tensorflow的Virtualenv安装方式安装

最新推荐文章于 2025-08-23 15:40:37 发布

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最新推荐文章于 2025-08-23 15:40:37 发布

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文章标签：操作系统 python shell

原文链接：http://www.cnblogs.com/simplelovecs/p/5149982.html

本文详细介绍了在Ubuntu系统中通过virtualenv环境安装TensorFlow的过程，包括安装依赖、创建虚拟环境、激活环境及安装TensorFlow的具体步骤。同时提供了解决安装过程中可能出现的CUDA配置错误和Python版本不匹配等问题的方法。

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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：

    _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
sudo ln -s libcurand.so libcurand.so.7.0

转载于:https://www.cnblogs.com/simplelovecs/p/5149982.html