前
5def40a3
Add host customization support for the NodeJS version 5 年前
更多推荐
所有评论(0)